Efficiency assessment of Turkish power plants using data envelopment analysis

The performance of electricity generation plants in Turkey are analyzed and compared. The data set contains inputs from 65 thermal, hydro and wind power plants, owned by private and public sectors. Data envelopment analysis (DEA) is used as the primary mathematical tool. Two efficiency indexes, reflecting operational and investment performance, are defined and pursued. Constant returns to scale, variable returns to scale and assurance region type DEA models are used in the analysis. Scale efficiency is also considered. Performance comparisons include public versus private sector plants, and natural gas versus coal versus oil fired plants. Also, relationships between efficiency scores and various input/output factors are investigated and some interesting trends are identified.     

Assessment of operational and environmental performance of the thermal power plants in Turkey by using data envelopment analysis

In this study, efficiency analyses of the eleven lignite-fired, one hard coal-fired and three natural gas-fired state-owned thermal power plants used for electricity generation were conducted through data envelopment analysis (DEA). Two efficiency indexes, operational and environmental performance, were defined and pursued. In the calculation of the operational performance, main production indicators were used as input, and fuel cost per actual production (Y) was used as output (Model 1). On the other hand, in the calculation of the environmental performance, gases emitted to the environment were used as output (Model 2). Data envelopment analysis (DEA) is the main instrument for the measurement of relative performances of the decision making units with multiple inputs and outputs. Constant returns to scale (CRS or CCR) and variable returns to scale (VRS or BCC) type DEA models were used in the analyses. The relationship between efficiency scores and input/output factors was investigated. Employing the obtained results, the power plants were evaluated with respect to both the cost of electricity generation and the environmental effects.     

The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants

Different from previous efficiency researches, which normally assume a uniform disposability for all undesirable outputs in a production process, this paper proposes a model that distinguishes weak and strong disposability assumptions among various undesirable outputs based on their respective technical features. The paper illustrates the approach using a research sample covering 582 base-load Chinese coal-fired power plants in 2002. The final results show that imposing the technically correct disposability features on undesirable outputs makes a significant difference to the final efficiency evaluation. This suggests the necessity of properly distinguishing disposability features among undesirable outputs in a production process in efficiency models.     

Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies

This paper presents Data Envelopment Analysis (DEA) model with uncertain data for performance assessment of electricity distribution companies. During the past two decades, DEA has been widely used for benchmarking the electricity distribution companies. However, there is no study among many existing DEA approaches where the uncertainty in data is allowed and, at the same time, the distribution of the random data is permitted to be unknown. The proposed method of this paper develops a new DEA method with the consideration of uncertainty on output parameters. The method is based on the adaptation of recently developed robust optimization approaches proposed by Ben-Tal and Nemirovski [2000. Robust solutions of linear programming problems contaminated with uncertain data. Mathematical Programming 88, 411–421] and Bertsimas et al. [2004. Robust linear optimization under general norms.     

Assessing the power generation,pollution control,and overall efficiencies of municipal solid waste incinerators in Taiwan

This paper evaluates the productivity of municipal solid waste incinerators (MSWIs) by addressing the following questions: (1) to what extent should one further increase the production of power generation while maintaining the emission of noxious air at the current level?; (2) To what extent should one further decrease the emission of noxious air while maintaining the production of power generation at the current level?; and (3) To what extent should one increase the production of power generation and decrease the emission of noxious air simultaneously? To effectively address these questions to improve performance, the power generation and pollution control efficiencies are evaluated using TODEA (two-objective data envelopment analysis), as well as the overall efficiency evaluated using Tone’s NS-overall model (slacks-based measure with non-separable desirable and undesirable outputs for evaluating overall efficiency). A MSWI case study in Taiwan with the panel data covering the period of 2004–2008 reveals that the power generation and overall efficiencies of build-operate-transfer are more efficient, on average, than those of public-own-operate and build-own-operate. However, the three building and operation types do not significantly differ in pollution control efficiency.     

Technical efficiency of thermoelectric power plants

This paper analyses the technical efficiency of Portuguese thermoelectric power generating plants with a two-stage procedure. In the first stage, the plants' relative technical efficiency is estimated with DEA (data envelopment analysis) to establish which plants perform most efficiently. These plants could serve as peers to help improve performance of the least efficient plants. The paper ranks these plants according to their relative efficiency for the period 1996–2004. In a second stage, the Simar and Wilson [Simar, L., Wilson, P.W., 2007. Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics 136, 1–34] bootstrapped procedure is adopted to estimate the efficiency drivers. Economic implications arising from the study are considered.     

Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis

Electricity is essential in the economic development of a nation. Due to the rapid growth of economy and industrial development in Taiwan, the demand for use of electricity has increased rapidly. This study evaluates the power-generation efficiency of major thermal power plants in Taiwan during 2004–2006 using the data envelopment analysis (DEA) approach. A stability test was conducted to verify the stability of the DEA model. According to the results, all power plants studied achieved acceptable overall operational efficiencies during 2004–2006, and the combined cycle power plants were the most efficient among all plants. The most important variable in this DEA model is the “heating value of total fuels”. Findings from this study can be beneficial in improving some of the existing power plants and for more efficient operational strategies and related policy-making for future power plants in Taiwan.     

Social cost-efficient service quality—Integrating customer valuation in incentive regulation: Evidence from the case of Norway

In order to overcome the perverse incentives of excessive maintenance reductions and insufficient network investments arising with incentive regulation of electricity distribution companies, regulators throughout Europe have started regulating service quality. In this paper, we explore the impact of incorporating customers’ willingness-to-pay for service quality in benchmarking models on cost efficiency of distribution networks. Therefore, we examine the case of Norway, which features this approach to service quality regulation. We use the data envelopment analysis technique to analyse the effectiveness of such regulatory instruments. Moreover, we discuss the extent to which this indirect regulatory instrument motivates a socially desired service quality level. The results indicate that internalising external or social cost of service quality does not seem to have played an important role in improving cost efficiency in Norwegian distribution utilities.     

Efficiency analysis of Turkish natural gas distribution companies by using data envelopment analysis method

This paper analyzes the performance of 38 Turkish natural gas distribution companies by using a non-parametric method, Data Envelopment Analysis (DEA). The results are used to determine the most proper model specification, to detect the important criteria affecting the efficiency levels, and to find the common characteristics of the most inefficient firms. We find that public firms compared to private firms, non-tender firms compared to tender firms, large firms compared to small firms and firms operating in more developed areas compared to firms operating in underdeveloped areas that utilize resources and manage costs more efficiently. However, we cannot reach a certain conclusion about the comparison of old firms versus the new firms. Lastly, we try to detect the common characteristics of the most inefficient firms and find that most of these firms are immature and low scale companies. Therefore, we think these firms can increase efficiency level either by increasing their delivery amounts through higher penetration rates or by merging or doing both together.     

Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach

In this study energy use pattern for canola production in Golestan province of Iran was studied and the degrees of technical and scale efficiency of producers were analyzed using a non-parametric data envelopment analysis technique. The study also helped to identify the wasteful uses of energy by inefficient farmers and to suggest reasonable savings in energy uses from different inputs. Further, the effect of optimization of energy on energy ratio and energy productivity was investigated. Data used in this study were obtained from 130 randomly selected canola farms from Golestan, the most important center of canola production in Iran. The inputs were human labor, diesel, machinery, fertilizers, chemicals, water for irrigation, seeds and electrical energies; while the yield value of canola was considered as output. The results revealed that, the total energy of 17,786 MJ ha⁻¹ was consumed for canola production; about 15% of farmers were found to be technically efficient and the mean efficiency of farmers was found to be 0.74 and 0.88 under constant and variable returns to scale assumptions, respectively. The results also suggested that, on average, a potential 9.5% (1696 MJ ha⁻¹) reduction in total energy input could be achieved provided that all farmers operated efficiently.     

Comprehensive evaluation of coal-fired power plants based on grey relational analysis and analytic hierarchy process

In China, coal-fired power plants are the main supplier of electricity, as well as the largest consumer of coal and water resources and the biggest emitter of SO_x, NO_x, and greenhouse gases (GHGs). Therefore, it is important to establish a scientific, reasonable, and feasible comprehensive evaluation system for coal-fired power plants to guide them in achieving multi-optimisation of their thermal, environmental, and economic performance. This paper proposes a novel comprehensive evaluation method, which is based on a combination of the grey relational analysis (GRA) and the analytic hierarchy process (AHP), to assess the multi-objective performance of power plants. Unlike the traditional evaluation method that uses coal consumption as a basic indicator, the proposed evaluation method also takes water consumption and pollutant emissions as indicators. On the basis of the proposed evaluation method, a case study on typical 600 MW coal-fired power plants is carried out to determine the relevancy rules among factors including the coal consumption, water consumption, pollutant, and GHG emissions of power plants. This research offers new ideas and methods for the comprehensive performance evaluation of complex energy utilisation systems, and is beneficial to the synthesised consideration of resources, economy, and environment factors in system optimising and policy making.     

Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: A case study

This paper provides an empirical analysis of the determinants of energy efficiency in 32 power electric generation management companies over the period 2005-2009. The study uses non-parametric Data Envelopment Analysis (DEA) to estimate the relative technical efficiency and productivity change of these companies. In order to verify the stability of our DEA model and the importance of each input variable, a stability test is also conducted. The results of the study indicate that average technical efficiency of companies decreased during the study period. Nearly half of the companies (14) are below this average level of 88.7% for five years. Moreover, it is shown that the low increase of productivity changes is more related to low efficiency rather than technology changes.     

An analysis of power generation from municipal solid waste (MSW) incineration plants in Taiwan

Heavily (about 99%) depending on imported energy, Taiwan, a country in the subtropics, has limited natural resources. In this regard, biomass energy from (MSW) municipal solid waste incineration plants thus became attractive during the 1990s. The objective of this paper is to present a comprehensive analysis of MSW-to-energy in Taiwan. This paper gave a concise summary of current status of domestic energy consumption &; power generation, MSW generation &; MSW incineration treatment, and electricity generation from MSW incineration plants since 2000. Based on the electricity generation in 2008 (i.e., 2967 GWh), the environmental benefit of mitigating CO₂ emissions and the economic benefit of selling electricity were preliminarily calculated to be around 1.9 × 10⁶ tons and US$ 1.5 × 10⁸, respectively. However, since the heat content of incinerated MSW and the methodologies were used on the recommendation of the (IPCC) Intergovernmental Panel on Climate Change, the net emissions of CO₂ equivalent from methane (CH₄) &; nitrous oxide (N₂O) have been estimated to be at around 76,000 and 88,000 tons/year compared to coal and oil, respectively.     

Resource and environment efficiency analysis of provinces in China: A DEA approach based on Shannon’s entropy

Data envelopment analysis (DEA) has been widely used in energy efficiency and environment efficiency analysis in recent years. Based on the existing environment DEA technology, this paper presents several DEA models for estimating the aggregated efficiency of resource and environment. These models can evaluate DMUs’ energy efficiencies and environment efficiencies simultaneously. However, efficiency ranking results obtained from these models are not the same, and each model can provide some valuable information of DMUs’ efficiencies, which we could not ignore. Under this situation, it may be hard for us to choose a specific model in practice. To address this kind of performance evaluation problem, the current paper extends Shannon-DEA procedure to establish a comprehensive efficiency measure for appraising DMUs’ resource and environment efficiencies. In the proposed approach, the measure for evaluating a model's importance degree is provided, and the targets setting approach of inputs/outputs for DMU managers to improve DMUs’ energy and environmental efficiencies is also discussed. We illustrate the proposed approach using real data set of 30 provinces in China.     

Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach

In this study a non-parametric method of Data Envelopment Analysis (DEA) is used to estimate the energy efficiencies of soybean producers based on eight energy inputs including human labor, diesel fuel, machinery, fertilizers, chemicals, water for irrigation, electricity and seed energy and single output of grain yield. The study also helps to rank efficient and inefficient farmers and to identify optimal energy requirement and wasteful uses of energy. Data were collected using face-to-face surveys from 94 farms in Golestan province which is the most important center of soybean production in Iran. Based on the results, average yield and energy consumption for soybean production were 3233.15 kg ha⁻¹ and 35372.23 MJ ha⁻¹, respectively. Also, the results of DEA application showed that, the technical, pure technical and scale efficiencies of farmers were 0.853, 0.919 and 0.926, respectively. Moreover, energy saving target ratio for soybean production was calculated as 20.12%, indicating that by following the recommendations resulted from this study, about 7116.84 MJ ha⁻¹ of total input energy could be saved while holding the constant level of soybean yield. Also, electrical energy had the highest share (78.08%) from total saving energy, followed by fertilizers (10.46%) and diesel fuel (6.18%) energy inputs.     

Thermodynamic assessment of IGCC power plants with hot fuel gas desulfurization

In IGCC power plants, hot gas desulfurization (HGD) represents an attractive solution to simplify syngas treatments and to improve the efficiency, potentially reducing the final cost of electricity. In the present study, the various consequences of the introduction of a HGD station in the power plant are discussed and evaluated, in comparison with conventional near-ambient temperature clean-up. Attention is paid to the potential improvements of the overall energy balance of the complete power station, along with the requirements of the sorbent regeneration process, to the influence of the desulfurization temperature and to the different solutions needed to control the NO_x emissions (altered by the presence of HGD).     

Eco-efficiency of the world cement industry: A data envelopment analysis

Chemical reactions and the combustion of dirty fuels, such as coal and petroleum coke (petcoke), that are used in cement production processes generate a significant amount of CO₂ emissions. In this paper, we provide an eco-efficiency measure for 21 prototypes of cement industries operating in many countries by applying both a data envelopment analysis (DEA) and a directional distance function approach, which are particularly suitable for models where several production inputs and desirable and undesirable outputs are taken into account. To understand whether this eco-efficiency is due to a rational utilization of inputs or to a real carbon dioxide reduction as a consequence of environmental regulation, we analyze the cases where CO₂ emissions can either be considered as an input or as an undesirable output. Empirical results show that countries where cement industries invest in technologically advanced kilns and adopt alternative fuels and raw materials in their production processes are eco-efficient. This gives a comparative advantage to emerging countries, such as India and China, which are incentivized to modernize their production processes.     

Performance and costs of power plants with capture and storage of CO2

This paper assesses the three leading technologies for capture of CO₂ in power generation plants, i.e., post-combustion capture, pre-combustion capture and oxy-fuel combustion. Performance, cost and emissions data for coal and natural gas-fired power plants are presented, based on information from studies carried out recently for the IEA Greenhouse Gas R&D Programme by major engineering contractors and process licensors. Sensitivities to various potentially significant parameters are assessed.     

燃煤电厂固体废弃物资源化利用经济分析

从循环经济基本理念出发,在了解浙江省燃煤电厂固体废弃物资源化利用现状的基础上,通过经济分析探讨了实现资源化市场运作的可能性以及政府政策干预和导向的功能实现条件。     

RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks

The optimal design of supply chain networks is often examined based on one or more economic or other criteria (e.g., cost, profit environmental impact, danger, time). However, the efficiency of the derived solutions is often ignored. In this work, a recursive DEA (RDEA) algorithm is presented, which introduces a different way of designing a supply chain network. The selection of possible installed facilities is based on minimum cost and maximum efficiency, through a MILP model. Optimal supply chain structure is obtained when the termination criterion is met, yielding only the efficient solutions, while simultaneously reducing the overall cost. An application of this RDEA algorithm to a biomass supply chain is examined. A comparative study is also presented, demonstrating the results obtained when solving the MILP without the proposed algorithm and with the use of an RDEA.