Micro-grid capacity programming method meeting coupling type electric cold and heat demand

Abstract

The invention discloses a micro-grid capacity programming method meeting a coupling type electric cold and heat demand, comprising: establishing a micro-grid capacity energy supply device capacity programming model meeting a coupling type electric cold and heat demand, and a micro-grid capacity energy supply device optimum capacity programming calculation method based on the multi-target particle swarm technology. According to the mode, the method solves the problem that a current programmed micro-grid needs to simultaneously provide power supply and cool supply (or heat supply) for users, and the problem of capacity optimum allocation among different energy supply devices when a coupling relation exists between electric cold supply and electric heat supply. The model realizes multi-target optimization under the condition of considering engineering, economy and security constraints of micro-grid energy supply devices.

Description

technical field [0001] The invention relates to the technical field of smart grids, in particular to a capacity planning method for micro-grids with coupled electric cooling and heating requirements. Background technique [0002] Micro-grid (also known as micro-grid) is an emerging energy Internet / smart grid technology. It is an energy supply system that efficiently utilizes distributed renewable energy and clean energy, and has self-control, protection and management. Microgrid has many advantages. First, it can achieve efficient energy utilization; second, it can meet various energy needs of users at the lowest cost; third, it can improve the reliability of power supply for users; finally, it can effectively stabilize Supply volatility brought about by renewable energy. [0003] The beneficiaries of the development of microgrids are large energy users. The characteristics of its energy use requirements include: higher energy supply reliability and quality, multiple ener...

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Problems solved by technology

However, only the typical days of the four seasons are considered, and the dynamic operating characteristics of the combined heat and power unit are given by the linear relationship between the heat-to-electricity ratio and the load rate, which is relatively rough.

In addition, this model is a unified model that includes multiple operating strategies, which increases the difficulty of solving on the one hand; , its main operation mode is determined, so the adaptability of the planning results of the model to the actual operation needs to be improved

[0010] In terms of solving the capacity planning model of the microgrid, there is no use of particle swarm computing technology to solve the multi-objective optimization problem of multi-energy microgrid capacity planning with coupled cooling, heating and electricity demand relations.

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