Operational optimization of a building-level integrated energy system considering additional potential benefits of energy storage

AbstractAs a key component of an integrated energy system (IES), energy storage can effectively alleviate the problem of the times between energy production and consumption. Exploiting the benefits of energy storage can improve the competitiveness of multi-energy systems. This paper proposes a method for day-ahead operation optimization of a building-level integrated energy system (BIES) considering additional potential benefits of energy storage. Based on the characteristics of peak-shaving and valley-filling of energy storage, and further consideration of the changes in the system’s load and real-time electricity price, a model of additional potential benefits of energy storage is developed. Aiming at the lowest total operating cost, a bi-level optimal operational model for day-ahead operation of BIES is developed. A case analysis of different dispatch strategies verifies that the addition of the proposed battery scheduling strategy improves economic operation. The results demonstrate that the model can exploit energy storage’s potential, further optimize the power output of BIES and reduce the economic cost.

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Research on Operational Optimization Technology of Regional Integrated Energy System Considering Operating Cost and Reliability

Proceedings of PURPLE MOUNTAIN FORUM 2019-International Forum on Smart Grid Protection and Control - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-13-9783-7_4 ◽

2019 ◽

pp. 39-49

Author(s):

Xiaochen Zhang ◽

Jinda Zhu ◽

Dongmei Yang ◽

Yonghua Chen ◽

Wei Du

Keyword(s):

Operating Cost ◽

Energy System ◽

Operational Optimization ◽

Integrated Energy System

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Optimal scheduling of building integrated energy system based on demand response

E3S Web of Conferences ◽

10.1051/e3sconf/202018501068 ◽

2020 ◽

Vol 185 ◽

pp. 01068

Author(s):

Mengju Wei ◽

Yang Yang ◽

Mengjin Hu ◽

Yongli Wang ◽

Siyi Tao ◽

...

Keyword(s):

Renewable Energy ◽

Demand Response ◽

Cloud Model ◽

Operating Cost ◽

Energy System ◽

Model Particle ◽

On Demand ◽

Integrated Energy System ◽

Building Level ◽

Particle Group

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.

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