4.5 Article

Operation optimization of integrated energy systems based on heat storage characteristics of heating network

Journal

ENERGY SCIENCE & ENGINEERING
Volume 9, Issue 2, Pages 223-238

Publisher

WILEY
DOI: 10.1002/ese3.842

Keywords

dynamic heat energy transfer; economy; integrated energy systems; operation optimization; virtual energy storage

Categories

Funding

  1. National Key Research and Development Program of China [2016YFB0900100]
  2. Fundamental Research Funds for the Central Universities [2019FR001]

Ask authors/readers for more resources

This paper proposes an operation optimization model of electric-heat integrated energy system considering the virtual energy storage characteristics of the heat supply network, and solves the model with a Monte Carlo Simulation embedded Quantum Particle Swarm Optimization algorithm to improve the robustness of scheduling optimization results. In a simulation case, it is shown that considering the virtual energy storage of the heat supply network enhances the complementary potential of the electric-heat integrated energy system and reduces the operation cost of the system.
With the development of multi-energy technology, the electric-heat integrated energy system has become an important research direction for multi-energy joint supply. The dynamic characteristics and energy storage capacity of heat supply network provide potential for joint dispatching of electric heating energy system. Aiming at the problem of electric-heat joint dispatching, this paper presents an operation optimization model of electric-heat integrated energy system considering the virtual energy storage characteristics of heat supply network. Firstly, according to the characteristics of transmission delay and user temperature fuzzy, the virtual energy storage characteristics of heat supply network are studied, and a model of the dynamic transfer of energy in the heat system was built. Then, the operation optimization model of the electric-heat integrated energy system is established to minimize the operation cost. In order to improve the robustness of scheduling optimization results, the Monte Carlo Simulation embedded Quantum Particle Swarm Optimization algorithm is proposed to solve the model. In order to prove the validity of the proposed model, this paper selects a park (a 36 node thermal system) in the northwest region of China as a simulation case. The results show that the operation optimization method considering the virtual energy storage of heat supply network will greatly enhance the complementary potential of the electric-heat integrated energy system and reduce the operation cost of the system.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available