A cooperative train control model for energy saving

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This paper proposes a cooperative train control model to minimize energy consumption in subway systems. The model optimizes driving strategies and efficiently uses regenerative energy between successive trains. It calculates optimal driving strategies given trip times that consider variable forces, speed limits, and gradients. It then formulates a model to adjust trip times for successive trains to better reuse regenerative energy. Case studies on a Beijing subway line show the approach effectively saves energy.

Education

A COOPERATIVE TRAIN CONTROL MODEL FOR ENERGY
SAVING
ABSTRACT
Energy efficiency is paid more and more attention in subway systems to reduce the
operational cost as well as ensure an environmentally friendly transportation mode. Optimization
on the driving strategy and efficient utilization of the regenerative energy are two effective
methods to reduce the energy consumption in electric rail systems. This paper proposes a
cooperative train control model to minimize the practical energy consumption, i.e., the difference
between the traction energy of the successive train and the reused energy from regeneration.
Firstly, we design a numerical algorithm to calculate the optimal driving strategy with a given
trip time, in which the variable traction forces, speed limits, and gradients are considered. Then
we formulate a cooperative train control model to adjust the trip time of the successive train for
efficient use of the regenerative energy. Finally, the optimal driving strategy of the following trip
is obtained for the successive train with the optimal departure time. Furthermore, some case
studies based on the Beijing Yizhuang subway line are presented to illustrate the effectiveness of
the proposed approach on energy-saving.

This document discusses the optimization of hydro-mechanical power split transmissions. It begins by providing background on continuously variable transmissions and why hydro-mechanical power split transmissions are promising. It then describes the optimization problem as designing the transmission to maximize average efficiency by selecting displacements of the hydraulic machines and gear ratios. An optimization algorithm using particle swarm methods is used to solve this problem. Finally, the optimization method will be applied to study transmissions for a compact loader and agricultural tractor.

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UOC Universitat Oberta de Catalunya

In this presentation the authors (Angel A. Juan, Jarrod Goentzel, Tolga Bektas) discuss the vehicle routing problem with multiple driving ranges. The presentation describes an integer programming formulation and a multi-round heuristic algorithm that iteratively constructs a solution to the problem. Using a set of benchmarks adapted from the literature, the algorithm is employed to analyse how distance-based costs are increased when considering ‘greener’ fleet configurations – ie, when using electric vehicles with different degrees of autonomy.

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This document discusses electro-hydraulic actuators and modeling them using bond graphs. It introduces electro-hydraulic actuators and how they involve both electrical and hydraulic systems with multiple energy conversions. It explains that bond graphs can model systems with different energy domains using a single model. The document then presents the working of electro-hydraulic actuators, how they deliver power without taking up much space or weight. It describes creating a simplified one-line bond graph and state space equation to model the actuator, ignoring some parameters. It concludes that bond graphs can efficiently model heterogeneous systems like electro-hydraulic actuators and the complexity can be varied as needed.

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elelijjournal

In the deregulated power system, transmission pricing has become a very important task because it is necessary to develop an efficient, feasible and reliable pricing scheme that can generate the useful economic signals to network users such as generating companies, transmission companies, distribution companies and customers. The objective of this paper is to compare transmission usage and cost allocation scheme to loads (and/or generators) based on Shapley value method and power flow tracing method.Modified Kirchhoff matrix is used for power flow tracing. A comparison is done between the both methods. A case study based on sample 6 bus power system is applied to check the feasibility and reliability of the proposed usage and cost allocation methodology.

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This document presents a study on designing a standalone hybrid renewable energy system (HRES) for a residential community in Pakistan using PV, wind, diesel, and battery. Nine system configurations were analyzed using HOMER software to determine the optimal and most economical design. HOMER results showed a PV-wind-battery system with 13.4 kW PV, 4 kW wind, and 20 battery units was optimal, with a net present cost of $28,620 and cost of energy of $0.311/kWh. MATLAB/Simulink modeling validated this design could maintain voltages and safe battery SOC while meeting load, even with generation and demand fluctuations. The HRES design and control strategy presented provides a tool for planning

Optimal power flow based congestion management using enhanced genetic algorithms

IJECEIAES

Congestion management (CM) in the deregulated power systems is germane and of central importance to the power industry. In this paper, an optimal power flow (OPF) based CM approach is proposed whose objective is to minimize the absolute MW of rescheduling. The proposed optimization problem is solved with the objectives of total generation cost minimization and the total congestion cost minimization. In the centralized market clearing model, the sellers (i.e., the competitive generators) submit their incremental and decremental bid prices in a real-time balancing market. These can then be incorporated in the OPF problem to yield the incremental/ decremental change in the generator outputs. In the bilateral market model, every transaction contract will include a compensation price that the buyer-seller pair is willing to accept for its transaction to be curtailed. The modeling of bilateral transactions are equivalent to the modifying the power injections at seller and buyer buses. The proposed CM approach is solved by using the evolutionary based Enhanced Genetic Algorithms (EGA). IEEE 30 bus system is considered to show the effectiveness of proposed CM approach.

The document introduces a new model for predicting energy consumption in vehicles using a random forest algorithm. It aims to create a more versatile tool that can predict energy use for different vehicle types and specifications, as well as varying environmental conditions. The model is tested using cross-validation and other methods to analyze the robustness of the random forest approach for energy consumption forecasting. The goal is to develop an accurate model that can predict energy use for light-duty and heavy-duty fuel vehicles as well as other vehicle types like hybrid and electric vehicles anywhere in the world.

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Bahlakoana Kikine

This document summarizes a study analyzing the potential for a run-of-river hydropower plant with the following key findings: The optimal design was determined to have a flow of 2.57 m3/s, use a Francis turbine with 92.2 m net head, generate 2.1 MW/yr of power and 5173 MWh/yr of energy. Calculations using RETScreen software found the project would reach the profit breakeven point within 7 years. This estimated annual energy production could supply electricity to around 1400 homes. The study analyzed flow duration curves, developed energy-power curves, and conducted cost-benefit and cash flow analyses to determine the optimal plant capacity.

Scientific research of paper presentation.pdf

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This paper discusses a modeling framework for calculating electricity prices in Rwanda based on different types of power generation. The results come from simulating hydro, thermal, and solar power. A graphical user interface was used to calculate output based on inputs. Total power losses were calculated for each substation based on transmission distance and amounted to 1398.4694 kW. The paper concludes that using models and computational techniques can help Rwandan institutions and support decision making and future electricity network and pricing predictions. It is recommended to apply these modeling approaches across Rwanda's electricity production, transmission and distribution.

Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...

IJAAS Team

This document presents a matrix methodology for allocating the costs of reactive power flows in transmission networks. The methodology traces reactive power flows through the network using Kirchhoff's current law and proportional sharing principles. It then allocates the costs of reactive power to generators and loads using the MVAr-mile method. The methodology is demonstrated on sample 6-bus and IEEE 14-bus test systems. Results show the allocated reactive power flows to different loads and the costs allocated to loads for recovery of total reactive power costs in the transmission network.

Cuckoo Search Algorithm for Congestion Alleviation with Incorporation of Wind...

IJECEIAES

The issue to alleviate congestion in the power system framework has emerged as an alluring field for the power system researchers. The research conducted in this article proposes a cuckoo search algorithm-based congestion alleviation strategy with the incorporation of wind farm. The bus sensitivity factor data are computed and utilized to sort out the sutiable position for the installation of the wind farm. The generators contributing in the real power rescheduleing process are selected as per the generator sensitivity values. The cuckoo search algorithm is implemented to minimize the congestion cost with the embodiment of the wind farm. The proposed method is tested on 39 bus New England framework and the results obtained with the cuckoo search-based congestion management approach outperforms the results opted with other heuristic optimization techniques in the past research literatures.

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This document provides a detailed review of vibration energy harvesting in automotive suspension systems. It discusses how regenerative suspensions with energy harvesting shock absorbers can convert wasted vibration energy into electricity. The most common energy harvesting systems used in vehicle suspensions are electromagnetic harvesters, which can be either linear or rotary. Linear electromagnetic harvesters directly convert vertical vibration into electricity, while rotary harvesters use mechanisms like ball screws or rack-pinions to transform linear vibration into rotational motion to drive a generator. Both types aim to improve fuel efficiency by recovering energy normally lost as heat in traditional dampers.

Simulating combined cycle gas turbine power plants in aspen hysys

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The document describes a methodology for simulating the off-design operation of a triple-pressure reheat combined cycle gas turbine (CCGT) power plant in Aspen HYSYS. It presents the modeling equations that capture the full off-design characteristics of plant components like compressors, turbines, heat recovery steam generators, and steam turbines. It also proposes a specially tailored procedure for solving the complex nonlinear calculations required in Aspen HYSYS. The simulation results from the Aspen HYSYS model are then compared to an equivalent model from GateCycle, showing good agreement between the two with average differences of less than 2.0% for power outputs and 1.5% for thermal efficiencies.

International Journal of Computational Engineering Research(IJCER)

ijceronline

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This paper presents a new multi-objective optimization algorithm for solving economic load dispatch problems in power systems. The algorithm uses linear programming techniques to minimize total generation cost while meeting constraints like line flows, voltage limits, and emission levels. It models both real and reactive power optimization problems and can handle emergency situations like transmission line outages. The algorithm is tested on two power system examples and shown to obtain optimal solutions balancing objectives such as economy, reliability and environmental impact.

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Due to the growth of demand for electric power, electric power loss reduction takes great attention for the power utility. In this paper, a low-level generation or distributed generation (DG) has been used for transmission power losses reduction. Karbala city transmission network (which is the case study) has been represented by using MATLAB m-file to study the load flow and the power loss for it. The paper proposed the particle swarm optimization (PSO) technique in order to find the optimal number and allocation of DG with the objective to decrease power losses as possible. The results show the effect of the optimal allocation of DG on power loss reduction.

Capacitor Placement and Reconfiguration of Distribution System with hybrid Fu...

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Soft Computing Technique Based Enhancement of Transmission System Lodability ...

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Due to the growth of electricity demands and transactions in power markets, existing power networks need to be enhanced in order to increase their loadability. The problem of determining the best locations for network reinforcement can be formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). The complexity of the problem makes extensive simulations necessary and the computational requirement is high. This paper compares the effectiveness of Evolutionary Programming (EP) and an ordinal optimization (OO) technique is proposed in this paper to solve the MDCP involving two types of flexible ac transmission systems (FACTS) devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), for system loadability enhancement. In this approach, crude models are proposed to cope with the complexity of the problem and speed up the simulations with high alignment confidence. The test and Validation of the proposed algorithm are conducted on IEEE 14–bus system and 22-bus Indian system.Simulation results shows that the proposed models permit the use of OO-based approach for finding good enough solutions with less computational efforts.

Control and energy management of a large scale grid connected pv system

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Power quality is highlighted as an important parameter in modern power systems. Moreover, grid-connected photovoltaic power plants are increasing significantly in size and capacity. Elsewhere, due to the progressive integration of nonlinear loads in the grid, the principal role of a Solar Energy Conversion System (SECS) is not only to capture the maximum power from solar but, also to ensure some ancillary services and improve the quality of power. This paper presents a novel strategy dedicated to improve the management of active power generation, reactive power compensation and power quality of a SECS, while guaranteeing the possibility of exploiting the full capacity of the Power Conditioning System (PCS) and the PhotoVoltaic System (PVS). The proposed control algorithm is applied to a large scale PVS connected to the grid through a cascade of a DC-DC converter and a PWM inverter. This control strategy manages the SECS function’s priorities, between main active power generation, reactive power compensation and active filtering in such a way to guarantee a smooth and stable DC voltage and ensure a sinusoidal grid current. Top priority is given to the active power production over power quality improvement. Then, priority is given to reactive power compensation over mitigation of current harmonics absorbed by the non-linear load connected to the Point of Common Coupling (PCC). Moreover, the whole system upper limits of active and reactive powers have been determined in the (PQ) power plane on the basis of PVS available power, converters rated power and DC bus voltage smoothness and stability. Finally, a control procedure dedicated to the calculation of the inverter current commands is proposed in order to exploit the full capacity of the SECS and respect the determined power limits. Simulation results confirm the effectiveness and the performance of this control strategy and prove that the SECS can operate at its full power whilst the power quality can be improved by reactive power compensation and active filtering.

Control and energy management of a large scale grid-connected PV system for p...

Asoka Technologies

Environmental and economic benefits of car exhaust heat recovery

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Car exhaust heat recovery is being investigated in recent years as a way to increase the efficiency of Internal Combustion engines . Also to reduce CO2 emissions by converting the thermal energy to electrical, employing either thermal fluid systems (mainly the Rankine Cycle) or Thermoelectric Generators. Research has shown that conversion of 10% of this waste heat into electricity may result to an increase of fuel efficiency of up to 20%. Particularly, in the case of heavy duty vehicles . There is evidence in the literature that assuming certain designs and manufacturing costs, a heat recovery system can increase the efficiency by almost 30%.

Abstract

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This thesis examines the efficiency of a hybrid turbocharger for use in a hybrid electric vehicle through computer simulation. The aim is to evaluate the viability of an internal combustion engine equipped with a hybrid turbocharger. Applying a hybrid turbocharger can improve engine efficiency without significant increases in losses. Fuel consumption simulations of a vehicle using an engine with a hybrid turbocharger found marginal decreases in fuel consumption between -2.5% to 1.6% compared to a non-hybrid turbocharger engine. The hybrid turbocharger electric motor can also help reduce turbo lag, which has a negative impact on engine performance, emissions and fuel consumption, especially for a hybrid vehicle.

Integrating probabilistic assessment of security of electricity supply into l...

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EFEU / FLEXe Ahonen Tero energy efficiency opportunities at system levels

CLIC Innovation Ltd

This document discusses opportunities for improving energy efficiency at the systems level for fluid handling systems. It notes that while component efficiency has improved, there are still significant savings potential through optimized variable speed operation, improved system design and integration. Specific opportunities mentioned include using more efficient motor designs integrated with flow devices, optimizing system sizing using tools to right-size pumps and motors, implementing variable speed control optimized for different operating conditions, and redesigning fluid devices like pulpers to reduce energy consumption by 30-50%. The EFEU program aims to develop these system-level efficiency improvements and estimates potential savings of 2-4% from more efficient pumps and motors and up to 30% from optimized speed control and system sizing.

A comparative study of energy management schemes for a fuel cell hybrid emerg...

Asoka Technologies

This paper presents a comparative analysis of different energy management schemes for a fuel-cell-based emergency power system of a more-electric aircraft. The fuel-cell hybrid system considered in this paper consists of fuel cells, lithium-ion batteries, and supercapacitors, along with associated dc/dc and dc/ac converters. The energy management schemes addressed are state of the art and are most commonly used energy management techniques in fuel-cell vehicle applications, and they include the following: the state machine control strategy, the rule-based fuzzy logic strategy, the classical proportional–integral control strategy, the frequency decoupling/fuzzy logic control strategy, and the equivalent consumption minimization strategy. The main criteria for performance comparison are the hydrogen consumption, the state of charges of the batteries/supercapacitors, and the overall system efficiency. Moreover, the stresses on each energy source, which impact their life cycle, are measured using a new approach based on the wavelet transform of their instantaneous power. A simulation model and an experimental test bench are developed to validate all analysis and performances.

Energy-Efficient Driving in the Portuguese Rail Operation (MSc. Dissertation ...

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The main share of energy consumption in railways consists of traction energy, i.e., energy required to move the trains. The amount of energy consumed is much influenced by the way the train is driven within schedule. As each driver has its own driving style and since the deduction of the energy-efficient driving strategy is not trivial, there are now available Driving Advice Systems to assist drivers in choosing the most energy-efficient actions. The aim of this study was to develop an energy-efficient driving model in order to derive, for a given route and running time, an energy-efficient speed profile. The driving model was used to build efficient driving strategies for regional and inter-regional rail services in the Douro line. The model’s energy saving potential evaluation was done by using a train-running simulator in order to compare the driver’s actions and speed profiles of real cases with the most efficient driving strategies for the same situations. The simulation results point to an energy saving potential between 11 and 15%, just by changing the driving style. Finally, a Driver Advice System prototype was developed, in order to assist the driver in adopting an efficient driving strategy. The prototype has been developed for the Android platform, to be implemented in a low-cost equipment, such as a tablet, equipped with GPS receiver.

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This document discusses energy efficiency in railway transportation across three key areas: railway infrastructure, traffic management, and dynamic train movement. 1) Railway infrastructure, such as line gradients and curvatures, have a significant impact on energy consumption for train haulage. Steeper gradients and tighter curves increase resistance and energy use. 2) Traffic management procedures, like station design and use of automatic block systems, also influence energy efficiency. Level crossings and stopping before signals cause unnecessary braking and acceleration that waste energy. 3) Dynamic train movement parameters including weight, speed, and acceleration must be optimized given the infrastructure. Heavier trains and higher speeds increase energy consumption.

What's hot

Abstract

Ana Francisca Menezes

Undergrad_Poster

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Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...

IJAAS Team

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Farag1995

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Power losses reduction of power transmission network using optimal location o...

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Control and energy management of a large scale grid connected pv system

Asoka Technologies

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Asoka Technologies

Environmental and economic benefits of car exhaust heat recovery

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Abstract

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Abstract

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Scientific research of paper presentation.pdf

Cost Allocation of Reactive Power Using Matrix Methodology in Transmission Ne...

Cuckoo Search Algorithm for Congestion Alleviation with Incorporation of Wind...

Control and maximization of energy using pmsg based generator (2)

Power Generation

Simulating combined cycle gas turbine power plants in aspen hysys

International Journal of Computational Engineering Research(IJCER)

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Power losses reduction of power transmission network using optimal location o...

Capacitor Placement and Reconfiguration of Distribution System with hybrid Fu...

Soft Computing Technique Based Enhancement of Transmission System Lodability ...

Control and energy management of a large scale grid connected pv system

Control and energy management of a large scale grid-connected PV system for p...

Environmental and economic benefits of car exhaust heat recovery

Abstract

Integrating probabilistic assessment of security of electricity supply into l...

EFEU / FLEXe Ahonen Tero energy efficiency opportunities at system levels

A comparative study of energy management schemes for a fuel cell hybrid emerg...

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