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Book ChapterDOI

Optimal Placement of GEV Aggregation in Smart Grid: An Evolutionary Computation Algorithm Approach

TL;DR: In this article, a self-adaptive firefly algorithm (SAFA) is proposed for optimal placement of gridable electric vehicle (GEV) aggregation in smart grid in order to minimize power losses and maximize voltage profile.
Abstract: Self-adaptive firefly algorithm (SAFA) is proposed for optimal placement of gridable electric vehicle (GEV) aggregation in smart grid in this paper. An objective function is developed to minimize power losses and maximize voltage profile. The load flow study is carried out on IEEE 33 bus test system and it is noted that timely placement of GEV aggregation in the power network will lead to reduction in the active/reactive power losses and improvement in voltage. The results are compared with other methods, and the proposed algorithm yields promising results.
References
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Book ChapterDOI
26 Oct 2009
TL;DR: In this article, a new Firefly Algorithm (FA) was proposed for multimodal optimization applications. And the proposed FA was compared with other metaheuristic algorithms such as particle swarm optimization (PSO).
Abstract: Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly algorithm is superior to existing metaheuristic algorithms. Finally we will discuss its applications and implications for further research.

3,436 citations

Journal ArticleDOI
TL;DR: A proposed framework to effectively integrate the aggregated battery vehicles into the grid as distributed energy resources to act as controllable loads to levelize the demand on the system during off-peak conditions and as a generation/storage device during the day to provide capacity and energy services to the grid.

869 citations

Journal ArticleDOI
TL;DR: In this article, the authors review the current status and implementation impact of V2G/grid-to-vehicle (G2V) technologies on distributed systems, requirements, benefits, challenges, and strategies for VUE interfaces of both individual vehicles and fleets.
Abstract: Plug-in vehicles can behave either as loads or as a distributed energy and power resource in a concept known as vehicle-to-grid (V2G) connection. This paper reviews the current status and implementation impact of V2G/grid-to-vehicle (G2V) technologies on distributed systems, requirements, benefits, challenges, and strategies for V2G interfaces of both individual vehicles and fleets. The V2G concept can improve the performance of the electricity grid in areas such as efficiency, stability, and reliability. A V2G-capable vehicle offers reactive power support, active power regulation, tracking of variable renewable energy sources, load balancing, and current harmonic filtering. These technologies can enable ancillary services, such as voltage and frequency control and spinning reserve. Costs of V2G include battery degradation, the need for intensive communication between the vehicles and the grid, effects on grid distribution equipment, infrastructure changes, and social, political, cultural, and technical obstacles. Although V2G operation can reduce the lifetime of vehicle batteries, it is projected to become economical for vehicle owners and grid operators. Components and unidirectional/bidirectional power flow technologies of V2G systems, individual and aggregated structures, and charging/recharging frequency and strategies (uncoordinated/coordinated smart) are addressed. Three elements are required for successful V2G operation: power connection to the grid, control and communication between vehicles and the grid operator, and on-board/off-board intelligent metering. Success of the V2G concept depends on standardization of requirements and infrastructure decisions, battery technology, and efficient and smart scheduling of limited fast-charge infrastructure. A charging/discharging infrastructure must be deployed. Economic benefits of V2G technologies depend on vehicle aggregation and charging/recharging frequency and strategies. The benefits will receive increased attention from grid operators and vehicle owners in the future.

788 citations

Journal ArticleDOI
01 Mar 2012
TL;DR: This paper presents a novel approach to determining the feasible optimal solution of the ED problems using the recently developed Firefly Algorithm, and shows that the proposed FA is able to find more economical loads than those determined by other methods.
Abstract: The growing costs of fuel and operation of power generating units warrant improvement of optimization methodologies for economic dispatch (ED) problems. The practical ED problems have non-convex objective functions with equality and inequality constraints that make it much harder to find the global optimum using any mathematical algorithms. Modern optimization algorithms are often meta-heuristic, and they are very promising in solving nonlinear programming problems. This paper presents a novel approach to determining the feasible optimal solution of the ED problems using the recently developed Firefly Algorithm (FA). Many nonlinear characteristics of power generators, and their operational constraints, such as generation limitations, prohibited operating zones, ramp rate limits, transmission loss, and nonlinear cost functions, were all contemplated for practical operation. To demonstrate the efficiency and applicability of the proposed method, we study four ED test systems having non-convex solution spaces and compared with some of the most recently published ED solution methods. The results of this study show that the proposed FA is able to find more economical loads than those determined by other methods. This algorithm is considered to be a promising alternative algorithm for solving the ED problems in practical power systems.

578 citations

Journal ArticleDOI
30 Jul 2013
TL;DR: The key is to provide the methodologies, approaches, and foresights for the emerging technologies of V2H, V2V, and V2G, namely, the vehicle-to-home (V2H), vehicle- to-vehicle (V 2V), and vehicle-To-grid (V1G) technologies.
Abstract: Electric vehicles (EVs) are regarded as one of the most effective tools to reduce the oil demands and gas emissions. And they are welcome in the near future for general road transportation. When EVs are connected to the power grid for charging and/or discharging, they become gridable EVs (GEVs). These GEVs will bring a great impact to our society and thus human life. This paper investigates and discusses the opportunities and challenges of GEVs connecting with the grid, namely, the vehicle-to-home (V2H), vehicle-to-vehicle (V2V), and vehicle-to-grid (V2G) technologies. The key is to provide the methodologies, approaches, and foresights for the emerging technologies of V2H, V2V, and V2G.

523 citations