Innovative technologies and challenges in the field of smart grid

International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –

6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME

129

INNOVATIVE TECHNOLOGIES AND CHALLENGES IN THE FIELD OF

SMART GRID

Mamatha Sandhu1, Dr.Tilak Thakur

2

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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ISSN 0976 – 6545(Print) ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), pp. 129-143

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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.

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