Day-Ahead Scheduling of Integrated Electric Heating System Considering Thermal Inertia

doi:10.3969/j.issn.1008-0198.2023.02.006

Abstract

Abstract: For the problem of optimal scheduling of integrated energy systems involving wind power consumption, a stochastic optimal scheduling strategy with systematic consideration of mixed uncertainties is proposed by mining multiple thermal inertia. The thermal inertia of the network based on the dynamic characteristics of the heat network and the thermal storage characteristics is explored, the thermal load elasticity constraint is introduced into the modeling of thermal inertia of buildings, and heat pumps and thermal storage are used as time-shiftable electric loads and heat sources, which are jointly modeled with CHP units to solve the peak-valley mismatch of electric and thermal loads.On this basis, the IES model considering multiple thermal inertia is established, the coupled system of 33-node heat network and 9-node grid is used as an example for the analysis. And the traditional heuristic particle swarm algorithm with the mixed integer nonlinear programming algorithm is compared. The results show that by mining the multiple thermal inertia to broad the flexibility of the energy system, the complementary aid and flexible dispatch between multiple heterogeneous energy sources can be realized, and the mathematical planning algorithm can effectively improve the solving efficiency far than the particle swarm algorithm.

Key words: integrated energy systems, flexibility, thermal inertia, mixed integer nonlinear programming

CLC Number:

TM731

DAI Mengdi, KE Deping, SONG Lin, WANG Huiji. Day-Ahead Scheduling of Integrated Electric Heating System Considering Thermal Inertia[J]. Hunan Electric Power, 2023, 43(2): 32-38.

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