Impact of renewable energy on power system cost and reliability

This paper develops computational models that can help lead to a detailed understanding of the operational integration challenges of renewable energy (solar photovoltaic and wind) in an individual utility system. We have developed an enhanced operational model to consider additional constraints from the special characteristics of the renewable energy. The mixed integer programming (MIP) model treats the renewable energy supply, operating reserves, and demand as exogenous known information, and it solves for the unit commitment (UC) and the economic dispatch (ED) decisions. Based on a utility system case study we find the following 1) the imperfect dayahead forecast raises the operating cost and reduces the system reliability; 2) the unit commitment decision changes more frequently as the forecast uncertainty increases or the balancing reserve requirement increases; 3) nearly all available renewable energy is utilized with some curtailment in winter and spring; and 4) the integration cost for larger renewable penetration (14-22%) is modest around $1-2/MWh. The contribution of this paper is two-fold. First, we introduce a UC/ED model that incorporates the wind and the solar supply characteristics, as well as the corresponding balancing reserve requirements. The model can be solved relatively fast on a large-scale utility system. Second, we analyze the impact of high penetration renewable energy, primarily PV, on cost and reliability based on a realistic utility system.