A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Energy management for a commercial building microgrid with stationary and mobile battery storage
Highlights Studies the impacts of stationary (BESS) and mobile (EV) integration to commercial building. Models stochastic nature of solar generation, building load, EV energy demands and availabilities. Stochastic DSM outperformances deterministic DSM for different load patterns, wide ranges of solar installation capacity and electricity prices. Moderate number of gridable EVs helps cut down the operational cost while meeting their energy demands.
Abstract This paper investigates the Demand Side Management (DSM) in a commercial building microgrid with solar generation, stationary Battery Energy Management System (BESS) and gridable (V2G) Electric Vehicle (EV) integration. Taking into consideration of a comprehensive pricing model, we first formulate a deterministic DSM as a mixed integer linear programming problem, assuming perfect knowledge of the uncertainties in the system. A two-stage stochastic DSM is further developed that addresses the stochastic nature in solar generation, loads, EV availabilities and EV energy demands. The proposed DSMs are validated with real solar generation, loads, BESS and EV data using sample average approximation. Detailed case studies show that the stochastic DSM outperforms its deterministic counterpart for cost saving for a wide range of prices, though at the expense of higher computational time. Computational results also demonstrate that moderate number of EVs helps to cut down the overall operation cost, which sheds light on the benefit of future large scale EV integration to smart buildings.
Energy management for a commercial building microgrid with stationary and mobile battery storage
Highlights Studies the impacts of stationary (BESS) and mobile (EV) integration to commercial building. Models stochastic nature of solar generation, building load, EV energy demands and availabilities. Stochastic DSM outperformances deterministic DSM for different load patterns, wide ranges of solar installation capacity and electricity prices. Moderate number of gridable EVs helps cut down the operational cost while meeting their energy demands.
Abstract This paper investigates the Demand Side Management (DSM) in a commercial building microgrid with solar generation, stationary Battery Energy Management System (BESS) and gridable (V2G) Electric Vehicle (EV) integration. Taking into consideration of a comprehensive pricing model, we first formulate a deterministic DSM as a mixed integer linear programming problem, assuming perfect knowledge of the uncertainties in the system. A two-stage stochastic DSM is further developed that addresses the stochastic nature in solar generation, loads, EV availabilities and EV energy demands. The proposed DSMs are validated with real solar generation, loads, BESS and EV data using sample average approximation. Detailed case studies show that the stochastic DSM outperforms its deterministic counterpart for cost saving for a wide range of prices, though at the expense of higher computational time. Computational results also demonstrate that moderate number of EVs helps to cut down the overall operation cost, which sheds light on the benefit of future large scale EV integration to smart buildings.
Energy management for a commercial building microgrid with stationary and mobile battery storage
Wang, Yubo (author) / Wang, Bin (author) / Chu, Chi-Cheng (author) / Pota, Hemanshu (author) / Gadh, Rajit (author)
Energy and Buildings ; 116 ; 141-150
2015-12-30
10 pages
Article (Journal)
Electronic Resource
English
Energy management for a commercial building microgrid with stationary and mobile battery storage
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