Park-level multi-energy complementary system optimization scheduling method and device

Abstract

The invention discloses a park-level multi-energy complementary system optimization scheduling method, which comprises the following steps: generating an operation plan curve of a system through multi-time scale optimization scheduling according to actual measurement information and prediction information in combination with typical working conditions, and obtaining an optimization scheduling result by taking the lowest comprehensive cost as a target, and evaluating the optimization scheduling result according to the comprehensive energy efficiency index, and determining the rationality of the optimization parameter. When the index requirements are difficult to meet by adjusting the optimization parameters, an adjustment suggestion of the system configuration parameters is given. The invention aims to solve the implementation problem of optimization scheduling of the park-level multi-energy complementary system in the continuous capacity increasing and expansion process, and can flexibly adjust an optimization object by means of a semi-physical model according to the real-time scale of the park and a predictable reconstruction project, thereby improving the rationality of an optimization result and the accuracy of scheduling implementation.

Description

technical field [0001] The invention belongs to the technical field of comprehensive energy scheduling, and in particular relates to a park-level multi-energy complementary system optimal scheduling method, and also relates to a park-level multi-energy complementary system optimal scheduling device. Background technique [0002] The regional energy system represented by parks is an effective way to promote the local consumption of renewable energy, improve the efficiency of comprehensive energy utilization, and achieve the goal of energy conservation and emission reduction. At present, although the energy supply structure of most industrial parks has achieved "multi-energy supply", the effect of "optimized complementarity" between various energy subsystems has not yet been achieved. Energy monitoring is not in place, energy dispatching methods are extensive, and energy management methods Singleness is the root cause of low energy utilization efficiency and "too much to suppl...

AI Technical Summary

Problems solved by technology

[0004] 1) The coverage rate of the energy information collection system is low, the level of automation is poor, and the energy data is fragmented and decentralized, making it difficult to provide support for the optimal scheduling of the system

[0005] 2) Research tends to the precise modeling of complex systems and the advanced construction of optimization algorithms, ignoring the rationality and feasibility of the model itself and algorithm parameters

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