研究目的
To study the day-ahead coordination of a multi-source power system by presenting a stochastic scheduling model that aims to find a base-case solution with relatively stable operation cost in the presence of uncertain renewable generation.
研究成果
The proposed stochastic coordinated scheduling model effectively addresses the uncertainties of renewable generation in a multi-source power system, providing stable operation costs and improved system security. The use of Copula theory for scenario generation and modification ensures accuracy and reflects real-world conditions.
研究不足
The study focuses on day-ahead scheduling and may not fully address real-time operational challenges. The computational requirements increase with the number of scenarios, potentially limiting scalability for larger systems.
1：Experimental Design and Method Selection:
The study employs a stochastic scheduling model for day-ahead coordination of a multi-source power system, utilizing Monte Carlo simulation for scenario generation and Copula theory for modeling correlations between wind and photovoltaic generations.
2：Sample Selection and Data Sources:
Historical data for wind and photovoltaic generation are used to model uncertainties and generate scenarios.
3：List of Experimental Equipment and Materials:
A 6-bus power system with three thermal units, two hydro units, one wind farm, one photovoltaic station, seven transmission lines, and three loads is used for case studies.
4：Experimental Procedures and Operational Workflow:
The model is solved using Gurobi 6.5 on a personal computer, with scenarios generated via Copula theory and modified to reflect true fluctuation characteristics.
5：5 on a personal computer, with scenarios generated via Copula theory and modified to reflect true fluctuation characteristics.
Data Analysis Methods:
5. Data Analysis Methods: The effectiveness of the proposed approach is evaluated through numerical simulations on the 6-bus power system.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
