| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 5118789 | Resources, Conservation and Recycling | 2017 | 17 Pages |
â¢A regional heuristic interval recourse power system analysis method is developed in east china power system.â¢Contraction ratios are used to remove solutions of violation constraints of interval linear programming.â¢Power consumptions from 2015 to 2020 are predicted.â¢Solutions associated with different scenarios have been obtained.
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.
