INNOVATIVE TECHNOLOGIES AND CHALLENGES IN THE FIELD OF SMART GRID by iaemedu

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									International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
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 INNOVATIVE TECHNOLOGIES AND CHALLENGES IN THE FIELD OF
                     SMART GRID

                                Mamatha Sandhu1, Dr.Tilak Thakur2
            1
             (Electrical Engineering Department, Chitkara University, Punjab Campus, India)
      2
          (Electrical Engineering Department, PEC University of Technology, Chandigarh, India)


ABSTRACT

       A Smart Grid is an electricity network that can intelligently integrate the actions of all users
connected to it - generators, consumers and those that do both – in order to efficiently deliver
sustainable, economic and secure electricity supplies. It integrates innovative tools and technologies
from generation, transmission and distribution all the way to consumer appliances and equipment.
This paper reviews the researches and studies on Smart Grids (SGs); one can see variety of problems
and challenges in the field of Smart Grid.

Keywords: Smart Grids (SGs), Distributed Energy Resources (DER), Micro-generation (MG),
micro-grid (MG), Renewable Energy Sources (RES)

1.        INTRODUCTION

        A Smart Grid employs innovative products and services together with intelligent monitoring,
control, communication, and self-healing technologies to:
    • better facilitate the connection and operation of generators of all sizes and technologies;
    • allow consumers to play a part in optimizing the operation of the system;
    • provide consumers with greater information and choice of supply; significantly reduce the
        environmental impact of the whole electricity supply system;
    • deliver enhanced levels of reliability and security of supply.
        Smart Grids deployment must include not only technology, market and commercial
considerations, environmental impact, regulatory framework, standardization usage, ICT
(Information & Communication Technology) and migration strategy but also societal requirements
and governmental edicts [1]. Electricity delivery network consists of two primary systems. First, the
transmission system which delivers electricity from power plants to distribution substations. Second
the distribution system which delivers electricity from distribution substations to consumers [2].
Traditionally, the electrical ″grid″ only refers to the interconnected transmission system. On the other
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hand, the term ″Smart Grid″ is used to refer to the entire electrical system, including generation,
transmission [3-8], and distribution as well as into the home or building. It is well known that the
distribution system is the largest and most complex part of the entire electrical system [9]. Thus,
many research papers have focused on smart grids at the distribution level. A Smart Grid delivers
electricity from suppliers to consumers using digital technology to save energy, reduce cost and
increase reliability and transparency [10]. Smart Grids increase the connectivity, automation and
coordination between suppliers, consumers and networks that perform either long distance
transmission or local distribution tasks [9, 10]. There are different terms for Smart Grid such as:
smart electric grid, smart power grid, intelligent grid, intelligrid, and Future Grid.

2.      SMART GRID PRINCIPLE CHARACTERISTICS

       A smarter grid as shown in Fig.1 will be needed to accommodate not only large, centralized
power plants, but also a much wider range and greater number of DER. These distributed resources
include renewable, distributed generation, energy storage and plug-in electric vehicles. And their
deployment will increase rapidly all along the value chain, from suppliers to marketers to consumers.
This characteristic of the smart grid will enable the generation portfolio to move toward a more
decentralized model that will include a balance of large, centralized generating plants as well as DER
[11].




          Figure 1: The Smart Grid accommodates all generation and storage options

       The future offers several growth pathways for DER, depending on how technologies and
markets evolve. The Smart Grid will experience a significant growth of DER as follows:

        1. DER numbers will increase dramatically. The Smart Grid must expect and enable a
substantial increase in the number of new energy sources. Renewable portfolio standard (RPS)
programs require investor-owned utilities to provide a more significant portion of their electricity
from renewable sources many of which will be distributed. DER is also likely to grow rapidly among
consumers as the total cost of ownership is reduced, more favorable regulations are created, profit
incentives are made increasingly available and the desire to reduce the impact on the environment
increases.

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        2. DER will be everywhere. Deployment will occur throughout the distribution system.
Utilities will install it. Power marketers will embrace it. And all types of consumers—commercial,
industrial, residential—will adopt it. DER will be located close to the consumers as well as
aggregated into centralized energy farms where appropriate. The grid will be expected to enable the
same widespread deployment of DER that occurred with personal computers, cell phones, and the
Internet.




 Figure 2: Renewable generation sources are an important option: the smart grid must enable
               the integration of intermittent resources such as wind turbines.

        The plug-in hybrid electric vehicle (PHEV) connected in the “vehicle to grid” mode is
positioned to be a game changing technology providing new options for generation and storage
“everywhere.”
        3. DER will be grid-connected. Stand-alone generation will continue to be common. But in
the future, more DER will be connected to the grid at many different points—at transmission
voltages, at distribution voltages, and in AC and DC networks and micro-grids. Solutions will be
found to make existing back-up generators (BUGs) attractive for interconnection, including methods
to significantly reduce their environmental impact.
        4. DER will be aggregated. For instance, wind and solar units may be aggregated into energy
“farms” and scattered invented Fig.2. The diversity of DER will include many individual sources that
have relatively small capacities such as photovoltaic (PV) arrays, wind turbines, fuel cells, plug-in
hybrid vehicles, and advanced energy storage. These devices will typically be connected to medium-
and low-voltage distribution lines or will become part of a micro-grid. Their benefits and
affordability will lead to a significant increase in the deployment of DER by consumers. In fact,
consumers may represent the largest market well into the next decade as they use distributed
generation to save money and improve reliability. But diversity will include larger plants, too. Large
power customers and marketers will invest in CHP units and non-utility generation facilities.
Combustion turbines will be built at a rate consistent with fuel costs and will be located closer to
load centers than conventional, centralized power stations. As we now turn our attention to what is
required to reach our DER goals, it is important to remember that the Smart Grid must also
accommodate new centralized plants. We will continue to need conventional, large, centralized
power stations to help meet the expected future increase in demand. A smarter grid and a bigger grid
are complementary [11].



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3.     KEY TECHNOLOGIES INVOLVED IN SMART GRID

        A smart grid uses digital technology to improve reliability, security, and efficiency of the
electric system [12, 14], which includes: Advanced digital meters, Distribution automation, Low-cost
communication systems, Distributed energy resources, Broadband communications for distribution
applications, Reactive power control based on intelligent coordination controls, and Fault analysis
and reconfiguration schemes based on intelligent switching operations Closed loop systems using
advanced protection, Distributed storage and generation, Real-time angle and voltage stability and
collapse detection, a true Smart Grid will utilize these technologies to integrate in order to maximize
the benefits [14].

3.1      STRONG AND FLEXIBLE NETWORK TOPOLOGY
         A strong, flexible grid structure is the basis for smart grid. As China's the uneven
development of energy distribution and productive forces, in order to meet the needs of economic
scale power transmission and resource allocation optimization. Ultra-high voltage (UHV)
transmission can improve the transmission capacity and reduce transmission losses and increase
economic transmission distance, but also have an obvious advantage in saving line corridor area,
save project investment, protect the ecological environment. Therefore, the development of special
high-voltage power grid, build power "highway" has become an inevitable choice. With the
expansion of the scale grid, the formation of interconnected bulk power system, grid stability and
fragility of the security problems are becoming increasingly prominent and requirements on planning
and designing the main grid structure be increased. Accordingly, only the flexible grid structure can
cope with the ice disaster, war and other unexpected catastrophic events. [15]

3.2     SMART GRID COMMUNICATION SYSTEM
        High-speed, bi-directional, real-time, integrated communications technology for smart grid
must have the following characteristics: First, with features of two-way, real-time, reliability. Due to
security considerations, in theory, the communication system should be of electricity communication
network, isolated with the public network. Second, with advanced technology, it can carry smart grid
existing business and future business expansion. Third is with independent intellectual property
rights, and with the ability of power business custom development and business scalability for smart
grid.

3.3     PARAMETER MEASUREMENT AND DEMAND SIDE MANAGEMENT
        In the future, smart grid will use the smart metering with two-way communication, enabling a
variety of functions, including can measure electricity use and electricity at different time each day,
but also save the peak electricity price signals and tariff rates, and to notify the user what kind of
rates for the implementation of the policy. Also allow users to rate their own policy, according to the
preparation of a timetable for the internal use of electricity automation user's strategy. Thus wide
area measurement system (WAMS) should be an important direction of development as the power
monitoring system In the future as technology advances; smart meters also may be used as the
Internet router, based on their end-users to promote the Integration of communication, the broadband
running business and television signals transmitted.

3.4     INTELLIGENT           SCHEDULING           TECHNOLOGY               AND       WIDE-AREA
PROTECTION SYSTEM
       Smart scheduling is an important part of smart grid, smart grid scheduling technology support
system is the core of the intelligent scheduling research and construction, which is technical
foundation of promoting the ability of Scheduling system to control large power grids and optimize

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the allocation of resources, Risk Defense, Scientific decision-making management, Flexible and
efficient regulation and Market deployment. The key technologies of the intelligent Scheduling
include:
1) Fast simulation and modeling (FSM). [16]
2) Intelligent early-warning technology.
3) Optimal scheduling technology,
4) Prevention and control technology, incident handling and incident recovery techniques (such as
the Intelligent Fault Identification and Recovery).
5) Intelligent Data Mining Techniques.
6) Scheduling decision-making visualization technology. It also includes an emergency command
system [17,18] and advanced distribution automation and related technologies, which advanced
distribution automation system includes system monitoring and control, power distribution system
management functions and interaction with the user (such as load management, measurement and
real-time pricing) [19].

3.5     ADVANCED POWER ELECTRONICS TECHNOLOGY
        Power electronics technology is a modem technology by using power electronic devices to
transform and control power, and energy-saving effect can be up to 10% to 40%, and reduce the
volume of mechanical and electrical equipment, meanwhile be able to achieve the best efficiency. At
present, the semiconductor power devices develop in the direction of high-pressure-based, high-
capacity-oriented, and the power electronics industry has appeared to SVC as the representative of
the flexible AC transmission technology, HVDC transmission as the representative of the new ultra-
high pressure technology, high frequency as the representative of electric drive technology,
intelligent switch as the representative of breaking synchronization technology, as well as static-var
generator (SVG) and the dynamic voltage restorer as the representative of custom power technology
etc.

3.6     DISTRIBUTED ENERGY ACCESS [20-27]
        Distributed energy includes distributed generation and distributed energy storage, and smart
grid lies in building the intelligent network system with intelligent judgments, adaptive ability and
distributed management, which can monitor and collect power information of the network and the
user in real-time, and use the most economic and secure transmission and distribution methods to
convey electricity to end-users, in order to achieve energy optimal allocation and utilization ,improve
grid operations reliability and energy efficiency. Distributed Energy Resources (DER) have many
different types, including hydroelectric power, wind power, solar power, micro turbines, fuel cells
and energy storage devices (such as the flywheel, super capacitors, superconducting magnetic energy
storage and sodium sulfur batteries etc.).

4.      INNOVATIVE CONTROL TECHNOLOGIES

         Computational intelligence (CI) is the study of adaptive mechanisms to enable or facilitate
intelligent behavior in complex, uncertain and changing environments [28]. These adaptive
mechanisms include those nature-inspired and artificial intelligence paradigms that exhibit an ability
to learn or adapt to new situations, to generalize, abstract, discover and associate. The typical
paradigms of CI are illustrated in Fig. 3 [29]. These paradigms can be combined to form hybrids as
shown in Fig.3, resulting in neuro-fuzzy systems, neuro swarm systems, fuzzy-PSO systems, fuzzy-
GA systems, neuro-genetic systems, etc. Thus, the hybrids are superior to any one of the paradigms.



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                     Figure 3: Five main CI paradigms and typical hybrids.

CI-based control technologies are powerful in the following typical ways:
   • Neural networks and fuzzy systems can capture the nonlinearity in power systems and smart
       grids.
   • Neural networks allow for behavioral modeling. Such models allow and are essential for
       making fast, dynamic decisions in a smart grid.
   • Fuzzy and neuro-fuzzy systems allow for making fast and accurate decisions in an uncertain
       smart grid environment with a lot of variability.
   • Artificial immune systems immunize against transients that result from disturbances and
       faults in smart grids, thus providing fault tolerance.
   • Swarm intelligence and evolutionary computation allow for offline, large-scale optimization
       of smart grid operations.
   • Adaptive critic design-based approaches allow for the design of robust, adaptive and optimal
       controllers in a dynamic, uncertain and variable smart grid environment.
   • ACDs allow for dynamic optimization and scheduling in an uncertain and variable smart grid
       environment.
   • CI approaches bring self-healing features to the smart grid.

5.     POWER CONVERTERS APPLICATIONS FOR HIGH-VOLTAGE SMART GRID

       Several topologies, originating from drives applications have been proposed in recent years
for medium and high-voltage grid applications. These topologies cover a wide range of applications,
e.g., FACTS, STATCOM, DVR, UPFC, IPFC, dc transmission systems, etc., as well as the grid
connection of renewable sources [30]–[33]. Most of these applications are based on the traditional
two-level voltage source power converter topology [31], [33]. However, due to advances in power
semiconductor devices, particularly in the IGBT technology there has been increasing interest

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recently in multilevel power converters especially for medium to high-power at high-voltage [34]–
[40]. Since the development of the neutral-point clamped three-level converter [41], several
alternative multilevel converter topologies have been reported in the




Figure 4: Multilevel topologies. (a) One leg of a three-level diode clamped converter.(b) One leg
of a three-level converter with bidirectional switch interconnection. (c) One leg of a three-level
 flying capacitor converter. (d) Three-level converter using three two-level converters. (e) One
                        leg of a three-level H-bridge cascaded converter




                 Figure 5: Generalized multi cellular power converter structure

literature [42]–[46] that can be classified into the following five categories: a) multilevel
configurations with diode clamps; b) multilevel configurations with bidirectional switch
interconnection; c) multilevel configurations with flying capacitors; d) multilevel configurations with
multiple three-phase inverters; and e)multilevel configurations with cascaded single phase H-bridge
inverters. Examples of these topologies are shown in Fig. 4.
        Among the advantages of these converters, the reduced harmonic content of output voltage
and reduced switching losses at the same harmonic performance compared to a two-level converter,
are notable. In order to extend the applicability of the multilevel converters to higher voltage/power
applications the interconnection of multilevel structures is proposed in [47]. Three topologies are of

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interest for these multilevel multi cellular converters, namely: the diode-clamped circuit [Fig. 4(a)],
the flying capacitor circuit [Fig. 4(c)], and the series isolated H-bridge circuit [Fig. 4(e)]. The
generalized structure for such a three-phase multi cellular converter is shown in Fig. 5.The topology
consists of two ac to dc power conversion stages and a dc to dc conversion stage, based on a medium
frequency (MF) transformer, to achieve galvanic isolation between the ac terminals by means of a
reduced size system compared to a traditional line frequency transformer.

6.      SMART GRID CHALLENGES

        Some challenges at different levels will be faced. At the System Planning and Maintenance
level, decision making regarding local opposition to new plants and lines; planning uncertainties,
lack of predictive real-time system controls; and not enough focus on supply-side reliability solutions
are considered vital challenges. At the Energy Auction level, public resistance to deregulation,
inadequate time dependent pricing information available to consumers, lack of consumer
participation and lack of environmental credits/imposition of taxes needs to be addressed. Moreover,
Communications difficulty among system operators as well as lack of predictive real-time
management tools is additional challenges. Lack of predictive control signals to operate devices and
lack of energy storage devices affects deployment of smart devices. Last but not the least; funding is
required to support new technologies in this area for the Smart Grid [48]. There are many tools that
can be used to design a Smart Grid. They are different in complexity and performance. Thus,
evaluation measures [48] should be addressed to evaluate these tools. This includes: Reliability, and
power quality, Dynamic optimization, scheduling and prediction, Data management, data mining,
measurements, State Estimation and devices for real-time analysis, and Analytical ability.

7.     DOMESTIC SMART GRID TECHNOLOGIES

         Emerging new technologies like distributed generation, distributed storage, and demand-side
load management will change the way we consume and produce energy. These techniques enable the
possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams.
By smartly applying future energy production, consumption, and storage techniques, a more energy-
efficient electricity supply chain can be achieved.
The goal of research is to determine a methodology to use the domestic optimization potential to: 1)
optimize efficiency of current power plants; 2) support the introduction of a large penetration level of
renewable sources (and thereby facilitate the means that are needed for CO reduction); and 3)
optimize usage of the current grid capacity.
         The goal of control methodology is to exploit the optimization potential of domestic
technologies. Although some of these technologies themselves may lead to a decreased domestic
energy usage (electricity and heat), the initial goal of this method is not to decrease domestic energy
usage, but to optimize the electricity import/export by reshaping the energy profiles of the houses.
The energy profiles are reshaped such that they can be supplied more efficiently or by a higher share
of renewable sources. Besides improving efficiency, optimization can (and has to) enhance the
reliability of supply [49], [50]. The primary functionality of the system is to control the domestic
generation and buffering technologies in such a way that they are used properly.
         Furthermore, the required heat and electricity supply and the comfort for the residents should
be guaranteed. Some devices have some scheduling freedom in how to meet these requirements. This
scheduling freedom of the domestic devices is limited by the comfort and technical constraints and
can be used for optimizations. More scheduling freedom can be gained when residents are willing to
decrease their comfort level leading to less restrictive constraints for the scheduling. This (small)
decrease in comfort should lead to benefits for the residents, e.g., a reduced electricity bill. The

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optimization objective can differ, depending on the stakeholder of the control systems. The objective
for residents or utilities can be earning/saving money and therefore the goal is to generate electricity
when prices are high and consume electricity when prices are low. For network operators the goal
can be to maintain grid stability and decrease the required capacity while an environmental goal can
be to improve the efficiency of power plants. Therefore, an optimization methodology should be able
to work towards different objectives. Next to different objectives, control methodologies can have
different scopes for optimization: a local scope (within the house), a scope of a group of houses, e.g.,
a neighborhood (micro-grid) or a global scope (virtual power plant). Every scope again might result
in different optimization objectives as follows:
        1) Local Scope: On a local scope the import from and export into the grid can be optimized
without cooperation with other houses. Possible optimization objectives are shifting electricity
demand to more beneficial periods (e.g., nights) and peak shaving. The ultimate goal can be to create
an independent house, which implies no net import from or net export into the grid. A house that is
physically isolated from the grid is called an islanded house. The advantages of a local scope are that
it is relatively easy to realize; there is no communication with others (privacy); and there is no
external entity deciding which appliances are switched on or off (social acceptance).
        2) Micro-grid: In a micro-grid a group of houses together optimize their combined import
from and export into the grid, optionally combined with larger scale DG (e.g., wind turbines).
The objectives of a micro-grid can be shifting loads and shaving peaks such that demand and supply
can be matched better internally. The ultimate goal is perfect matching within the micro-grid,
resulting in an islanded micro-grid. The advantage of a group of houses is that their joint
optimization potential is higher than that of individual houses since the load profile is less dynamic
(e.g., startup peaks of appliances disappear in the combined load). Furthermore, multiple micro
generators working together can match more demand than individual micro generators since better
distribution in time of the production are possible [51]. However, for a micro-grid a more complex
optimization methodology is required.
        3) Virtual Power Plant (VPP): The original VPP concept is to manage a large group of micro
generators with a total capacity comparable to a conventional power plant. Such a VPP can replace a
power plant while having a higher efficiency; moreover, it is much more flexible than a normal
power plant. Especially this last point is interesting since it expresses the usability to react on
fluctuations. This original idea of a VPP can of course be extended to all domestic technologies.
Again, for a VPP also a complex optimization methodology is required. Furthermore,
communication with every individual house is required and privacy and acceptance issues may
occur.

8.   INTEGRATING DISTRIBUTED                       GENERATION            WITH       SMART        GRID
ENABLING TECHNOLOGIES

        The integration of distributed generation and Smart Grid enabling technologies and concepts
to power systems has been widely accepted by the industry and academia as the key to achieve a
more reliable, efficient, and secure grid, with an active participation from customers, and
environmentally sustainable. However, there is a lack of information about the costs and economic
benefits of research and development projects about distributed generation and Smart Grids.
Distributed generation (DG), including renewable energy sources (RESs) at distribution scale, brings
proved benefits to network operation, the environment, and customers as well [52]. In addition,
advancement of information and communication technologies has brought attention to new and
improved technologies and concepts applied to power systems. These technologies, programs and
concepts are grouped under the giant umbrella known as smart grids (SG).


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8.1   SG ENABLING TECHNOLOGIES AND CONCEPTS FOR DG INTEGRATION
       According to the integration level, this section presents some of the most widely discussed
technologies and concepts that enable the integration of DG through the implementation of smart
power grids. These elements were extracted from the research of several demonstration projects
conducted by the International Council on Large Electric Systems (CIGRE) Working Group C6.11
“Development and Operation of Active Distribution Networks,” [53, 54].

8.2   DISTRIBUTED MONITORING AND CONTROL
      Distributed monitoring and control refers to technologies and systems acting over feeder
parameters in a decentralized way.

        1) Automatic Voltage Control
Automatic voltage control (AVC) facilitates DG integration remotely measuring feeder voltages and
taking control over substation primary transformer and advanced voltage regulators (AVRs) across
the network [55-57].
        2) Power Flow Management
Power flow management through optimal power flow (OPF) applied to distribution networks could
increase network energy export capabilities, avoiding network reinforcement and allowing voltage
control and optimal DG capacity allocation [58-60].
        3) Dynamic Line Rating
Dynamic line rating (DLR) combines remote measurements from feeders and weather stations to
provide real-time thermal capacity of the network. This information allows optimal accommodation
of DG based on RESs and avoids network reinforcements [61, 62].

8.3   NETWORK OPERATION
        This category includes procedures and strategies applied over the distribution network, or
applied to portions of it. These procedures and strategies rely on advanced controllers with high
integration of remote terminal units (RTUs) and intelligent electronic devices (IEDs), through ICT
applications.

        1) Demand Side Management
Demand side management (DSM) programs bring active participation of “prosumers” (portmanteau
for producers and consumers) in network operation. By shifting/shaving load profiles, or allowing
direct load control, DSM programs contribute to voltage and frequency control, improving security
and reliability, and allowing increased allocation of RESs to distribution networks [63-66].
        2) Advanced Fault Management
Combining communication-based adaptive protection relays, wide area monitoring (WAM) such as
phasor measurement units (PMUs), and fast acting switching devices with communication
capabilities, an advanced fault management can limit the extent of an abnormal condition and rapidly
restore large portion of the network, isolating the faulted sections (self-healing) [67,68].
        3) Advanced Distribution Management Systems
With higher penetration of DG to networks, DNOs require more robust and advanced distribution
management systems (DMSs) able to integrate information and control of highly automated grids.
Some characteristics a DMS should have include supervisory control and data acquisition (SCADA),
OPF capabilities, integration with numerous IEDs and RTUs, easy integration with existent
equipment, DER and micro-grid remote control capability, advanced fault management, and web
access [69-71].



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        Figure 6: Distribution feeder with DG connected and SG enabling technologies

        The methodology presented here proposes a feasibility analysis for the connection of a
distributed generator to a distribution feeder combined with an AVC at the connection node, and a
DLR, by hourly optimal power flow calculation to measure overloads, both functions performed by
the DMS at the distribution substation (Fig 6).

CONCLUSIONS

        This paper has reviewed characteristic of current electricity grid and the weaknesses
associated with these characteristics and opportunities that smart grid technologies can provide to
make the grids capable of working far more efficiently. In traditional grids, power supply is
dominated by central generations, there is low response to power quality issues and power outages,
there is limitation on integration of renewable sources of energy, and power system is vulnerable to
natural disasters. More distributed generators including renewable energy sources are integrated into
the grid. The smart power grid becomes much more complex than a traditional power grid as time-
varying sources of energy and new dynamic loads are integrated into it. The smart grid’s complexity
will evolve over time and require new technologies for efficient, reliable and secure operation and
control as the demand for electricity increases. This paper presented a methodology for technologies
improvement, also showed the technical and economic assessment of integrating distributed
generation with smart grid enabling technologies in distribution systems. Needed now is an effort to
develop an integrated vision for Smart Grid.

REFERENCES

 [1]   EPRI Intelligrid, http://intelligrid.epri.com/.
 [2]    Office of electricity delivery and energy reliability, ″ Smart grid, ″ Internet:
       http://www.oe.energy.gov/ smartgrid.htm, Accessed: August 2009
 [3]    Paul Marken, John Marczewski, Robert D'Aquila, Paul Hassink, Jim Roedel , ″ VFT – A
       Smart Transmission Technology That Is Compatible With the Existing and Future Grid, ″
       IEEE Power Systems Conference and Exposition, 2009.
 [4]   P. E. Marken, ″Variable frequency transformer – a simple and reliable interconnection
       technology, ″ EPRI HVDC Conference, September 2007
 [5]   J. Gagnon, D. Galibois, D. McNabb, D. Nadeau, P. Paquette, E. Larsen, D.McLaren, D.
       Piwko, C. Wegner, H. Mongeau, ″A 100 MW variable frequency transformer (VFT) on the
       Hydro-Québec Network,″ CIGRE, France, 2006


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 [6]    D. Nadeau, ″A 100-MW variable frequency transformer (VFT) on the Hydro- Québec
        TransÉnergie Network – the behavior during disturbance,″ IEEE PES General Meeting,
        Page(s): 26-28, 2007
 [7]    Vu, Begouic, Novosel, ″ Grids get smart protection and control, ″IEEE Computer
        Applications in Power, Vol. 10, No. 4 , Page(s): 40-44, 1997.
 [8]    H.F. Wang, ″Multi-agent co-ordination for the secondary voltage control in power system
        contingencies″, In Proc. IEE Generation, Transmission and Distribution, Vol. 148, Page(s):
        61-66, Jan 2001
 [9]    Saint B, ″ Rural distribution system planning using Smart Grid Technologies, ″IEEE Rural
        Electric Power Conference, REPC '09, Page(s):B3 - B3-8, April 2009.
 [10]    Pipattanasomporn, Feroze, Rahman, ″ Multi-agent systems in a distributed smart grid:
        Design and implementation, ″ IEEE/PES Power Systems Conference and Exposition, PES
        '09, Page(s):1 – 8, March 2009
 [11]    http://www.smartgridinformation.info/pdf/1262_ doc_1.pdf
 [12]    Brown R.E, ″ Impact of Smart Grid on distribution system design, ″ IEEE Power and Energy
        Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century,
        Page(s):1 – 4, July 2008
 [13]   U.S. Department of Energy (DOE)’s, ″ Modern grid initiative, Internet:
        http://www.netl.doe.gov/moderngrid/, Accessed: August 2009
 [14]    Momoh J.A, ″ Smart grid design for efficient and flexible power networks operation and
        control, ″ IEEE/PES Power Systems Conference and Exposition, PES '09, Page(s):1 – 8,
        March 2009
 [15]   Sun Yuanzhang. Attention to The Layout Flexibility [EB/OL]. 2008-03-26.
 [16]    EPRI. Distribution Fast Simulation and Modeling (DFSM ) High Level Requirements
        [EB/OL]. [2009-01-10].
 [17]   Fan Mingtian, Liu Sige, Zhang Zuping, et al. A research and review on the emergency
        management of power supply in urban power network[J] . Power System Technology , 2007 ,
        31 (10) : 38-41 (inChinese).
 [18]   Tian Shiming, Chen Xi, Zhu Chaoyang, et al. Study on electric power emergency
        management platform[J]. Power System Technology , 2008, 32(1): 26-30(in Chinese).
 [19]   Yu Yixin, Luan Wenpeng. Smart grid[J]. Power System and Clean Energy, 2009, 25(1): 7-
        11.
 [20]   Li Yalou, Zhou Xiaoxin , Lin Jiming, et al. A review of new energypower generation part in
        2008 IEEE PES general meeting[J].Power System Technology, 2008, 32(20): 1-7(in
        Chinese).
 [21]   Lu Zongxiang , Wang Caixia , Min Yong , et al . Overview on microgrid research[J].
        Automation of Electric Power Systems, 2007,31(19) : 100-106(in Chinese).
 [22]    Wu Lei, Yuan Yue, Ji Kan, et al. Microgrid and its application in earthquake prevention and
        disaster reduction[J] . Power System Technology, 2008, 32(16): 32-36(in Chinese).
 [23]    Zhang Ling, Wang Wei, Sheng Yinbo. Microgrid technology based on clean energy power
        generation system[J]. Power System and Clean Energy, 2009, 25(1): 40-43(in Chinese).
 [24]   Zhao Yan , H u Xuehao . Impacts of distributed generation on distribution system voltage
        sags[J]. Power System Technology, 2008 , 32(14): 5-9(in Chinese).
 [25]   Chi Yongning , Liu Yanhua , Wang Weisheng , et al . Study on impact of wind power
        integration on power system[J]. Power System Technology, 2007, 31(3): 77-81(in Chinese).
 [26]   Lin Li, Sun Caixin, Wang Yongping, et al. Calculation analysis and control strategy for
        voltage stability of power grid with large capacity wind farm interconnected[J]. Power
        System Technology, 2008, 32(3) : 41-46( in Chinese).


                                                140
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME

 [27] Li Bin, Liu Tianqi, Li Xingyuan. Impact of distributed generation on power system voltage
      stability[J]. Power System Technology, 2009, 33(3) : 84-88(in Chinese).
 [28] A. Engelbrecht, Computational Intelligence: An Introduction, John Wiley & Sons, Ltd,
      England, 2007, ISBN 978-0-470-03561-0.
 [29] G. K. Venayagamoorthy, “A Successful Interdisciplinary Course on Computational
      Intelligence,” IEEE Computational IntelligenceMagazine – A special issue on Education,
      Vol. 4, No. 1, February 2009,pp. 14-23.
 [30] B. Wu, High-Power Converters and AC Drives. NewYork: IEEE Press—Wiley Interscience,
      2006.
 [31] V. G. Agelidis, G. D. Demetriades, and N. Flourentzou, “Recent advances in high-voltage
      direct-current power transmission systems,” in Proc. IEEE Int. Conf. Ind. Technol. (ICIT),
      Dec. 2006, pp. 206–213.
 [32] A. Rufer, “Today’s and tomorrow’s meaning of power electronics within the grid
      interconnection,” presented at the 12th Eur. Conf. Power Electron. (EPE), Aalborg, Denmark,
      Sep. 2007, keynote paper.
 [33] F. Blaabjerg and F. Iov, “Wind power—A power source now enabled by power electronics,”
      presented at the 9th Brazilian Power Electron. Conf. (COBEP), Blumenau, Santa Catarina,
      Brazil, Oct. 2007.
 [34] Y. H. Liu, J. Arrillaga, andN. R.Watson, “Cascaded H-bridge voltage reinjection—Part II:
      Application to HVDC transmission,” IEEE Trans.Power Del., vol. 23, no. 2, pp. 1200–1206,
      Apr. 2008.
 [35] D. Soto and T. C. Green, “Voltage balance and control in a multi-level unified power flow
      controller,” IEEE Trans. Power Del., vol. 16, no. 4, pp. 732–738, Oct. 2001.
 [36] B. R. Lin and T. C.Wei, “A novel NPC inverter for harmonics elimination and reactive power
      compensation,” IEEE Trans. Power Del., vol. 19, no. 3, pp. 1449–1456, Jul. 2004.
 [37] A. Bellini, S. Bifaretti, and S. Costantini, “Implementation on a microcontroller of a space
      vector modulation technique for NPC inverters,” in Proc. IEEE Int. Symp. Ind. Electron.
      (ISIE),May 2004, pp. 935–940.
 [38] Y. Li and B.Wu, “A novel DC voltage detection technique in the CHB inverter-based
      STATCOM,” IEEE Trans. Power Del., vol. 23, no. 3, pp. 1613–1619, Jul. 2008.
 [39] D. Soto and T. C. Green, “A comparison of high-power converter topologies for the
      implementation of FACTS controllers,” IEEE Trans. Ind. Electron., vol. 49, no. 5, pp. 1072–
      1080, Oct. 2002.
 [40] Y. Cheng, C. Qian, M. L. Crow, S. Pekarek, and S. Atcitty, “A comparison of diode-clamped
      and cascaded multilevel converters for STATCOM with energy storage,” IEEE Trans. Ind.
      Electron., vol. 53,no. 5, pp. 1512–1521, Oct. 2006.
 [41] A. Nabae, I. Takahashi, and H. Akagi, “A new neutral-point-clamped PWM-inverter,” IEEE
      Trans. Ind. Appl., vol. IA-17, no. 5, pp. 518–523, 1981.
 [42] F. Blaabjerg and F. Iov, “Wind power—A power source now enabled by power electronics,”
      presented at the 9th Brazilian Power Electron. Conf. (COBEP), Blumenau, Santa Catarina,
      Brazil, Oct. 2007.
 [43] Y. H. Liu, J. Arrillaga, andN. R.Watson, “Cascaded H-bridge voltage reinjection—Part II:
      Application to HVDC transmission,” IEEE Trans. Power Del., vol. 23, no. 2, pp. 1200–1206,
      Apr. 2008.
 [44] D. Soto and T. C. Green, “Voltage balance and control in a multi-level unified power flow
      controller,” IEEE Trans. Power Del., vol. 16, no. 4,pp. 732–738, Oct. 2001.
 [45] Y. Li and B.Wu, “A novel DC voltage detection technique in the CHB inverter-based
      STATCOM,” IEEE Trans. Power Del., vol. 23, no. 3, pp. 1613–1619, Jul. 2008.


                                              141
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME

 [46] Y. Cheng, C. Qian, M. L. Crow, S. Pekarek, and S. Atcitty, “A comparison of diode-clamped
      and cascaded multilevel converters for STATCOM with energy storage,” IEEE Trans. Ind.
      Electron., vol. 53, no. 5, pp. 1512–1521, Oct. 2006.
 [47] D.Gerry, P.Wheeler, J. Clare, R. J. Bassett,C.D.M.Oates, and R. W. Crookes, “Multi-level,
      multi-celular structures for high voltage power conversion,” presented at the EPE, Graz,
      Austria, Aug. 2001.
 [48] Momoh J.A, ″ Smart grid design for efficient and flexible power networks operation and
      control, ″ IEEE/PES Power Systems Conference and Exposition, PES '09, Page(s):1 – 8,
      March 2009
 [49] J. Scott, P. Vaessen, and F. Verheij, “Reflections on smart grids for the future,” Dutch
      Ministry        of      Economic         Affairs,    Apr.      2008      [Online].Available:
      http://www.kema.com/nl/papers/Reflections.aspx
 [50] Distributed Generation in Liberalised Electricity Markets 2002.
 [51] A. Molderink, V. Bakker,M. Bosman, J. Hurink, and G. Smit, “A three step methodology to
      improve domestic energy efficiency,” in IEEE PESConf. Innov. Smart Grid Technol., 2010.
 [52] H. A. Gil and G. Joos, "Models for Quantifying the Economic Benefits of Distributed
      Generation," IEEE Transactions on Power Systems, vol. 23, pp. 327-335, 2008.
 [53] C. D'Adamo, S. Jupe, and C. Abbey, "Global Survey on Planning and Operation of Active
      Distribution Networks - Update of CIGRE C6.11 Working Group Activities," in 20th
      International Conference and Exhibition on Electricity Distribution, CIRED 2009., pp. 1-4.
 [54] (2010). CIGRE SC C6 - Distribution Systems and Dispersed Generation. [Online].
      Available: http://www.cigre-c6.org/
 [55] M. Gillie, J. Hiscock, and A. Creighton, "On Site Trial of the New SuperTAPP N+ AVC
      Relay - a Step Towards an Active Network," in IET-CIRED Seminar SmartGrids for
      Distribution., 2008, pp. 1-4.
 [56] T. G. Hazel, N. Hiscock, and J. Hiscock, "Voltage Regulation at Sites with Distributed
      Generation," IEEE Transactions on Industry Applications, vol. 44, pp. 445-454, 2008.
 [57] V. Thornley, J. Hill, P. Lang, and D. Reid, "Active Network Management of Voltage
      Leading to Increased Generation and Improved Network Utilisation," in IET-CIRED Seminar
      SmartGrids for Distribution., 2008, pp. 1-4.
 [58] P. N. Vovos, A. E. Kiprakis, A. R. Wallace, and G. P. Harrison, "Centralized and Distributed
      Voltage Control: Impact on Distributed Generation Penetration," IEEE Transactions on
      Power Systems, vol. 22, pp. 476-483, 2007.
 [59] P. Djapic, C. Ramsay, D. Pudjianto, G. Strbac, J. Mutale, N. Jenkins, and R. Allan, "Taking
      an Active Approach," IEEE Power and Energy Magazine, vol. 5, pp. 68-77, 2007.
 [60] S. C. E. Jupe and P. C. Taylor, "Distributed Generation Output Control for Network Power
      Flow Management," IET Renewable Power Generation, vol. 3, pp. 371-386, 2009.
 [61] T. Yip, A. Chang, G. Lloyd, M. Aten, and B. Ferri, "Dynamic Line Rating Protection for
      Wind Farm Connections," in 2009 CIGRE/IEEE PES Joint Symposium Integration of Wide-
      Scale Renewable Resources Into the Power Delivery System, 2009, pp. 1-5.
 [62] J. Ausen, B. F. Fitzgerald, E. A. Gust, D. C. Lawry, J. P. Lazar, and R. L. Oye, "Dynamic
      Thermal Rating System Relieves Transmission 7 Constraint," in IEEE 11th International
      Conference on Transmission & Distribution Construction, Operation and Live-Line
      Maintenance, ESMO 2006.
 [63] (2010). Benfits of Demand Response in Electricity Markets and Recommendations for
      Achieving Them - a Report to the United States Congress - US Department of Energy.
      [Online]. Available: http://eetd.lbl.gov/eetd.html



                                              142
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME

 [64] A. J. Roscoe and G. Ault, "Supporting High Penetrations of Renewable Generation Via
      Implementation of Real-Time Electricity Pricing and Demand Response," IET Renewable
      Power Generation, vol. 4, pp. 369-382, 2010.
 [65] S. Grijalva and M. U. Tariq, "Prosumer-Based Smart Grid Architecture Enables a Flat,
      Sustainable Electricity Industry," in 2011 IEEE PES Innovative Smart Grid Technologies
      (ISGT), 2011, pp. 1-6.
 [66] A. J. Conejo, J. M. Morales, and L. Baringo, "Real-Time Demand Response Model," IEEE
      Transactions on Smart Grid, vol. 1, pp. 236-242, 2010.
 [67] EPRI. (2010). Methodological Approach for Estimating the Benefits and Costs of Smart Grid
      Demonstration Projects. [Online]. Available: www.epri.com
 [68] M. Kezunovic, "Smart Fault Location for Smart Grids," IEEE Transactions on Smart Grid,
      vol. 2, pp. 11-22, 2011.
 [69] (2010). Innovative Distributed Power Grid Interconnection and Control Systems - Final
      Report - NREL - US Department of Energy. [Online]. Available: http://www.nrel.gov/
 [70] A. G. Madureira and J. A. Pecas Lopes, "Coordinated Voltage Support in Distribution
      Networks with Distributed Generation and Microgrids," IET Renewable Power Generation,
      vol. 3, pp. 439-454, 2009.
 [71] R. A. F. Currie, G. W. Ault, C. E. T. Foote, N. M. McNeill, and A. K. Gooding, "Smarter
      Ways to Provide Grid Connections for Renewable Generators," in 2010 IEEE Power and
      Energy Society General Meeting, 2010, pp. 1-6.
 [72] Dr. Damanjeet Kaur, “Smart Grids and India”, International Journal of Electrical
      Engineering & Technology (IJEET), Volume 1, Issue 1, 2010, pp. 157 - 164, ISSN Print:
      0976-6545, ISSN Online: 0976-6553.
 [73] K.Raja, I.Syed Meer Kulam Ali, P.Tamilvani and K.Selvakumar, “Wind and Solar Integrated
      to Smart Grid using Islanding Operation”, International Journal of Electrical Engineering &
      Technology (IJEET), Volume 4, Issue 1, 2013, pp. 27 - 35, ISSN Print: 0976-6545,
      ISSN Online: 0976-6553.
 [74] M.Saisesha, V.S.N.Narasimharaju, R.Madhu Sudanarao and M.Balaji, “Control of Power
      Inverters in Renewable Energy and Smart Grid Integration”, International Journal of
      Electrical Engineering & Technology (IJEET), Volume 4, Issue 1, 2013, pp. 200 - 207,
      ISSN Print: 0976-6545, ISSN Online: 0976-6553.




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