A robust optimization approach for optimal load dispatch of community energy hub

Xinhui Lu, Zhaoxi Liu, Li Ma, Lingfeng Wang, Kaile Zhou and Nanping Feng

Applied Energy, 2020, vol. 259, issue C

Abstract: As an important segment in the multi-energy systems, energy hub plays a significant role in improving the efficiency, flexibility and reliability of the multi-energy systems. In addition, load dispatch is an important optimization problem in the energy system, which has great significance to reduce energy consumption, environmental pollution and user's energy costs. In this regard, this paper proposes an optimal load dispatch model for a community energy hub, which aims to reduce the total cost of community energy hub, including operation cost and CO2 emission cost of the system. In the community energy hub, the combined heat and power (CHP) unit, gas boiler, heat storage unit, photovoltaic (PV) array, wind turbine (WT), and electric vehicles (EVs) are included. The uncertainties of EVs are modeled using the Monte Carlo simulation, and a robust optimization approach is adopted to deal with the future electricity price uncertainties. In addition, the proposed model comprehensively considers both electrical and thermal demand response (DR) programs. In the paper, three scheduling scenarios with different EV charging/discharging and DR settings are discussed. The simulation results show that the total costs can be effectively reduced by adopting coordinated charging/discharging mode for EVs. Meanwhile, the results also reveal that the consumers’ total cost can be further reduced by implementing the DR programs.

Keywords: Demand response; Electric vehicles; Energy hub; Load dispatch; Robust optimization (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (54)

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DOI: 10.1016/j.apenergy.2019.114195

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