Power market equilibrium solution method based on two-layer particle swarm optimization algorithm

Abstract

The invention discloses a power market equilibrium solution method based on a two-layer particle swarm optimization algorithm. The power market equilibrium solution method based on the two-layer particle swarm optimization algorithm includes the steps of (1) constructing a power producer main energy quotation strategy and an ISO (international organization for standardization) market clearing model based on the rules of single-time power market bidding; (2) constructing an Nash fitness calculation function for a bidding strategy combination of power producers; (3) searching for possible strategy combinations of the power producers through an outer particle swarm optimization algorithm, solving the Nash fitness of each strategy combination according to the Nash fitness calculation functionand combined with an inner particle swarm optimization algorithm and an interior point method, and then solving and acquiring an Nash equilibrium strategy combination as a power market optimal strategy via corresponding Nash fitness for each strategy combination. The power market equilibrium solution method based on the two-layer particle swarm optimization algorithm has the advantages of avoidingsemi-smooth nonlinear equations formed for solving double-layer optimization of the power generators through the use of particle swarm optimization algorithm to search for equilibrium solutions, andsimplifying the algorithm at the cost of time under the premise of ensuring accurate results.

Description

technical field [0001] The invention relates to the field of electric power technology, in particular to a method for solving the equilibrium of an electric power market based on a two-layer particle swarm algorithm. Background technique [0002] Nash equilibrium is an effective tool to predict and analyze the trend of electricity market, and it is of great significance to the design and supervision of the market. Solving the equilibrium of the electricity market has always been a very complicated problem. The classical Cournot equilibrium and supply function equilibrium analytical calculation methods cannot be adapted to the actual electricity market equilibrium calculation because they do not consider network congestion and output constraints. Therefore, it is necessary to explore effective methods to solve the electricity market equilibrium problem. [0003] At present, non-linear complementary algorithms and cyclic iteration methods are widely used at home and abroad. ...

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Problems solved by technology

Among them, the nonlinear complementary algorithm converts the optimal response function of the generator into a set of semi-smooth nonlinear complementary equations through the KKT condition. The dimension of the relaxation factor is high, and the algorithm is extremely complicated.

However, the cyclic iteration method uses the idea of ​​repeatedly solving the optimal response function of each power supplier, and often fails to find an equilibrium solution due to poor convergence.

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