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A risk aversion optimal model for microenergy grid low carbon‐oriented operation considering power‐to‐gas and gas storage tank
Author(s) -
Ju Liwei,
Zuo Xiaoting,
Tan Qinliang,
Zhao Rui,
Wang Wei
Publication year - 2019
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4672
Subject(s) - renewable energy , solar power , grid , photovoltaic system , power (physics) , energy storage , electricity generation , environmental economics , engineering , mathematical optimization , economics , electrical engineering , mathematics , physics , geometry , quantum mechanics
Summary Power‐to‐gas storage (P2GS) provides a new approach for clean energy accommodation, which could be used to support the development of the microenergy grid (MEG). This paper designs a novel structure of MEG including power sources, heating sources, and P2GS. The risk condition values (CVaR) is applied to analyze the uncertainties from wind power plant, photovoltaic power generation, and solar collectors, and a multiobjective optimal model is proposed for balancing the operation economic benefit and the risk level. Then different membership functions are selected for converting the multiobjective model into a mixed integer programming model. Finally, an industrial park in northern China was selected to verify the proposed model. The results show that (a) complementary effect exists in different clean energy sources and P2GS can convert excess energy into CH 4 for power generation, which are better for achieving the power‐to‐gas‐to‐power cycle optimization effect. (b) The proposed optimal model could balance revenue and risk, rationally control its operation risk while pursuing the maximum operation benefits, which is better to achieve MEG's optimal equilibrium operation. (c) Maximum emission trade allowance could enhance MEG's enthusiasm for clean energy accommodation, and P2GS could be a feasible way for near‐zero carbon emissions. Therefore, the proposed risk aversion optimal model could increase the economic benefits and control the risks and provide decision support for decision makers.