Distributed electric heating equipment operation optimization algorithm based on user load requirements

Abstract

The invention discloses a distributed electric heating equipment operation optimization algorithm based on user load requirements. The algorithm comprises the following steps: inputting a local time-of-use electricity price curve, office time of staff in a building to be optimized, an outdoor temperature curve and initial indoor temperature to construct environment parameters; building a room thermal characteristic function according to the window-wall ratio, the material heat conductivity coefficient and the specific heat of different rooms; inputting operation parameters of the electric heating equipment, and constructing an operation function of the electric heating equipment; according to room use characteristics, setting different target temperature for different time periods, and creating a refined target temperature function; carrying out optimization solution on the output of the distributed electric heating equipment by taking the lowest operation electric charge as an optimization target; and optimizing and solving each room step by step, and solving an electric heating equipment output curve of each room by adopting mixed integer programming. The system operation optimization is taken as a target, the development of the optimal operation control strategy of the distributed electric heating equipment is realized, the power utilization cost can be saved, and the invention has a relatively high market application prospect.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to an operation optimization algorithm for distributed electric heating equipment based on user load demands. Background technique [0002] Distributed electric heating is a scattered heating mode that converts electrical energy into heat energy and directly releases heat to meet heating needs. It is accepted by users for its large adjustment, control and guarantee capabilities. In recent years, more and more users in the northern region choose electric heating instead of traditional coal-fired heating. While helping the energy revolution, it is also one of the important ways to develop green energy and promote low-carbon emission reduction. With the maturity of big data technology and the increase of energy demand, more and more enterprises have proposed various business models and innovative concepts for energy optimization services. [0003] In the existing electric heatin...

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Problems solved by technology

[0003] In the existing electric heating control system, the ambient temperature suitable for human life and work is used as the only temperature setting value, resulting in unnecessary consumption of a large amount of energy in some areas with low heat demand

In fact, the heat storage characteristics of buildings make the distributed electric heating load have time-shift characteristics, and the electric heating load is affected by factors such as building parameters, outdoor environment, and indoor temperature setpoints, which leads to the fact that only the living and working environment Heating with temperature as the only temperature setting value cannot achieve comfortable and convenient heating, which will cause waste of energy and decrease of comfort

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