The European Union (EU) energy policy for sustainable development has been the topic of continuous debate, research, and analysis, which frequently focused on objectives and the evaluation of ...quantitative and qualitative performance. Different approaches can be used for the assessment of sustainable development goals. The authors of the article conducted a literature review of relevant research papers dated 2016–2020. The most common are quantitative methods based on hard data. Some qualitative studies based on soft data are also available but rare. This article proposes hybrid Rough Set Data Envelopment Analysis (DEA) and Rough Set Network DEA models that integrate both approaches. Also, the models allow the inclusion of uncertainty in the underlying data. The article uses hard data of the International Energy Agency (IEA) and the results of the EU survey regarding the influence of the socio-economic environment on CO2 emissions in EU countries. The authors demonstrate that multifaceted and objective assessment is possible by merging concepts from the set theory and operational research.
The paper addresses the problem of insufficient knowledge on the impact of noise on the auto-regressive integrated moving average (ARIMA) model identification. The work offers a simulation-based ...solution to the analysis of the tolerance to noise of ARIMA models in electrical load forecasting. In the study, an idealized ARIMA model obtained from real load data of the Polish power system was disturbed by noise of different levels. The model was then re-identified, its parameters were estimated, and new forecasts were calculated. The experiment allowed us to evaluate the robustness of ARIMA models to noise in their ability to predict electrical load time series. It could be concluded that the reaction of the ARIMA model to random disturbances of the modeled time series was relatively weak. The limiting noise level at which the forecasting ability of the model collapsed was determined. The results highlight the key role of the data preprocessing stage in data mining and learning. They contribute to more accurate decision making in an uncertain environment, help to shape energy policy, and have implications for the sustainability and reliability of power systems.
The complexity and speed of change in technological systems pose new challenges to technology management. Particular attention should be given to the issue of modelling the uncertainty of assessments ...and creating rules for determining the weights of the technology assessment criteria. The article aims to present a comprehensive hybrid technology prioritisation model based on the Data Envelopment Analysis and the concept of Rough Sets. The technology prioritisation process that uses the proposed model includes three consecutive stages: (i) the formulation of technology assessment matrix, (ii) the removal of the criteria redundancy based on indiscernibility relation defined in the Rough Set Theory, (iii) the development of rough variables and prioritisation using the DEA super-efficiency model. The combination of DEA and RS is a unique proposal to classify and rank objects based on the tabular representation of their conditional attributes under circumstances of uncertainty. Application of the developed hybrid model to the real data of the technology foresight project “NT FOR Podlaskie 2020” positively verified the assumed effects of its use. The obtained results allow a more objective and rational justification of the chosen technology, simplification of interpretation and better authentication of results from the perspective of decision-makers.
The article presents the concept of environmental efficiency analysis based on the method of Data Envelopment Analysis in the case of the existence of desirable and undesirable results. Theoretical ...considerations are illustrated by a case study of European countries and evaluation of productivity taking into account not only economic growth but also effects which are undesirable and impossible to eliminate entirely, such as the impact on the environment. The differences in the results are explained by the relationship between policies aiming at supporting research and development with the use of the Tobit regression model. The added value of this work is to propose an integration of environmental DEA method with the concept of technological competitors. The possibility of applying the concept of DEA to technological competition was presented in the form of classification and benchmarking of the European countries. It is concluded that European countries are highly diversified in regard to the efficiency of environmental performance.
The primary problems pertaining to productivity or - more precisely - efficiency are: how to define it and how to measure it. This article studies technical efficiency in Stochastic Frontier Analysis ...(SFA) - the input-oriented frontier model - in the construction industry and compares it with Data Envelopment Analysis (DEA) results. The models explored in this paper were constructed on the basis of two outputs and personnel cost as an input. The research sample consisted of European countries. The aim was to determine whether there are substantial differences in estimation of efficiency derived from those two alternative frontier approaches. The comparison of results according to the models may translate into higher reliability of the undertaken labour efficiency analysis in construction and its conclusions. Although the results are not characterized by high compatibility, the conducted analysis indicated the most attractive countries taking into account labour cost to profit and turnover ratios of enterprises. One of the determinants which should not be ignored when analysing the labour efficiency is the level of development of a country; however, it is not the sole factor affecting the efficiency of the sector.
This paper presents the assessment of the European Union member states in terms of the circular economy (CE) targets, using a combination of the Data Envelopment Analysis (DEA) method and factor ...analysis. This approach fills in the existing knowledge gap by providing an innovative methodology of an objectivised comparative evaluation of the degree of implementation of the CE principles by the EU countries. Assessing countries’ performance in achieving the goals of the circular economy is a challenge due to the lack of a generally accepted methodology, the multitude of indicators, and the insufficient data. Countries may be compared in a narrow way, according to single indicators, but a more holistic synthetic assessment of countries is also needed to determine their position against each other. In such cases, DEA may be successfully used. The study resulted in the identification of two clusters of countries with similar profiles of relative efficiency in the CE goals’ implementation. It was concluded that the position of a particular country in achieving the CE aims was strongly correlated its GDP per capita. Moreover, factor analysis showed that many CE indicators are strongly correlated with each other and may be aggregated into five meta-indicators (factors): Recycling rate of general waste, Waste production, Jobs and investments, Recycling rate of special waste, and Circular material use rate. In addition to simple rankings and indication of benchmarks, the article offers a novel concept of technology competitors which was used to group units competing for positions in the ranking.
Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of ...this source of energy. The need to optimise energy systems, ensure power continuity, and balance energy supply and demand is driving the continuous development of forecasting methods and approaches based on meteorological data or photovoltaic plant characteristics. This article presents the results of a meta-review of the solar forecasting literature, including the current state of knowledge and methodological discussion. It presents a comprehensive set of forecasting methods, evaluates current classifications, and proposes a new synthetic typology. The article emphasises the increasing role of artificial intelligence (AI) and machine learning (ML) techniques in improving forecast accuracy, alongside traditional statistical and physical models. It explores the challenges of hybrid and ensemble models, which combine multiple forecasting approaches to enhance performance. The paper addresses emerging trends in solar forecasting research, such as the integration of big data and advanced computational tools. Additionally, from a methodological perspective, the article outlines a rigorous approach to the meta-review research procedure, addresses the scientific challenges associated with conducting bibliometric research, and highlights best practices and principles. The article’s relevance consists of providing up-to-date knowledge on solar forecasting, along with insights on emerging trends, future research directions, and anticipating implications for theory and practice.
The increasing demand for clean energy and the global shift towards renewable sources necessitate reliable solar radiation forecasting for the effective integration of solar energy into the energy ...system. Reliable solar radiation forecasting has become crucial for the design, planning, and operational management of energy systems, especially in the context of ambitious greenhouse gas emission goals. This paper presents a study on the application of auto-regressive integrated moving average (ARIMA) models for the seasonal forecasting of solar radiation in different climatic conditions. The performance and prediction capacity of ARIMA models are evaluated using data from Jordan and Poland. The essence of ARIMA modeling and analysis of the use of ARIMA models both as a reference model for evaluating other approaches and as a basic forecasting model for forecasting renewable energy generation are presented. The current state of renewable energy source utilization in selected countries and the adopted transition strategies to a more sustainable energy system are investigated. ARIMA models of two time series (for monthly and hourly data) are built for two locations and a forecast is developed. The research findings demonstrate that ARIMA models are suitable for solar radiation forecasting and can contribute to the stable long-term integration of solar energy into countries’ systems. However, it is crucial to develop location-specific models due to the variability of solar radiation characteristics. This study provides insights into the use of ARIMA models for solar radiation forecasting and highlights their potential for supporting the planning and operation of energy systems.
The public sector is under growing pressure to increase its efficiency. Expectations from the political authorities, local communities, stakeholders and media towards the public-sector entities are ...high. Modern management methods must be introduced to meet them. Data Envelopment Analysis (DEA) is an important method used in comparative studies of public sector efficiency. Voivodeship Funds for Environmental Protection and Water Management (VFEPWMs) are public entities that financially support actions aimed at environmental protection and water management. Their task is to acquire and redistribute financial resources to support projects related to environmental protection. VFEPWMs face the challenge of increasing the use of available funds and the efficiency of their use. The paper presents the use of DEA method — which is as a modern engineering management tool — to evaluate the VFEPWMs performance. In the DEA performance analysis of VFEPWM, it is assumed that each unit may be characterised by their input resources, effects, environmental variables and transformation processes that transform resources into effects. VFEPWMs have better performance if they transform resources into desirable effects (actions) more efficiently. The results of the conducted analysis allow comparing the performance of particular VFEPWMs, to identify model units and to develop benchmarking graphs. The analysis is performed not only to assess the current level of VFEPWM performance but also to acquire information allowing to remove inefficiency.
PDF
