The Benefits of Distributed Generation in Smart-Grid Environment- A Case Study


Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

The Benefits of Distributed Generation in Smart-Grid Environment- A Case Study

  1. 1. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 143 The Benefits of Distributed Generation in Smart-Grid Environment- A Case Study Jitendra Singh Bhadoriya, Aashish Kumar Bohre, Dr. Ganga Agnihotri, Dr. Manisha Dubey DAVV INDORE, MANIT BHOPAL, MANIT BHOPAL MANIT BHOPALAbstract: This work presents a review on multi objective simple form, they consist of a compressor, combustor,performance index-based size and location determination of recuperator, small turbine, and generator. Sometimes, theydistributed generation in distribution systems with different have only one moving shaft, and use air or oil for lubrication.load models. Normally, a constant power (real and reactive) MTs are small scale of 0.4–1m3 in volume and 20–500kW inload model is assumed in most of the studies made in the size. Unlike the traditional combustion turbines, MTs run atliterature. It is shown that load models can significantly less temperature and pressure and faster speed (100,000 rpm),affect the optimal location and sizing of distributed which sometimes require no gearbox. Some existinggeneration (DG) resources in distribution systems. The commercial examples have low costs, good reliability, fastsimulation technique based on particle swarm technology is speed with air foil bearings ratings range of 30–75kW arestudied. Government of India has recently formed “Smart installed in North-eastern US and Eastern Canada andGrid Forum” and “Smart Grid Task Force” for enablement Argentina by Honeywell Company and 30–50kW forof smart grid technology into Indian Power Distribution Capstone and Allison/GE companies, respectively . AnotherUtilities as a part of their Smart Grid initiative to meet their example is ABB MT: of size 100kW, which runs at maximumgrowing energy demand in similar with the developed power with a speed of 70,000 rpm and has one shaft with nocountry like USA, Europe etc. gearbox where the turbine, compressor, and a special designed high speed generator are on the same shaft.Keywords: Distributed generation (DG), Smart Grid, particleswarm (PSO). I. INTRODUCTIONDistributed generation (DG) is not a new concept but it is anemerging approach for providing electric power in the heart ofthe power system. It mainly depends upon the installation andoperation of a portfolio of small size, compact, and cleanelectric power generating units at or near an electrical load(customer). Till now, not all DG technologies and types areeconomic, clean or reliable. Some literature studies delineatingthe future growth of DGs are. Surveying DG concepts mayinclude DG definitions, technologies, applications, sizes,locations, DG practical and operational limitations, and theirimpact on system operation and the existing power grid. Thiswork focuses on surveying different DG types, technologies,definitions, their operational constraints, placement and sizingwith new methodology particle swarm optimization. Fig. 1. Distributed generation types and technologies.Furthermore, we aim to present a critical survey by proposingnew DG in to conventional grid to make it smart grid. B) Electrochemical devices: fuel cell (FC) The fuel cell is a device used to generate electric power and provide thermal energy from chemical energy through II. DG TYPES AND RANGE electrochemical processes. It can be considered as a battery supplying electric energy as long as its fuels are continued toThere are different types of DGs from the constructional and supply. Unlike batteries, FC does not need to be charged fortechnological points of view as shown in Fig. 1. These types of the consumed materials during the electrochemical processDGs must be compared to each other to help in taking the since these materials are continuously supplied. FC is a well-decision with regard to which kind is more suitable to be known technology from the early 1960s when they were usedchosen in different situations. However, in our paper we are in the Modulated States Space Program and many automobileconcerned with the technologies and types of the new industry companies. Later in 1997, the US Department ofemerging DGs: micro-turbines and fuel cells. The different Energy tested gasoline fuel for FC to study its availability forkinds of distributed generation are discussed below. generating electric power. FC capacities vary from kW to MW for portable and stationary units, respectively. A) Micro-turbine (MT)Micro-turbine technologies are expected to have a bright C) Storage devicesfuture. They are small capacity combustion turbines, which It consists of batteries, flywheels, and other devices, which arecan operate using natural gas, propane, and fuel oil. In a charged during low load demand and used when required. It is
  2. 2. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 144usually combined with other kinds of DG types to supply the IV. IMPORTANT OF LOAD MODELINGrequired peak load demand. These batteries are called “deep The power system engineer bases decisions concerning systemcycle”. Unlike car batteries, “shallow cycle” which will be reinforcements and system performance in large part on thedamaged if they have several times of deep discharging, deep results of power flow and stability simulation studies.cycle batteries can be charged and discharged a large number Representation inadequacies that cause under or over buildingof times without any failure or damage. These batteries have a of the system or degradation of reliability could prove to becharging controller for protection from overcharge and over costly. In performing power system analysis, models must bedischarge as it disconnects the charging process when the developed for all pertinent system components, includingbatteries have full charge. The sizes of these batteries generating stations, transmission and distribution equipment,determine the battery discharge period. However, flywheels and load devices. Much attention has been given to models forsystems can charge and provide 700kW in 5 s. generation and transmission/distribution equipment. The representation of the loads has received less attention and D) Renewable devices continues to be an area of greater uncertainty. Many studiesGreen power is a new clean energy from renewable resources have shown that load representation can have significantlike; sun, wind, and water. Its electricity price is still higher impact on analysis results. Therefore, efforts directed atthan that of power generated from conventional oil sources. improving load modeling are of major importance. E) DG capacities: V. LOAD MODELS AND IMPACT INDICES DG capacities are not restrictedly defined as they depend The optimal allocation and sizing of DG units under different on the user type (utility or customer) and/or the used voltage-dependent load model scenarios are to be investigated. applications. These levels of capacities vary widely from Practical voltage-dependent load models, i.e., residential, one unit to a large number of units connected in a modular industrial, and commercial, have been adopted for form. investigations. The load models can be mathematically expressed as:Table 1 Comparison between common energy types for power and time durationPower period DG Remarkssupplied typeLong period Gas turbine and Provide P and Q except Where Pi and Qi are real and reactive power at bus i, Poi andsupply FC stations FC provides P only. Qoi are the active and reactive operating points at bus i, Vi is Used as base load the voltage at bus i, and α and β are real and reactive power provider. exponents. In the constant power model conventionally used inUnsteady Renewable Depend on weather power flow studies, α = β = 0 is assumed. The values of thesupply energy systems; conditions. real and reactive exponents used in the present work for PV arrays, WT Provide P only and need industrial, residential, and commercial loads are given in Table a source of Q in the 3. network. Table 2 Load types and exponent values. Used in remote places. Need control on their operation in some applications.Short period FC storage Used for supplysupply units, batteries, continuity. PV cells Store energy to use it in need times for a short period. III. DESCRIPTION OF A POWER SYSTEMA power system must be safe, reliable, economical, benign tothe environment and socially acceptable. The power system issubdivided into Generation, Transformer, Transmission andSub-Transmission, Distribution and Loads. The followingsection will examine each of the sub-system in detailed. Thedistribution system is the part that the sub-transmission linestypically deliver their power to locations called substationswhere the voltage is transformed downward to a voltage that isrequired by the customers. The voltage of the distributionsystem is between 4.6KV and 25KV. Fig. 2 IEEE 38-bus test system
  3. 3. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 145 VI. METHODOLOGY Analysis such as Load Flow Analysis, Fault Analysis, StabilityParticle swarm optimization (PSO) is a population based Analysis and Optimal Dispatch on Power Generation.stochastic optimization technique developed by Dr. Eberhartand Dr. Kennedy in 1995, inspired by social behavior of bird i) Load Flow Analysis is important to analyze any planning forflocking or fish schooling. power system improvement under steady state conditions such as to build new power generation capacity, new transmissionPSO shares many similarities with evolutionary computation lines in the case of additional or increasing of loads, to plantechniques such as Genetic Algorithms (GA). The system is and design the future expansion of power systems as well as ininitialized with a population of random solutions and searches determining the best operation of existing systems.for optima by updating generations. However, unlike GA, PSOhas no evolution operators such as crossover and mutation. In ii) Fault Analysis is important to determine the magnitude ofPSO, the potential solutions, called particles, fly through the voltages and line currents during the occurrence of variousproblem space by following the current optimum particles. types of fault.Compared to GA, the advantages of PSO are that PSO is easy iii) Stability Analysis is necessary for reliable operation ofto implement and there are few parameters to adjust. PSO has power systems to keep synchronism after minor and majorbeen successfully applied in many areas: function disturbances.optimization, artificial neural network training, fuzzy systemcontrol, and other areas where GA can be applied. iv) Optimal Dispatch is to find real and reactive power to power plants to meet load demand as well as minimize the operation cost. VII. THE PSO ALGORITHMAs stated before, PSO simulates the behaviors of bird flocking. All the analysis discussed above is an importance toolSuppose the following scenario: a group of birds are randomly involving numerical analysis that applied to a power system.searching food in an area. There is only one piece of food in In this analysis, there is no known analytical method to solvethe area being searched. All the birds do not know where the the problem because it depends on iterative is. But they know how far the food is in each iteration. So Iterative technique is one of the analysis that using a lot ofwhats the best strategy to find the food? The effective one is mathematical calculations which takes a lot of times toto follow the bird which is nearest to the food. perform by hand. So, to solve the problems, the development of this toolbox based on MATLAB 7.8 with Graphical UserPSO is initialized with a group of random particles (solutions) Interface (GUI) will help the analysis become quick and easy.and then searches for optima by updating generations. In everyiteration, each particle is updated by following two "best" The PSAT kernel is the power flow algorithm, which alsovalues. The first one is the best solution (fitness) it has takes care of the state variable initialization. Once the powerachieved so far. (The fitness value is also stored.) This value is flow has been solved, the user can perform further staticcalled pbest. Another "best" value that is tracked by the and/or dynamic analyses. These are:particle swarm optimizer is the best value, obtained so far by 1) Continuation Power Flow (CPF);any particle in the population. This best value is a global best 2) Optimal Power Flow (OPF);and called gbest. When a particle takes part of the population 3) Small signal stability analysis;as its topological neighbors, the best value is a local best and is 4) Time domain simulations.called lbest. Besides mathematical algorithms and models, PSAT includesAfter finding the two best values, the particle updates its a variety of additional tools, as follows:velocity and positions with following equations. 1) User-friendly graphical user interfaces; v[] = v[] + c1 * rand() * (pbest[] - present[]) + c2 * rand() 2) Simulink library for one-line network diagrams; *(gbest[] - present[]) 3) Data file conversion to and from other formats;present[] = persent[] + v[] 4) User defined model editor and installer;Where v[] is the particle velocity, persent[] is the current 5) Command line usage.particle (solution). pbest[] and gbest[] are defined as statedbefore, rand () is a random number between (0,1). c1, c2 are TABLE 3 Functions available on MATLAB andlearning factors usually c1 = c2 = 2. GNU/OCTAVE platforms VIII. OVERVIEW OF POWER SYSTEM TOOL ANALYSISPower System Analysis is an analysis that is so importantnowadays. It is not only important in economic scheduling, butalso necessary for planning and operation for a system. Basedon that, in recently years, there are many researches, newdevelopments and analysis was introduced to people in orderto mitigate the problems that involving Power System
  4. 4. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 146IX. DISTRIBUTED POWER APPLICATIONS power demands are among the major potential benefits thatDistributed power technologies are typically installed for one can accrue to the consumers.or more of the following purposes: Grid –Side Benefits: The grid benefits by way of reduced(i) Overall load reduction – Use of energy efficiency and other transmission and distribution losses, reduction in upstreamenergy saving measures for reducing total consumption of congestion on transmission lines, optimal use of existing gridelectricity, sometimes with supplemental power generation. assets, higher energy conversion efficiency than in central generation and improved grid reliability. Capacity additions(ii) Independence from the grid – Power is generated locally to and reductions can be made in small increments closelymeet all local energy needs by ensuring reliable and quality matching the demands instead of constructing Central Powerpower under two different models. Plants which are sized to meet a estimated future rather than a. Grid Connected – Grid power is used only as a current demand under distributed generation. back up during failure of maintenance of the onsite Benefits To Other Stake Holders: Energy Service generator. Companies get new opportunities for selling, financing and b. Off grid – This is in the nature of stand-alone managing distributed generation and load reduction power generation. In order to attain self-sufficiency it technologies and approaches. Technology developers, usually includes energy saving approaches and an manufacturers and vendors of distributed power equipment see energy storage device for back-up power. This opportunities for new business in an expanded market for their includes most village power applications in products. Regulators and policy maker’s support distributed developing countries. power as it benefits consumers and promotes competition.(iii) Supplemental Power- Under this model, power generatedby the grid is augmented with distributed generation for the B) The following are among the more important factors thatfollowing reasons: - contributed to the emergence of distributed generation as a a. Standby Power- Under this arrangement power new alternative to the energy crisis that surfaced in the USA. availability is assured during grid outages. b. Peak shaving – Under this model the power that is i. Energy Shortage –States likes California and New York that locally generated is used for reducing the demand for experienced energy shortages decided to encourage businesses grid electricity during the peak periods to avoid the and homeowners to install their own generating capacity and peak demand charges imposed on big electricity take less power from the grid. The California Public Utilities users. Commission for instance approved a programme of 125 US million $ incentives programme to encourage businesses and(iv) Net energy sales – Individual homeowners and homeowners to install their own generating capacity and takeentrepreneurs can generate more electricity than they need and less power from the grid. In the long run the factorssell their surplus to the grid. Co-generation could fall into this enumerated below would play a significant part in thecategory. development of distributed generation.(v) Combined heat and power - Under this model waste heat ii. Digital Economy –Though the power industry in the USAfrom a power generator is captured and used in manufacturing met more than 99% of the power requirements of the computerprocess for space heating, water heating etc. in order to based industries, these industries found that even a momentaryenhance the efficiency of fuel utilization. fluctuation in power supply can cause computer crashes. The(vi) Grid support – Power companies resort to distributed industries, which used computer, based manufacturinggeneration for a wide variety of reasons. The emphasis is on processes shifted to their own back-up systems for powermeeting higher peak loads without having to invest in generation.infrastructure (line and sub-station upgrades). iii. Continued Deregulation of Electricity Markets – The X. THE BENEFITS OF DISTRIBUTED progressive deregulation of the electricity markets in the USA POWER led to violent price fluctuations because the power generators,A) Energy consumers, power providers and all other state who were not allowed to enter into long-term wholesaleholders are benefited in their own ways by the adoption of contracts, had to pass on whatever loss they suffered only ondistributed power. The most important benefit of distributed the spot markets. In a situation like that in California wherepower stems from its flexibility, it can provide power where it prices can fluctuate by the hour, flexibility to switch onto andis needed and when it is needed. off the grid alone gives the buyer the strength to negotiate with the power supplier on a strong footing. Distributed generationThe major benefits of distributed power to the various in fact is regarded as the best means of ensuring competition instakeholders are as follows: the power sector.Major Potential Benefits of Distributed Generation C) Both in the USA and UK the process of de-regulation didConsumer-Side Benefits: Better power reliability and quality, not make smooth progress on account of the difficultieslower energy cost, wider choice in energy supply options, created by the regulated structure of the power market and abetter energy and load management and faster response to new monopoly enjoyed the dominant utilities.
  5. 5. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 147D) In fact, the current situation in the United States in the 7. Rahul Tongia; “Smart Grids White Paper” Center for Studypower sector is compared to the situation that arose in the of Science, Technology and PolicyTelecom Sector on account of the breakup of AT&T (CSTEP) CAIR Building, Raj Bhavan CircleCorporation’s monopoly 20 years ago. In other words 8. A. Bharadwaj; R. Tongia;. “Distributed Power Generation:distributed generation is a revolution that is caused by Rural India – A Case Study” supported in part by theprofound regulatory change as well as profound technical United Nations Foundation 5000 Forbes Avenue,change. Pittsburgh, PA 15213, USA. A.Hadi; F. Rashidi; “Design of Optimal Power Distribution Networks Using XI. CONCLUSION Multiobjective Genetic Algorithm” U. Furbach (Ed.): KISmart Grid is the modernization of the electricity delivery 2005, LNAI 3698, pp. 203 – 215, 2005.© Springer-Verlagsystem so that it monitors, protects and automatically Berlin Heidelberg 2005optimizes the operation of its interconnected elements – fromthe central and distributed generator through the high-voltage BIOGRAPHIESnetwork and distribution system, to industrial users and Jitendra Singh Bhadoriya,building automation systems, to energy storage installations Jitendra Singh Bhadoriya was born in Distt. Bhopal , India,and to end-use consumers and their thermostats, electric in 1989. He received BE degree (2011) from UIT- RGPVvehicles, appliances and other household devices. Smart grid Bhopal in electrical engineering , and at the moment he is anis the integration of information and communications system M-Tech (instrumentation) scholar at SCHOOL OFinto electric transmission and distribution networks. Some of INSTRUMENTATION DAVV, lndore, India. Email:the enabling technologies & business practice that make smart JITENDRIY@INDIA.COMgrid deployments possible include: Aashish Kumar Bohre, • Smart Meters Aashish Kumar Bohre was born in Distt. Hoshangabad, • Meter Data Management India, in 1984. He received BE degree (2009) from UIT- • Field area networks RGPV Bhopal, and M-Tech degree (Power System) in 2011 • Integrated communications systems from MANIT, Bhopal. At the moment he is PhD. scholar at • IT and back office computing MANIT, Bhopal, India. Email: • Data Security • Electricity Storage devices Dr. Ganga Agnihotri, • Demand Response Ganga Agnihotri received BE degree in Electrical • Distributed generation engineering from MACT, Bhopal (1972), the ME degree • Renewable energy (1974) and PhD degree (1989) from University of Roorkee, India. Since 1976 she is with Maulana Azad College of Technology, Bhopal in various positions. Currently she is professor. Her research interest includes Power System Analysis, Power System Optimization and Distribution REFERENCES Operation. 1. Sinha, A.; Neogi, S.; Lahiri, R.N.; Chowdhury, S.; Chowdhury, S.P.; Chakraborty, N.” Smart Grid Initiative Manisha Dubey was born in Jabalpur in India on 15th for Power Distribution Utility in India” pp:1-8 Power and December 1968. She received her B.E (Electrical), M.Tech. Energy Society General Meeting, 2011 IEEE (Power Systems) and Ph.D (Electrical Engg.) in 1990, 1997 2. Kumar ,L.D.;K.Ram Charan; “master slave control of interline power flow controller using PSO technique” issue and 2006 respectively. She is working as Professor at the 2,Vol.5(july 2012) international journal of emerging trends Department of Electrical Engineering, National Institute of in engineering & development Technology, Bhopal, India. Her research interests include 3. S.Mary Raja Slochanal; N.Shanmuga Vadivoo. power systems, Genetic Algorithms, Fuzzy Logic systems and “Distribution System Restoration Using Genetic Algorithm application of Soft Computing Techniques in power system with Distributed Generation” Vol.3 No.4 (aprail 2009) dynamics and control. modern applied science 4. Rangan Banerjee;. “Comparison of options for distributed generation in India” Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15217, USAEnergy policies Elsevier 5. S.P.Chowdhury, , S.Chowdhury, , Chui Fen Ten, and P.A.Crossley. “Islanding Protection of Distribution Systems with Distributed Generators A Comprehensive Survey Report “pp;1-8 2008 IEEE 6. S. M.Shamsuddin ;. “Particle Swarm Optimization: Technique, System and Challengegs” Volume 14– No.1, January 2011, International Journal of Computer Applications (0975 – 8887)