研究目的
To develop the linear operation model of HSBP plant considering with intricate energy flow, and propose an optimal operation strategy to maximize its revenues in electricity markets.
研究成果
The proposed optimal operation strategy for HSBP plants, incorporating stochastic programming and CVaR for risk management, effectively maximizes revenues in electricity markets. Case studies demonstrate the benefits of participating in both DA and RT markets, the complementary nature of solar and biomass energy, and the importance of TES capacity in optimizing revenues.
研究不足
The study assumes the HSBP plant as a price-taker in the DA market and a potential price-maker in the RT market, which may not fully capture the dynamics of all electricity markets. The linearization of the power block efficiency and the use of historical data for solar irradiation and market prices may also introduce approximations.
1：Experimental Design and Method Selection:
The study employs a two-stage stochastic mixed integer linear programming (MILP) framework to model the operation strategy of a HSBP plant in electricity markets, considering uncertainties in solar irradiation and market prices.
2：Sample Selection and Data Sources:
Historical data of solar irradiation in Texas and market prices from the ERCOT market are used.
3：List of Experimental Equipment and Materials:
A HSBP plant with a rated capacity of 110 MW, including a solar field, biomass boiler, TES system, and power block.
4：Experimental Procedures and Operational Workflow:
The HSBP plant participates in both day-ahead (DA) and real-time (RT) markets, with bids determined based on stochastic programming and CVaR for risk management.
5：Data Analysis Methods:
The model is solved using CPLEX in MATLAB, with scenario reduction techniques applied to manage computational complexity.
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
