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
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