Day-ahead resource scheduling including demand response for electric vehicles

Soares, João; Morais, H.; Sousa, Tiago; Vale, Zita; Faria, Pedro

doi:10.1109/pesgm.2014.6939118

Cited by 9 publications

(10 citation statements)

References 16 publications

(29 reference statements)

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“…In our opinion, this is a potential indicator that energy resource management-related research is getting more mature in the last years and ready for publication in journal. Energy resource management has been considered by some researchers as one of the most complicated optimization problems in power systems due to its combinatorial nature, nonlinearities, and large number of energy resources which leads to high dimensionality and highly constrained problems [23,[41][42][43]. Adequate optimization frameworks are a key part of the new paradigm brought by the smart grid operation.…”

Section: Complexitymentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

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Section: Complexitymentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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“…According to [75][76][77], when ignoring the perturbation on the capacitor voltage ˆo u , the load is a constant voltage source, and by high-frequency approximation, Equation (17) can be simplified to:…”

Section: Dynamic Characteristicsmentioning

confidence: 99%

“…In [14,15], a two-stage optimization model is adopted to minimize the peak load and load fluctuation. V2G control strategies aiming at peak shaving and valley filling are presented in [16][17][18][19], with costs of all energy resources and system operation as the minimization objective. In [20][21][22] control strategies based on aggregators' cost or EV owners' cost are introduced.…”

Section: Introductionmentioning

confidence: 99%

Topology of a Bidirectional Converter for Energy Interaction between Electric Vehicles and the Grid

2014

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Abstract:In vehicle-to-grid (V2G) systems, electric vehicles interact with the grid as distributed energy storage systems that offer many potential benefits. As an energy interface between a vehicle and the grid, the bidirectional converter plays a crucial role in their interaction. Its reliability, safety, cost, efficiency, weight, size, harmonics, and other factors are of essential importance for V2G realization, especially for on-board operations. Beyond the common existing topologies for bidirectional chargers, this paper introduces a novel high-power-factor bidirectional single-stage full-bridge (BSS-FBC) topology, which offers advantages in power density, size, weight, cost, efficiency, power quality, dynamic characteristic, reliability, and complexity. Its operational principles and control strategies are presented. Harmonic analysis on the basis of double-Fourier integral is performed with detailed comparison of line current harmonic characteristics between the BSS-FBC topology and unipolar/bipolar controlled single-phase pulse width modulation (PWM) converters. A dynamic model of the topology is derived, its dynamic behavior analyzed, and its compensator design method developed. Simulation and experimental results are employed to verify the design and analysis. Design considerations for the key parameters are discussed. A 3.3 kW prototype is developed for this topology and validated in its vehicle applications. The results demonstrate clearly the benefits and advantages of the new topology.

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“…While, virtual power player based simulation technique is applied to accomplish DSM and V2G operations [9]. While, the authors in [10] incorporated DR scheduling policy for energy management of PEVs.…”

Section: Introductionmentioning

confidence: 99%

Fast Performance Computing Model for Smart Distributed Power Systems

Younas

Khan

Ali

et al. 2017

SJCMS

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Plug-in Electric Vehicles (PEVs) are becoming the more prominent solution compared to fossil fuels cars technology due to its significant role in Greenhouse Gas (GHG) reduction, flexible storage, and ancillary service provision as a Distributed Generation (DG) resource in Vehicle to Grid (V2G) regulation mode. However, large-scale penetration of PEVs and growing demand of energy intensive Data Centers (DCs) brings undesirable higher load peaks in electricity demand hence, impose supply-demand imbalance and threaten the reliability of wholesale and retail power market. In order to overcome the aforementioned challenges, the proposed research considers smart Distributed Power System (DPS) comprising conventional sources, renewable energy, V2G regulation, and flexible storage energy resources. Moreover, price and incentive based Demand Response (DR) programs are implemented to sustain the balance between net demand and available generating resources in the DPS. In addition, we adapted a novel strategy to implement the computational intensive jobs of the proposed DPS model including incoming load profiles, V2G regulation, battery State of Charge (SOC) indication, and fast computation in decision based automated DR algorithm using Fast Performance Computing resources of DCs. In response, DPS provide economical and stable power to DCs under strict power quality constraints. Finally, the improved results are verified using case study of ISO California integrated with hybrid generation.

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Day-ahead resource scheduling including demand response for electric vehicles

Cited by 9 publications

References 16 publications

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Topology of a Bidirectional Converter for Energy Interaction between Electric Vehicles and the Grid

Fast Performance Computing Model for Smart Distributed Power Systems

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