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

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 th...

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Bibliographic Details
Published in:Sustainability Vol. 15; no. 16; p. 12459
Main Authors: Li, Dedi, Zong, Yue, Lai, Xinjie, Huang, Huimin, Zhao, Haiqi, Dong, Shufeng
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.08.2023
Subjects:
Algorithms
Alternative energy sources
Analysis
Collaboration
Costs
Electricity
Electricity distribution
Energy consumption
Energy resources
Energy storage
Fuzzy sets
Hydrogen
Linear programming
Load
Mathematical models
Monte Carlo method
Monte Carlo simulation
Natural gas
Optimization
Planning
Renewable resources
Research methodology
Solar energy industry
Supply and demand
Sustainability
Wind power
China
ISSN:2071-1050, 2071-1050
Online Access:Get full text
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Summary: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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ISSN:2071-1050
2071-1050
DOI:10.3390/su151612459