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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 BHOPAL


Abstract: 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, they
distributed 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 in
load model is assumed in most of the studies made in the           size. Unlike the traditional combustion turbines, MTs run at
literature. 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 existing
generation (DG) resources in distribution systems. The             commercial examples have low costs, good reliability, fast
simulation technique based on particle swarm technology is         speed with air foil bearings ratings range of 30–75kW are
studied. Government of India has recently formed “Smart            installed in North-eastern US and Eastern Canada and
Grid Forum” and “Smart Grid Task Force” for enablement             Argentina by Honeywell Company             and 30–50kW for
of smart grid technology into Indian Power Distribution            Capstone and Allison/GE companies, respectively . Another
Utilities as a part of their Smart Grid initiative to meet their   example is ABB MT: of size 100kW, which runs at maximum
growing energy demand in similar with the developed                power with a speed of 70,000 rpm and has one shaft with no
country 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, particle
swarm (PSO).

                  I. INTRODUCTION
Distributed generation (DG) is not a new concept but it is an
emerging approach for providing electric power in the heart of
the power system. It mainly depends upon the installation and
operation of a portfolio of small size, compact, and clean
electric power generating units at or near an electrical load
(customer). Till now, not all DG technologies and types are
economic, clean or reliable. Some literature studies delineating
the future growth of DGs are. Surveying DG concepts may
include DG definitions, technologies, applications, sizes,
locations, DG practical and operational limitations, and their
impact on system operation and the existing power grid. This
work focuses on surveying different DG types, technologies,
definitions, their operational constraints, placement and sizing
with new methodology particle swarm optimization.                      Fig. 1. Distributed generation types and technologies.
Furthermore, we aim to present a critical survey by proposing
new 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 to
There are different types of DGs from the constructional and       supply. Unlike batteries, FC does not need to be charged for
technological points of view as shown in Fig. 1. These types of    the consumed materials during the electrochemical process
DGs 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 used
chosen in different situations. However, in our paper we are       in the Modulated States Space Program and many automobile
concerned with the technologies and types of the new               industry companies. Later in 1997, the US Department of
emerging DGs: micro-turbines and fuel cells. The different         Energy tested gasoline fuel for FC to study its availability for
kinds 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 devices
future. They are small capacity combustion turbines, which         It consists of batteries, flywheels, and other devices, which are
can operate using natural gas, propane, and fuel oil. In a         charged during low load demand and used when required. It is
National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal                      144


usually combined with other kinds of DG types to supply the         IV. IMPORTANT OF LOAD MODELING
required peak load demand. These batteries are called “deep         The power system engineer bases decisions concerning system
cycle”. Unlike car batteries, “shallow cycle” which will be         reinforcements and system performance in large part on the
damaged 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 building
of times without any failure or damage. These batteries have a      of the system or degradation of reliability could prove to be
charging controller for protection from overcharge and over         costly. In performing power system analysis, models must be
discharge as it disconnects the charging process when the           developed for all pertinent system components, including
batteries 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 for
systems 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 studies
Green power is a new clean energy from renewable resources          have shown that load representation can have significant
like; sun, wind, and water. Its electricity price is still higher   impact on analysis results. Therefore, efforts directed at
than 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 duration
Power           period       DG Remarks
supplied        type
Long period Gas turbine and Provide P and Q except                  Where Pi and Qi are real and reactive power at bus i, Poi and
supply          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 in
Unsteady        Renewable          Depend on weather                power flow studies, α = β = 0 is assumed. The values of the
supply          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    supply
supply          units, batteries, continuity.
                PV cells           Store energy to use it in
                                   need times for a short
                                   period.

  III. DESCRIPTION OF A POWER SYSTEM
A power system must be safe, reliable, economical, benign to
the environment and socially acceptable. The power system is
subdivided into Generation, Transformer, Transmission and
Sub-Transmission, Distribution and Loads. The following
section will examine each of the sub-system in detailed. The
distribution system is the part that the sub-transmission lines
typically deliver their power to locations called substations
where the voltage is transformed downward to a voltage that is
required by the customers. The voltage of the distribution
system is between 4.6KV and 25KV.
                                                                                   Fig. 2 IEEE 38-bus test system
National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal                       145


                 VI. METHODOLOGY                                      Analysis such as Load Flow Analysis, Fault Analysis, Stability
Particle swarm optimization (PSO) is a population based               Analysis and Optimal Dispatch on Power Generation.
stochastic optimization technique developed by Dr. Eberhart
and Dr. Kennedy in 1995, inspired by social behavior of bird          i) Load Flow Analysis is important to analyze any planning for
flocking or fish schooling.                                           power system improvement under steady state conditions such
                                                                      as to build new power generation capacity, new transmission
PSO shares many similarities with evolutionary computation            lines in the case of additional or increasing of loads, to plan
techniques such as Genetic Algorithms (GA). The system is             and design the future expansion of power systems as well as in
initialized with a population of random solutions and searches        determining the best operation of existing systems.
for optima by updating generations. However, unlike GA, PSO
has no evolution operators such as crossover and mutation. In         ii) Fault Analysis is important to determine the magnitude of
PSO, the potential solutions, called particles, fly through the       voltages and line currents during the occurrence of various
problem 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 of
to implement and there are few parameters to adjust. PSO has          power systems to keep synchronism after minor and major
been successfully applied in many areas: function                     disturbances.
optimization, artificial neural network training, fuzzy system
control, 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 ALGORITHM
As stated before, PSO simulates the behaviors of bird flocking.       All the analysis discussed above is an importance tool
Suppose 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 solve
the area being searched. All the birds do not know where the          the problem because it depends on iterative technique.
food is. But they know how far the food is in each iteration. So      Iterative technique is one of the analysis that using a lot of
what's the best strategy to find the food? The effective one is       mathematical calculations which takes a lot of times to
to 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 User
PSO 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 every
iteration, each particle is updated by following two "best"           The PSAT kernel is the power flow algorithm, which also
values. The first one is the best solution (fitness) it has           takes care of the state variable initialization. Once the power
achieved so far. (The fitness value is also stored.) This value is    flow has been solved, the user can perform further static
called 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 includes
After 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 stated
before, rand () is a random number between (0,1). c1, c2 are                 TABLE 3 Functions available on MATLAB and
learning factors usually c1 = c2 = 2.                                                GNU/OCTAVE platforms

    VIII. OVERVIEW OF POWER SYSTEM
              TOOL ANALYSIS
Power System Analysis is an analysis that is so important
nowadays. It is not only important in economic scheduling, but
also necessary for planning and operation for a system. Based
on that, in recently years, there are many researches, new
developments and analysis was introduced to people in order
to mitigate the problems that involving Power System
National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal                       146


IX. DISTRIBUTED POWER APPLICATIONS                                   power demands are among the major potential benefits that
Distributed 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 upstream
energy saving measures for reducing total consumption of             congestion on transmission lines, optimal use of existing grid
electricity, 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 closely
meet all local energy needs by ensuring reliable and quality         matching the demands instead of constructing Central Power
power 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 generated
by the grid is augmented with distributed generation for the
                                                                     B) The following are among the more important factors that
following 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 take
entrepreneurs can generate more electricity than they need and       less power from the grid. In the long run the factors
sell their surplus to the grid. Co-generation could fall into this   enumerated below would play a significant part in the
category.                                                            development of distributed generation.
(v) Combined heat and power - Under this model waste heat            ii. Digital Economy –Though the power industry in the USA
from a power generator is captured and used in manufacturing         met more than 99% of the power requirements of the computer
process for space heating, water heating etc. in order to            based industries, these industries found that even a momentary
enhance 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 manufacturing
generation for a wide variety of reasons. The emphasis is on         processes shifted to their own back-up systems for power
meeting 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 wholesale
holders are benefited in their own ways by the adoption of           contracts, had to pass on whatever loss they suffered only on
distributed power. The most important benefit of distributed         the spot markets. In a situation like that in California where
power stems from its flexibility, it can provide power where it      prices can fluctuate by the hour, flexibility to switch onto and
is 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 generation
The major benefits of distributed power to the various               in fact is regarded as the best means of ensuring competition in
stakeholders are as follows:                                         the power sector.

Major Potential Benefits of Distributed Generation                   C) Both in the USA and UK the process of de-regulation did
Consumer-Side Benefits: Better power reliability and quality,        not make smooth progress on account of the difficulties
lower energy cost, wider choice in energy supply options,            created by the regulated structure of the power market and a
better energy and load management and faster response to new         monopoly enjoyed the dominant utilities.
National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal                          147


D) In fact, the current situation in the United States in the              7.   Rahul Tongia; “Smart Grids White Paper” Center for Study
power sector is compared to the situation that arose in the                     of Science, Technology and Policy
Telecom Sector on account of the breakup of AT&T                                (CSTEP) CAIR Building, Raj Bhavan Circle
Corporation’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 the
profound 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.): KI
Smart Grid is the modernization of the electricity delivery                     2005, LNAI 3698, pp. 203 – 215, 2005.© Springer-Verlag
system so that it monitors, protects and automatically                          Berlin Heidelberg 2005
optimizes the operation of its interconnected elements – from
the central and distributed generator through the high-voltage                         BIOGRAPHIES
network 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- RGPV
vehicles, appliances and other household devices. Smart grid           Bhopal in electrical engineering , and at the moment he is an
is the integration of information and communications system            M-Tech (instrumentation) scholar at SCHOOL OF
into electric transmission and distribution networks. Some of          INSTRUMENTATION DAVV, lndore, India. Email:
the enabling technologies & business practice that make smart          JITENDRIY@INDIA.COM
grid 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: aashish_bohre@yahoo.co.in
         • 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                                        Email:manishadubey6@gmail.com
    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)

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

  • 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 BHOPAL Abstract: 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, they distributed 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 in load model is assumed in most of the studies made in the size. Unlike the traditional combustion turbines, MTs run at literature. 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 existing generation (DG) resources in distribution systems. The commercial examples have low costs, good reliability, fast simulation technique based on particle swarm technology is speed with air foil bearings ratings range of 30–75kW are studied. Government of India has recently formed “Smart installed in North-eastern US and Eastern Canada and Grid Forum” and “Smart Grid Task Force” for enablement Argentina by Honeywell Company and 30–50kW for of smart grid technology into Indian Power Distribution Capstone and Allison/GE companies, respectively . Another Utilities as a part of their Smart Grid initiative to meet their example is ABB MT: of size 100kW, which runs at maximum growing energy demand in similar with the developed power with a speed of 70,000 rpm and has one shaft with no country 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, particle swarm (PSO). I. INTRODUCTION Distributed generation (DG) is not a new concept but it is an emerging approach for providing electric power in the heart of the power system. It mainly depends upon the installation and operation of a portfolio of small size, compact, and clean electric power generating units at or near an electrical load (customer). Till now, not all DG technologies and types are economic, clean or reliable. Some literature studies delineating the future growth of DGs are. Surveying DG concepts may include DG definitions, technologies, applications, sizes, locations, DG practical and operational limitations, and their impact on system operation and the existing power grid. This work focuses on surveying different DG types, technologies, definitions, their operational constraints, placement and sizing with new methodology particle swarm optimization. Fig. 1. Distributed generation types and technologies. Furthermore, we aim to present a critical survey by proposing new 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 to There are different types of DGs from the constructional and supply. Unlike batteries, FC does not need to be charged for technological points of view as shown in Fig. 1. These types of the consumed materials during the electrochemical process DGs 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 used chosen in different situations. However, in our paper we are in the Modulated States Space Program and many automobile concerned with the technologies and types of the new industry companies. Later in 1997, the US Department of emerging DGs: micro-turbines and fuel cells. The different Energy tested gasoline fuel for FC to study its availability for kinds 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 devices future. They are small capacity combustion turbines, which It consists of batteries, flywheels, and other devices, which are can operate using natural gas, propane, and fuel oil. In a charged during low load demand and used when required. It is
  • 2. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 144 usually combined with other kinds of DG types to supply the IV. IMPORTANT OF LOAD MODELING required peak load demand. These batteries are called “deep The power system engineer bases decisions concerning system cycle”. Unlike car batteries, “shallow cycle” which will be reinforcements and system performance in large part on the damaged 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 building of times without any failure or damage. These batteries have a of the system or degradation of reliability could prove to be charging controller for protection from overcharge and over costly. In performing power system analysis, models must be discharge as it disconnects the charging process when the developed for all pertinent system components, including batteries 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 for systems 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 studies Green power is a new clean energy from renewable resources have shown that load representation can have significant like; sun, wind, and water. Its electricity price is still higher impact on analysis results. Therefore, efforts directed at than 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 duration Power period DG Remarks supplied type Long period Gas turbine and Provide P and Q except Where Pi and Qi are real and reactive power at bus i, Poi and supply 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 in Unsteady Renewable Depend on weather power flow studies, α = β = 0 is assumed. The values of the supply 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 supply supply units, batteries, continuity. PV cells Store energy to use it in need times for a short period. III. DESCRIPTION OF A POWER SYSTEM A power system must be safe, reliable, economical, benign to the environment and socially acceptable. The power system is subdivided into Generation, Transformer, Transmission and Sub-Transmission, Distribution and Loads. The following section will examine each of the sub-system in detailed. The distribution system is the part that the sub-transmission lines typically deliver their power to locations called substations where the voltage is transformed downward to a voltage that is required by the customers. The voltage of the distribution system is between 4.6KV and 25KV. Fig. 2 IEEE 38-bus test system
  • 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, Stability Particle swarm optimization (PSO) is a population based Analysis and Optimal Dispatch on Power Generation. stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird i) Load Flow Analysis is important to analyze any planning for flocking or fish schooling. power system improvement under steady state conditions such as to build new power generation capacity, new transmission PSO shares many similarities with evolutionary computation lines in the case of additional or increasing of loads, to plan techniques such as Genetic Algorithms (GA). The system is and design the future expansion of power systems as well as in initialized with a population of random solutions and searches determining the best operation of existing systems. for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In ii) Fault Analysis is important to determine the magnitude of PSO, the potential solutions, called particles, fly through the voltages and line currents during the occurrence of various problem 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 of to implement and there are few parameters to adjust. PSO has power systems to keep synchronism after minor and major been successfully applied in many areas: function disturbances. optimization, artificial neural network training, fuzzy system control, 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 ALGORITHM As stated before, PSO simulates the behaviors of bird flocking. All the analysis discussed above is an importance tool Suppose 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 solve the area being searched. All the birds do not know where the the problem because it depends on iterative technique. food is. But they know how far the food is in each iteration. So Iterative technique is one of the analysis that using a lot of what's the best strategy to find the food? The effective one is mathematical calculations which takes a lot of times to to 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 User PSO 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 every iteration, each particle is updated by following two "best" The PSAT kernel is the power flow algorithm, which also values. The first one is the best solution (fitness) it has takes care of the state variable initialization. Once the power achieved so far. (The fitness value is also stored.) This value is flow has been solved, the user can perform further static called 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 includes After 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 stated before, rand () is a random number between (0,1). c1, c2 are TABLE 3 Functions available on MATLAB and learning factors usually c1 = c2 = 2. GNU/OCTAVE platforms VIII. OVERVIEW OF POWER SYSTEM TOOL ANALYSIS Power System Analysis is an analysis that is so important nowadays. It is not only important in economic scheduling, but also necessary for planning and operation for a system. Based on that, in recently years, there are many researches, new developments and analysis was introduced to people in order to mitigate the problems that involving Power System
  • 4. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 146 IX. DISTRIBUTED POWER APPLICATIONS power demands are among the major potential benefits that Distributed 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 upstream energy saving measures for reducing total consumption of congestion on transmission lines, optimal use of existing grid electricity, 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 closely meet all local energy needs by ensuring reliable and quality matching the demands instead of constructing Central Power power 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 generated by the grid is augmented with distributed generation for the B) The following are among the more important factors that following 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 take entrepreneurs can generate more electricity than they need and less power from the grid. In the long run the factors sell their surplus to the grid. Co-generation could fall into this enumerated below would play a significant part in the category. development of distributed generation. (v) Combined heat and power - Under this model waste heat ii. Digital Economy –Though the power industry in the USA from a power generator is captured and used in manufacturing met more than 99% of the power requirements of the computer process for space heating, water heating etc. in order to based industries, these industries found that even a momentary enhance 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 manufacturing generation for a wide variety of reasons. The emphasis is on processes shifted to their own back-up systems for power meeting 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 wholesale holders are benefited in their own ways by the adoption of contracts, had to pass on whatever loss they suffered only on distributed power. The most important benefit of distributed the spot markets. In a situation like that in California where power stems from its flexibility, it can provide power where it prices can fluctuate by the hour, flexibility to switch onto and is 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 generation The major benefits of distributed power to the various in fact is regarded as the best means of ensuring competition in stakeholders are as follows: the power sector. Major Potential Benefits of Distributed Generation C) Both in the USA and UK the process of de-regulation did Consumer-Side Benefits: Better power reliability and quality, not make smooth progress on account of the difficulties lower energy cost, wider choice in energy supply options, created by the regulated structure of the power market and a better energy and load management and faster response to new monopoly enjoyed the dominant utilities.
  • 5. National Conference on Modeling & Simulation of Electrical Systems [MSES-2013], TIT & S, Bhopal 147 D) In fact, the current situation in the United States in the 7. Rahul Tongia; “Smart Grids White Paper” Center for Study power sector is compared to the situation that arose in the of Science, Technology and Policy Telecom Sector on account of the breakup of AT&T (CSTEP) CAIR Building, Raj Bhavan Circle Corporation’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 the profound 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.): KI Smart Grid is the modernization of the electricity delivery 2005, LNAI 3698, pp. 203 – 215, 2005.© Springer-Verlag system so that it monitors, protects and automatically Berlin Heidelberg 2005 optimizes the operation of its interconnected elements – from the central and distributed generator through the high-voltage BIOGRAPHIES network 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- RGPV vehicles, appliances and other household devices. Smart grid Bhopal in electrical engineering , and at the moment he is an is the integration of information and communications system M-Tech (instrumentation) scholar at SCHOOL OF into electric transmission and distribution networks. Some of INSTRUMENTATION DAVV, lndore, India. Email: the enabling technologies & business practice that make smart JITENDRIY@INDIA.COM grid 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: aashish_bohre@yahoo.co.in • 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 Email:manishadubey6@gmail.com 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)