Virtual power plant day-ahead scheduling optimization model

Abstract

The invention provides a virtual power plant day-ahead scheduling optimization model. A model aggregation unit comprises a gas turbine, a wind turbine generator set, a photovoltaic set, a water drawing energy storage power station and loads. For the characteristics that the electricity price probability distribution description is relatively accurate and the prediction is relatively high, random programming is adopted to process the uncertainty of the electricity price; and for the characteristics that the wind power and photovoltaic output probability distribution is difficult to precise describe and the prediction precision is relative low, an information gap decision theory (IGDT) is adopted to process the uncertainty of wind power and photovoltaic output, different weights are provided to wind power and photovoltaic output deviation coefficients, and the IGDT is enabled to simultaneously process the uncertainty of wind power and photovoltaic output. In addition, for the blindness of uncertainty decisions and the different risk degrees of different strategies, the risk cost is introduced, and the risks corresponding to different decision schemes are quantified. According to the invention, a larger decision making space is provided for a decision maker, and the VPP is enabled to make the optimal decision under more conditions, so that the benefit of the virtual power plant (VPP) is increased.

Description

technical field [0001] The invention belongs to the field of power system dispatching, in particular to a day-ahead scheduling optimization model of a virtual power plant. Background technique [0002] In recent years, distributed power generation based on renewable energy has developed rapidly. However, the characteristics of small capacity, large quantity, scattered access and intermittent output of distributed power have limited its large-scale development. Aggregating renewable energy in the form of a virtual power plant (VPP) and participating in the large power grid and electricity market can not only overcome the above shortcomings, but also improve the stability of renewable energy when it is connected to the grid and the competitiveness when it enters the electricity market, thereby gaining Benefits of economies of scale. In the process of scheduling optimization, VPP faces various uncertain factors such as power market price and renewable energy output, which brin...

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Problems solved by technology

[0005] Purpose of the invention: The present invention provides a date scheduling optimization model for a virtual power plant, which solves the difficulty in describing the probability distribution of wind and solar power output in the existing power plant scheduling, and the prediction accuracy is low, and it is not suitable to use probability-based analysis methods to deal with such uncertainties. Can better provide decision makers with the optimal strategy

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