A Stochastic-CVaR Optimization Model for CCHP Micro-Grid Operation with Consideration of Electricity Market, Wind Power Accommodation and Multiple Demand Response Programs

Wang Wang,Zhao Zhao,Sun Sun,Yang Yang,Tang Tang

doi:10.3390/en12203983

Wang Wang, Zhao Zhao + Show 3 more

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https://doi.org/10.3390/en12203983

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Journal: Energies	Publication Date: Oct 19, 2019
Citations: 15	License type: CC BY 4.0

Affiliation: North China Electric Power University

Abstract

Combined cooling, heating and power (CCHP) micro-grids have the advantage of high energy efficiency, and can be integrated with renewable energies and demand response programs (DRPs). With the deepening of electricity market (EM) reforms, how to carry out operation optimization under EM circumstances will become a key problem for CCHP micro-grid development. This paper proposed a stochastic-CVaR (conditional value at risk) optimization model for CCHP micro-grid operation with consideration of EM participation, wind power accommodation and multiple DRPs. Specifically, based on the stochastic scenarios for EM clearing prices and wind power outputs uncertainties, the stochastic optimization method was applied to ensure the realization of operational cost minimization and wind power accommodation; the CVaR method was implemented to control the potential risk of operational cost increase. Moreover, by introducing multiple DRPs, the electrical, thermal and cooling loads can be transformed as flexible sources for CCHP micro-grid operation. Simulations were performed to show the following outcomes: (1) by applying the proposed stochastic-CVaR approach and considering multiple DRPs, CCHP micro-grid operation can reach better performance in terms of cost minimization, risk control and wind power accommodation etc.; (2) higher energy utilization efficiency can be achieved by coordinately optimizing EM power biddings; etc.

Highlights

With the continuous development of the society and economy, energy and environmental issues have become increasingly prominent
Under the premise of satisfying people’s demand for multiple energy carriers, how to improve energy efficiency and achieve clean production have become a hot issue of current concern [1,2]
This paper proposed a stochastic-conditional value at risk (CVaR) optimization model for CCHP micro-grid operation with

Summary

Introduction

With the continuous development of the society and economy, energy and environmental issues have become increasingly prominent. Under the premise of satisfying people’s demand for multiple energy carriers, how to improve energy efficiency and achieve clean production have become a hot issue of current concern [1,2]. Due to the integration of distributed renewable generations, energy convertors, energy storages and multiple energy demands etc., the combined cooling, heating and power (CCHP) micro-grid provides an effective solution for this issue from a regional perspective [3,4,5]. The main question in the optimization of CCHP micro-grid operation is that what is optimum arrangement of energy components in each time period for providing multiple energy demands with minimum cost [6]. For CCHP micro-grid, the uncertainties such as distributed wind and/or photovoltaic (PV) power outputs etc., as well as the coupling of multi-energy flows are extremely.

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Conclusion