Low-Carbon Economic Dispatching of Combined Heat and Power System Considering Electric-thermal Integrated Demand Response

Zhang, Xiaoyue; Wang, Jin; Ren, Shengnan; Liu, Ting; Zhao, Shuhao; Gong, Li

doi:10.1109/ei252483.2021.9713049

Cited by 5 publications

(8 citation statements)

References 3 publications

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“…The mathematical model of the equipment developed in this paper and the corresponding parameters taken are referenced from [19,20].…”

Section: Energy Supplymentioning

confidence: 99%

“…Lithium bromide units can use high-temperature flue gas for cooling, with the model and operating constraints shown in the equation below [20].…”

Section: Absorption Refrigerationmentioning

confidence: 99%

“…The model and operating constraints of a fuel cell, which generates electrical energy through a chemical reaction, are shown in the following equation [20]:…”

Section: Fuel Cellsmentioning

confidence: 99%

“…The power-to-hydrogen system converts electrical energy into hydrogen through the electrolysis of water, with the simplified model and operational constraints shown in the following equation [20]:…”

mentioning

confidence: 99%

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Chance-Constrained Dispatching of Integrated Energy Systems Considering Source–Load Uncertainty and Photovoltaic Absorption

Zong

Lai

et al. 2023

Sustainability

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Because of their renewable and non-polluting characteristics in power production, distributed photovoltaics have been developed, but they have also been criticized for the volatility of their output power. In this paper, an integrated energy system optimal dispatching model is proposed to improve the local absorption capacity of distributed photovoltaics. First, an integrated energy system consisting of electricity, heat, cooling, gas, and hydrogen is modeled, and a mathematical model of the system is constructed. After that, the uncertainty of distributed photovoltaic power and load demand is modeled, and a typical scenario data set is generated through Monte Carlo simulation and K-means clustering. Finally, an optimal dispatching model of the integrated energy system is constructed to minimize the daily operating cost, including energy consumption, equipment operation and maintenance, and curtailment penalty costs, as the optimization objective. In the objective, a segmented curtailment penalty cost is Introduced. Moreover, this paper presents a chance constraint to convert the optimization problem containing uncertain variables into a mixed integer linear programming problem, which can reduce the difficulty of the solution. The case shows that the proposed optimal dispatching model can improve the ability of photovoltaics to be accommodated locally. At the same time, due to the introduction of the segmented curtailment penalty cost, the system improves the absorption of distributed photovoltaic generation at peak tariff intervals and enhances the economy of system operation.

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“…The mathematical model of the equipment developed in this paper and the corresponding parameters taken are referenced from [19,20].…”

Section: Energy Supplymentioning

confidence: 99%

“…Lithium bromide units can use high-temperature flue gas for cooling, with the model and operating constraints shown in the equation below [20].…”

Section: Absorption Refrigerationmentioning

confidence: 99%

“…The model and operating constraints of a fuel cell, which generates electrical energy through a chemical reaction, are shown in the following equation [20]:…”

Section: Fuel Cellsmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Chance-Constrained Dispatching of Integrated Energy Systems Considering Source–Load Uncertainty and Photovoltaic Absorption

Zong

Lai

et al. 2023

Sustainability

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show abstract

“…Tian et al proposed a "source-charge" lowcarbon optimal scheduling model for data center microgrids considering power to gas and carbon capture based on stochastic programming [8]. Aiming at the difficulty of optimal scheduling of IES under the operation condition of a multi-energy complementary mechanism, multi-objective optimization operation was studied in terms of reducing system maintenance costs, CO2 emission, and abandoned renewable energy [9]. Zhao et al proposed a multi-stage low-carbon robust optimization scheduling method of integrated electricity and heat systems considering carbon capture and wind power uncertainty [10].…”

Section: Introductionmentioning

confidence: 99%

Low Carbon Optimal Scheduling of Integrated Energy Systems Based on Carbon Capture Devices

Wei

Dai

et al. 2023

J. Phys.: Conf. Ser.

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Carbon pollution has gradually become a serious environmental problem in recent years. The low-carbon optimization dispatch of the Integrated Energy Systems (IES) can realize the complementary and energy-use substitution of multiple energy sources and solve the problem of high carbon emission. In this paper, we first construct a system model and a carbon emission model. Then, we introduce carbon capture equipment into the system and construct a system optimization model with equipment constraints for each unit. Finally, we solve the proposed model with a complex solver in Matlab to verify the accuracy of the proposed model and the effectiveness of the method. The results show that the strategy can effectively reduce the carbon emissions of the IES.

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Research on Energy Storage Planning of Distributed Multi-energy Systems Considering the Demand Response of Electric and Heat Loads

Sun

Zhao

Xu³

et al. 2023

Lecture Notes in Electrical Engineering

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Low-Carbon Economic Dispatching of Combined Heat and Power System Considering Electric-thermal Integrated Demand Response

Cited by 5 publications

References 3 publications

Chance-Constrained Dispatching of Integrated Energy Systems Considering Source–Load Uncertainty and Photovoltaic Absorption

Chance-Constrained Dispatching of Integrated Energy Systems Considering Source–Load Uncertainty and Photovoltaic Absorption

Low Carbon Optimal Scheduling of Integrated Energy Systems Based on Carbon Capture Devices

Research on Energy Storage Planning of Distributed Multi-energy Systems Considering the Demand Response of Electric and Heat Loads

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