The electric power industry is facing unprecedented transformations and challenges with the implementation of the smart grids. This new grid paradigm has arisen to build a flexible electric power ...system that better coordinates energy resources and loads aiming at efficiently delivering sustainable, economic and secure electricity supplies. As a part of the smart grids (SGs), microgrids (MGs) have been developed to exploit the full benefits from the integration of distributed energy resources, especially distributed renewable generation based on variable and intermittent sources, such as wind and solar. Nevertheless, meeting all these goal requires the implementation of innovative energy storage technologies integrated with high efficiency and very fast response electronic power conditioning systems to interface with the electrical grid. Power electronics systems play a key role in regulating the raw energy from energy storage systems (ESSs) and connecting to the electrical grid. Hence, this paper performs a comprehensive analysis of major technologies in electrical energy storage systems and their electronic interface for applications in smart grids. The work provides a complete study of the technology profile of both energy storage and power electronics suitable for applications in the evolving grid.
The exponential increase in load demand of the residential sector results in decreased quality of service and increased demand-supply gap in the electricity market. To tackle these concerns, ...utilities need to manage the demand response (DR) of the connected loads. However, most of the existing DR management schemes have not explored the issue of reducing peak load while taking consumer constraints into account such as user comfort and willingness to participate. To address this issue, a new data analytical DR management scheme for residential load is proposed in this paper with an aim to reduce the peak load demand. The proposed scheme is based on the analysis of consumers' consumption data gathered from smart homes for which factors such as appliance adjustment factor, appliance priority index, appliance curtailment priority, etc., have been developed. Based on these factors, different algorithms with respect to consumer's and utility's perspective have been proposed to take DR decisions in the peak load scenario. Moreover, an incentive scheme is also presented to increase the consumers' participation in the proposed scheme. The proposed scheme is tested on the dataset gathered from PJM and Open Energy Information. The results obtained show that it efficiently reduces the peak load at the grid to a great extent. Moreover, it also increases the savings of the consumers by reducing their overall electricity bills.
Rising energy costs, losses in the present-day electricity grid, risks from nuclear power generation, and global environmental changes are motivating a transformation of the conventional ways of ...generating electricity. Globally, there is a desire to rely more on renewable energy resources (RERs) for electricity generation. RERs reduce greenhouse gas emissions and may have economic benefits, e.g., through applying demand side management with dynamic pricing so as to shift loads from fossil fuel-based generators to RERs. The electricity grid is presently evolving toward an intelligent grid, the so-called smart grid (SG). One of the major goals of the future SG is to move toward 100% electricity generation from RERs, i.e., toward a 100% renewable grid. However, the disparate, intermittent, and typically widely geographically distributed nature of RERs complicates the integration of RERs into the SG. Moreover, individual RERs have generally lower capacity than conventional fossil fuel-based plants, and these RERs are based on a wide spectrum of different technologies. In this article, we give an overview of recent efforts that aim to integrate RERs into the SG. We outline the integration of RERs into the SG along with their supporting communication networks. We also discuss ongoing projects that seek to integrate RERs into the SG around the globe. Finally, we outline future research directions on integrating RERs into the SG.
This paper presents an intelligent controller for "load frequency control (LFC)" application in "smart grid (SG)"environment having changes in communication topology (CT) via a multi-agent system ...(MAS) technology. In this study, network-induced effects, time delay, and change in CT have been addressed to examine the system performance in a closed loop. An event-triggered control method is used to reduce the communication burden in a network. An intelligent controller based on reinforcement learning consists of two levels, estimator agent and controller agent, in each multi-area system. Particle swarm optimization is used to tune the controller parameters. Furthermore, the proposed control strategy and system architecture as MAS for LFC in SG are analyzed in detail, verified for various load conditions and different network configurations. In addition, mean-square error of the power system states with CT is also analyzed. The results of this study validate the feasibility of the proposed control, as well as the capability of the MAS for the operation of LFC in SG with changes in CT.
The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid ...also known as, smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication (SGC) system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SGC system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. By separating the control plane from the data plane, SDN helps the network operators to manage the network flexibly. Since SG heavily relies on communication networks, therefore, SDN has also paved its way into the SG. By applying SDN in SG systems, efficiency and resiliency can potentially be improved. SDN, with its programmability, protocol independence, and granularity features, can help the SG to integrate different SG standards and protocols, to cope with diverse communication systems, and to help SG to perform traffic flow orchestration and to meet specific SG quality of service requirements. This paper serves as a comprehensive survey on SDN-based SGC. In this paper, we first discuss taxonomy of advantages of SDN-based SGC. We then discuss SDN-based SGC architectures, along with case studies. This paper provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.
Implementing blockchain techniques has enabled secure smart trading in many realms, e.g. neighboring energy trading. However, trading information recorded on the blockchain also brings privacy ...concerns. Attackers can utilize data mining algorithms to obtain users' privacy, specially, when the user group is located in nearby geographic positions. In this paper, we present a consortium blockchain-oriented approach to solve the problem of privacy leakage without restricting trading functions. The proposed approach mainly addresses energy trading users' privacy in smart grid and screens the distribution of energy sale of sellers deriving from the fact that various energy trading volumes can be mined to detect its relationships with other information, such as physical location and energy usage. Experiment evaluations have demonstrated the effectiveness of the proposed approach.
Currently, renewable energy is rapidly developing across the world in response to technical, economic and environmental developments, as well as political and social initiatives. On the other hand, ...excessive penetration of distributed generation (DG) systems into electrical networks may lead to various problems and operational limit violations, such as over and under voltages, excessive line losses, overloading of transformers and feeders, protection failure and high harmonic distortion levels exceeding the limits of international standards. These problems occur when the system exceeds its hosting capacity (HC) limit. The HC is a transactive approach that provides a way for the distribution network to be integrated with different types of energy systems. Accordingly, HC assessment and enhancements become an essential target for both distribution system operators and DG investors. This paper provides, for the first time, a systematic and extensive overview of the HC research, developments, assessment techniques and enhancement technologies. The paper consists of four HC principal sections: historical developments, performance limits, perceptions and enhancement techniques. Besides, practical experiences of system operators, energy markets and outcomes gained from real case studies are presented and discussed. It was concluded that success in integrating more distributed generation hinges on accurate hosting capacity assessment.
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•Distributed generation plays an important role in energy systems across the world.•This paper presents a comprehensive overview of hosting capacity in power systems.•Hosting capacity developments, limitations, and enhancement techniques are discussed.•Practical experiences of system operators and real case studies are presented.•Success in integrating more distributed generation hinges on accurate hosting capacity assessment.
In this paper, an edge computing system for IoT-based (Internet of Things) smart grids is proposed to overcome the drawbacks in the current cloud computing paradigm in power systems, where many ...problems have yet to be addressed such as fully realizing the requirements of high bandwidth with low latency. The new system mainly introduces edge computing in the traditional cloud-based power system and establishes a new hardware and software architecture. Therefore, a considerable amount of data generated in the electrical grid will be analyzed, processed, and stored at the edge of the network. Aided with edge computing paradigm, the IoT-based smart grids will realize the connection and management of substantial terminals, provide the real-time analysis and processing of massive data, and foster the digitalization of smart grids. In addition, we propose a privacy protection strategy via edge computing, data prediction strategy, and preprocessing strategy of hierarchical decision-making based on task grading (HDTG) for the IoT-based smart girds. The effectiveness of our proposed approaches has been demonstrated via the numerical simulations.
A smart grid is a new form of electricity network with high fidelity power-flow control, self-healing, and energy reliability and energy security using digital communications and control technology. ...To upgrade an existing power grid into a smart grid, it requires significant dependence on intelligent and secure communication infrastructures. It requires security frameworks for distributed communications, pervasive computing and sensing technologies in smart grid. However, as many of the communication technologies currently recommended to use by a smart grid is vulnerable in cyber security, it could lead to unreliable system operations, causing unnecessary expenditure, even consequential disaster to both utilities and consumers. In this paper, we summarize the cyber security requirements and the possible vulnerabilities in smart grid communications and survey the current solutions on cyber security for smart grid communications.
Traditionally, energy consumers pay non-commodity charges (e.g., transmission, environmental and network costs) as a major component of their energy bills. With the distributed energy generation, ...enabling energy consumption close to producers can minimize such costs. The physically constrained energy prosumers in power networks can be logically grouped into virtual microgrids (VMGs) using telecommunication systems. Prosumer benefits can be optimised by modelling the energy trading interactions among producers and consumers in a VMG as a Stackelberg game in which producers lead and consumers follow. Considering renewable (RES) and non-renewable energy (nRES) resources, and given that RES are unpredictable thus unschedulable, we also describe cost and utility models that include load uncertainty demands of producers. The results show that under Stackelberg equilibrium (SE), the costs incurred by a consumer for procuring either the RES or nRES are significantly reduced while the derived utility by producer is maximized. We further show that when the number of prosumers in the VMG increases, the CO 2 emission cost and consequently the energy cost are minimized at the SE. Lastly, we evaluate the peer-to-peer (P2P) energy trading scenario involving noncooperative energy prosumers with and without Stackelberg game. The results show that the P2P energy prosumers attain 47% higher benefits with Stackelberg game.
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