Abstract
In this paper, we compare the properties of the traditional additive-based data envelopment analysis (hereafter, referred to as DEA) models and propose two generalized DEA models, i.e., the big M additive-based DEA (hereafter, referred to as BMA) model and the big M additive-based super-efficiency DEA (hereafter, referred to as BMAS) model, to evaluate the performance of the biomass power plants in China in 2012. The virtues of the new models are two-fold: one is that they inherited the properties of the traditional additive-based DEA models and derived more new additive-based DEA forms; the other is that they can rank the efficient decision making units (hereafter, referred to as DMUs). Therefore, the new models have great potential to be applied in sustainable energy project evaluation. Then, we applied the two new DEA models to evaluate the performance of the biomass power plants in China and find that the efficiency of biomass power plants in the northern part of China is higher than that in the southern part of China. The only three efficient biomass power plants are all in the northern part of China. Furthermore, based on the results of the Wilcoxon-Mann-Whitney rank-sum test and the Kolmogorov-Smirnov test, there is a great technology gap between the biomass power plants in the northern part of China and those in the southern part of China.
Highlights
As a developing country with a huge population, China is always relatively short of energy storage.with the rapid development of the economy, along with industrialization and urbanization, the energy consumption of China will increase to four billion Mtce, and the gap between energy production and consumption will reach half of the total energy volume
This paper presents two new models, the big M additive-based DEA (BMA)
It is noted that the maximum value of the efficiency in the southern part is 0.9888, indicating that the three efficient biomass power plants are all in the northern part of China
Summary
As a developing country with a huge population, China is always relatively short of energy storage. According to the publicized the International Energy Agency (IEA) data in 2012, China has abundant biomass resources with a productivity of about five billion tons per year, and this amount ranks only next to fossil resource. The installation capacity has increased by 30% each year, and according to the Long-Term Renewable Energy Development Plan, in 2020, the expected biomass power installation capacity will be 30 GW. With the industrial plan and policy incentives, biomass power in China has entered the track of high-speed development. Under this situation, if enough data can be collected and used to evaluate the industry efficiency quantitatively, the assessment can provide a basis for decision making and suggest industrial or policy measurements to improve efficiency, which, in return, will accelerate the industrialization of biomass power in China and keep the development leading in the optimal direction
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