Abstract
AbstractWith 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.
Highlights
Energy is the foundation of human survival and development and the lifeblood of the national economy
In order to bridge this gap, this paper proposes a heating network model that takes into account the latency of the heat transfer process and the virtual energy storage characteristics of the primary heat network from the temperature dynamics of the district heat network, and establishes an electro-heat integrated energy system (IES) optimization scheduling model that takes into account the heat transfer dynamics characteristics
In order to prove the validity of this method more clearly in this paper, the example is constructed to compare two typical scenarios: Scenario 1: Electro-heat IES operation optimization model without considering the dynamic properties of heat energy transfer
Summary
Energy is the foundation of human survival and development and the lifeblood of the national economy. Ref [6] proposed an electro-heat coupling model that takes into account the constraint of heat exchange link. Ref [8] proposed an electro-heat coupling model of the overall energy flow based on the energy balance characteristics and the irreversibility of heat transport. Ref [9] proposed an electro-heat coupling model that takes into account the transmission losses of networks. In order to prove the validity of this method more clearly in this paper, the example is constructed to compare two typical scenarios: Scenario 1: Electro-heat IES operation optimization model without considering the dynamic properties of heat energy transfer. Scenario 2: Electro-heat IES operation optimization model considering dynamic properties of heat energy transfer
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