Abstract

With the development of renewable energy technology, integrating a variety of renewable energy integrated energy systems can effectively solve the problem of optimizing the scheduling of buildings with high energy consumption and fast growth rate. Based on the modeling and analysis of various energy equipment in the system, the integrated energy system of building buildings, based on the demand response compensation price, with the lowest construction operating cost as the goal function, establishes the optimization scheduling model of building-level integrated energy system based on demand response, and uses the particle group algorithm based on cloud model improvement to optimize the solution of the model. The study is introduced for simulation to compare the two different modes of participation in demand response, and the optimal performance of cloud model particle group algorithm and elementary particle group algorithm. The results show that the cloud model particle group algorithm model based on demand response can effectively save the operating cost of the building-level integrated energy system, and reduce the power grid side load peak and valley difference.

Highlights

  • The diversified development of building functions makes the connection between various energy-using equipment in the building more and more closely, and the requirements of comprehensive and systematic energy use are put forward [1]

  • Buildings have a variety of energy demand sourcing, but the energy structure is unreasonable, easy to increase the power grid side load peak and valley difference characteristics, on the other hand, buildings in the use of energy equipment flexible and diverse, energy efficiency is huge potential [2]

  • Building integrated energy system to enhance the interaction with power grid side information by participating in demand response projects, to achieve the optimization of building electricity behavior [3]

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Summary

Introduction

The diversified development of building functions makes the connection between various energy-using equipment in the building more and more closely, and the requirements of comprehensive and systematic energy use are put forward [1]. Buildings have a variety of energy demand sourcing, but the energy structure is unreasonable, easy to increase the power grid side load peak and valley difference characteristics, on the other hand, buildings in the use of energy equipment flexible and diverse, energy efficiency is huge potential [2]. Technologies such as (pv system, PV), (wind turbine, WT), (combined cooling, heating and power system, CCHP), (battery, BT) and (thermal energy storage, TES) have been used in various types of buildings.

Objective function
Basic particle group algorithm
Simulation of building energy systems
Schedule Gas Electricity IDR
Conclusion

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