A Weakly Robust Optimal Scheduling Method for Micro Energy Networks

Abstract

The invention provides a weakly robust optimal scheduling method for a micro-energy network. This method obtains the structure information, energy price, decision information, user power and renewable energy output information of the micro energy network; establishes the energy conversion and power balance model of the micro energy network according to the structure information of the micro energy network; Energy price and decision information, as well as energy conversion and power balance models, establish a weakly robust optimal scheduling model for micro-energy networks; transform the uncertainty constraints in the weakly robust optimal scheduling model into deterministic constraints according to the equation transformation theory; According to the optimal solution obtained by GAMS software, the micro-energy grid is dispatched. The method of the present invention can solve the problem of safe operation of the micro-energy network under uncertain parameters such as user power and renewable energy output, can effectively balance the economy and risk of scheduling, and improve the conservatism of traditional robust optimal scheduling , can better provide a scheduling scheme that adapts to the actual situation.

Description

Technical field [0001] The present invention relates to optimal scheduling of a micro-energy source, and more particularly to a weak rod optimization schedule method of a micro-energy source. Background technique [0002] The micro-energy network is a micro-integrated energy system. As an important part of the energy Internet is one of the main bearing forms of future human social energy. At present, the optimization scheduling of micro-source networks has not considered the uncertainty of user power and renewable energy, will threaten the safe operation of the micro-energy network. [0003] In recent years, robust optimization has been widely used in the operating scheduling of power systems in uncertain environment. However, the traditional robust optimization methods, is concerned that the feasibility of uncertain parameters of the solution in the worst scenario, the scheduled program was a strong conservative. [0004] In response to the above problems, the present invention ...

AI Technical Summary

Problems solved by technology

However, the traditional robust optimization method focuses on the feasibility of solving uncertain parameters in the worst scenario, and the obtained scheduling scheme is highly conservative.

Images