Demand response in smart electricity grids equipped with renewable energy sources: A review
TL;DR: In this article, a review of demand response in renewable energy resources (RERs) is presented, along with a complete benefit and cost assessment of DR and the effects of DR in electricity prices.
Abstract: Dealing with Renewable Energy Resources (RERs) requires sophisticated planning and operation scheduling along with state of art technologies. Among many possible ways for handling RERs, Demand Response (DR) is investigated in the current review. Because of every other year modifications in DR definition and classification announced by Federal Energy Regulatory Commission (FERC), the latest DR definition and classification are scrutinized in the present work. Moreover, a complete benefit and cost assessment of DR is added in the paper. Measurement and evolution methods along with the effects of DR in electricity prices are discussed. Next comes DR literature review of the recent papers majorly published after 2008. Eventually, successful DR implementations, around the world, are analyzed.
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TL;DR: In this article, a survey of demand response potentials and benefits in smart grids is presented, with reference to real industrial case studies and research projects, such as smart meters, energy controllers, communication systems, etc.
Abstract: The smart grid is conceived of as an electric grid that can deliver electricity in a controlled, smart way from points of generation to active consumers. Demand response (DR), by promoting the interaction and responsiveness of the customers, may offer a broad range of potential benefits on system operation and expansion and on market efficiency. Moreover, by improving the reliability of the power system and, in the long term, lowering peak demand, DR reduces overall plant and capital cost investments and postpones the need for network upgrades. In this paper a survey of DR potentials and benefits in smart grids is presented. Innovative enabling technologies and systems, such as smart meters, energy controllers, communication systems, decisive to facilitate the coordination of efficiency and DR in a smart grid, are described and discussed with reference to real industrial case studies and research projects.
1,901 citations
TL;DR: In this paper, the authors review different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power, considering both supply and demand side measures.
Abstract: The paper reviews different approaches, technologies, and strategies to manage large-scale schemes of variable renewable electricity such as solar and wind power. We consider both supply and demand side measures. In addition to presenting energy system flexibility measures, their importance to renewable electricity is discussed. The flexibility measures available range from traditional ones such as grid extension or pumped hydro storage to more advanced strategies such as demand side management and demand side linked approaches, e.g. the use of electric vehicles for storing excess electricity, but also providing grid support services. Advanced batteries may offer new solutions in the future, though the high costs associated with batteries may restrict their use to smaller scale applications. Different “P2Y”-type of strategies, where P stands for surplus renewable power and Y for the energy form or energy service to which this excess in converted to, e.g. thermal energy, hydrogen, gas or mobility are receiving much attention as potential flexibility solutions, making use of the energy system as a whole. To “functionalize” or to assess the value of the various energy system flexibility measures, these need often be put into an electricity/energy market or utility service context. Summarizing, the outlook for managing large amounts of RE power in terms of options available seems to be promising.
1,180 citations
TL;DR: This paper provides a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program, and presents various optimization models for the optimal control of the DR strategies that have been proposed so far.
Abstract: The smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.
854 citations
Cites background from "Demand response in smart electricit..."
...1) Time-Based DR: These programs offer customers timevarying prices that are defined based on the cost of electricity in different time periods [27]....
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...A description of existing DR architectures is presented in [27] with a report on their requirements, benefits and costs, and also a brief review of DR implementations in USA, Europe and China....
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TL;DR: In this paper, a review of the use of reinforcement learning for demand response applications in the smart grid is presented, and the authors identify a need to further explore reinforcement learning to coordinate multi-agent systems that can participate in demand response programs under demand-dependent electricity prices.
429 citations
TL;DR: This review provides a comprehensive overview of all reported cell configurations that involve electroactive organic compounds working either in the solid state or in solution for aqueous or nonaqueous electrolytes and highlights the most promising systems based on such various chemistries.
Abstract: As the world moves toward electromobility and a concomitant decarbonization of its electrical supply, modern society is also entering a so-called fourth industrial revolution marked by a boom of electronic devices and digital technologies. Consequently, battery demand has exploded along with the need for ores and metals to fabricate them. Starting from such a critical analysis and integrating robust structural data, this review aims at pointing out there is room to promote organic-based electrochemical energy storage. Combined with recycling solutions, redox-active organic species could decrease the pressure on inorganic compounds and offer valid options in terms of environmental footprint and possible disruptive chemistries to meet the energy storage needs of both today and tomorrow. We review state-of-the-art developments in organic batteries, current challenges, and prospects, and we discuss the fundamental principles that govern the reversible chemistry of organic structures. We provide a comprehensive overview of all reported cell configurations that involve electroactive organic compounds working either in the solid state or in solution for aqueous or nonaqueous electrolytes. These configurations include alkali (Li/Na/K) and multivalent (Mg, Zn)-based electrolytes for conventional "sealed" batteries and redox-flow systems. We also highlight the most promising systems based on such various chemistries relying on appropriate metrics such as operation voltage, specific capacity, specific energy, or cycle life to assess the performances of electrodes.
408 citations
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TL;DR: In this article, the relevant issues and aims at providing a general definition for distributed power generation in competitive electricity markets are discussed, which can be defined as electric power generation within distribution networks or on the customer side of the network.
2,484 citations
TL;DR: In this article, the authors present a summary of demand response in deregulated electricity markets and highlight the most common indices used for DR measurement and evaluation, and some utilities' experiences with different demand response programs are discussed.
1,751 citations
TL;DR: This work proposes a robust integer programming problem of moderately larger size that allows controlling the degree of conservatism of the solution in terms of probabilistic bounds on constraint violation, and proposes an algorithm for robust network flows that solves the robust counterpart by solving a polynomial number of nominal minimum cost flow problems in a modified network.
Abstract: We propose an approach to address data uncertainty for discrete optimization and network flow problems that allows controlling the degree of conservatism of the solution, and is computationally tractable both practically and theoretically. In particular, when both the cost coefficients and the data in the constraints of an integer programming problem are subject to uncertainty, we propose a robust integer programming problem of moderately larger size that allows controlling the degree of conservatism of the solution in terms of probabilistic bounds on constraint violation. When only the cost coefficients are subject to uncertainty and the problem is a 0−1 discrete optimization problem on n variables, then we solve the robust counterpart by solving at most n+1 instances of the original problem. Thus, the robust counterpart of a polynomially solvable 0−1 discrete optimization problem remains polynomially solvable. In particular, robust matching, spanning tree, shortest path, matroid intersection, etc. are polynomially solvable. We also show that the robust counterpart of an NP-hard α-approximable 0−1 discrete optimization problem, remains α-approximable. Finally, we propose an algorithm for robust network flows that solves the robust counterpart by solving a polynomial number of nominal minimum cost flow problems in a modified network.
1,747 citations
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TL;DR: In this article, the authors argue that the transition to a smart grid has to be evolutionary to keep the lights on; on the other hand, the issues surrounding the smart grid are signifi cant enough to demand major changes in power systems operating philosophy.
Abstract: Many believe the electric power system is undergoing a profound change driven by a number of needs. There's the need for environmental compliance and energy conservation. We need better grid reliability while dealing with an aging infrastructure. And we need improved operational effi ciencies and customer service. The changes that are happening are particularly signifi cant for the electricity distribution grid, where "blind" and manual operations, along with the electromechanical components, will need to be transformed into a "smart grid." This transformation will be necessary to meet environmental targets, to accommodate a greater emphasis on demand response (DR), and to support plug-in hybrid electric vehicles (PHEVs) as well as distributed generation and storage capabilities. It is safe to say that these needs and changes present the power industry with the biggest challenge it has ever faced. On one hand, the transition to a smart grid has to be evolutionary to keep the lights on; on the other hand, the issues surrounding the smart grid are signifi cant enough to demand major changes in power systems operating philosophy.
1,661 citations
TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.
Abstract: Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.
1,394 citations