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Journal ArticleDOI

Assessing the performance of biogas plants with multi-criteria and data envelopment analysis

TL;DR: An assessment of 41 agricultural biogas plants located in Austria to determine their relative performance in terms of economic, environmental, and social criteria and corresponding indicators suggests that MCDA, and the use of IRIS in particular, constitutes a useful approach that can be applied in a complementary way to DEA.
About: This article is published in European Journal of Operational Research.The article was published on 2009-09-16 and is currently open access. It has received 128 citations till now. The article focuses on the topics: Data envelopment analysis & Multiple-criteria decision analysis.

Summary (3 min read)

1. Introduction

  • Over the last two decades, a growing environmental awareness has changed the focus of energy planning processes from an almost exclusive concern with cost minimization of supply-side options to the need of explicitly including multiple and potentially conflicting aspects, such as cost and environmental issues, in decision support models.
  • The Kyoto Protocol, the EU Renewables Directive 2001/77/EC, and the European Biomass Action Plan are examples of ambitious political goals fostering the development of energy conversion technologies based on RES.
  • With these intentions in mind, this paper also addresses the challenge of determining how MCDA methods can be used in the context of efficiency evaluation, trying to keep the spirit behind DEA, while being able to use MCDA’s capabilities of explicitly incorporating the preferences of a decision-maker, not necessarily in the form of trade-off restrictions.
  • Uncertainty is an intrinsic characteristic of real-world problems arising from multiple sources of distinct nature.
  • In Section 5 the findings from the analysis are discussed and some conclusions are drawn.

2.1. DEA

  • The attainment of high levels of performance is a key issue for the success of every organization.
  • DEA models use these inputs and outputs to compute an efficiency score for a given DMU when this particular DMU is compared with all the other DMUs considered.
  • The weights are chosen by the LP model such that a DMU is ‘‘shown in its best light”, i.e., that its efficiency score is maximized.
  • The CCR model was presented in the seminal work of Charnes et al. (1978).
  • In fact, the inputs and outputs are not generally equally relevant and some preference information must be included in the analysis.

2.2. MCDA

  • The above-mentioned considerations about DEA led us to envisage the use of MCDA models to perform efficiency evaluation.
  • In assessing the performance of DMUs in which technical, economic and environmental aspects are at stake, it is often important to use known standards (or theoretical maxima) and efficiency profiles.
  • The ELECTRE TRI method belongs to the ELECTRE family of multi-criteria methods developed by Bernard Roy and his co-workers (Roy, 1996).
  • Also, a set of indifference (qj), preference (pj) and veto (vj) thresholds for each criterion j and reference profiles can be defined.
  • Information about these parameter values can be provided through the introduction of intervals, linear constraints, or even sorting examples (which are translated into constraints on the parameters that guarantee that those example results are reproduced).

3. Case study

  • In Austria, an effective promotion of renewable energy technologies has been pursued in recent years, driven by the need to achieve ambitious energy and climate policy goals.
  • 1 Note that in 2006 a revised Green Electricity Act and Ordinance entered into force, with amended feed-in tariffs and budget restrictions (BGB1.
  • As a result, many different technologies, design concepts, and specific applications occurred on the market, some of which were either not very productive, energy-efficient, or reliable.
  • Due to the attractive feed-in tariffs granted, anaerobic digestion of energy crops currently mainly aims at the generation of electricity, and much less so at heat generation (or the feed-in of purified biogas into the natural gas grid, if available).

4.1. Description of the data and parameters used

  • The DMUs considered are a representative set of energy crop digestion plants in Austria, aimed at covering the whole spectrum of existing plant types and operating conditions.
  • Cooling, safe transport and appropriate storage were also scrutinized.
  • The sampled installations are geographically well distributed over the country.
  • The main groups of evaluation aspects at stake for assessing the efficiency of energy crop digestion plants are: (1) substrate provision, storage and pre-treatment; (2) biogas production (by means of anaerobic digestion); (3) net utilization of heat and electricity; (4) digestate handling and disposal; and (5) greenhouse gas (GHG) emissions.
  • For further details on data collection see Braun et al. (2005, 2007) and Laaber et al. (2005), and for further details about the various inputs and outputs and DEA model specifications scrutinized see Madlener (2006).

4.2. DEA

  • In the first DEA model considered in this paper, the authors have used substrate (i2) and labor (i1) as inputs and the amount of net electricity (o1) and external heat (o2) as outputs.
  • See Scheel, 2001; Seiford and Zhu, 2002), and although the choice influences the results, there does not seem to be an undisputed ideal method to handle undesirable outputs (Dyson et al., 2001).
  • A scale transla- Please cite this article in press as: Madlener, R. et al., Assessing the perf Journal of Operational Research (2008), doi:10.1016/j.ejor.2007.12.051 tion was used to account for the negative net values, another modeling option known to have an influence on the results (Lovell and Pastor, 1995).
  • Keeping the same inputs and outputs presented here, the main implications of using the variable returns to scale version (BCC-O) would be to add DMU 15 to the set of efficient units, without GHG emissions, and adding DMUs 33 and 38 to the set of efficient units, with GHG emissions considered.

4.3. MCDA

  • In the MCDA approach the objective was to identify groups of DMUs that could be assigned to different efficiency labels, rather than computing a precise efficiency score or deriving a complete ranking.
  • Each plant has to be assigned to one of these ordered categories, according to the multiple evaluation criteria.
  • Note that although this approach leads to a high number of indicators as the number of criteria increases, it mimics the spirit of DEA: to allow each DMU to be evaluated according to multiple indicators and to choose the most favorable indicators (within the constraints that the decision-maker may impose, as the authors will illustrate further below).
  • DMUs in the best categories, several options can be envisaged: (1) to make the category bound more demanding; (2) to require the support of more than one indicator (e.g., the support of half of the indicators, as depicted in Fig. 4); and/or (3) to add some information about the relative power of the indicators.

4.5. Further analyses with IRIS

  • The choice of the best and worst DMUs in the MCDA study was performed without making any distinction between the indicators.
  • This implies that the importance of g2 (electricity/ODS) cannot be lower than the importance of g1 (electricity/labor).
  • Optionally, the ELECTRE TRI models also allow incorporating veto thresholds, such that, for instance, a DMU that is classified as C1 according to a given indicator will not be able to reach category C4 in a multi-criteria evaluation.
  • A form which is easily perceived by managers is to ask for intervals for some of the parameters (for instance, the weights), aimed at capturing information that is not precisely known but can be taken as bounded within some acceptable limits.
  • The MCDA analysis may complement the DEA analysis by providing another perspective from which the conclusions of DEA may be either strengthened or weakened.

5. Discussion and conclusions

  • DEA is a data-oriented approach that requires no a priori specification of the functional form of the production model converting inputs into outputs.
  • Moreover, managerial preference information is often required, since inputs and outputs do not generally have the same importance in assessing the efficiency of operational units.
  • This has been the main motivation for the use of MCDA techniques, in order to assess the extent by which these could overcome those characteristics of DEA, and what adaptations would be needed to improve the quality of the assessment.
  • An authority certifying sustainable development practices may use this type of MCDA to label energy production plants according to their efficiency, taking into account the inputs they consume, the energy and other desirable outputs they produce, as well as greenhouse gas emissions and other undesirable outputs.
  • DEA, on the other hand, can be particularly suited to identify DMUs with efficiency gaps relative to the state of the art, given the observed efficiency frontier.

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Citations
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Journal ArticleDOI
TL;DR: In this article, the authors reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation.
Abstract: Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.

1,868 citations


Cites background or methods from "Assessing the performance of biogas..."

  • ...In the referred literatures, the listed MCDA methods in Table 5 were mainly applied in all kinds of sustainable energy DM problems [11,13,29,30,32,33,35–47,49,50,52,54,55,57,60,65,66,71–91], such as the selection of CCHP alternatives, the comparisons of renewable energy plants and the DM of energy policy....

    [...]

  • ...Elimination et choice translating reality (ELECTRE) [32,46,47,65,66,75,82,88,90] 9...

    [...]

  • ...Such methods have been widely used in energy DM [32,46,47,65,66,75,82,88,90]....

    [...]

  • ...The energy issues applyingMCDA includes energy planning and selection [11–13,30–47], energy resource allocation [48–54], energy exploitation [55,56], energy policy [57–59], building energy management [60–67], transportation energy systems [68,69] and others [70–75]....

    [...]

Journal ArticleDOI
TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.
Abstract: Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

1,394 citations


Cites background from "Assessing the performance of biogas..."

  • ...Madlener [170] performed a multi-criteria study with the aim of evaluating the performance of a large number of agricultural biogas plants in order to determine their relative performance in terms of economic, environmental, and social criteria and corresponding indicators....

    [...]

  • ...[170] Madlener R, Antunes CH, Dias LC....

    [...]

Journal ArticleDOI
TL;DR: The aim is to investigate how ELECTRE and ELECTRE-based methods have been considered in various areas, including area of applications, modifications to the methods, comparisons with other methods, and general studies of the ELECTRE methods.

419 citations

Journal ArticleDOI
TL;DR: In this article, a review of 144 published scholarly papers appearing in 45 high-ranking journals between 2006 and 2015 have been obtained to achieve a comprehensive review of DEA application in energy efficiency, where the selected articles have been categorized based on year of publication; author (s) nationalities, scope of study, time duration, application area, study purpose, results and outcomes.
Abstract: The main aim of this review article is to review of DEA models in regarding to energy efficiency. This paper reviewed and summarized the different models of DEA that have been applied around the world to development of energy efficiency problems. Consequently, a review of 144 published scholarly papers appearing in 45 high-ranking journals between 2006 and 2015 have been obtained to achieve a comprehensive review of DEA application in energy efficiency. Accordingly, the selected articles have been categorized based on year of publication; author (s) nationalities, scope of study, time duration, application area, study purpose, results and outcomes. Results of this review paper indicated that DEA showed great promise to be a good evaluative tool for future analysis on energy efficiency issues, where the production function between the inputs and outputs was virtually absent or extremely difficult to acquire.

414 citations

Journal ArticleDOI
TL;DR: In this article, the authors summarized previous research efforts on Data Envelopment Analysis (DEA) applied to energy and environment in the past four decades, including concepts and methodologies on DEA environmental assessment.

358 citations

References
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TL;DR: A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs and methods for objectively determining weights by reference to the observational data for the multiple outputs and multiple inputs that characterize such programs.

25,433 citations

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TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
Abstract: In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serves as a planning aid to management. Data Envelopment Analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments, however they may have been planned or executed. Mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities. The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs. A separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of DEA directly on observational data. Technical inefficiencies are identified with failures to achieve best possible output levels and/or usage of excessive amounts of inputs. Methods for identifying and correcting the magnitudes of these inefficiencies, as supplied in prior work, are illustrated. In the present paper, a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decreasing returns to scale in multiple input and multiple output situations. The results are discussed and related not only to classical single output economics but also to more modern versions of economics which are identified with "contestable market theories."

14,941 citations


"Assessing the performance of biogas..." refers methods in this paper

  • ...For the cases where the constant returns to scale assumption is dropped, Banker et al. (1984) proposed a variable returns to scale (VRS) version of the CCR model, referred to as the BCC model....

    [...]

Book
30 Nov 1999
TL;DR: In this article, the basic CCR model and DEA models with restricted multipliers are discussed. But they do not consider the effect of non-discretionary and categorical variables.
Abstract: List of Tables. List of Figures. Preface. 1. General Discussion. 2. The Basic CCR Model. 3. The CCR Model and Production Correspondence. 4. Alternative DEA Models. 5. Returns to Scale. 6. Models with Restricted Multipliers. 7. Discretionary, Non-Discretionary and Categorical Variables. 8. Allocation Models. 9. Data Variations. Appendices. Index.

4,395 citations


"Assessing the performance of biogas..." refers background or methods in this paper

  • ...Three basic DEA models are generally distinguished: CCR model, BCC model, and Additive model (see Cooper et al., 2000, 2004; for a presentation and comparative analysis of these models)....

    [...]

  • ...DEA is a non-parametric performance measurement technique, based on linear programming (LP), for assessing the efficiency of DMUs (e.g., Charnes et al., 1985; Cooper et al., 2000) relative to an observed set of production possibilities....

    [...]

  • ...It is now widely recognized that the largest source of atmospheric pollution stems from fossil fuel combustion, upon which current energy production and use patterns throughout the world rely heavily....

    [...]

  • ...From an interdisciplinary point of view, the assessment of the global performance of different entities (potential solutions, courses of action, decision alternatives) can no longer be based on a single-dimensional axis of evaluation, such as cost or benefit....

    [...]

Book
01 Jan 2007
TL;DR: In this article, the authors deal with exergy and its applications to various energy systems and applications as a potential tool for design, analysis and optimization, and its role in minimizing and/or eliminating environmental impacts and providing sustainable development.
Abstract: This book deals with exergy and its applications to various energy systems and applications as a potential tool for design, analysis and optimization, and its role in minimizing and/or eliminating environmental impacts and providing sustainable development. In this regard, several key topics ranging from the basics of the thermodynamic concepts to advanced exergy analysis techniques in a wide range of applications are covered as outlined in the contents. It provides comprehensive coverage of exergy and its applications. It connects exergy with three essential areas in terms of energy, environment and sustainable development. It presents the most up-to-date information in the area with recent developments. It provides a number of illustrative examples, practical applications, and case studies. It features an easy to follow style, starting from the basics to the advanced systems.

1,983 citations

Journal ArticleDOI
TL;DR: In this article, the authors reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation.
Abstract: Multi-criteria decision analysis (MCDA) methods have become increasingly popular in decision-making for sustainable energy because of the multi-dimensionality of the sustainability goal and the complexity of socio-economic and biophysical systems. This article reviewed the corresponding methods in different stages of multi-criteria decision-making for sustainable energy, i.e., criteria selection, criteria weighting, evaluation, and final aggregation. The criteria of energy supply systems are summarized from technical, economic, environmental and social aspects. The weighting methods of criteria are classified into three categories: subjective weighting, objective weighting and combination weighting methods. Several methods based on weighted sum, priority setting, outranking, fuzzy set methodology and their combinations are employed for energy decision-making. It is observed that the investment cost locates the first place in all evaluation criteria and CO2 emission follows closely because of more focuses on environment protection, equal criteria weights are still the most popular weighting method, analytical hierarchy process is the most popular comprehensive MCDA method, and the aggregation methods are helpful to get the rational result in sustainable energy decision-making.

1,868 citations

Frequently Asked Questions (1)
Q1. What are the contributions in "Assessing the performance of biogas plants with multi-criteria and data envelopment analysis" ?

This paper performs an assessment of 41 agricultural biogas plants located in Austria to determine their relative performance in terms of economic, environmental, and social criteria and corresponding indicators. To be able to use IRIS while keeping the spirit behind DEA, the evaluation criteria were defined as different output/input efficiency ratios, and no information about criteria weights was introduced at the outset. The results suggest that MCDA, and the use of IRIS in particular, constitutes a useful approach that can be applied in a complementary way to