Integrated Energy System Dispatch Considering Carbon Trading Mechanisms and Refined Demand Response for Electricity, Heat, and Gas

To realize a carbon-efficient and economically optimized dispatch of the integrated energy system (IES), this paper introduces a highly efficient dispatch strategy that integrates demand response within a tiered carbon trading mechanism. Firstly, an efficient dispatch model making use of CHP and P2G technologies is developed to strengthen the flexibility of the IES. Secondly, an improved demand response model based on the price elasticity matrix and the capacity for the substitution of energy supply modes is constructed, taking into account three different kinds of loads: heat, gas, and electricity. Subsequently, the implementation of a reward and penalty-based tiered carbon trading mechanism regulates the system’s carbon trading costs and emissions. Ultimately, the goal of the objective function is to minimize the overall costs, encompassing energy purchase, operation and maintenance, carbon trading, and compensation. The original problem is reformulated into a mixed-integer linear programming problem, which is solved using CPLEX. The simulation results from four example scenarios demonstrate that, compared with the conventional carbon trading approach, the aggregate system costs are reduced by 2.44% and carbon emissions are reduced by 3.93% when incorporating the tiered carbon trading mechanism. Subsequent to the adoption of demand response, there is a 2.47% decrease in the total system cost. The proposed scheduling strategy is validated as valuable to ensure the low-carbon and economically efficient functioning of the integrated energy system.

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Publication Details

Journal
Energies
Published
2024-09-21
DOI
https://doi.org/10.3390/en17184705
Citations
8
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
1.67
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Integrated Energy System Dispatch Considering Carbon Trading Mechanisms and Refined Demand Response for Electricity, Heat, and Gas

Lihui Gao, Nan Chen, Junheng Gao, Shuanghao Yang
8 citations
Energies
Integrated Energy Systems Optimization
1.67
article

Integrated Energy System Dispatch Considering Carbon Trading Mechanisms and Refined Demand Response for Electricity, Heat, and Gas

Lihui Gao, Nan Chen, Junheng Gao, Shuanghao Yang
article en
8 citations

Abstract

To realize a carbon-efficient and economically optimized dispatch of the integrated energy system (IES), this paper introduces a highly efficient dispatch strategy that integrates demand response within a tiered carbon trading mechanism. Firstly, an efficient dispatch model making use of CHP and P2G technologies is developed to strengthen the flexibility of the IES. Secondly, an improved demand response model based on the price elasticity matrix and the capacity for the substitution of energy supply modes is constructed, taking into account three different kinds of loads: heat, gas, and electricity. Subsequently, the implementation of a reward and penalty-based tiered carbon trading mechanism regulates the system’s carbon trading costs and emissions. Ultimately, the goal of the objective function is to minimize the overall costs, encompassing energy purchase, operation and maintenance, carbon trading, and compensation. The original problem is reformulated into a mixed-integer linear programming problem, which is solved using CPLEX. The simulation results from four example scenarios demonstrate that, compared with the conventional carbon trading approach, the aggregate system costs are reduced by 2.44% and carbon emissions are reduced by 3.93% when incorporating the tiered carbon trading mechanism. Subsequent to the adoption of demand response, there is a 2.47% decrease in the total system cost. The proposed scheduling strategy is validated as valuable to ensure the low-carbon and economically efficient functioning of the integrated energy system.

EnergiesVol. 17(18)
Changchun University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 16%
Integrated Energy Systems Optimization
1.67
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