Method and system for optimizing load declaration of electricity sellers in electricity spot market

Abstract

The method and system for optimizing the load declaration of electricity sellers in the electricity spot market provided by the present invention belong to the technical field of electricity trading, and obtain the historical information of the electricity market and the real-time information of the electricity market; according to the historical information of the electricity market and the real-time information of the electricity market, Taking the minimization of electricity purchase cost as the goal, the day-ahead market load declaration model of electricity sellers is established; the improved deep Q network algorithm is used to optimize and solve the day-ahead market load declaration model of electricity retailers, and the day-ahead market load declaration curve of electricity retailers is obtained. The present invention aims at minimizing the comprehensive power purchase cost of electricity sellers, takes load limitation and deviation assessment as constraints, comprehensively considers the uncertainty of various clearing electricity prices and loads, improves the accuracy of power load declaration, and improves the load declaration The referenceability of the results makes the power purchase of electricity sellers more reasonable in the electricity market, significantly reduces the cost of electricity sellers' purchase of electricity, reduces the waste of resources, and makes resource allocation more reasonable.

Description

technical field [0001] The present invention relates to the technical field of electric power trading, in particular to a method and system for optimizing the load declaration of electricity sellers in the electric power spot market. Background technique [0002] With the opening of the electricity sales side of the electricity market, social capital has invested in various electricity sales companies, breaking the monopoly of electricity sales, building multiple electricity sales entities, and greatly changing the existing electricity market structure and operating model. Facing the new situation of various electricity retailers participating in electricity market transactions, reasonable power declaration and price decision-making methods are of great significance for electricity retailers to optimize their own trading plans, maximize revenue and optimize the allocation of electricity market resources. [0003] The main business of electricity sellers is to purchase electr...

AI Technical Summary

Problems solved by technology

This type of algorithm assumes that the uncertainty obeys a certain mathematical probability distribution, thereby reducing the difficulty of model construction. However, the error between the artificially assumed probability distribution and the actual uncertainty law will directly affect the rationality and reliability of the decision-making results.

The robust optimization method fuzzily expresses uncertainty with an interval that considers extreme results, avoids artificial assumptions about uncertainty, and improves computational efficiency; however, this type of algorithm often leads to more conservative decision results

[0005] The above-mentioned self-organization behavior optimization decision-making model based on stochastic optimization, robust optimization and other methods makes the power load declaration of electricity retailers unreasonable, affects the rationality of market electricity price prediction and formulation, and makes it difficult to guarantee the smoothness of electricity sales and purchase transactions. Rationality, so as to increase the cost of electricity purchase, resulting in waste or unreasonable allocation of resources

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