Virtual power plant mid-term dispatch optimization

• Published in: Applied energy Vol. 101; pp. 134 - 141
• Main Authors: Pandžić, Hrvoje, Kuzle, Igor, Capuder, Tomislav
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Kidlington Elsevier Ltd 01.01.2013; Elsevier
• Subjects: Applied sciences; case studies; Contracts; Economic data; Electric energy; Electric power generation; Electric power plants; electricity; Energy; Energy economics; Exact sciences and technology; General, economic and professional studies; Linear programming; Markets; Methodology. Modelling; Natural energy; Optimal dispatch; Optimization; power generation; Power plants; Power sources; solar energy; uncertainty; Virtual power plant; wind; Wind power; Optimal dispatch; Virtual power plant; Linear programming
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2012.05.039

► Mid-term virtual power plant dispatching. ► Linear modeling. ► Mixed-integer linear programming applied to mid-term dispatch scheduling. ► Operation profit maximization combining bilateral contracts and the day-ahead market. Wind power plants incur practically zero marginal costs during their operation. However, variable and uncertain nature of wind results in significant problems when trying to satisfy the contracted quantities of delivered electricity. For this reason, wind power plants and other non-dispatchable power sources are combined with dispatchable power sources forming a virtual power plant. This paper considers a weekly self-scheduling of a virtual power plant composed of intermittent renewable sources, storage system and a conventional power plant. On the one hand, the virtual power plant needs to fulfill its long-term bilateral contracts, while, on the other hand, it acts in the market trying to maximize its overall profit. The optimal dispatch problem is formulated as a mixed-integer linear programming model which maximizes the weekly virtual power plant profit subject to the long-term bilateral contracts and technical constraints. The self-scheduling procedure is based on stochastic programming. The uncertainty of the wind power and solar power generation is settled by using pumped hydro storage in order to provide flexible operation, as well as by having a conventional power plant as a backup. The efficiency of the proposed model is rendered through a realistic case study and analysis of the results is provided. Additionally, the impact of different storage capacities and turbine/pump capacities of pumped storage are analyzed.