Robust Optimization Model for Photovoltaic Power Producer’s Bidding Decision-Making in Electricity Market

Lifeng Liu,Yuwei Wang,Huisheng Gao,Wei Sun

doi:10.1155/2020/6109648

Abstract

With the deepening of electricity market (EM) reform and the high penetration of photovoltaic (PV) energy in power system, the uncertainties of a PV power output and fluctuation of EM prices would bring substantial financial risks for PV power producers (PPPs). This paper proposed a robust optimization model for PPP’s power bidding decision-making. Specifically, the random PV power outputs are modeled by the uncertainty set, which need no probabilistic information and can fully depict the continuous range of uncertainties. Subsequently, with respect to any scenario for day-ahead EM prices, PPP’s optimal power bidding strategy is obtained under the worst-case realization within the uncertainty set, which guarantees the robustness in resisting the negative impact of random PV power outputs on PPP’s profit. Moreover, a reformulation approach was introduced for equivalently transforming our model into a tractable framework. Simulation was implemented to validate the feasibility and effectiveness of applying our proposed model.

Highlights

It is considered that the global climate changes and energy depletion, most serious threats to sustainable development, result from the overexploitation and utilization of fossil fuels [1,2,3]
Gomes et al [9] proposed a scenario-based stochastic optimization (SO) model for a PV power producers (PPPs) participating in the day-ahead market, where the uncertainties of PV power and electricity market (EM) prices are simulated by multiple stochastic scenarios
The robust optimization model is mathematically formulated for a PPP to make bidding decisions in spot EM

Summary

Introduction

It is considered that the global climate changes and energy depletion, most serious threats to sustainable development, result from the overexploitation and utilization of fossil fuels [1,2,3]. Gomes et al [9] proposed a scenario-based stochastic optimization (SO) model for a PPP participating in the day-ahead market, where the uncertainties of PV power and EM prices are simulated by multiple stochastic scenarios. The random PV power outputs are modeled by an (budget parameter embedded) uncertainty set, which need no probabilistic information and can fully depict the continuous range of uncertainties; on the other hand, with respect to any scenario for dayahead EM prices, PPP’s optimal power bidding strategy is obtained under the worst-case realization within the uncertainty set, which guarantees the robustness in resisting the negative impact of random PV power outputs on PPP’s profit.

Methodology

Limitation

Simulation and Comparisons