The invention relates to the technical field of short-term electric quantity regulation and control, in particular to an electric quantity regulation and control method and
system based on a
quantum algorithm and a neural network in an
electric power market environment. According to the method, a plurality of
quantum registers are constructed to form a
population and are initialized, the
quantum registers are individuals representing market decisions, and the market decisions are sets of declared quantity-price curves of all participants in the
electricity market; the quantum code of one participant is selected from each quantum register to serve as a candidate solution, the fitness of the candidate solution is evaluated, and updating variation is conducted on half of the quantum registers with the smaller fitness of the candidate solution so as to iterate the
population; when the number of
population iterations reaches a set threshold value, selecting an individual which meets the constraint conditions of each participant and has the maximum optimization target as an optimal
declaration strategy; obtaining a
declaration quantity price decision of each participant through optimal
declaration strategy inverse quantum coding; the optimization objective as the individual's market decision is to maximize the sum of producer and
consumer residuals. According to the method, the defect of poor power resource configuration efficiency in the prior art is overcome, market decision optimization is performed in combination with the
quantum genetic algorithm, declaration reference is provided for each participant, so that clearing power is improved, power configuration is optimized, and configuration efficiency is improved.