Virtual power plant integration with smart grids: a Review

Zhang, Weishi; He, Chuan; Qian, Hanhan; Lin, Ziqi; Li, Yongbo; Zhao, Xin; Zhang, Wei; Shu, Congzhong

doi:10.1109/cieec54735.2022.9846220

Cited by 6 publications

(2 citation statements)

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“…Current power systems present two important challenges: the need to reduce dependence on fossil fuels and greenhouse gas emissions and the increase in power demand, which is accelerated by the proliferation of electric vehicles (EVs) and fast charging systems. In this situation, virtual power plants (VPPs) arise as a means to better integrate uncertain renewable energy into the power system, as well as to improve the control of distributed energy resources and help with grid support [1][2][3]. A VPP can be defined as the aggregation and coordination of resources (renewable/non-renewable generation, controllable loads, energy storage systems, and/or EV) with economic and/or technical objectives.…”

Section: Introductionmentioning

confidence: 99%

“…Very recent literature reveals the research community's active interest in the development of VPPs as a means for better integrating and managing renewable energy systems and other resources, valuing their economic and technical impact on power systems [4][5][6]. VPPs are classified into commercial (CVPP) and technical (TVPP) depending on their main objective: CVPPs aim to reduce costs or improve profits, while TVPPs aim to support the grid [2]. However, according to the authors' opinion, these objectives are complementary, and they should coexist in order for VPPs to be attractive to resource owners and useful for the power system.…”

Section: Introductionmentioning

confidence: 99%

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A Genetic Algorithm for Residential Virtual Power Plants with Electric Vehicle Management Providing Ancillary Services

González-Romera,

Romero-Cadaval,

Roncero-Clemente

et al. 2023

Electronics

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Virtual power plants are a useful tool for integrating distributed resources such as renewable generation, electric vehicles, manageable loads, and energy storage systems under a coordinated management system to obtain economic advantages and provide ancillary services to the grid. This study proposes a management system for a residential virtual power plant that includes household loads, photovoltaic generation, energy storage systems, and electric vehicles. With the proposed management system, the virtual power plant is economically optimized (as in commercial virtual power plants) while providing ancillary services (as in technical virtual power plants) to the distribution grid. A genetic algorithm with appropriate constraints is designed and tested to manage the energy storage system and the charge/discharge of electric vehicles, with several economic and technical objectives. Single-objective optimization techniques are compared to multi-objective ones to show that the former perform better in the studied scenarios. A deterministic gradient-based optimization method is also used to validate the performance of the genetic algorithm. The results show that these technical targets (usually reserved for larger virtual power plants) and economic targets can be easily managed in restricted-sized virtual power plants.

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Section: Introductionmentioning

confidence: 99%