Regional Energy Efficiency Research Articles

Государственные и региональные координационные центры системы управления энергоэффективностью регионов

В статье рассмотрены основные направления технологических мероприятий по повышению энергоэффективности экономики регионов Российской Федерации. Обращается внимание на роль системного подхода к решению вопросов энергоэффективности. Обращается особое внимание на объединение интересов и усилий государственных органов исполнительной власти всех уровней, организаций всех форм собственности и граждан. Показана необходимость создания системы государственного управления эффективностью использования энергоресурсов и сети государственных Координационных центров. Обоснована необходимость законодательного повышения правового статуса существующих региональных центров энергосбережения (энергоэффективности), создав на их базе государственные Координационные центры управления энергоэффективностью с передачей им, полностью или частично, функций и полномочий Федеральной и региональных энергетических комиссий. The article discusses the main directions of technological measures to improve the energy efficiency of the economy of the regions of the Russian Federation. Attention is drawn to the role of a systematic approach to solving energy efficiency issues. Special attention is paid to combining the interests and efforts of state Executive bodies at all levels, organizations of all forms of ownership and country nationals. The necessity of creating a system of state management of energy efficiency and a network of State Coordination centers is shown. The necessity of legislative improvement of the legal status of existing regional energy saving (energy efficiency) centers by creating on their basis state Coordination centers for energy efficiency management with the transfer to them, in whole or in part, of the functions and powers of the Federal and regional energy commissions is justified.

Sustainable Evolution of China’s Regional Energy Efficiency Based on a Weighted SBM Model with Energy Substitutability

The rapid economy expansion in China has substantially increased energy consumption. Under the stringent environmental policy and the requirement of green economy development, the accurate assessment and analysis of energy efficiency is an increasingly significant issue for energy development policy making in China. This study uses the weighted slacks-based model (weighted SBM) considering the energy substitutability to evaluate the regional energy efficiency (EE) in 29 Chinese provinces, from 1991 to 2015, and explores the sustainable evolution characteristics of EE by comparative and convergence analyses from different perspectives. The empirical results show that EE has significant geographic differences. On the one hand, EE increases from the west to the east of China, and its volatility has a rising trend over the period 1991–2015. Only the EE in the eastern area had a stable rising trend, and the EE differences are difficult to reduce in the short term. On the other hand, the economic zones in the south of China, such as Central Bohai, Pearl River Delta, and Yangtze River Delta, have higher EE. We also find a significant EE improvement occurred during the Eleventh and the Twelfth Five-Year plans. By means of the convergence analysis of energy efficiency across different areas and economic zones over different time intervals, it is shown that EE in the southeast coast provinces have a better catching-up effect and adjustment rate toward the efficient frontier, while the western inland provinces are less effective over the period 1991–2005. Further, we empirically find that the industry policies including industry transfer policy promote EE globally, but the regional differences and fluctuations in EE remain serious. Certain policy implications are discussed with regard to sustainable regional development and an effective industry transfer policy.

Polycentric spatial structure and energy efficiency: Evidence from China's provincial panel data

Against the background of the increasing number of large and medium-sized cities and the improvement of the intercity transportation infrastructure, a polycentric urban network is gradually emerging in China. Based on panel data of 23 provinces of China over the period of 1998–2018, the dynamic impact of the polycentric spatial structure on the energy efficiency and the mechanism of this impact are explored in this paper. First, the results reveal that there exists an inverted U-shaped relationship between the polycentric spatial structure and the energy efficiency. Nevertheless, the polycentric spatial structure has not yet reached the optimal level in all provinces. Second, the market integration and factor flow are important paths for the polycentric spatial structure to affect the energy efficiency. Third, the inverted U-shaped impact of the polycentric spatial structure on the energy efficiency is mainly reflected in the eastern and central regions, while the phenomenon is not significant in the western region. Finally, the distances between cities and the level of the transportation infrastructure have significant non-linear moderating effects in the process of the polycentric spatial structure affecting the energy efficiency. These findings provide empirical evidence for the coordinated development of China's regional space planning and energy efficiency.

National environmental audit and improvement of regional energy efficiency from the perspective of institution and development differences

This paper examines the causal relationship between national environmental audit and regional energy efficiency from the perspective of institutional environment and development level differences for the period 2007–2017. The empirical results show that national environmental audit can significantly improve regional energy efficiency. In well-developed regions and regions with sound institutional environment, the external governance effect of national environmental audit on regional energy efficiency is more pronounced. Further studies also find that the external governance effect of the national environmental audit is to improve regional energy efficiency by promoting technological progress. Therefore, the Chinese government should strengthen the intensity of environmental audit, and different audit strategies should be adopted according to the institutional environment and development level differences. In addition, the Chinese government should integrate environmental audit with innovation policies, and improve energy efficiency through technological progress, so as to achieve efficient energy use and sustainable economic development.

Multi-attribute decision making with Pythagorean fuzzy sets via conversions to intuitionistic fuzzy sets and ORESTE method

The aim of this paper is to study the conversions between Pythagorean fuzzy sets and Atanassov's intuitionistic fuzzy sets. Besides, an ORESTE method based on multi-attribute decision making with Pythagorean fuzzy sets is developed by utilising the developed conversions. In this paper, according to the geometric representations of Pythagorean fuzzy sets and Atanassov's intuitionistic fuzzy sets, two types of conversions between the two fuzzy sets are constructed, which are further used to derive information measures include entropy and cross-entropy measures of Pythagorean fuzzy sets. Then, by combining with the ORESTE method, a direct decision procedure for multi-attribute decision making with Pythagorean fuzzy information is developed. Finally, a numerical example of the evaluation of regional energy efficiency is shown to illustrate the feasibility and validity of the developed decision procedure.

Триетапний метод прогнозування рівнів енергоспоживання в економіці з урахуванням регіональних потенціалів енергозбереження

We perfected the known two-stage method of forecasting energy consumption levels by applying its methodical approaches for three hierarchical levels of the structure of Ukrainian economy: country, regions, types of economic activity in regions. This approach makes it possible to determine the demand for fuel and energy resources at the regional levels of structuring the economy with regard for the specific features of their economic development. According to regional energy efficiency programs, it is possible to estimate more accurately the energy saving potentials and volumes of the replacement of scarce fuels with their cheap local types. The three-stage method is based on the refined normative method that is used at three hierarchical levels with regard for the estimated energy saving potentials from structural and technological shifts in the economy. The forecasts obtained agree with each other by Kulyk's method twice. The country-level forecast is consistent with the forecast for total regional energy consumption. For each region, the forecast of regional energy consumption is consistent with the forecast of total energy consumption at the levels of types of economic activity in the region with regard for structural and technological shifts. If the coordination of consumption levels between the types of economic activity and the region will introduce corrections to the regional energy consumption, then the coordination of levels of the country and regions is carried out at the second time. In other words, forecasting is carried out at three levels with two matches of the results of forecasting energy consumption –- between the first and second as well as second and third levels. If it is necessary to correct the forecasts of second level, reconciliation between the forecasts of first and second levels is performed again. Kulyk's vector method is used to agree on predictive decisions. We also present a method for calculating the forecasts of energy consumption at three hierarchical levels with the corresponding agreement of these forecasts. Based on the described methodology and estimated volumes of energy saving potentials at regional levels and for more significant types of economic activity in the regions, we performed a forecast of heat energy consumption for the period to 2040 , taking into account the volumes of technological energy saving in the regions. Keywords: method, demand, region, energy consumption, forecasting, type of economic activity, adjustment

Does financial agglomeration promote the increase of energy efficiency in China?

Whether financial agglomeration is conducive to the improvement of energy efficiency is of great significance for China to better follow the path of energy conservation and emission reduction, and green sustainable development. Based on the balanced panel data of 285 cities in China from 2005 to 2017, this paper analyzes the impact of financial agglomeration on energy efficiency. Theoretical analysis shows that financial agglomeration can influence energy efficiency through scale economy effect, innovation driving effect, information spillover effect and structural adjustment effect. Dynamic spatial econometric results show that, from a national perspective, financial agglomeration has a positive impact on energy efficiency. However, from the perspective of different regions and different city sizes, it is found that financial agglomeration can have different effects on energy efficiency. Financial agglomeration has a significant positive impact on energy efficiency in eastern and central regions, megacities and big cities. Financial agglomeration has a significant negative impact on energy efficiency in western China, and has no significant effect on energy efficiency in medium-sized and small cities. Finally, based on the conclusions of the study, specific proposals for financial agglomeration to improve energy efficiency are proposed.

Energy Price and Energy Efficiency in China: A Linear and Nonlinear Empirical Investigation

The empirical conclusions regarding the relationship between energy price and energy efficiency are relatively mixed. This paper systematically examines the influence of energy price on energy efficiency in China based on data from 30 provinces between 2003 and 2017, using linear and nonlinear effect analysis. We found that the impact of energy price on energy efficiency in China was positive in general. However, there existed heterogeneous effects of energy price on energy efficiency in various regions, and the effect differed with differences in energy efficiency levels based on the panel quantile regression analysis. Finally, the nonlinear effect analysis based on the panel threshold model indicated that the effect of energy price on energy efficiency increased with the rise of the environmental regulation level and economic growth rate, while it decreased with the ascent of the degree of energy price distortion and economic development level. In particular, when the value of a region’s economic development level and economic growth rate was within a certain range, the impact was not statistically significant. Overall, these findings contribute to a deeper understanding regarding the effect of energy price on energy efficiency in China.

Using a network DEA model to assess the energy efficiency of regions in China

This paper assesses 30 provinces’ data in China by using a network DEA model with undesirable output. The results denote that the proposed model could evaluate the internal energy consumption well. And the main cause of the energy inefficiency is environmental inefficiency. Therefore, China’s provinces should tighten restriction on CO2 emissions and reduce their dependence on fossil fuels by using more green energy.

“Leaky Bucket” of Kazakhstan’s Power Grid: Losses and Inefficient Distribution of Electric Power

This paper aims to determine and explain the main factors for power losses (the so-called “leaky bucket” effect) in Kazakhstan and the reasons for inefficient energy distribution within the country. Energy efficiency in Kazakhstan is much lower compared to more economically developed countries. The differences between energy efficiency in various regions of Kazakhstan are also significant. This article explores the impact of administrative monopoly tariffs on the regional energy efficiency, based on a national study conducted in Kazakhstan in 2017. The purpose of the study was to identify the administrative barriers and their impact on the sustainability of enterprise development. What hinders the distribution of energy resources among different regions is artificial barriers in the energy market and the administrative tariff monopoly for electric power. This leads to the inefficient distribution of resources throughout the country. In addition, it is difficult to leverage low distribution efficiency in the absence of a market. The authors attempt to prove that the magnitude of administrative barriers directly affects the efficiency and competitiveness of business, as well as the final prices of goods and services for the end consumer.

Research on multi-source coordination evaluation model of regional energy Internet

Energy Internet is the direction of energy development and an important means to change energy structure and improve energy efficiency. In order to promote the application and development of energy Internet, starting with the study of the key factors affecting the level of energy efficiency in the regional energy system, a multi-source optimization energy efficiency evaluation index system of regional energy Internet is established. Through the subjective evaluation of the first level indicators, the objective evaluation of the second level indicators and the final comprehensive empowerment, the comprehensive evaluation model of regional energy Internet multi-source optimization energy efficiency is built. Finally, taking a multi-source coordinated optimization operation of a park in Zhejiang Province as an example, the scientific rationality of the evaluation indexes and methods is verified.

'Neighbors as Competitors' or 'Neighbors as Partners': How Does Market Segmentation Affect Regional Energy Efficiency in China?

Existing studies have focused on the negative impact of inefficient resource allocation on energy performance in China’s factor market, but neglected to further explore the underlying reason for this phenomenon from the perspective of market segmentation. In this paper, the epsilon-based measure model, which combines the merits of radial and non-radial Data Envelopment Analysis, is employed to measure the energy efficiency, and price index method derived from Iceberg Transport Cost model is used to examine the degrees of market segmentation. On the basis, we use the Tobit model to empirically investigate the impact of market segmentation on China’s energy efficiency. The results show that although energy efficiency in the eastern region is higher than that in the central and western regions, the energy efficiency gap is narrowing significantly between the eastern and central, but insignificantly between the western and eastern. Although efforts have been made towards a unified national market, the western provinces still have more segmented markets than the eastern still. Econometric analysis indicates that market segmentation is negative to China’s energy efficiency significantly. This finding remains robust even if the endogeneity is excluded and the dependent variable is re-measured by the slack-based measure model, but is of a regional heterogeneity. We also find that factor market distortion, enterprises’ R&D investment, and industrial agglomeration are three mediation mechanisms through which market segmentation affects energy efficiency. In-depth analysis indicates that there is a Race to the Top competition centering on market segmentation among Chinese local officials in geospatial and economic space, which triggers a long-term inhibition to energy efficiency.

Research on China’s Regional Energy Efficiency Evaluation and Influencing Factors Based on the DEA-Tobit Model

Research on China’s Regional Energy Efficiency Evaluation and Influencing Factors Based on the DEA-Tobit Model

Energy and Emission Efficiency of the Slovak Regions

This paper examines changing regional patterns of energy and emission efficiency in the Slovak regions in the period of 2008–18. Firstly; we review literature on key approaches to evaluating energy and emission efficiency; followed by discussing the pros and cons of specific methods. A slacks-based model of data envelopment analysis is applied in order to investigate changing patterns of energy and emission efficiency in 79 Slovak regions (LAU 1). Thereafter; changes in energy and emission efficiency are associated with policy interventions supported by the European Structural and Cohesion Funds (ESCF) in the period of 2011–15. The evaluation found no support for the hypothesis with regard to the positive impact of the ESCF on the increase in energy and emission efficiency. Combined support from three ESCF policy measures (€606.44m) was substantial; but accounted for a mere 6.3% of the total firm expenditure on product and process innovations in the period of 2007–15 (€9,573m). Productivity-boosting technological innovations and structural changes in the Slovak economy (a shift towards industries with a lower consumption of energy but a higher production of gross value added GVA) were major drivers of trends in energy and emission efficiency. If an increase in energy (emission) efficiency; rather than energy savings (a decrease in pollution), is a major objective of sustainable development policies; then innovation-oriented policies and changes in the structure of economic activities should be preferred to schemes supporting simple energy-saving (emission-cutting) projects

The network energy and environment efficiency analysis of 27 OECD countries: A multiplicative network DEA model

This research enhances the ability of the data envelopment analysis (DEA) model to analyse regional energy and environmental efficiency in three aspects. The first is a networked efficiency analysis of the regional economy-energy-environment model, which allows us to analyse internal conflicts between different departments in the region. Secondly, we use a multiplicative function instead of a linear function for frontier efficiency analysis. Multiplicative function frontier efficiency analysis model has two advantages: (1) The multiplicative function can allow both increasing marginal productivity and diminishing marginal productivity, while linear functions can only deal with diminishing marginal productivity. (2) The variables involved in regional production activities in the multiplicative function are no longer independent of each other, but have synergistic effects. (3) There is no inconsistency between internal evaluation and external evaluation when using the multiplicative model to measure the efficiency of the network structure. Thirdly, we found friction efficiency and conflict efficiency by comparing the network model with the traditional single model. Friction efficiency represents the DMU internal conflicts impact and conflict represents the degree of efficiency of the process is affected by the internal conflict. They can help decision makers understand more clearly the reasons for the inefficiency within DMU. Finally, we use 27 OECD countries as examples to conduct case studies. The results show that the multiplicative model is more reasonable in calculating regional energy and environmental efficiency than the traditional DEA model. On the other hand, the networked analytical structure can give policymakers more detailed analysis results than single process method.

Total factor energy efficiency in regions of China: An empirical analysis on SBM-DEA model with undesired generation

Due to the imbalance of regional development and the different energy efficiency of different regions in China, it is necessary to measure the total factor energy efficiency of various economic zones and get the actual situation of each region. The paper uses SBM-DEA Model considering undesired generations to measure the total factor energy efficiency in different regions of China. When analyzing the situation of multiple inputs and multiple outputs, the paper will adopt a decision making-unit that measures multiple inputs and outputs. Thirty provinces and municipalities are divided into eight economic zones by using the State Council’s division method. The average annual total factor energy measurement value in China from 2005 to 2016 is 0.4559 under the consideration of environmental constraints. With the existing technology and the constant investment scale, there is still a 50% increase in this value. This provides a theoretical upside for the further transformation and upgrading of China’s energy production capacity and the reform of the supply side. Then it uses Moran index to get the spatial correlation of TFEE separately. It shows that there is a significant spatial positive correlation of China’s total factor energy efficiency. The conclusion is that China’s total factor energy efficiency has not increased with economic growth, and the regional gap is large, and there is room for improvement of 50%. It also shows that there is a positive spatial correlation among regional TFEE values. That is, high TFEE value in certain area could promote the value of surrounding provinces, indicating that China’s current economic growth is still dominated by energy consumption, and China is also in the middle and late stages of industrialization.

‘Neighbors As Competitors’ or ‘Neighbors as Partners’: How Does Market Segmentation Affect Regional Energy Efficiency in China?

Existing studies have focused on the negative impact of inefficient resource allocation on energy performance in China’s factor market, but neglected to further explore the underlying reason for this phenomenon from the perspective of market segmentation. In this paper, the epsilon-based measure model, which combines the merits of radial and non-radial Data Envelopment Analysis, is employed to measure the energy efficiency, and price index method derived from Iceberg Transport Cost model is used to examine the degrees of market segmentation. On the basis, we use the Tobit model to empirically investigate the impact of market segmentation on China’s energy efficiency. The results show that although energy efficiency in the eastern region is higher than that in the central and western regions, the energy efficiency gap is narrowing significantly between the eastern and central, but insignificantly between the western and eastern. Although efforts have been made towards a unified national market, the western provinces still have more segmented markets than the eastern still. Econometric analysis indicates that market segmentation is negative to China’s energy efficiency significantly. This finding remains robust even if the endogeneity is excluded and the dependent variable is re-measured by the slack-based measure model, but is of a regional heterogeneity. We also find that factor market distortion, enterprises’ R&D investment, and industrial agglomeration are three mediation mechanisms through which market segmentation affects energy efficiency. In-depth analysis indicates that there is a Race to the Top competition centering on market segmentation among Chinese local officials in geospatial and economic space, which triggers a long-term inhibition to energy efficiency.

Dynamic and network slack-based measure analysis of China’s regional energy and air pollution reduction efficiencies

Abstract China’s rapid development over the past few decades has resulted in significant environmental pollution from CO2, SO2 and NO2 emissions amongst others, all of which can adversely affect human health. However, past efficiency analyses have tended to discuss energy efficiency and environmental efficiency separately, or have discussed ways in which governments can reduce pollution at the source. In other words, previous analyses of China’s energy efficiency have only been focused on one-stage, and very few studies have integrated the environment, government pollution reductions, and economic development in the analysis. Therefore, to fill this research gap, this study examined the first and second-stage energy and air pollution reduction efficiencies in thirty Chinese provinces and municipalities from 2013 to 2016 using a dynamic, network slack-based measure (DNSBM) model, in which labor, fixed assets and energy consumption were the input variables in the first production stage, GDP was the output variable, and CO2, SO2, and NO2 emissions were the link variables, and in the second treatment stage, pollution treatment investment was the input variable, the CO2, SO2, and NO2 emissions reductions were the output variables, and energy consumption/GDP was the carryover variable. It was found that; (1) Beijing, Shanghai, Guizhou, Hainan and Qinghai had the best performances over the 4 years, and Shaanxi, Shandong, Fujian, Jilin, Liaoning and Xinjiang had the worst performances and therefore had the greatest need for improvements; (2) the overall provincial efficiencies were generally relatively low and significant improvements were needed however, there were large differences between the provinces/municipalities; (3) the overall air pollution reduction efficiency governance in the second stage was low, indicating that more effective measures were needed to improve environmental efficiency and that the dynamic developments in government regulations and governance had resulted in a policy implementation lag; and (4) in 21 provinces, the first-stage productivity was significantly higher than the second-stage treatment productivity, indicating that the treatment stage needed to be strengthened.

Методика визначення енергоємності продукції на прикладі меблевої фабрики

Formulation of the problem. InUkraine, since 2007, enterprises, especially those involved in exporting products, have begun to be certified by ISO (International Organization for Standardization) standards. The first of these standards was ISO 9001 - the product quality standard. Nowadays, the implementation of ISO 50001 "Energy Management Systems" is spreading. One of the criteria for the implementation of this system is the development of energy efficiency indicators, one of which is the energy intensity of products: the ratio of the amount of fuel and energy resources (FER) spent on its production to output [1]. At present, there are no current methods of calculating the energy intensity of products inUkraine, but there are significant developments in this area. Until 2014, there was a system of normalization of fuel and energy resources costs. The development of specific rates of FER (energy consumption) was compulsory for enterprises of all industries with an annual consumption of 1000 tonnes or more of conditional fuel [2]. The governing bodies of the state in this area were regional energy efficiency inspectorates, which were subordinated to the State Energy Efficiency. The development of standards was, in most cases, based on a calculation and analysis method based on techniques developed during theUSSRwith adjustments related to technological progress, climate change, and the like. Purpose of research – calculate the energy intensity of products by the example of a furniture factory. Research methodology. Calculation of energy consumption of products made on the example of furniture factory LLC "Ukryug" is located in the village. Shkarovka Belotserkovsky district of Kiev region. The enterprise is engaged in production of furniture of the following types: cabinet furniture, kitchens, bedrooms, living rooms, children's, modular systems. Raw materials for furniture production are wood (particle board). The output of the enterprise is measured in square meters of processed raw materials, for 2016-2018 the average annual output was 3157,287 thousand square meters. Research results Calculation of energy intensity of products was carried out by determining the specific norms of consumption of heat and electric energy per unit of output, as well as the norms of fuel consumption for the supply of heat energy to the boiler plant of the enterprise. Calculation of heat energy consumption for heating and ventilation of industrial and office buildings is carried out according to the method of increased indicators [3], data on the external temperature and duration of the heating period were taken from [4], the standard for losses in the heat networks of the enterprise is taken from [5]. Norms of fuel consumption for heat supply to the boiler house were developed according to the method [6]. The calculation of consumption of electric energy was calculated according to [7]. The initial data for the calculations were provided by authorized employees of the enterprise. Conclusion The following indicators of energy intensity of products are calculated: - the norm of electric energy consumption for production; - rate of heat energy consumption for production; - rate of fuel consumption for heat supply to the boiler room; - rate of electric energy consumption for heat supply to the boiler room. These indicators are indicators of energy efficiency of the enterprise, which are designed taking into account the technical characteristics of the equipment, its operating time, climatic conditions, etc. According to these indicators, in the future periods energy efficiency of technological and auxiliary equipment will be evaluated as well as the boiler-house which produces heat.

Analysis of Energy Capacity of the Russian Economy in the Regional Context

Purpose: The purpose of this study is to consider options for adjusting primary reporting to clarify energy efficiency indicators. Design/Methodology/Approach: In particular, models based on the study of correlation of gross regional product with regional production factors are considered. This will make it possible to refine the actual output in the regional context. Findings: In comparison with the developed countries Russia essentially lags in the level of power consumption. For this reason, energy intensity is one of the priorities of the country's development. According to the data of Russian and international organizations, assessments of the state program of energy-saving implementation are very controversial, which does not allow making an objective conclusion about the achieved results. Practical Implications: For such assessments, methods of factor analysis of reasons for energy efficiency changes, which are difficult to implement in Russia, are widely used in the world. The reason for this is the low reliability of the initial data due to the peculiarities of obtaining them. As a result, there is an abnormal dispersion of data both throughout the country's economy and in the energy efficiency of regions. Originality/Value: A systematic analysis of the country’s energy efficiency problem also requires data from a regional perspective. It is here that the main difficulties are observed, caused by the impossibility of objectively linking production volumes to the actual location of energy resources used.