Regional heuristic interval recourse power system analysis for electricity and environmental systems planning in Eastern China

Runya Huang, Guohe Huang, Guanhui Cheng and Cong Dong

Resources, Conservation & Recycling, 2017, vol. 122, issue C, 185-201

Abstract: In some cases such as the power grid in eastern China, a regional power system analysis is confronted with multiple challenges: dynamics of electricity demands, nonlinearity of the relationship between these demands and influencing factors, fluctuation of system features, risks of resource unavailabilities, spatial heterogeneities of power supplies and demands, dynamical diversity and interactions of system components, and the multi-layer interactions of these challenges. In order to address these challenges, a regional heuristic interval recourse power system analysis (RHIRPSA) method is developed in this study and applied to electricity and environmental systems planning in eastern china. RHIRPSA can predict electricity demands effectively, and allow for incorporation of interval uncertainties into the optimization process and solutions in electricity systems. The objective is to maximize system profits under constraints of resources availability and environmental regulations. Three scenarios are considered to reflect the influence of different emission reduction policies on power generation and power dispatching. The results indicate that reasonable decision alternatives are generated. This study is helpful for (a) facilitating electricity consumption estimation, (b) providing reliable electricity systems management schemes to guide activities such as electricity-conversion technological development, capacity expansion and electricity allocation, (c) mitigating conflicts and interactions among economic profits, electricity generation patterns, air pollution emission control and system reliability, and (d) identifying the desired strategies for improving air quality in eastern China through optimizing the economic and environmental protection measures under policies of air pollution emission reduction.

Keywords: Electricity and environmental systems; Artificial neural network; Interval recourse linear programming; Eastern China (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:recore:v:122:y:2017:i:c:p:185-201

DOI: 10.1016/j.resconrec.2017.01.009

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