A new fuzzy model for investigating the effects of lightning on the risk-based self-scheduling strategy in a smart grid

Abstract The possibilistic-probabilistic self-scheduling problem is addressed in this paper to maximize the profit of a producer from several conventional units’ production, a wind turbine production and an Energy Storage System (ESS). Demand Response Program (DRP) is employed to reduce the uncertainty cost of the wind turbine production due to the wind speed uncertainty. Moreover, the unit commitment security constraints as well as the emission constraints are modelled as the restrictions of the proposed problem. This paper proposes a fuzzy-Markov model for modelling the effects of lightning uncertainty on the performance and self-scheduling of a producer in a smart grid in the presence of DRPs, renewable energies and ESSs. The DRPs and ESSs could be considered as the fast response resources and they play an important role in providing electricity demand and increasing the flexibility of the smart grid in the time of the occurrence of high-impact, low-probability events such as lightning. The generation units’ aging and its effect on self-scheduling problem are modelled. The problem is evaluated through different scenarios considering different amounts of risk levels. The risks associated with the uncertainty of the renewable resources and market prices are modelled using Conditional Value at Risk (CVaR). The mixed integer non-linear programming has been used to solve the self-scheduling problem and the problem is implemented in GAMS software and solved by COUENNE solver. The results show the effectiveness of the presented fuzzy technique for modeling the lightning uncertainty and the proposed method for solving the self-scheduling problem.