Configuration Planning of Expressway Self-Consistent Energy System Based on Multi-Objective Chance-Constrained Programming

Regarding the problem of optimal configuration self-consistent energy systems based on a 100% renewable supply for expressway electricity demand in no-grid areas, this paper proposes multi-objective planning model chance-constrained programming (CCP) to achieve optimization objectives low cost and high reliability. Firstly, number units different types wind turbines (WT), capacity photovoltaic (PV) cells, sets storage (ESS) are selected design variables our plan. After defining load grading shedding ESS scheduling strategy, Monte Carlo Simulation (MCS) method backward reduction applied uncertainties electric sources. Finally, set Pareto solutions optimized by non-dominated sorted genetic algorithm-II (NSGA-II) its unique best solution is determined Criteria Importance Though Intercriteria Correlation (CRITIC) Technique Order Preference Similarity Ideal Solution (TOPSIS) approach. Making use speed solar radiation intensity historical data an area northwest China last five years, eight case studies two typical scenarios designed carried out explore in-depth impact confidence levels fluctuation ranges results. The results verify that proposed can effectively improve robustness system satisfy power scenarios.