The high integration of wind energy in power systems requires operating reserves to ensure the reliability and security in the operation. The intermittency and volatility in wind power sets a challenge for day-ahead dispatching in order to schedule generation resources. Therefore, the quantification of operating reserves is addressed in this paper using extreme values through Monte-Carlo simulations. The uncertainty in wind power forecasting is captured by a generalized extreme value distribution to generate scenarios. The day-ahead dispatching model is formulated as a mixed-integer linear quadratic problem including ramping constraints. This approach is tested in the IEEE-118 bus test system including integration of wind power in the system. The results represent the range of values for operating reserves in day-ahead dispatching.
Load Estimating and Calculating the Components of Solar Systemijtsrd
This paper is focused to develop solar system in rural area because the electricity is the backbone of the country's economy and only 40 is electrified in Myanmar. In design load estimating and calculation the components for the solar system and moreover environmental impact and climate change is also a fact to consider in it. Myanmar has high solar potential, photovoltaic PV system must be installed for most of the rural areas where there is no national grid line. To develop off grid PV system which support for people to lift up their lives in rural areas. Mono crystalline or single crystalline silicon photovoltaic cells and lead acid batteries are going to use in the system. The load estimation, PV sizing, inverter selection and battery sizing are calculated mainly. Based on the results, the design consideration can be absolutely applicable for the one village. Aye Myo Thant | Thant Zaw Oo | Ohmmar Myint "Load Estimating and Calculating the Components of Solar System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25281.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/25281/load-estimating-and-calculating-the-components-of-solar-system/aye-myo-thant
Feasibility Study of a Grid Connected Hybrid Wind/PV SystemIJAPEJOURNAL
This paper investigates the feasibility of a grid connected, large-scale hybrid wind/PV system. From data available an area called RasElnaqab in Jordan is chosen because it enjoys both high average wind speed of 6.13 m/s and high average solar radiation of 5.9KWhr/m2 /day. MATLAB and HOMER software’s are used for sizing and economical analysis respectively. Results show that76124 SUNTECH PV panels and 38 GW87-1.5MW wind turbines are the optimal choice. The net present cost (NPC) is 130,115,936$, the cost of energy (COE) is 0.049$/KWhr with a renewable fraction of 74.1%.A stepby-step process to determine the optimal sizing of Hybrid Wind/PV system is presented and it can be applied anywhere.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Economic Load Dispatch for Multi-Generator Systems with Units Having Nonlinea...IJAPEJOURNAL
Economic Load Dispatch aims at distributing the load demand between various generation stations in a system such that the total cost of generation is minimum. This is of vital importance since it not only reduces the operation cost of the generation utility but also helps in conserving fast dwindling energy resources. Modern day power systems are large interconnected systems with a large number of generator units each having its own cost curve. Ideally the cost function of a unit is a quadratic function of the power generated by the unit and the cost curve obtained is a smooth parabola. But in practice cost curves deviate from the idealised one due the several reasons such as valve point effect, multi fuel operation, existence of forbidden zones etc. and as such may not be continuous or analytic. Also for a large interconnected system it becomes essential to consider the effect of transmission losses. Conventional numerical method based approaches work well with systems without losses but for large systems with losses obtaining convergence becomes difficult as the number of iterations required as well as the computational time are very high. These methods fail entirely if non ideal cost curves are considered. Hence soft computing based methods become essential. Here Gravity Search Algorithm(GSA) has been used to for finding economic load scheduling in a multi generator system, given a certain load demand, and taking into consideration the effects of practical constraints on the idealised load curve. The algorithms for finding the economic scheduling has been written in Matlab and has provided satisfactory results based on the given tolerance values. Also the traditional and soft computing based approaches have been compared to demonstrate the advantages of one over the other.
Load Estimating and Calculating the Components of Solar Systemijtsrd
This paper is focused to develop solar system in rural area because the electricity is the backbone of the country's economy and only 40 is electrified in Myanmar. In design load estimating and calculation the components for the solar system and moreover environmental impact and climate change is also a fact to consider in it. Myanmar has high solar potential, photovoltaic PV system must be installed for most of the rural areas where there is no national grid line. To develop off grid PV system which support for people to lift up their lives in rural areas. Mono crystalline or single crystalline silicon photovoltaic cells and lead acid batteries are going to use in the system. The load estimation, PV sizing, inverter selection and battery sizing are calculated mainly. Based on the results, the design consideration can be absolutely applicable for the one village. Aye Myo Thant | Thant Zaw Oo | Ohmmar Myint "Load Estimating and Calculating the Components of Solar System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25281.pdfPaper URL: https://www.ijtsrd.com/engineering/electrical-engineering/25281/load-estimating-and-calculating-the-components-of-solar-system/aye-myo-thant
Feasibility Study of a Grid Connected Hybrid Wind/PV SystemIJAPEJOURNAL
This paper investigates the feasibility of a grid connected, large-scale hybrid wind/PV system. From data available an area called RasElnaqab in Jordan is chosen because it enjoys both high average wind speed of 6.13 m/s and high average solar radiation of 5.9KWhr/m2 /day. MATLAB and HOMER software’s are used for sizing and economical analysis respectively. Results show that76124 SUNTECH PV panels and 38 GW87-1.5MW wind turbines are the optimal choice. The net present cost (NPC) is 130,115,936$, the cost of energy (COE) is 0.049$/KWhr with a renewable fraction of 74.1%.A stepby-step process to determine the optimal sizing of Hybrid Wind/PV system is presented and it can be applied anywhere.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Economic Load Dispatch for Multi-Generator Systems with Units Having Nonlinea...IJAPEJOURNAL
Economic Load Dispatch aims at distributing the load demand between various generation stations in a system such that the total cost of generation is minimum. This is of vital importance since it not only reduces the operation cost of the generation utility but also helps in conserving fast dwindling energy resources. Modern day power systems are large interconnected systems with a large number of generator units each having its own cost curve. Ideally the cost function of a unit is a quadratic function of the power generated by the unit and the cost curve obtained is a smooth parabola. But in practice cost curves deviate from the idealised one due the several reasons such as valve point effect, multi fuel operation, existence of forbidden zones etc. and as such may not be continuous or analytic. Also for a large interconnected system it becomes essential to consider the effect of transmission losses. Conventional numerical method based approaches work well with systems without losses but for large systems with losses obtaining convergence becomes difficult as the number of iterations required as well as the computational time are very high. These methods fail entirely if non ideal cost curves are considered. Hence soft computing based methods become essential. Here Gravity Search Algorithm(GSA) has been used to for finding economic load scheduling in a multi generator system, given a certain load demand, and taking into consideration the effects of practical constraints on the idealised load curve. The algorithms for finding the economic scheduling has been written in Matlab and has provided satisfactory results based on the given tolerance values. Also the traditional and soft computing based approaches have been compared to demonstrate the advantages of one over the other.
A REVIEW OF VARIOUS MPPT TECHNIQUES FOR PHOTOVOLTAIC SYSTEMijiert bestjournal
Solar PV system is becoming an important part of re newable energy,as more than 45% of required energy in the world will be generated by P V array. Hence it is necessary that concentration should be given in order to reduce ap plication cost & to increment their performance. In this paper various techniques invol ving a comprehensive technique of MPPT applied to PV system is discussed which are availab le until June 2014. In an attempt to improve more efficient & effective energy extraction for a solar PV system,this paper investigates & compares typical MPPT control strategies used in so lar PV industry. But as there will be confusion while selecting a MPPT,because every tec hnique has its own existence,therefore a proper detailed study of different MPPT is essentia l. In this review paper a comprehensive study of MPPT technique with detailed explanation & class ification based on features,such as number of control variable involved,different control str ategies employed,types of circuitry useful for PV system & related commercial application. In this paper,atleast 15 distinct techniques have been reviewed with many variation on implementation,thus this paper would become a convenient reference for future work for PV power g eneration .
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Energy Harvesting Using Adaptive Duty-Cycling Algorithm - Wireless Sensor Net...IJERDJOURNAL
ABSTRACT: With the wide spread use of wireless sensor network, the management of the energy resources has become a topic of reseaech. Wireless sensor nodes which harvest energy from the environment have become an to battery hooped up nodes. Requirements for economical use of the extracted energy led to development of algorithms that manage the node functions depending on the amount of collected energy. This article introduces a unique solution of adaptively setting the duty-cycle of a wireless sensor nodes so as to maximize its monitoring lifetime. The developed algorithms are particularly suited to energy harvesting wireless sensor networks situated in locations where energy is scarce or where harvested power exhibits ample diurnal or seasonal variation. The results described in this article shows that the proposed wireless sensor network architecture can represent a viable solution for monitoring indoor environments characterized by low illumination. The setup was tested and validated under various lighting conditions, using the adaptive techniques described in the paper.
A probabilistic multi-objective approach for FACTS devices allocation with di...IJECEIAES
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Impact of compressed air energy storage system into diesel power plant with w...IJECEIAES
The wind energy plays an important role in power system because of its renewable, clean and free energy. However, the penetration of wind power (WP) into the power grid system (PGS) requires an efficient energy storage systems (ESS). compressed air energy storage (CAES) system is one of the most ESS technologies which can alleviate the intermittent nature of the renewable energy sources (RES). Nyala city power plant in Sudan has been chosen as a case study because the power supply by the existing power plant is expensive due to high costs for fuel transport and the reliability of power supply is low due to uncertain fuel provision. This paper presents a formulation of security-constrained unit commitment (SCUC) of diesel power plant (DPP) with the integration of CAES and PW. The optimization problem is modeled and coded in MATLAB which solved with solver GORUBI 8.0. The results show that the proposed model is suitable for integration of renewable energy sources (RES) into PGS with ESS and helpful in power system operation management.
An Higher Case Operation and Analysis of a Multiple Renewable Resources Conne...IJERA Editor
In our nation the usage of electricity is increasing day-by-day. According to that conserdations, the generated
power from the non-renewable sources will not satisfy the demands properly. so for these purpose, by using
multiple renewable sources, it will be very useful to some type of dc applications. The power produced from the
individual renewable sources will not be satisfy the demand at all times. So by integration of a multiple
renewable sources such as wind and solar a huge amount of power will be produced. These power will be
coordinated to the ac grid or directly to dc consumers. For integration of renewable sources an aggregated model
has to be proposed. In according to these operation BESS (battery energy storage system)is equipped with the
system for maintaining the power balance. For obtaining the power balance the adaptive droop control technique
has to be proposed and droop curves are evaluated. The droop characteristics are selected on the basis of the
deviation between the optimized and real-time SOC of the BESS. In these paper, the operational analysis can be
performed when real time soc is higher than the optimised soc and droop curves are plotted.
This paper discusses about a LabVIEW based controller for the hybrid renewable energy system operated AC-DC microgrid with the major objectives of: i) predicting the power generation potential of the solar–PV and wind generators ii) effective power management iii) load scheduling based on the available power with the renewable sources and iv) grid/islanding mode of operation of the microgrid. In order topredict the output power of wind generator and Solar-PV system, an artificial neural network is developed.The laboratory-scale model of three phase, 400 V, 10 kVA microgrid structure is developed at National Institute of Technology Calicut, India. The developed LabVIEW based controller has been tested successfully for a real-time load and source in the laboratory environment. Test results show that the designed controller is effectively managing the output powerof the primary energy sources under different scenarios.
A grid connected hybrid generation system (HGS) consisting of wind energy conversion System (WECS)/Photo voltaic (PV) System/solid oxide fuel cell (SOFC) is designed and simulated by using Matlab/Simulink. SOFC is the replacement of battery, attached to produce the clean energy when these renewable energy sources are unable to produce required amount of electric power. A controller is used to regulate the flow of H2 through the valveto the SOFC and the rest amount of H2 is stored in storage tank. Also, an operational control strategy (OCS) is developed to utilize maximum amount of power of PV to the required load and rest amount of power is coming from wind to fulfill the load demand. Hence, the electrolyzer is supplied by the wind power to convert the water in to H2 and oxygen. Also the power quality factor (PQF) analysis is exercised to measure the quality of power transmission.
POWER FACTOR IMPROVEMENT OF INDUSTRIAL LOAD BY MATLAB SIMULATIONpaperpublications3
Abstract: It is a framework considering industrial loads for improvement of power factor of industrial load system. Most of loads in industries are inductive in nature and thus having low power factor. Low power factor is highly undesirable and it increases current and also increases losses of active power. This paper discusses how to calculate the correct value of capacitor to improve power factor to overcome above mentioned problems. Because improving power factor will give efficient utilization of electrical power.
Systems engineering and analysis track presentation from Milsoft's 2009 User Conference. It was delivered by Jennifer Taylor and Chris Hammond. The Milsoft Electric Utility Solutions Users Conference is the premier event for both our users and vendors offering interoperable utility management services that enhance Milsoft Smart Grid Solutions. If you’d like to be on our mailing list, just email: missy.brooks@milsoft.com.
Large-scale grid-tied photovoltaic (PV) station are increasing rapidly. However, this large penetration of PV system creates frequency fluctuation in the grid due to the intermittency of solar irradiance. Therefore, in this paper, a robust droop control mechanism of the battery energy storage system (BESS) is developed in order to damp the frequency fluctuation of the multi-machine grid system due to variable active power injected from the PV panel. The proposed droop control strategy incorporates frequency error signal and dead-band for effective minimization of frequency fluctuation. The BESS system is used to consume/inject an effective amount of active power based upon the frequency oscillation of the grid system. The simulation analysis is carried out using PSCAD/EMTDC software to prove the effectiveness of the proposed droop control-based BESS system. The simulation result implies that the proposed scheme can efficiently curtail the frequency oscillation.
Simulation of Optimal Control Strategy for a Solar Photovoltaic Power Systemijtsrd
This paper proposes a single stage PV system based on a linear quadratic regulator LQR . The system makes use of a single phase power converter connected to the grid connected system through an LCL filter. The PandO algorithm is used to generate the reference signal for the fluctuating dc bus voltage as well as to extract the maximum power from the solar panels. The proposed work has been carried out in MATLAB, and the results are presented. C. B. Sree Hara Vamsi | B. Kumar Reddy "Simulation of Optimal Control Strategy for a Solar Photovoltaic Power System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29786.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29786/simulation-of-optimal-control-strategy-for-a-solar-photovoltaic-power-system/c-b-sree-hara-vamsi
Stochastic control for optimal power flow in islanded microgridIJECEIAES
The problem of optimal power flow (OPF) in an islanded mircrogrid (MG) for hybrid power system is described. Clearly, it deals with a formulation of an analytical control model for OPF. The MG consists of wind turbine generator, photovoltaic generator, and diesel engine generator (DEG), and is in stochastic environment such as load change, wind power fluctuation, and sun irradiation power disturbance. In fact, the DEG fails and is repaired at random times so that the MG can significantly influence the power flow, and the power flow control faces the main difficulty that how to maintain the balance of power flow? The solution is that a DEG needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Adopting the Rishel’s famework and using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation. Finally, numerical examples and sensitivity analyses are included to illustrate the importance and effectiveness of the proposed model.
An integrated OPF dispatching model with wind power and demand response for d...IJECEIAES
In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system.
A REVIEW OF VARIOUS MPPT TECHNIQUES FOR PHOTOVOLTAIC SYSTEMijiert bestjournal
Solar PV system is becoming an important part of re newable energy,as more than 45% of required energy in the world will be generated by P V array. Hence it is necessary that concentration should be given in order to reduce ap plication cost & to increment their performance. In this paper various techniques invol ving a comprehensive technique of MPPT applied to PV system is discussed which are availab le until June 2014. In an attempt to improve more efficient & effective energy extraction for a solar PV system,this paper investigates & compares typical MPPT control strategies used in so lar PV industry. But as there will be confusion while selecting a MPPT,because every tec hnique has its own existence,therefore a proper detailed study of different MPPT is essentia l. In this review paper a comprehensive study of MPPT technique with detailed explanation & class ification based on features,such as number of control variable involved,different control str ategies employed,types of circuitry useful for PV system & related commercial application. In this paper,atleast 15 distinct techniques have been reviewed with many variation on implementation,thus this paper would become a convenient reference for future work for PV power g eneration .
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Energy Harvesting Using Adaptive Duty-Cycling Algorithm - Wireless Sensor Net...IJERDJOURNAL
ABSTRACT: With the wide spread use of wireless sensor network, the management of the energy resources has become a topic of reseaech. Wireless sensor nodes which harvest energy from the environment have become an to battery hooped up nodes. Requirements for economical use of the extracted energy led to development of algorithms that manage the node functions depending on the amount of collected energy. This article introduces a unique solution of adaptively setting the duty-cycle of a wireless sensor nodes so as to maximize its monitoring lifetime. The developed algorithms are particularly suited to energy harvesting wireless sensor networks situated in locations where energy is scarce or where harvested power exhibits ample diurnal or seasonal variation. The results described in this article shows that the proposed wireless sensor network architecture can represent a viable solution for monitoring indoor environments characterized by low illumination. The setup was tested and validated under various lighting conditions, using the adaptive techniques described in the paper.
A probabilistic multi-objective approach for FACTS devices allocation with di...IJECEIAES
This study presents a probabilistic multi-objective optimization approach to obtain the optimal locations and sizes of static var compensator (SVC) and thyristor-controlled series capacitor (TCSC) in a power transmission network with large level of wind generation. In this study, the uncertainties of the wind power generation and correlated load demand are considered. The uncertainties are modeled in this work using the points estimation method (PEM). The optimization problem is solved using the multi-objective particle swarm optimization (MOPSO) algorithm to find the best position and rating of the flexible AC transmission system (FACTS) devices. The objective of the problem is to maximize the system loadability while minimizing the power losses and FACTS devices installation cost. Additionally, a technique based on fuzzy decision-making approach is employed to extract one of the Pareto optimal solutions as the best compromise one. The proposed approach is applied on the modified IEEE 30bus system. The numerical results evince the effectiveness of the proposed approach and shows the economic benefits that can be achieved when considering the FACTS controller.
Impact of compressed air energy storage system into diesel power plant with w...IJECEIAES
The wind energy plays an important role in power system because of its renewable, clean and free energy. However, the penetration of wind power (WP) into the power grid system (PGS) requires an efficient energy storage systems (ESS). compressed air energy storage (CAES) system is one of the most ESS technologies which can alleviate the intermittent nature of the renewable energy sources (RES). Nyala city power plant in Sudan has been chosen as a case study because the power supply by the existing power plant is expensive due to high costs for fuel transport and the reliability of power supply is low due to uncertain fuel provision. This paper presents a formulation of security-constrained unit commitment (SCUC) of diesel power plant (DPP) with the integration of CAES and PW. The optimization problem is modeled and coded in MATLAB which solved with solver GORUBI 8.0. The results show that the proposed model is suitable for integration of renewable energy sources (RES) into PGS with ESS and helpful in power system operation management.
An Higher Case Operation and Analysis of a Multiple Renewable Resources Conne...IJERA Editor
In our nation the usage of electricity is increasing day-by-day. According to that conserdations, the generated
power from the non-renewable sources will not satisfy the demands properly. so for these purpose, by using
multiple renewable sources, it will be very useful to some type of dc applications. The power produced from the
individual renewable sources will not be satisfy the demand at all times. So by integration of a multiple
renewable sources such as wind and solar a huge amount of power will be produced. These power will be
coordinated to the ac grid or directly to dc consumers. For integration of renewable sources an aggregated model
has to be proposed. In according to these operation BESS (battery energy storage system)is equipped with the
system for maintaining the power balance. For obtaining the power balance the adaptive droop control technique
has to be proposed and droop curves are evaluated. The droop characteristics are selected on the basis of the
deviation between the optimized and real-time SOC of the BESS. In these paper, the operational analysis can be
performed when real time soc is higher than the optimised soc and droop curves are plotted.
This paper discusses about a LabVIEW based controller for the hybrid renewable energy system operated AC-DC microgrid with the major objectives of: i) predicting the power generation potential of the solar–PV and wind generators ii) effective power management iii) load scheduling based on the available power with the renewable sources and iv) grid/islanding mode of operation of the microgrid. In order topredict the output power of wind generator and Solar-PV system, an artificial neural network is developed.The laboratory-scale model of three phase, 400 V, 10 kVA microgrid structure is developed at National Institute of Technology Calicut, India. The developed LabVIEW based controller has been tested successfully for a real-time load and source in the laboratory environment. Test results show that the designed controller is effectively managing the output powerof the primary energy sources under different scenarios.
A grid connected hybrid generation system (HGS) consisting of wind energy conversion System (WECS)/Photo voltaic (PV) System/solid oxide fuel cell (SOFC) is designed and simulated by using Matlab/Simulink. SOFC is the replacement of battery, attached to produce the clean energy when these renewable energy sources are unable to produce required amount of electric power. A controller is used to regulate the flow of H2 through the valveto the SOFC and the rest amount of H2 is stored in storage tank. Also, an operational control strategy (OCS) is developed to utilize maximum amount of power of PV to the required load and rest amount of power is coming from wind to fulfill the load demand. Hence, the electrolyzer is supplied by the wind power to convert the water in to H2 and oxygen. Also the power quality factor (PQF) analysis is exercised to measure the quality of power transmission.
POWER FACTOR IMPROVEMENT OF INDUSTRIAL LOAD BY MATLAB SIMULATIONpaperpublications3
Abstract: It is a framework considering industrial loads for improvement of power factor of industrial load system. Most of loads in industries are inductive in nature and thus having low power factor. Low power factor is highly undesirable and it increases current and also increases losses of active power. This paper discusses how to calculate the correct value of capacitor to improve power factor to overcome above mentioned problems. Because improving power factor will give efficient utilization of electrical power.
Systems engineering and analysis track presentation from Milsoft's 2009 User Conference. It was delivered by Jennifer Taylor and Chris Hammond. The Milsoft Electric Utility Solutions Users Conference is the premier event for both our users and vendors offering interoperable utility management services that enhance Milsoft Smart Grid Solutions. If you’d like to be on our mailing list, just email: missy.brooks@milsoft.com.
Large-scale grid-tied photovoltaic (PV) station are increasing rapidly. However, this large penetration of PV system creates frequency fluctuation in the grid due to the intermittency of solar irradiance. Therefore, in this paper, a robust droop control mechanism of the battery energy storage system (BESS) is developed in order to damp the frequency fluctuation of the multi-machine grid system due to variable active power injected from the PV panel. The proposed droop control strategy incorporates frequency error signal and dead-band for effective minimization of frequency fluctuation. The BESS system is used to consume/inject an effective amount of active power based upon the frequency oscillation of the grid system. The simulation analysis is carried out using PSCAD/EMTDC software to prove the effectiveness of the proposed droop control-based BESS system. The simulation result implies that the proposed scheme can efficiently curtail the frequency oscillation.
Simulation of Optimal Control Strategy for a Solar Photovoltaic Power Systemijtsrd
This paper proposes a single stage PV system based on a linear quadratic regulator LQR . The system makes use of a single phase power converter connected to the grid connected system through an LCL filter. The PandO algorithm is used to generate the reference signal for the fluctuating dc bus voltage as well as to extract the maximum power from the solar panels. The proposed work has been carried out in MATLAB, and the results are presented. C. B. Sree Hara Vamsi | B. Kumar Reddy "Simulation of Optimal Control Strategy for a Solar Photovoltaic Power System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29786.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29786/simulation-of-optimal-control-strategy-for-a-solar-photovoltaic-power-system/c-b-sree-hara-vamsi
Stochastic control for optimal power flow in islanded microgridIJECEIAES
The problem of optimal power flow (OPF) in an islanded mircrogrid (MG) for hybrid power system is described. Clearly, it deals with a formulation of an analytical control model for OPF. The MG consists of wind turbine generator, photovoltaic generator, and diesel engine generator (DEG), and is in stochastic environment such as load change, wind power fluctuation, and sun irradiation power disturbance. In fact, the DEG fails and is repaired at random times so that the MG can significantly influence the power flow, and the power flow control faces the main difficulty that how to maintain the balance of power flow? The solution is that a DEG needs to be scheduled. The objective of the control problem is to find the DEG output power by minimizing the total cost of energy. Adopting the Rishel’s famework and using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation. Finally, numerical examples and sensitivity analyses are included to illustrate the importance and effectiveness of the proposed model.
An integrated OPF dispatching model with wind power and demand response for d...IJECEIAES
In the day-ahead dispatching of network-constrained electricity markets, renewable energy and distributed resources are dispatched together with conventional generation. The uncertainty and volatility associated to renewable resources represents a new paradigm to be faced for power system operation. Moreover, in various electricity markets there are mechanisms to allow the demand participation through demand response (DR) strategies. Under operational and economic restrictions, the operator each day, or even in intra-day markets, dispatchs an optimal power flow to find a feasible state of operation. The operation decisions in power markets use an optimal power flow considering unit commitment to dispatch economically generation and DR resources under security restrictions. This paper constructs a model to include demand response in the optimal power flow under wind power uncertainty. The model is formulated as a mixed-integer linear quadratic problem and evaluated through Monte-Carlo simulations. A large number of scenarios around a trajectory bid captures the uncertainty in wind power forecasting. The proposed integrated OPF model is tested on the standard IEEE 39-bus system.
This paper proposes a feedback linearization control of doubly fed induction generator based wind energy systems for improving decoupled control of the active and reactive powers stator. In order to enhance dynamic performance of the controller studied, the adopted control is reinforced by a fuzzy logic controller. This approach is designed without any model of rotor flux estimation. The difficulty of measuring of rotor flux is overcome by using high gain observer. The stability of the nonlinear observer is proved by the Lyapunov theory. Numerical simulations using MATLAB-SIMULINK shown clearly the robustness of the proposed control, particularly to the disturbance rejection and parametric variations compared with the conventional method.
Optimal Configuration of Wind Farms in Radial Distribution System Using Parti...journalBEEI
Recently, a wide range of wind farm based distributed generations (DGs) are being integrated into distribution systems to fulfill energy demands and to reduce the burden on transmission corridors. The non-optimal configuration of DGs could severely affect the distribution system operations and control. Hence, the aim of this paper is to analyze the wind data in order to build a mathematical model for power output and pinpoint the optimal location. The overall objective is minimization of power loss reduction in distribution system. The five years of wind data was taken from 24o 44’ 29” North, 67o 35’ 9” East coordinates in Pakistan. The optimal location for these wind farms were pinpointed via particle swarm optimization (PSO) algorithm using standard IEEE 33 radial distribution system. The result reveals that the proposed method helps in improving renewable energy near to load centers, reduce power losses and improve voltage profile of the system. Moreover, the validity and performance of the proposed model were also compared with other optimization algorithms.
Economic viability and profitability assessments of WECS IJECEIAES
Technical and technological advances in alternative energy sources have led many countries to add green energy to their power plants to reduce carbon emissions and air pollution. At present, many electricity companies are looking to use alternative sources of energy because of high electrical energy prices. Wind energy is more useful than many renewable energies such as solar, heat, biomass, etc. The Wind Energy Conversion System (WECS) is a system that converts the kinetic energy of the wind into electrical energy to feed the known loads. WECS can be found in a variety of technology. Climate change and load demand are essential determinants of WECS optimization modelling. In this paper, proposed a strategy focused primarily on economic analysis WECS. The strategy based on a weather change to find the optimal designing and modelling for four different types of WECS using HOMER software. Finally, several criteria were used to determine which type of WECS was the most profitable investment and less payback period.
Dynamic Voltage Stability Comparison of Thermal and Wind Power Generation wit...IJECEIAES
This paper presents a static and dynamic voltage stability analysis of a power network with thermal and wind generation considering static and dynamic load models. The thermal plant was modeled as a synchronous machine and the wind farm as a variable speed induction generator based on a doubly-fed induction generator. The load considered the ZIP, exponential recovery, induction motor, and frequency-dependent load models. The bifurcation points were found by continuation power flow and sensitivity analyses. In addition, dynamic voltage stability assessments were performed considering changes in the moment of inertia and the frequency parameters. All simulations were carried out in a 4-bus power system and using the power system analysis toolbox (PSAT) and MATLAB script code. The results show that the thermal generator had difficulties to maintain stability under dynamic load variations and frequency changes, the wind generator had difficulties to maintain voltage for the load with induction motors, and both generators had difficulties when the moment of inertia is increased.
PSS/E based placement wind/PV hybrid system to improve stability of Iraqi grid IJECEIAES
Proper employment of Hybrid Wind/ PV system is often implemented near the load, and it is linked with the grid to study dynamic stability analysis. Generally, instability is because of sudden load demand variant and variant in renewable sources generation. As well as, weather variation creates several factors that affect the operation of the integrated hybrid system. So this paper introduces output result of a PV /wind via power electronic technique; DC chopper; that is linked to Iraqi power system to promote the facilitating achievement of Wind/ PV voltage. Moreover, PSS/E is used to study dynamic power stability for hybrid system which is attached to an effective region of Iraqi Network. The hybrid system is connected to Amara Old bus and fault bus is achieved to that bus and the stability results reflects that settling time after disturbance is not satisfactory. But, it is found that PV/wind generation system influences Iraqi grid stability to be better than that with only PV generation and the latter is better than stability of the grid that is enhanced with only wind generation. These results represent an important guideline for Iraqi power system planner.
The following article presents the control of the power generated by the Doubly Fed Induction Generator, integrated into the wind system, whose rotor is linked to the power converters (Rotor Side Convert (RSC) and Grid Side Converter (GSC)) interfaced by the DC-BUS and connected to the grid via a filter (Rf, Lf) in order to obtain an optimal power to the grid and to ensure system stability. The objective of this study is to understand and to make the comparison between Sliding mode Control technique and the Flux Oriented Control in order to control the Doubly Fed Induction Generator powers exchanged with the grid, it also aims at maintaining the DC-BUS voltage constant and a unit power factor at the grid connection point.The results of simulation show the performance of the Sliding mode Control in terms of monitoring, and robustness with regard to the parametric variations, compared to the Flux Oriented Control. The performance of the systems was tested and compared with the use of MATLAB/Simulink software.
Evaluation of wind-solar hybrid power generation system based on Monte Carlo...IJECEIAES
The application of wind-photovoltaic complementary power generation systems is becoming more and more widespread, but its intermittent and fluctuating characteristics may have a certain impact on the system's reliability. To better evaluate the reliability of stand-alone power generation systems with wind and photovoltaic generators, a reliability assessment model for stand-alone power generation systems with wind and photovoltaic generators was developed based on the analysis of the impact of wind and photovoltaic generator outages and derating on reliability. A sequential Monte Carlo method was used to evaluate the impact of the wind turbine, photovoltaic (PV) turbine, wind/photovoltaic complementary system, the randomness of wind turbine/photovoltaic outage status and penetration rate on the reliability of Independent photovoltaic power generation system (IPPS) under the reliability test system (RBTS). The results show that this reliability assessment method can provide some reference for planning the actual IPP system with wind and complementary solar systems.
A NOVEL SYSTEM OPTIMIZATION OF A GRID INDEPENDENT HYBRID RENEWABLE ENERGY SYS...ijscmcj
Hybrid renewable energy based off-grid or distribute power supply has customarily thought to be a solitary
innovation based restricted level of supply to meet the essential needs, without considering dependable
energy procurement to rural or remote commercial enterprises. The aim of the paper is to propose a design
idea off-grid hybrid system to fulfil the load demand of the telecom base station by using renewable energy
resources for rural regions. HOMER software tool is used for simulation and optimization and it also
analysis the total net present cost (TNPC) $100,757, carbon emission is zero percent, initial cost $70,920,
operating cost $2,334, Capacity Shortage 0.17% and the cost of energy (COE) $0.502. The HOMER
simulation outcome gives the most feasible hybrid system configuration for electric power supply to the
remote location telecom base station.
Enhancement of reactive power capability of doubly fed induction generator 2-3IAEME Publication
With the growing integration into power grids, wind power plants are very important for
power system. According to the grid codes wind power plants should have the ability to perform
voltage control and reactive power compensation at the Point of Common Coupling (PCC). In
general, the entire wind farm operates within a power factor range of 0.95 leading and lagging. This
operation drastically under utilizes the reactive output of the machine. The results offered in this
paper demonstrates enhancement of reactive power capability of Doubly Fed Induction Generator
(DFIG). This additional reactive power supports to improve the post fault voltage and reduces the
overall system losses and also reduces the cost of the generation. The utilization of extended reactive
limits in voltage control may prevent system collapse.
Reliability Constrained Unit Commitment Considering the Effect of DG and DR P...IJECEIAES
Due to increase in energy prices at peak periods and increase in fuel cost, involving Distributed Generation (DG) and consumption management by Demand Response (DR) will be unavoidable options for optimal system operations. Also, with high penetration of DGs and DR programs into power system operation, the reliability criterion is taken into account as one of the most important concerns of system operators in management of power system. In this paper, a Reliability Constrained Unit Commitment (RCUC) at presence of time-based DR program and DGs integrated with conventional units is proposed and executed to reach a reliable and economic operation. Designated cost function has been minimized considering reliability constraint in prevailing UC formulation. The UC scheduling is accomplished in short-term so that the reliability is maintained in acceptable level. Because of complex nature of RCUC problem and full AC load flow constraints, the hybrid algorithm included Simulated Annealing (SA) and Binary Particle Swarm Optimization (BPSO) has been proposed to optimize the problem. Numerical results demonstrate the effectiveness of the proposed method and considerable efficacy of the time-based DR program in reducing operational costs by implementing it on IEEE-RTS79.
Voltage Compensation in Wind Power System using STATCOM Controlled by Soft Co...IJECEIAES
When severe voltage sags occur in weak power systemsassociated with gridconnected wind farms employing doubly fed induction generators, voltageinstability occurs, which may lead to forced disconnection of wind turbine.Shunt flexible AC transmission system devices like static synchronous compensator (STATCOM) may be harnessed to provide voltage support bydynamic injection of reactive power.In this work, the STATCOM providedvoltage compensation at the point of common coupling in five test cases,namely, simultaneous occurrence of step change (drop) in wind speed and dip in grid voltage, single line to ground, line to line, double line to groundfaults and sudden increment in load by more than a thousand times. Threetechniques were employed to control the STATCOM, namely, fuzzy logic,particle swarm optimization and a combination of both. A performancecomparison was made among the three soft computing techniques used tocontrol the STATCOM on the basis of the amount of voltage compensationoffered at the point of common coupling. The simulations were done with thehelp of SimPowerSystems available with MATLAB / SIMULINK and theresults validated that the STATCOM controlled by all the three techniques offered voltage compensation in all the cases considered.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This paper presents a study analysis of a complete wind energy conversion system, the system based on a doubly fed induction generator (DFIG); a vector control with stator flux orientation of the DFIG is also used to control independently the active and reactive powers. A comparative study have been performed between the conventional PI controller and fuzzy logic control to investigate its dynamic and static performances. This research work involves the study of a phase in advance, to provide effective assistance, to all those who have to make decisions regarding the planning and implementation of wind energy projects. The main objective is to model the wind chain and the use of two types of strategies for the control of this generator to ensure a good regulation we started with the modeling of the wind chain then the modeling of the DFIG and then the use of the two strategies for the regulation of the latter .The complete system is modeled and simulated in the MATLAB/ Simulink. The performance and robustness are analyzed and compared by Matlab / Simulink .Simulation results prove the excellent performance of fuzzy control unit as improving power quality and stability of wind turbine.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
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heat and mass transfer processes. A computer program for
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condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
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water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
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introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
The Internet of Things (IoT) is a revolutionary concept that connects everyday objects and devices to the internet, enabling them to communicate, collect, and exchange data. Imagine a world where your refrigerator notifies you when you’re running low on groceries, or streetlights adjust their brightness based on traffic patterns – that’s the power of IoT. In essence, IoT transforms ordinary objects into smart, interconnected devices, creating a network of endless possibilities.
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Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
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characteristics in the wind power [2-6]. A probabilistic approach has been addressed to capture
the intermittency in day-ahead dispatching models. In the unit-commitment formulation, a stochastic
approach is used, particularly, the authors in [7] report about the use of scenarios for generation with
distribution probability functions, the demand is considered constant. Formulations with a stochastic
approach has been suggested to manage wind power uncertainty in power system operation [8-11] and in
microgrids in [12]. The flexibility in power system operation will be a critical issue under high penetration of
wind power to deal with uncertainty and intermittency. In [10], the authors proposed an approach based on
a model to clear a network-constrained electricity market with offers made by wind generators. In [13]
the optimal power flow approach is addressed to minimize the rescheduling including total congestion cost
minimization. In [14] the authors propose a dispatching model to consider simultaneously wind power and
demand response.
The quantification of reserves under high penetration of wind power has been addressed in various
electricity markets with different approaches, for instance, PJM (Pennsylvania, New Jersey and Maryland) in
US classifies ancillary services as regulating and load-following reserves [15][13]. The operating reserves
deals with the variability and intermittency of power wind from a power dispatching point of view, in fact, in
[16], the authors affirm about the operational problems associated with renewable sources. In [17] an optimal
reactive power scheduling problem is solved using an evolutionary search algorithm.
This paper provides a methodology to identify the proper level of reserves in power systems with
penetration of wind power using extreme value theory as a novelty to characterize low probability cases with
high impact in the operation reliability. This paper deals with the uncertainty and variability introduced by
wind power to determine reserves in day-ahead dispatching. The model proposed in this paper is based on
a model for day-ahead dispatching as a mixed-integer linear quadratic optimization problem with unit
commitment. The model takes into account startup and shutdown characteristics for thermal units.
The quantification of operating reserves is addressed via generalized extreme value functions.
We propose a quantification of ramp reserves in day ahead dispatching considering extreme values
to characterize those high-impact low probability events. Therefore, in day-ahead dispatching or even in
intra-day dispatching enough reserves has to be planned to compensate wind power volatility.
The dispatching decision has to deal with the inherent uncertainty in order to dispatch economically
the generation resources considering the system reliability at the same time. We propose the construction of
wind power ramps trajectories through Monte-Carlo simulations to quantify the probability distribution of
ramp reserves. Specifically, we propose a GEV (generalized extreme value) distribution function to produce
wind power ramps trajectories considering 5% of the events are in the tails.
2. MODELLING UNCERTAINTY WITH SCENARIOS
In this section, we present the methodology and discussion about the generation of scenarios
considering the uncertainty of wind power. Specifically, the generation of wind power trajectories for
a 24-hour period to capture the uncertainty associated to wind power ramps. The use of GEV functions to
generate trajectories capture low probability events as the intermittents power ramp given by wind power.
The identification of ramps events are important to quantify reserves to compensate wind power ramps
during the operation.
The most critical situations arise with extreme values of wind power ramps. Recent studies [18] has
demonstrated that real-world wind power ramps exhibit heavier tails. In particular, the historical data from
wind power generation in ERCOT (Electric Reliability Council of Texas) reveals that less than 5% of hourly
wind power ramps had a magnitude greater than three standard deviations [19], [20]. Those extreme values in
the tails will require operating reserves during operation to compensate the deviations and to guarantee wind
power integration. To quantify operating reserves considering the uncertainty associated to wind power
ramps, we use extreme value theory to generate wind power trajectories with heavier tails. The wind power
ramps can be suitable modeled by a generalized extreme value distribution (GEV) function given by,
1/
exp 1
r
r
(1)
Defined on the set,
: 1 / 0r r u (2)
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Where the parameters satisfy,
, (3)
The model has three parameters: is a location parameter, is a scale parameter and is a shape
parameter. According to the parameter , there are three classes of distributions widely known as
the Gumbel, Fréchet and Weibull families, or type I, II and III, respectively [21]. Specifically, if 0 then
the distribution is a type I function, if 0 then the distribution is a type II function, and if 0 then
the distribution is a type III function. The parameter indicates the tail behavior, in other words,
the distribution of wind power ramp events behind a threshold value given by . In particular, the tail
behavior for wind power ramp is given by type II distribution. In order to appreciate the tails in the GEV,
Figure 1 shows a contrast of a Gaussian distribution and a GEV distribution.
Figure 1. Gaussian distribution and GEV distribution
We use a Monte-Carlo framework to generate trajectories for a 24-hour period under the assumption
than 5% of hourly wind power ramps had a magnitude greater than three standard deviations. Figure 2 and
Figure 3, represents the wind power trajectories around a mean value to represent extreme values in the left
and right tail respectively. The mean value corresponds to bid made by the wind power producer.
Figure 2. Wind power scenarios with values in
the left tail
Figure 3. Wind power scenarios with values in
the right tail
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For GEV distribution, extreme quantiles of the annual maximum distribution are given by the inverse of (1),
1 log 1pz p
(4)
The p quantile implies that with confidence wind power ramp is no greater than . More precisely,
the level is expected to be exceed on average once every years.
3. DAY-AHEAD DISPATCHING FORMULATION
,i t
PC Production cost function for unit i at time t
,i tP Generation of unit i at time
,w tP Wind power forecast for unit w at time t
t
DP Power demand at time t
t
LP Power losses at time t
T Number of periods in the planning horizon
G Number of generating power units
W Number of wind power units
.i t
C Cost of load-following for unit i at time t
,i t
Load-following ramping for unit i at time t
limit
i
Load-following ramping limits for unit i
,
min
i t
P Lower limit of power generation of unit unit i
,
max
i t
P Upper limit of power generation of unit unit i
,i tu Binary commitment state for unit i at time t
,i t
upC Startup cost for unit i at time t
,i t
downC Shutdown cost for unit i at time t
,i tl Binary startup variable for unit i
,i tk Binary shutdown variable for unit i
t Index for time
The day-ahead dispatching is formulated as a mixed-integer linear quadratic optimization problem.
The objective function is composed of production cost of power generation, cost for load-following (up and
down), and costs for startup and shutdown of each generating unit (5). The operating costs of wind units are
zero. The constraints includes the power balance constraint (7). The load following ramping limits are given
by the restriction (8). The integer constraints indicating the binary startup and shutdown states are in (9).
The power unit generating limits in (10). The constraint about the capacity limits, the tap changing and phase
shifting for transformers are given in (11).
, ,.,min
i t i ti ti t
P
t T i G
C P C b
(5)
, ,, ,i t i ti t i t
up downb C l C k (6)
Subject to:
, ,
L
t ti t w t
D
i G w W
P P P P
(7)
,
limit0 i t i
(8)
, ,0,1 , 0,1i t i tl k (9)
1 p pz
pz 1/ p
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, , ,
min max
i t i t i t
P P P (10)
,
L, , 0i t t t
DH P P P (11)
4. CASE OF STUDY
We propose to quantify the operating reserve in day-ahead dispatching performing an optimal power
flow for the wind power trajectories generated with GEV functions according to the premise: than 5% of
hourly wind power ramps had a magnitude greater than three standard deviations. In particular, we use
the IEEE 39-bus test system, this system includes 10 generators, 46 branches and 19 loads. The data of
the generators is listed in Table 1. The system load curve for a 24-hour period has a peak load of 4531 MW at
hour 20 as shown in Figure 4.
Table 1. Generator Data for the IEEE 39 Bus system
Gen #
1 6.9 6.9 920 736 0 250
2 6.9 6.9 920 736 0 678
3 6.9 6.9 920 736 0 650
4 6.9 6.9 920 736 0 632
5 6.9 6.9 920 736 0 508
6 6.9 6.9 920 736 0 650
7 6.9 6.9 920 736 0 560
8 6.9 6.9 920 736 0 540
9 6.9 6.9 920 736 0 830
10 6.9 6.9 920 736 0 1000
Figure 4. System load curve
The cost data are quadratic functions as reported in [22-24]. Table 2 lists the cost functions for
the ten conventional generators. This quadratic cost functions characterize more appropriately the cost
structure of thermal generation in power systems.
Table 2. Cost Functions
Gen Cost Function [$]
1
2
3
4
5
6
7
8
9
10
C C vC wC minP maxP
2
1 0.00194 7.85 310C P P
2
2 0.0035 8.5 260C P P
2
3 0.00482 7 78C P P
2
4 0.00128 6.4 459C P P
2
5 0.0024 6 80C P P
2
6 0.0032 5.8 400C P P
2
7 0.0053 6.24 120C P P
2
8 0.00185 8.4 60C P P
2
9 0.0025 5.75 450C P P
2
10 0.00142 8.2 510C P P
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5. SIMULATION RESULTS
In this section, we provide simulation results to quantify operating reserves with high penetration of
wind power. The day-ahead dispatching model for the IEEE-39 bus test system is a mixed-integer linear
quadratic optimization problem. We use GUROBI 7.5.1 [25] under the platform of Matpower [26] as solver.
The simulations were completed by a PC with Intel Core i7 - 3537U CPU @ 2.00 GHZ with 8.00 GB RAM.
We run a day-ahead dispatching to obtain results from scenarios to capture wind power uncertainty. We run
the wind power scenarios for both tails. The cost function, in Figure 5, reveals values in the right tail given
the wind power modelling with generalized extreme values, corresponding to scenarios with high operating
costs. The parameters for the generalized extreme function are 0.346, 4041.57, 513638.
Figure 6 reveals values in the left tail, corresponding to scenarios with high penetration of wind power.
The generalized extreme values parameters are 0.224, 4821.49, 528257, it represents
the cost function in terms of a GEV function.
Figure 5. Operating cost for the IEEE 39-bus test
system with values in the right tail
Figure 6. Operating cost for the IEEE 39-bus test
system with values in the left tail
For wind power, the percentage of cases beyond three sigmas for each period is reported in Table 3.
In hour two, there is a five percentage (5%) of cases where the wind power output is beyond three sigmas in
the right tail. Wind generation is a variable energy resource with changing availability level over the time
(variability), which cannot be predicted with perfect accuracy (uncertainty) [27] As wind power increases,
the additional variability and uncertainty introduced in the system will cause an increase of operating
reserves in the system [19]. In order to proposed a operaing reserve function in MW related to the power
system, we quantified the operating reserve up in the left stage and the operating reserve down in
the right stage.
Table 3. Percentaje of cases in each hour beyond three sigmas
Period [Hour] Cases (%) Period [Hour] Cases (%) Period [Hour] Cases (%)
1 4.2 9 4.6 17 1.6
2 5 10 1.4 18 2.6
3 3.4 11 2.6 19 1.8
4 4 12 2.6 20 2.8
5 3.2 13 2.2 22 3.2
6 4.2 14 2 22 3.4
7 4 15 2.8 23 1.6
8 2.2 16 1.8 24 2
In addition, we plot downward ramping reserves and upward ramping reserves under the modelling
of wind power using generalized extreme values to quantify reserves. Figure 7 shows the downward ramping
reserves, the mean value is 2600 MW, but, the key result is about the values in the right tail. We observe
values around 3100 MW. This values indicates that the operation planning in day-ahead dispatching may
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require 3100 MW to mitigate the wind power uncertainty. Figure 8 shows the upward ramping reserves.
In both cases, there is values in the tails. The operating reserves are adjusted to a GEV function type II,
the parameters of scale, location and shape are indicated in Table 4 for downward and upward operating
reserves.
Figure 7. Downward ramping reserve quantities for
the right tail in the IEEE 39-bus test system
Figure 8. Upward ramping reserve quantities for
the left tail in the IEEE 39-bus test system
Table 4. Operating reserves function
ε β µ
Left Tail -0.215 200.1 2537.5
Right Tail -0.224 164.3 2617.5
6. CONCLUSION
This paper provides insights about the dispersion related with wind power and an aproach to
quantify the reserves needed to mitigate the intermittency. This paper proposes a mixed integer linear
quadractic problem to characterize day-ahead dispatching. The results offers evidences that wind power
uncertainty have great impact on the scheduling of generating units in the day-ahead market with
implications on ramping reserves. The operating reserves follow a generalized extreme value (GEV)
distribution if the wind power follow a GEV function type II as its suggest by the analysis of wind data of
wind plants. The approach proposed in this paper allows to deduce the expected distribution function for
operating reserves.
ACKNOWLEDGEMENTS
The authors acknowledge the support of the Universidad Autónoma de Occidente in Cali, Colombia.
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