Optimal scheduling of Virtual Power Plant with risk management

Due to intense electricity consumption, environmental concerns and technological development, a great number of renewable distributed resources have been widely installed in the distributed network. However, the reality that renewable distributed resources frequently fluctuate under high penetration makes effective use a challenge. Fortunately, with improved communication architecture and control techniques, this could be achieved by a Virtual Power Plant (VPP). VPP can aggregate various resources in a distributed generation portfolio, by creating one single operating profile. The aim of this paper is mainly to analyze optimal scheduling of VPP to maximize its profit, with due consideration given to the uncertainty of renewable energy output, such as wind power, and to make the energy mix respond to system need. A risk quantization method (CVaR) is introduced to deal with uncertainty. This paper presents a VPP scheduling model, which takes VPP total operation cost, traded electricity cost, unit earnings, supply-demand balancing and other constraints into account, with a CVaR assessment method embedded into this model. According to the scenarios generated by uncertainty of wind power output, numerical results for a proposed case are discussed. These results show the expected profit of VPP scheduling is closely associated with different degrees of confidence , which is a great help for VPP operators when making the tradeoff between risk and profit.

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Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.