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| 1 |
ID:
121341
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2013.
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| Summary/Abstract |
In order to assess the environmental efficiency of power industry in China, this paper first proposes a new non-radial DEA approach by integrating the entropy weight and the SBM model. This will improve the assessment reliability and reasonableness. Using the model, this study then evaluates the environmental efficiency of the Chinese power industry at the provincial level during 2005-2010. The results show a marked difference in environmental efficiency of the power industry among Chinese provinces. Although the annual, average, environmental efficiency level fluctuates, there is an increasing trend. The Tobit regression analysis reveals the innovation ability of enterprises, the proportion of electricity generated by coal-fired plants and the generation capacity have a significantly positive effect on environmental efficiency. However the waste fees levied on waste discharge and investment in industrial pollutant treatment are negatively associated with environmental efficiency.
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| 2 |
ID:
105821
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| Publication |
2011.
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| Summary/Abstract |
This paper uses a new unit commitment model which can simulate the interactions among plug-in hybrid electric vehicles (PHEVs), wind power, and demand response (DR). Four PHEV charging scenarios are simulated for the Illinois power system: (1) unconstrained charging, (2) 3-hour delayed constrained charging, (3) smart charging, and (4) smart charging with DR. The PHEV charging is assumed to be optimally controlled by the system operator in the latter two scenarios, along with load shifting and shaving enabled by DR programs. The simulation results show that optimally dispatching the PHEV charging load can significantly reduce the total operating cost of the system. With DR programs in place, the operating cost can be further reduced.
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