A multi-objective hydropower purchase optimization method and system of a provincial power network under time-of-use electricity price

Abstract

The invention belongs to the field of hydropower energy optimization operation, discloses a multi-objective hydropower purchase optimization method and system of a provincial power network under time-of-use electricity price. The method establishes and solves a multi-objective time-of-use electricity price model based on the response of user demand to the time-of-use electricity price. The conditional value-at-risk (VaR) based on portfolio theory is introduced as a risk index, and a multi-objective optimization model is proposed to maximize the expected profit and minimize the risk of power purchase. The power purchase ratio scheme and the power purchase risk scheme are optimized to obtain the inter-provincial power purchase risk decision and the optimal power purchase ratio. The inventioncombines the sensitivity of the user to the change of the electricity price, considers the minimization of the peak and valley load of the system, maximizes a plurality of objectives of the user satisfaction, establishes a multi-objective time-of-use electricity price model based on the user response, improves the feasibility of the time-of-use electricity price scheme, and lays a foundation forestablishing a maximum expected benefit model of power purchase.

Description

technical field [0001] The invention belongs to the field of optimized operation of hydropower energy, and in particular relates to a multi-objective power purchase optimization method and system for hydropower in an inter-provincial power grid under time-of-use electricity prices. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] When establishing the peak-valley time-of-use electricity price, simply consider the model that minimizes the peak-valley difference, maximizes the valley load, and minimizes the peak load, or combines the two models to solve the peak-valley time-of-use electricity price scheme. [0004] When calculating the value at risk, the calculation formula of the optimal power purchase in the contract market is directly applied, without considering the combination fluctuation of the spot market, or the contract market and the spot market are regarded as a portfolio to calculate the valu...

AI Technical Summary

Problems solved by technology

[0008] (1) The existing technology does not consider the goal of maximizing user satisfaction while minimizing the peak-to-valley load difference of the system, which may cause user discomfort after using the time-of-use electricity price scheme

[0009] (2) The existing technology does not establish a time-of-use electricity price model based entirely on user responses, and the time-of-use electricity price scheme cannot fully reflect the actual situation to a certain extent

[0010] (3) The existing technology is establishing a risk minimization model, which is not based on the VaR value analysis method based on the portfolio theory, which has poor reliability for risk assessment

[0011] (4) The existing technology does not adopt the NSGA2 algorithm when constructing the power purchase expected return maximization model and risk minimization model, and cannot quickly obtain the optimal power purchase ratio scheme and the corresponding power purchase risk

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