Collaborative Robust Optimization Strategy of Electric Vehicles and Other Distributed Energy Considering Load Flexibility

Yuxuan Wang, Bingxu Zhang, Chenyang Li and Yongzhang Huang
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Yuxuan Wang: School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China
Bingxu Zhang: School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China
Chenyang Li: School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China
Yongzhang Huang: School of Electrical & Electronic Engineering, North China Electric Power University, Beijing 102206, China

Energies, 2022, vol. 15, issue 8, 1-22

Abstract: Aggregated electric vehicles (EVs) integrated to the grid and intermittent wind and solar energy increased the complexity of the economic dispatch of the power grid. Aggregated EVs have a great potential to reduce system operating costs because of their dual attributes of load and energy storage. In this paper, plugged-in EV is refined into three categories: rated power charging, adjustable charging, and flexible charging–discharging, and then control models are established separately; the concept of temporal flexibility for EV clusters is proposed for the adjustable charging and flexible charging–discharging of EV sets; then, the schedule boundary of EV clusters is determined under the flexibility constraints. The interval is used to describe the intermittent nature of renewable energy, and the minimum operating cost of the system is taken as the goal to construct a distributed energy robust optimization model. By decoupling the model, a two-stage efficient solution is achieved. An example analysis verifies the effectiveness and superiority of the proposed strategy. The proposed strategy can minimize the total cost while meeting the demand difference of EV users.

Keywords: EV cluster; schedulable capability; temporal flexibility; demand difference; robust optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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