研究目的
To present a novel energy-management method for a microgrid that includes renewable energy, diesel generators, battery storage, and various loads, addressing various uncertainties with a risk-constrained scenario-based stochastic programming framework.
研究成果
The proposed energy management system is effective in engineering practice and beneficial for both the microgrid and the customers. Future work will study the energy management system for the microgrid aggregator and virtual power plant under the electricity market environment.
研究不足
The study assumes forecast errors follow normal distributions and does not consider the operation costs of renewable energy and energy storage. The computational complexity increases with the number of scenarios.
1:Experimental Design and Method Selection:
A two-stage scenario-based stochastic programming approach is proposed to address uncertainties in the microgrid. The first stage uses forecast data, and the second stage uses real-time data.
2:Sample Selection and Data Sources:
Forecast data for wind speed, PV power, loads, and electricity prices are used, with Monte Carlo simulation generating scenarios.
3:List of Experimental Equipment and Materials:
Includes diesel generators, storage batteries, wind turbines, PV panels, and controllable loads.
4:Experimental Procedures and Operational Workflow:
The microgrid schedules controllable resources to maximize profit, with risk management using the conditional value at risk method.
5:Data Analysis Methods:
The problem is formulated as a mixed-integer linear problem (MILP) and solved by IBM CPLEX12.4.
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