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Operational performance management of the power industry: a distinguishing analysis between effectiveness and efficiency

  • S.I.: BOM in Social Networks
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Abstract

The trend toward a more competitive electricity market has led to efforts by the electric power industry to develop advanced efficiency evaluation models that adapt to market behavior operations management. The promotion of the operational performance management of the electric power industry plays an important role in China’s efforts toward energy conservation, emission control and sustainable development. Traditional efficiency measures are not able to distinguish sales effects from productive efficiency and thus are not sufficient for measuring the operational performance of an electricity generation system for achieving its specific market behavior operations management goals, such as promoting electricity sales. Effectiveness measures are associated with the capacity of an electricity generation system to adjust its input resources that influence its electricity generation and, thus, the capacity to match the electricity demand. Therefore, the effectiveness measures complement the efficiency measures by capturing the sales effect in the operational performance evaluation. This study applies a newly developed data envelopment analysis-based effectiveness measurement to evaluate the operational performance of the electric power industry in China’s 30 provincial regions during the 2006–2010 periods. Both the efficiency and effectiveness of the electricity generation system in each region are measured, and the associated electricity sales effects and electricity reallocation effects are captured. Based on the results of the effectiveness measures, the alternative operational performance improvement strategies and potentials in terms of input resources savings and electricity generation adjustments are proposed. The empirical results indicate that the current interregional electricity transmission and reallocation efforts are effective in China overall, and a moderate increase in electricity generation with a view to improving the effect on sales is more crucial for improving effectiveness.

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Notes

  1. The empirical study is conducted at the provincial level instead of the plant level so as to take the interregional transmission of electricity into account and thus the effect of electricity reallocation can be detected and the associated operational performance improvement strategy can be obtained.

  2. The factors include those for Raw coal, Cleaned coal, Washed coal, Coke, Coke oven gas, Coal gas, Crude oil, Gasoline, Kerosene, Diesel oil, Fuel oil, Liquefied petroleum gas, Refinery gas, Natural gas, and Biomass energy.

  3. There are two additional considerations on this assumption. First, since the beginning of 11th FYP period (2006–2010), the electricity supply and demand has become balanced at the national level because of the rapid increase in installed capacity and the accelerated grid reconstruction during the 10th FYP period, and thus, electricity blackout and brownout has become rare in most regions of China. In such background, we consider that, during our study period, electricity shortage is much more serious than electricity surplus since the social welfare loss (industry shut down, business break off and residence power cut) caused by electricity shortage is much higher than the loss from electricity abandoning and resources waste, and a priority at the “one hundred” scale is appropriate for characterizing this relationship. Secondly, to justify these parameters, we assessed the utilization of different \(\alpha _{rj}\) and \(\beta _{rj}\) which showed similar results, and, in addition, \(\alpha _{rj} =0.1\) and \(\beta _{rj} =0.001\) provide the most significant distinguishing results between effectiveness and efficiency measures.

  4. Exclude net electricity export from China to neighboring countries and regions (Hong Kong, Macau, Vietnam, Myanmar, Laos and North Korea) which account for \(<\)1 % of China’s electricity supply in 2010.

Abbreviations

AR:

After electricity reallocation

BR:

Before electricity reallocation

DEA:

Data envelopment analysis

DMU:

Decision making unit

EE:

Efficiency–effectiveness

FG:

Frontier gap

FYP:

Five Year Plan

GDP:

Gross domestic product

PF:

Production function

RE:

Reallocation effect

SPF:

Sales-truncated production function

VRS:

Variable returns to scale

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Acknowledgments

We gratefully acknowledge the financial support from the National Natural Science Foundation of China (Grant Nos. 71471018, 71101011 and 71521002); the Ministry of Science and Technology of Taiwan (MOST103-2221-E-006-122-MY3); and the Basic Scientific Research Foundation of BIT (20152142008). We also thank the reviewers for their valuable and constructive comments.

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Authors and Affiliations

  1. Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China

    Ke Wang, Jieming Zhang & Yi-Ming Wei

  2. School of Management and Economics, Beijing Institute of Technology, Beijing, China

    Ke Wang, Jieming Zhang & Yi-Ming Wei

  3. Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, China

    Ke Wang & Yi-Ming Wei

  4. Institute of Manufacturing Information and Systems, National Cheng Kung University, Tainan, Taiwan

    Chia-Yen Lee

  5. Research Center for Energy Technology and Strategy, National Cheng Kung University, Tainan, Taiwan

    Chia-Yen Lee

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  1. Ke Wang
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Correspondence to Ke Wang.

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Wang, K., Lee, CY., Zhang, J. et al. Operational performance management of the power industry: a distinguishing analysis between effectiveness and efficiency. Ann Oper Res 268, 513–537 (2018). https://doi.org/10.1007/s10479-016-2189-1

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