Electric power spot market e-commerce load declaration optimization method and system

Abstract

The invention provides an electric power spot market e-commerce load declaration optimization method and system, and belongs to the technical field of electric power transaction, and the method comprises the steps: obtaining electric power market historical information and electric power market real-time information; establishing a day-ahead market load declaration model of the electricity seller by taking minimization of the comprehensive electricity purchasing cost of the electricity seller as a target according to the historical information of the electricity market and the real-time information of the electricity market; and adopting an improved deep Q network algorithm to optimize and solve the electricity seller day-ahead market load declaration model, and obtaining an electricity seller day-ahead market load declaration curve. The method and system aim at minimizing the comprehensive electricity purchasing cost of the electricity seller, take load limitation and deviation assessment as constraints, comprehensively consider the uncertainty of various clearing electricity prices and loads, improve the accuracy of power load declaration, improve the reference of a load declaration result, enable the electricity purchasing of the electricity seller in the power market to be more reasonable, remarkably reduce the electricity purchasing cost of electricity vendors, reduce the waste of resources, and enable the resource allocation to be 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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