Collaborative optimization method for power-heat-gas integrated energy systems considering multiple uncertainties

doi:10.3969/j.issn.2097-0706.2024.04.006

Abstract

Abstract:

The uncertainties of wind outputs， solar outputs and loads of integrated energy systems（IES） challenge IES operational safety and planning. To address this issue， an IES integrating photovoltaics（PV） units and a biomass gasification combined heating and power（BCHP） unit is studied. A scheduling method based on integrated stochastic programming and information gap decision theory（IGDT） is proposed to eliminate the uncertainties on the source side and user side of the IES during its collaborative optimization. Stochastic programming can deal with the short-term uncertainty of PV outputs， and its optimization results are taken as the benchmark of load uncertainty optimization by IGDT.While resisting the operational risks triggered by the uncertainties in IGDT optimization， the IES managers tend to choose two strategies， risk-aversion strategy and risk-taking strategy. The test results on the case demonstrate that the daily power output of the BCHP unit under risk-aversion strategy is 50% higher under that under risk-taking strategy. Different dispatching results under different strategies give system managers flexible choices.

Key words: integrated energy systems, multiple uncertainties, information gap decision theory, stochastic programming, biomass gasification combined heat and power

CLC Number:

TK01：TM715

WANG Jinglong, WANG Hui, YANG Ye, ZHENG Yingying. Collaborative optimization method for power-heat-gas integrated energy systems considering multiple uncertainties[J]. Integrated Intelligent Energy, 2024, 46(4): 42-51.

Figures/Tables 10

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场景	综合成本	能源网互联成本	碳排放成本	系统内部成本
1	3 552.0	315.0	732.9	2 504.1
2	3 788.0	322.0	815.4	2 650.6
3	4 049.0	367.0	904.2	2 777.8
4	3 352.0	322.0	658.5	2 371.5
5	3 204.0	322.0	605.1	2 276.9