Optimal scheduling method considering wind power output and demand response nondeterminacy

Abstract

The present invention relates to the supply-demand side combination random scheduling technology, especially to an optimal scheduling method considering wind power output and demand response nondeterminacy. The method comprises the step 1, based on an extension probabilistic sequence operation theory, establishing a probability model representing excitation load response nondeterminacy and price load response nondeterminacy, considering influence of the demand response nondeterminacy on cost; the step 2, in response to wind power fluctuation and randomness as background, constructing the current optimal scheduling model of an electric power system considering the wind power output and demand response nondeterminacy at the same time based on a risk constraint and risk cost theory; and step 3, converting a random optimization problem as a linear convex optimization problem for solution through conversion of a target function and a constraint condition. The method provided by the invention performs modeling and analysis aiming at demand response nondeterminacy and performs fine description of the nondeterminacy in the demand response process so as to provide practical reference for the scheduling of the electric power system and improve the stability of the electric power system.

Description

technical field [0001] The invention belongs to the technical field of joint random scheduling of supply and demand sides, and in particular relates to an optimal scheduling method considering the uncertainty of wind power output and demand response. Background technique [0002] At present, global energy problems and environmental pollution problems are prominent and need to be solved urgently. Vigorously developing renewable energy to reduce greenhouse gas emissions and realize the clean transformation of energy production is an important way to achieve sustainable energy development. In recent years, my country has vigorously promoted the production and consumption of renewable energy in order to replace a high proportion of fossil energy. By the end of 2016, my country's cumulative installed capacity of renewable energy reached 570GW; the "Energy Development Strategy Action Plan" issued by the State Council mentioned that by 2020, the proportion of renewable energy in p...

AI Technical Summary

Problems solved by technology

However, most of the current research is based on the deterministic demand response model. However, in the process of demand response, due to the error of demand response model parameters and external condition predictions and the cognitive bias of the decision-making subject, there is uncertainty in the demand response on the user side.

At present, the research on the modeling and analysis of demand response uncertainty is relatively rough, and the uncertainty in the process of demand response has not been described in detail, which cannot provide a more practical reference for power system dispatching

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