scholarly journals The Synergies of Shared Autonomous Electric Vehicles with Renewable Energy in a Virtual Power Plant and Microgrid

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2016 ◽  
Author(s):  
Riccardo Iacobucci ◽  
Benjamin McLellan ◽  
Tetsuo Tezuka
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Electric Vehicles ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Transport Sector ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Vehicle Charging ◽  
Autonomous Electric Vehicles

The introduction of shared autonomous electric vehicles (SAEVs), expected within the next decade, can transform the car into a service, accelerate electrification of the transport sector, and allow for large scale control of electric vehicle charging. In this work, we investigate the potential for this system to provide aggregated storage when combined with intermittent renewable energy sources. We develop a simulation methodology for the optimization of vehicle charging in the context of a virtual power plant or microgrid, with and without grid connection or distributed dispatchable generators. The model considers aggregate storage availability from vehicles based on transport patterns taking into account the necessary vehicle redistribution. We investigate the case of a grid-connected VPP with rooftop solar and the case of a isolated microgrid with solar, wind, and dispatchable generation. We conduct a comprehensive sensitivity analysis to study the effect of several parameters on the results for both cases.

Optimal Operational Scheduling of Renewable Energy Sources Using Teaching–Learning Based Optimization Algorithm by Virtual Power Plant

2017 ◽  
Vol 139 (6) ◽  
Author(s):  
Mohammad Javad Kasaei ◽  
Majid Gandomkar ◽  
Javad Nikoukar
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Optimization Algorithm ◽  
Distribution Systems ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

In recent years, a large number of renewable energy sources (RESs) have been added into modern distribution systems because of their clean and renewable property. Nevertheless, the high penetration of RESs and intermittent nature of some resources such as wind power and photovoltaic (PV) cause the variable generation and uncertainty of power system. In this condition, one idea to solve problems due to the variable output of these resources is to aggregate them together. A collection of distributed generations (DGs) such as wind turbine (WT), PV panel, fuel cell (FC), and any other sources of power, energy storage systems, and controllable loads that are aggregated together and are managed by an energy management system (EMS) are called a virtual power plant (VPP). The objective of the VPP in this paper is to minimize the total operating cost for a 24-h period. To solve the problem, a metaheuristic optimization algorithm, teaching–learning based optimization (TLBO), is proposed to determine optimal management of RESs, storage battery, and load control in a real case study.

scholarly journals Capability-coordinated frequency control scheme of a virtual power plant with renewable energy sources

2019 ◽  
Vol 13 (16) ◽  
pp. 3642-3648 ◽  
Author(s):  
Jinho Kim ◽  
Eduard Muljadi ◽  
Vahan Gevorgian ◽  
Manish Mohanpurkar ◽  
Yusheng Luo ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Frequency Control ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Control Scheme

Optimal management of renewable energy sources by virtual power plant

2017 ◽  
Vol 114 ◽  
pp. 1180-1188 ◽  
Author(s):  
Mohammad Javad Kasaei ◽  
Majid Gandomkar ◽  
Javad Nikoukar
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Optimal Management ◽  
Virtual Power ◽  
Virtual Power Plant

scholarly journals Optimal Dispatch Strategy of Virtual Power Plant for Day-Ahead Market Framework

2021 ◽  
Vol 11 (9) ◽  
pp. 3814
Author(s):  
Poushali Pal ◽  
Parvathy Ayalur Krishnamoorthy ◽  
Devabalaji Kaliaperumal Rukmani ◽  
S. Joseph Antony ◽  
Simon Ocheme ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Plant ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Virtual Power ◽  
Distributed Energy ◽  
Distribution Method ◽  
Virtual Power Plant ◽  
Optimal Dispatch ◽  
Market Framework

Renewable energy sources prevail as a clean energy source and their penetration in the power sector is increasing day by day due to the growing concern for climate action. However, the intermittent nature of the renewable energy based-power generation questions the grid security, especially when the utilized source is solar radiation or wind flow. The intermittency of the renewable generation can be met by the integration of distributed energy resources. The virtual power plant (VPP) is a new concept which aggregates the capacities of various distributed energy resources, handles controllable and uncontrollable loads, integrates storage devices and empowers participation as an individual power plant in the electricity market. The VPP as an energy management system (EMS) should optimally dispatch the power to its consumers. This research work is proposed to analyze the optimal scheduling of generation in VPP for the day-ahead market framework using the beetle antenna search (BAS) algorithm under various scenarios. A case study is considered for this analysis in which the constituting energy resources include a photovoltaic solar panel (PV), micro-turbine (MT), wind turbine (WT), fuel cell (FC), battery energy storage system (BESS) and controllable loads. The real-time hourly load curves are considered in this work. Three different scenarios are considered for the optimal dispatch of generation in the VPP to analyze the performance of the proposed technique. The uncertainties of the solar irradiation and the wind speed are modeled using the beta distribution method and Weibull distribution method, respectively. The performance of the proposed method is compared with other evolutionary algorithms such as particle swarm optimization (PSO) and the genetic algorithm (GA). Among these above-mentioned algorithms, the proposed BAS algorithm shows the best scheduling with the minimum operating cost of generation.

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