Increasing Energy Prices Research Articles

IntelliHome: An internet of things‐based system for electrical energy saving in smart home environment

AbstractDespite there has been an increasing energy price due to factors such as supply, demand, government regulation, among others, users do not like to spend their time to analyze their power consumption and establish actions to save money. Hence, there is a need for smart solutions that help users to save energy at home in an easy way. The smart home concept is attracting the attention of both academia and industry to address this need. Nowadays, high volumes of data are available in the smart home context, facilitated by the growth of internet of things (IoT)‐based devices and advanced sensing infrastructure. Therefore, it is necessary to automatically extract useful knowledge from this information to cost‐effective use of energy at home. In this sense, this work presents IntelliHome, a smart‐home system that aims to reduce electrical energy consumption at home. To this end, IntelliHome uses big data analytics technologies and Machine Learning and statistical techniques to provide users with a meaningful perspective of their electricity consumption habits aiming to actively involve them in the energy‐saving process through real‐time information and energy‐saving recommendations. This work also discusses a case study and an evaluation aligned with the objectives of this work. The obtained results verify the effectiveness of the proposed system regarding electrical energy saving.

Structural design optimization of moving component in CNC machine tool for energy saving

Abstract With the increase of energy price and environment problem, the energy consumption of machine tool is attracting more attention. The moving components of machine tools consume a large amount of energy in the operating stage. Structure optimization of moving components is a key strategy for energy saving in machine tools design. Traditionally, structural optimization of machine tools is carried out for reducing energy consumption or improving static and dynamic performance. Given that these factors are important to the structure optimization in machine tools design, this paper presents a structural design optimization method for comprehensively considering energy consumption, static and dynamic performance of machine tool. Firstly, the energy consumption model of the moving components is proposed, and the structural performance indicators of the moving components are analyzed. Then, based on the experiment data obtained by uniform design method, five structure parameters that have great influence on performance indicators are selected as decision variables through sensitivity analysis. To improve the computation efficiency, approximation functional relationship between the five decision variables and the four performance indicators are built through response surface method (RSM). After that, an optimization objective is formulated by combining the four performance indicators through principal component analysis (PCA). Finally, a new hybrid algorithm which integrates Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithm is developed to solve the structure optimization problem. Through calculation and analysis, it is found that there is a linear relationship between the moving part mass and energy consumption. The results show that the energy consumption of optimized structure is reduced while ensuring the static and dynamic performance.

Large time‐varying parameter VARs: A nonparametric approach

SummaryIn this paper we introduce a nonparametric estimation method for a large Vector Autoregression (VAR) with time‐varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs. When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and compares well with large (parametric) Bayesian VARs with time‐varying parameters. The tool can also be used for structural analysis. As an example, we study the time‐varying effects of oil price shocks on sectoral U.S. industrial output. According to our results, the increased role of global demand in shaping oil price fluctuations largely explains the diminished recessionary effects of global energy price increases.

An Assessment of the Strategy of Working Capital Management in Polish Energy Companies

Working capital is a kind of a buffer that protects an enterprise against the loss of financial liquidity. Therefore, managing it is a key element from the point of view of financial security in every company. The purpose of the articles is to analyze working capital management in the largest Polish energy companies. In general, state-owned companies, especially those operating in the energy sector, have no problems with managing liquidity or working capital. However, recently in Poland, the turmoil associated with an increase in energy prices resulting largely from political licks have caused rapid drops in energy companies in the market. In such a situation, it is worth analyzing the working capital management strategies in detail. The analysis was carried out on the group of the largest Polish energy companies.

Annual changes in energy quality and quality of life: A cross-national study of 29 OECD and 37 non-OECD countries

Since the efficiency of obtaining energy is decreasing, it is important to determine how the degradation in energy quality will influence society. Despite the rising importance of net energy, few quantitative studies have been conducted on the relationship between energy quality and quality of life (QoL). Energy return on investment on a society scale at a national level (EROIsoc) is used as an indicator of energy quality, energy consumption (EC) per capita is used to represent energy quantity, and gross domestic product (GDP) per capita is used as an economic factor. Eight indices are used for QoL. Simple linear regression analysis is used to discuss the correlation coefficients between the three indicators (EROIsoc, GDP per capita, and EC per capita) and eight QoL indices for 29 OECD and 37 non-OECD countries, and their annual changes over the 25 years from 1990 to 2015. We demonstrate that the relationship between the three indicators and eight QoL indices changes annually and differs between OECD and non-OECD countries. We also demonstrate that although GDP per capita is the most influential factor among the three indicators for the Human Development Index (HDI), which is one of the best-known composite indices of well-being, the importance of GDP per capita for non-OECD countries has declined, especially in times of increasing energy prices, while the importance of EROIsoc for OECD countries has increased.

Assessing the duality of thermal performance and energy efficiency of residential buildings in hot arid climate of\xa0Laghouat, Algeria

Thermal comfort is the main driver of buildings energy consumption; it has been classified by building occupants to be of greater importance compared with visual and acoustic comfort. To respond correctly and quickly to the increase in energy price and pollution, thermal regulations and comfort approaches have emerged. This paper compares the thermal performances and energy demand of a vernacular and a low-income modern dwelling using two major thermal comfort approaches (Givoni’s approach and adaptive thermal comfort recommended by The American Society of Heating, Refrigerating and Air-Conditioning Engineers in ASHRAE standards 55-2010) and the energy professional’s method presented in the French Thermal Regulations RT2012. It shows the effectiveness of bioclimatic and passive strategies in reducing energy demand, increasing the thermal comfort level for the buildings, and therefore reducing greenhouse emissions. The results show that the vernacular house was comfortable during the warm day, which approved a 100% cooling energy efficiency (the thermal comfort has been achieved in a passive way), contrary to the contemporary dwelling, in which the use of air-conditioning modern systems was essential to meet the occupant needs in terms of thermal comfort. The difference between the houses’ energy performances was estimated, including a 39% reduction in energy demand.

The Inefficiency of Energy Pricing Policy: The Case of Iran

High-energy consumption leads to a serious threat to climate change and human health, while contributing to environmental pollution. Concerns about climate change, air quality, and water quality and availability have made Iranian people and government increasingly aware of the need to reconcile economic and environmental objectives. Government energy pricing policies have multiple and often conflicting objectives: economic efficiency, government revenues, maintenance or improvement of income distribution, promotion of particular sectors demand management and security of supply. Increasing energy efficiency is the quickest and least costly way of addressing energy security and the environmental as well as economic challenge. According to statistics, since 1988, the Iranian government has increased the price of energy by 23.2% annually to reduce the consumption of energy (Dargahi and Ghorbannejad in Iran Energy Econ 1(4):67–100, 2012). But in this period, the growth rate of energy intensity was about 1.6%. In Iranian economy, people know, in advance, to what extent the government would increase the energy price. People expect an increase in the price of all products due to the increase in energy price. In this paper, we study such a behavior which has led to inefficiency of the government policy. Consumer subsidies are quantified utilizing the price-gap approach that compares end-user prices and reference prices that would predominate in competitive markets where no subsidies are provided. An input–output analysis is undertaken to investigate impacts in the short term. We modify the conventional input–output price model to consider the effect of the increase in energy prices.

MAIN TRENDS OF THE EXECUTION OF REGIONAL BUDGETS IN 2018

In the process of the execution of consolidated budgets of the subjects of Federation in 2018 here were such positive events as strong revenues’ growth, significant budget surplus indicators in the most of the regions and the total reduction of the debt burden. But all these events did not lead to the evident growth of real incomes of the population. Profit tax revenues grew most significantly in the past year due to the increasing energy prices. Federal grants to the budgets of subjects of the Russian Federation increased considerably. The latter took place together with the shift from the goal-oriented kinds of support to regions (subsidies, subventions and other transfers) to the non-conditional kinds of grants. In the same time these is a shift from formalized to non-formalized categories of grants. In 2018 Russian regions succeeded to preserve the tendency towards the increase of the social expenditures. Significant volumes of consolidated budget surplus of several regions are a matter of grave concern because the high level of budget surplus exists in these regions together with serious decrease of real incomes of the population.

SPATIAL DISAGGREGATION OF THE BIOENERGY POTENTIAL FROM CROP RESIDUES USING GEOSPATIAL TECHNIQUE

Abstract. Limited national fossil fuel resources and sustained increases in energy prices have resulted in nationwide efforts to study and deploy alternative energy sources. Despite high prospect, biomass resources has not been effectively utilized in India due to the lack of information on amount, type and time of its availability on a geospatial frame work to facilitate its transportability, establishment of bio-fuel plants tailor made for specific crop residues. Hence, a comprehensive approach towards geospatial mapping of bio-energy potential from surplus crop residues of selected crops (rice. wheat, cotton and sugarcane) over the Haryana state of India is implemented by utilizing a hybrid model combining both statistical and remote sensing technique. Bioenergy potential was calculated from crop production statistics collected at district level. The grain production data were converted into gross residue potential using residue production ratio. The crop residue was further converted into collectable crop residue using collectable coefficient. To generate the spatial map of the selected crops, potential crop masks were prepared using multi-temporal satellite data. These crop masks were then converted to crop fraction at 1 km grid level. MODIS NPP data product was then processed and converted into same 1 km to account the spatial variability of biomass potential. Using these crop fractions as independent variables, relationship was established with NPP as dependent variable using a machine learning technique (Random Forest algorithm). These crop specific response curves (crop fraction vs NPP) were utilized as a weight to disaggregate district level gross biomass potential to 1 km grid level. The spatial map thus generated provided spatial details of the type and amount surplus crop residues and could be vital input for planning and policy making of utilization of the surplus biomass resources of India.

Space of energy well‐being: Social housing tenants’ everyday experiences of fuel poverty

This paper contributes to geographical perspectives on energy justice by arguing for the concept of “spaces of energy well‐being.” We build on the concepts of capabilities, home, and emotional embodiment to offer an understanding of the spatiality of well‐being. The paper draws on empirical material from a study conducted with social housing tenants in Port Kembla, Australia, following recent energy price increases. Interviews illustrate that social housing tenants engaged in reducing domestic energy consumption occupy a paradoxical space of well‐being. We argue that energy bills are lived and felt daily through bodies as anxiety, given that participants experience social housing as a therapeutic and safe place that allows possibilities to refashion the self. We better understand the dynamics of pride and shame from limiting energy use. Our analysis suggests that essential to understanding the ways social housing tenants relate to uneven access to fuel is as an emotionally embodied home making and unmaking practice.

SOFC’s Bumpy Road and Hopeful Future – a Case Study

Our world largely runs on fossil fuels with 60-80% of our electricity from burning coal and natural gas. The 2015 Paris Accords intensified greenhouse gas emissions reductions. Solid oxide fuel cells (SOFC) have wide fuel choices and less complicated reforming subsystems. SOFC can also be potentially and effectively operated as solid oxide electrolysis cells (SOEC), coupling with renewable energy sources, for example, solar and wind, and storing renewable energy in chemical form (e.g. hydrogen). However, several leading international SOFC developers have abandoned their commercialization efforts. This paper is an attempt to address and discuss concerns both from a technological and economic standpoint. Considering the rapid population growth, expected increase in energy demand and price and greenhouse gas reductions need, SOFC could play a critical role in the transition from fossil fuel era to renewable energy era.

Prospects for the development of biogas technologies at reservoirs of energy facilities

In connection with the increase in energy prices and the deterioration of the environmental situation, the problem of introducing biogas plants is becoming increasingly important. In this case, the selection of promising raw materials for the production of biogas becomes actual. The organization of energy-biological complexes on coolering reservoirs will allow not only to solve the problem of thermal emissions of power plants, but also to obtain biogas. The article deals in detail with the creation of energy-biological complexes at reservoirs of power engineering objects. Special attention is paid to the use of aquatic vegetation for the production of biogas, as a stage of utilization of excesses of the higher aquatic vegetation of the cooling reservoir of the power station.

Innovative development of agricultural production in Uzbekistan: condition and prospects

The article analyzes the current state of development of agricultural production in Uzbekistan for the period of agrarian reforms, which resulted in the formation of a class of owners in the field of agro-industrial complex, developed farmer and dekhkan farms, agrofirms, processing enterprises. For the further development of the agrarian market, it is necessary to form economic incentives for the development of production. The solution of this problem will allow to ensure the efficiency of the system of distribution of agricultural products, to make agricultural production a technological and competitive, stable exporter of agricultural products. In recent years, there have been positive changes in the growth of production and consumption of basic foodstuffs, their assortment is expanding, and the quality of products is improving. However, there are many factors hindering the development of the industry: the insecurity of enterprises with raw materials, the imperfection of the system of mutual settlements between enterprises of the agro-industrial complex, the increase in energy prices and transportation tariffs, etc. The agro-industrial complex of Uzbekistan has been tasked not only to consolidate the progress achieved, but also to ensure the growth of agricultural production and increase its competitiveness.

Promoting competition and protecting customers? Regulation of the GB retail energy market 2008\u20132016

In 1999 the GB retail energy market was open to competition for residential customers. In 2008 Ofgem began a series of regulatory interventions, notably a nondiscrimination condition and subsequently a restriction to four “simple tariffs”. This reversed its previous policy of minimal intervention. This paper explores the reasons for this change of policy, drawing upon the responses of economists and others to Ofgem and Competition and Market Authority (CMA) consultations. It argues that key factors were a significant increase in energy prices before 2008, the reduced involvement of economists in senior roles at Ofgem, and systematic changes in Government policy and the statutory regulatory framework. Finally, the paper examines what the CMA Energy Market Investigation had to say about this in 2016. The CMA found that these were inappropriate regulatory interventions, and laid part of the blame on arrangements for governance of the regulatory framework.

Mathematical modelling and structural optimization of a micro-channel liquid separation condenser in organic Rankine cycle and refrigeration cycle

The decrease in fossil energy reserves and increase in energy prices have resulted in a strong interest in utilizing low-grade energy or improving the efficiency of traditional energy system. Air-cooled condenser is a key component in thermodynamic cycles, such as organic Rankine cycle and vapor compression refrigeration cycle. Liquid separation condenser (LSC) is a newly developed fin-and-tube condenser with excellent comprehensive performance. In this study, a micro-channel LSC (MLSC) is applied in organic Rankine cycle and vapor compression refrigeration cycle. A mathematical model is developed for the numerical simulation and structural optimization of MLSC. The objective function of the structural optimization is to minimize the total annual cost, which is composed of investment and operating costs. Unlike the traditional optimization method for heat exchangers, an improved operating cost indicator is derived and modeled according to the impact of pressure drop (PD) during condensation in the context of thermodynamic cycles. A case study is elaborated to test the proposed methodology. The simulation and optimization results show that the performance of MLSC are sensible to the cycle context. The total cost of the studied MLSC in the context of vapor compression refrigeration cycle (VCRC) is 52.46% higher than that in the context of organic Rankine cycle (ORC). Compare with the benchmark MLSC, the total cost of the optimal MLSC can be reduced by up to 45.2% in the context of VCRC and 34.9% in the context of ORC. These results indicate that the present study provides a methodology for better understanding the importance and the performance improvement of the MLSC in the related cycle than the previous simplified method.

Unveiling the heterogeneous effect of energy taxes and income on residential energy consumption

The paper investigates the effect of energy taxes in the European Union (EU) across different levels of residential final energy consumption (RFEC) in the period 2005–2016. The analysis is based on quantile panel regression models that directly and indirectly consider energy taxes. More precisely, the developed models provide a multivariate framework for evaluating their effects and, at the same time, for validating the existence of the energy environmental Kuznets curve (EKC) across the selected quantiles.The results unveil significant heterogeneity in the RFEC responses across quantiles. Specifically, in less energy-consuming EU countries, an increase in energy taxes and energy prices influences stronger RFEC, and the rebound effect of real income and tertiary education is greater than in their more energy-consuming peers. Moreover, in the former, the energy EKC hypothesis holds, while in the latter, its existence is not clear, as well as the rebound effect caused by highly educated people. Consequently, EU energy policy aiming at achieving energy and environmental targets has to consider the heterogeneity in RFEC since the outcomes might be different for different energy-consuming groups of countries.

Cost-optimized energy-efficient building envelope measures for a multi-storey residential building in a cold climate

In this study we analyse cost-optimal building envelope measures including insulation for attic roof, ground floor and exterior walls, and efficient windows and doors for new buildings. The analysis is based on a multi-storey building in south of Sweden with an expected lifetime of at least 100 years. We integrate dynamic energy simulation, total and marginal economic analysis, and consider different scenarios of real discount rates and annual energy price increases. Our analysis shows that cost-optimal thicknesses of insulations for the building envelope elements are significantly higher than those required to meet the current Swedish building code’s minimum energy requirements. For windows, the cost-optimal U-value is about the same as required to fulfil the minimum requirement of the Swedish building code. Overall, large energy and cost savings are achieved when the cost-optimal measures are cumulatively implemented. Compared to the reference, annual space heating reduction of 28-43% is achieved for the building with the cost-optimal measures under the analysed period of 50 years. The cost savings varied between 21 and 188 k€.

A Model of Price Correlations between Clean Energy Indices and Energy Commodities

This paper theoretically and empirically examines the relationship between environmental value embedded in clean energy indices and energy value obtained from energy prices by focusing on the influence of energy risk on clean energy business including renewables. We propose a supply and demand-based correlation (CR) model of clean energy indices and energy prices that takes into account the influence of energy on clean energy business including renewables. We also propose a market risk model based on CR model to conduct the risk management for stocks of clean energy firms appropriately. Empirical studies estimate the model parameters using the stock indices and energy prices including S&P Global Clean Energy Index (GCE), Wilderhill Clean Energy Index (ECO), S&P/TSX Renewable Energy and Clean Technology Index (TXCT), S&P 500, WTI crude oil prices, and Henry Hub (HH) natural gas prices. It is shown by using the model that the correlations between GCE or ECO and WTI crude oil or HH natural gas prices be positive and be an increasing function of the corresponding energy prices. Results seem reasonable because the values of renewable energy businesses, which sell electricity in the spot market, are enhanced by the increase in energy prices, considering that electricity spot prices tend to increase in line with energy prices. In contrast, it is also shown that the correlations between S&P 500 and WTI or HH prices be still positive but be a decreasing function of the energy prices. This sharp contrast may come from the fact that the S&P 500 listed companies’ businesses can be damaged by high energy prices while not applicable to GCE and ECO companies. Regarding TXCT, the correlations with WTI are positive and are a decreasing function of WTI while those with HH tend to be positive and are an increasing function of HH. It may suggest that TXCT is not fully functioning but still developing as a clean energy index, taking into account the results of GCE and ECO. Regarding market risk, CR model demonstrates different VaR from ordinary normal distribution (OND) model because CR model includes more upward or downward sloping demand curve shape reflecting the reality of the markets than the exponential in OND model, resulting in positive or negative impacts of prices on the volatilities in high clean energy index regions, respectively. We compare CR model with existing dynamic conditional correlation (DCC) model. Since CR model demonstrates the same level of the correlations from DCC model, CR model can work well as the correlation model.

The Assessment of the Impacts of Carbon Taxation on Chinese Transport and Energy Sectors Based on a Computable General Equilibrium Model

To simulate the effects of carbon taxation on Chinese economy, especially on transport and energy sectors, a computable general equilibrium model was constructed and calibrated with Chinese social accounting matrix and other statistical data. Based on calculated sectoral carbon emissions, a commonly used carbon tax rate of 20 Euros per tonne CO2-eq was converted into a carbon tax rate of 9.94% (tax / energy expenditure) for the transport sector, 1.72% for the energy sector and 9.42% for other sector. The simulation results show that the implementation of these sectoral carbon tax rates will cause a total carbon emission reduction of 40271.6 KT CO2-eqs and an increase of government revenue by 7.17%. However, the carbon tax will also induce approximately a 1.3% loss for the transport sector, a 3% loss for the energy sector and a 0.9% loss for other sectors. Incomes of firms and households will decrease by 4.05% and 0.14%, respectively. It is found that in the transport sector, labour will replace capital due to the increase in energy prices caused by the carbon taxation. The high loss in the energy sector and its subsequence suggest that the energy sector should be exempted from the carbon tax.

Regression mathematical model of two-stage combined electrical technology of high-temperature convective drying and ozone-air grain processing

Large production of cereal crops in Russia in 2014-2018 (100-130 million tons) imply the need to dry 10-30 % of the crop collected annually in the country to ensure its quantitative and qualitative preser-vation. The main way to reduce the excess moisture of grain in the Russian Federation is high-temperature convective drying, but it refers to very energy-intensive technological operations and, therefore, is very expensive. In the context of the constant increase in energy prices in the Russian economy, the country's agricultural producers face the primary task of increasing the profitability of the grain industry, within which it is necessary to reduce material costs at all stages of production, including through the creation of new high-intensity energy-saving technologies and technical means for drying grain raw materials. The authors have developed a two-stage technology of high-temperature convective and ozone-air grain drying that meets these requirements. In the article, based on the analysis of the parametric scheme of the convective-ozone-air moisture removal method, compiled taking into account the conditions and possibilities of conducting experimental studies of the process at the industrial drying unit «ELEKTA-1» of small productivity, the optimization parameters of this process are defined, which are: reduction of the drying time and the total reduction in energy consumption, in addition, the main factors varied in the ex-periments are highlighted: the initial moisture content of the grain, the amount of ozone supply to 1 m3 of grain and time spent on moisture removal. Second-order regression mathematical models for the convec-tive-ozone-air drying of barley grain with different initial humidity (30, 25 and 20 %) have been developed and their statistical significance has been evaluated. An analysis of the experimental data of the combined drying options studied at 6 % moisture removal for one cycle of processing the grain material revealed the following parameters of the efficiency of the methods of convective ozone-air moisture removal: when drying grain with an initial humidity of 30 %, the process duration decreased by 28 % and the total energy consumption decreased amounted to 33-43 %; when drying grain with a moisture content of 25 %, the duration of the process is reduced by 19 %, energy consumption by 24-35 %; and when drying grain with a moisture content of 20 %, the duration of the process is reduced by 30-35 %, energy consumption by 35-40 %.