A multi-objective robust optimal allocation method to stabilize the fluctuation of renewable energy sources

Abstract

The invention discloses a multi-objective robust optimal allocation method for suppressing fluctuation of renewable energy. First of all, it aims at the uncertainty of the actual response of renewableenergy power generation and DR, Analyze the types of demand-side response resources, a robust interval model of available capacity is established, on this basis, Considering the fluctuation of grid-connected power of renewable energy generation, DR Resource Availability, A multi-objective robust optimal allocation model of multi-modal DR resources in smart distribution network is established to minimize the operating cost and maximize the utilization of renewable energy, and the complementarities of DR resources in different time scales are considered emphatically. To solve the above optimization problem, a non-dominated set ranking multi-objective genetic algorithm with elite strategy is used.

Description

technical field [0001] The invention belongs to the technical field of smart grid demand side response configuration, in particular to a multi-objective robust optimal configuration method for stabilizing renewable energy fluctuations through multi-modal demand side response resource configuration. Background technique [0002] Vigorously developing renewable energy generation (Renewable Energy Generation, REG) and promoting low-carbon end-use energy are important goals for the development of my country's future energy power system. In recent years, driven by incentive policies such as energy conservation and emission reduction, my country's REG has entered a period of rapid development and gradually formed a large-scale application. However, unlike traditional energy power generation (such as thermal power generation, natural gas power generation, etc.), REG's output is usually highly intermittent and volatile due to the impact of the external environment. Therefore, the l...

AI Technical Summary

Problems solved by technology

[0004] However, for the problem of using DR resources to stabilize renewable energy fluctuations under multiple time scales, there are still two problems in the current research work that need to be further explored and resolved: First, most of the existing research is based on multiple Research on joint scheduling of DR resources, renewable energy and conventional power generation resources in time scale

However, there are few relevant literatures on how to use the complementarity of response characteristics of different forms of DR resources to optimize the selection and configuration of DR under multiple time scales, so as to more efficiently stabilize the fluctuation of renewable energy output under different time scales. to report

Second, existing research often ignores the uncertainty of DR or uses stochastic programming, fuzzy programming and other methods to deal with it

However, in actual engineering, due to reasons such as information privacy and user subjective attitude, it is often difficult for decision makers to obtain an accurate probability distribution of the available capacity of demand response resources at each time period, which makes stochastic programming difficult to effectively apply to the above problems

In the fuzzy programming method, the determination of the membership function is highly dependent on the data samples and the subjective experience of the decision maker, so it is difficult to guarantee the optimality of the final decision in many cases.

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