Abstract
For the virtual power plants containing energy storage power stations and photovoltaic and wind power, the output of PV and wind power is uncertain and virtual power plants must consider this uncertainty when they participate in the auction in the electricity market. In this context, this paper studies the bidding strategy of the virtual power plant with photovoltaic and wind power. Assuming that the upper and lower limits of the combined output of photovoltaic and wind power are stochastically variable, the fluctuation range of the day-ahead energy market and capacity price is stochastically variable. If the capacity of the storage station is large enough to stabilize the fluctuation of the output of the wind and photovoltaic power, virtual power plants can participate in the electricity market bidding. This paper constructs a robust optimization model of virtual power plant bidding strategy in the electricity market, which considers the cost of charge and discharge of energy storage power station and transmission congestion. The model proposed in this paper is solved by CPLEX; the example results show that the model is reasonable and the method is valid.
Highlights
The randomness and fluctuation of the wind and photovoltaic power output restrain its grid connected capability [1, 2]
In order to promote large-scale bidding for wind and photovoltaic power, which needs energy storage station providing reserve service, in this paper, a robust optimization bidding model for virtual power plants is proposed, which considers the uncertainty of the wind and photovoltaic power output and the market price
Example results show the following: (1) Construction of joint probability distribution of wind and photovoltaic power output is based on Clay-Copula function; the combined output model of wind and photovoltaic power is simulated
Summary
The randomness and fluctuation of the wind and photovoltaic power output restrain its grid connected capability [1, 2]. Wen and Kumar [16] introduced the game model into the robust optimization problem of the power system and obtained an economic scheduling strategy with strong robustness to short-term uncertainty of wind power generation. [19] proposed a robust optimization method based on moment uncertain distribution to solve the problem of economic and environmental scheduling with wind power. Qiang et al [24] proposed the scheduling model of the wind power system based on the robust optimization framework, which solved the problem of the objective function deterioration. This paper takes the virtual power plant to maximize the economic benefits as the objective function and the virtual power plant output and market price as uncertainties and constructs the virtual power plant bidding strategy robust optimization model with energy storage station and photovoltaic and wind power
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