Regional smart energy system optimization configuration method and system

A technology of smart energy and configuration methods, applied in the directions of resources, data processing applications, forecasting, etc., can solve problems such as the lack of urban smart energy system planning methods

Pending Publication Date: 2021-05-18
CHINA ELECTRIC POWER RES INST +2
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] However, there is currently no planning method for urban smart energy systems. In order to reduce energy consumption and waste, solve energy shortages, fully utilize resources, and reduce carbon emissions, it is urgent for technicians to provide a feasible plan for urban smart energy systems. method

Method used

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  • Regional smart energy system optimization configuration method and system
  • Regional smart energy system optimization configuration method and system
  • Regional smart energy system optimization configuration method and system

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Experimental program
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Effect test

Embodiment 1

[0028] The present invention provides a method for optimal configuration of a regional smart energy system, such as figure 2 As shown, the method includes:

[0029] Step 101, obtaining the load demand of cold, heat and electricity in the area at each time in the optimization period;

[0030] Step 102, substituting the load demand of cooling, heating and electricity in the region at each time in the optimization cycle into the pre-built optimal configuration model, using the improved particle swarm optimization algorithm to solve the optimal configuration model, and obtaining the parameters to be optimized Optimal solution;

[0031] Among them, the improvement of the improved particle swarm optimization algorithm is to determine the similarity between each particle in the particle swarm and the optimal particle of the group, and divide the particles in the particle swarm into different subgroups according to the similarity, and according to each The swarm optimal particle of...

Embodiment 2

[0123] The present invention provides a regional smart energy system optimization configuration system, such as Figure 4 As shown, the system includes:

[0124] The obtaining module is used to obtain the load demand of cold, heat and electricity in the area at each time in the optimization cycle;

[0125] The optimization solution module is used for substituting the load demand of cold, heat and electricity in the region at each time in the optimization period into the pre-built optimal configuration model, using the improved particle swarm optimization algorithm to solve the optimal configuration model, and obtaining the Optimal solution of optimized parameters;

[0126] Among them, the improvement of the improved particle swarm optimization algorithm is to determine the similarity between each particle in the particle swarm and the optimal particle of the group, and divide the particles in the particle swarm into different subgroups according to the similarity, and accordi...

Embodiment 3

[0191] All users in a city's smart energy system are residential users. It is assumed that the heating / cooling pipelines of the district energy subsystem are laid close to the heating / cooling load nodes in the area, so the pipeline construction cost is not considered. Three energy subsystems are planned and constructed in the region. The energy production equipment of each regional energy subsystem is mainly photovoltaic, fan, cogeneration, gas boiler, electric boiler, electric refrigerator, absorption refrigerator, and the energy storage equipment is mainly For batteries and heat accumulators, the design life of the energy subsystem is 30 years. The voltage level of the city's smart energy system is 10kV, and the node load and line parameters are shown in Table 1.

[0192] Table 1

[0193] node 1 Load (MW+jMVar) node 2 Line Impedance (p.u.) 1 0.2+j0.116 13 0.02+j0.016 2 0.5+j0.125 1 0.0082505+j0.019207 3 0.8+j0.4 1 0.0082505+j0.019207 4...

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Abstract

The invention relates to an optimal configuration method and system for a regional smart energy system. The method comprises the following steps: acquiring load requirements of cold energy, heat energy and electricity energy in regions at all moments in an optimization period; substituting the load requirements of the cold energy, the hot energy and the electric energy in each moment region in the optimization period into a pre-constructed optimization configuration model, and solving the optimization configuration model by using an improved particle swarm algorithm to obtain an optimal solution of the to-be-optimized parameters. According to the technical scheme provided by the invention, the regional smart energy system is planned more reasonably, the operation economy of the system is ensured, and unnecessary loss and pollution are avoided.

Description

technical field [0001] The present invention relates to the technical field of energy Internet planning, and in particular to a method and system for optimal configuration of a regional smart energy system. Background technique [0002] With the rapid development of the energy Internet concept, people pay more and more attention to the comprehensive and efficient utilization of energy, and the problem of urban pollution is also becoming more and more prominent. It is urgent to build a power system that can reduce energy consumption and make full use of green energy. [0003] Therefore, the technicians have given a method such as figure 1 As shown in the urban smart energy system, the urban smart energy system generally includes multiple regional energy subsystems, which are uniformly dispatched by the urban smart energy system management system. Multiple regional energy subsystems also contain a variety of energy equipment. Compared with traditional For the planning of a si...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06G06N3/00
CPCG06N3/006G06Q10/04G06Q10/06315G06Q10/067G06Q50/06
Inventor 惠慧刘伟韦涛段青
Owner CHINA ELECTRIC POWER RES INST
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