Changes In Electricity Consumption Research Articles

Construction of a recurrent neural network-based electrical load forecasting model for a 110 kV substation: a case study in the Western Region of The Republic of Kazakhstan

Construction of a recurrent neural network-based electrical load forecasting model for a 110 kV substation: a case study in the Western Region of The Republic of Kazakhstan

Energy-growth nexus in Australia and New Zealand for the past 150years-evidence from time-varying and quantile Granger causality analysis.

Using historical data on energy from (Malanima 2020) and GDP from the Maddison Project Database, this paper investigates the energy-growth nexus in a less-studied region, mainly Australia and New Zealand, since 1870. The long annual series allow meaningful application of recently developed time-varying and quantile Granger causality analysis. Results indicate that there is a bi-directional Granger causal relationship between economic growth and energy, coal, and oil consumption at both ends of the distribution, and during various time periods over the past 150years. Little evidence is found on the Granger causal relationship from gas consumption to economic growth, but some evidence on the direction from economic growth to gas consumption. The Granger causal relationships between electricity consumption and GDP change over time, but results suggest much closer links between the two in most recent decades, and big (positive and negative) changes in electricity consumption significantly Granger causes economic growth.

Organizational level energy conservation and efficiency - a case of public sector organization in Karachi, Pakistan

Pakistan is facing chronic energy crises since many years. This paper aims to provide an overview of the current status of energy efficiency and conservation practices at organizational level in Pakistan. The first phase of this study evaluates the trends in electricity consumption in selected buildings over the last six years (2017–2022). Subsequently, a survey was conducted in selected buildings to assess employee morale and knowledge of energy efficiency and conservation. Results show an insignificant change in electricity consumption in selected buildings during the past six year’s period indicating a poor culture of energy savings in the selected organization. Despite a constant electricity consumption from 2017 to 2022, a significant fluctuation in average billing amounts was observed. This is possibly due to electricity tariff that has continuously been fluctuating since last few years in Pakistan including Karachi. Study reveals that more than 50% of the employees in selected organization were aware about the importance of energy efficiency and conservation however, they rarely practice the energy saving measures during their routine activities. This is perhaps due to the lack of sense of national stewardship among the employees. It was also found that most of the employees of the selected organization are aware and motivated towards the environmental and climate change concerns related to energy production and its efficient use. However, again a small number of employees were found practicing the energy conservation and efficiency measures. According to this study, companies should encourage staff members to save energy by offering frequent trainings and educational opportunities. Additionally, the organizations ought to think about switching to renewable energy sources.

Environmental Impact Analysis of Residential Energy Solutions in Latvian Single-Family Houses: A Lifecycle Perspective

This study aims to compare the technological solutions that can contribute to more sustainable energy use in the residential sector. Specifically, the goal of the study is to evaluate the environmental impact of different energy (heat and electricity) supply technologies applicable for an average size single-family building in Latvia, a country known for climatic condition characterized by cold winters with frequent snowfall. The study applies the lifecycle assessment methodology of ISO 14040 and the impact assessment method known as ReCiPe 2016 v1.1, which has not been used before for the scope addressed in the study in the context of single-family building energy supply technologies for climatic conditions in Latvia. Thus, the results of the study will provide new information for more sustainable energy solutions in this area of study. The technologies included in the defined scenarios are conventional boiler, electricity from the grid, Stirling engine, and solar photovoltaics (PV). The results of the lifecycle impact assessment for damage categories revealed that all scenarios have a high impact on human health due to fine particulate matter formation followed by global warming. Regarding the damage to the ecosystem, the terrestrial ecotoxicity category has highest impact, followed by global warming. Sensitivity analyses affirmed the model’s validity and also showed that the impacts of conventional systems were most sensitive to changes in electricity consumption, and therefore, the scenarios with electricity supply from a Stirling engine or PV can be considered a more robust solution under changing electricity demands from an environmental perspective.

Using neural networks to forecast marginal emissions factors: A CAISO case study

Marginal Emissions Factors (MEFs) quantify the time-dependent changes in CO2 emissions resulting from changes in electricity consumption. Accurate MEFs are critical for calculating the emissions impact of demand-side management (DSM) activities and programs, but current methods of calculating MEFs are limited by their temporal resolution, accuracy (particularly in grids with high penetrations of variable renewable energy), and ability to predict MEFs ahead of time, reducing their utility for DSM. We improve upon existing techniques by introducing a novel multi-layer perceptron to linear composite model that uses publicly available grid data to calculate historical MEFs and predict day-ahead MEFs. We test our model on publicly-available data from the California Independent System Operator over the period of 2019–2021, a grid with high daytime VRE generation. Results indicate that our model produces more accurate and more granular demand-based MEF estimations than comparable regression techniques and maintains high accuracy when use to forecast future MEFs. Our MEF framework can be applied to other regional grids to evaluate and design DSM strategies that leverage CO2 emissions-reductions as motivation for altering electricity consuming behaviors.

Changes in the Pattern of Weekdays Electricity Real Consumption during the COVID-19 Crisis

In this paper, using data from Romania, we analysed the changes in electricity consumption generated during the COVID-19 crisis, and the measures taken against the spread of the coronavirus to limit the effects of the pandemic. Using a seasonal autoregressive econometric model, we found that, beyond seasonal (weekly, monthly, quarterly, yearly) effects, the average daily electricity real consumption in Romania, during the state of the emergency period (16 March 16 to 14 May 2020) decreased by −194.8 MW (about −2.9%), compared to the historical data (2006–March 2022), and this decrease is not due to the action of some random factors, and it is not a manifestation of domain-specific seasonality. The literature discusses the hypothesis that during the pandemic time, the profile of daily electricity consumption on weekdays was close to the typical Sunday profile. We tested a similar hypothesis for Romania. As a methodology, we tried to go beyond the simple interpretation of statistics and graphics (as found in most papers) and we calculated some measures of distances (the Mahalanobis distance, Manhattan distance) and similarity (coefficient of correlation, cosines coefficient) between the vectors of daily electricity real consumptions, by hourly intervals. As the time interval, we have analysed, for Romania, the electricity real consumption over the period January 2006–March 2022, by day of the week and within the day, by hourly intervals (5911 observations). We found (not very strong) evidence supporting a hypothesis that, in the pandemic crisis, the profile of electricity consumption approaches the weekend pattern only for the state of the emergency period, and we could not find the same evidence for the state of the alert period (June 2020–March 2022). The strongest closeness is to the hourly consumption pattern of Saturday. That is, for Romania, in terms of electricity consumption, “under lockdown, every day is a Sunday” (Staffell) it is rather “under lockdown, every day is (almost) a Saturday”! During the state of the alert period, consumption returned to the pre-crisis profile. Since certain behaviours generated by the pandemic have been maintained in the medium and long term (distance learning, working from home, online sales, etc.), such studies can have policy implications, especially for setting energy policy measures (e.g., in balancing load peaks).

HOUSEHOLD-SPECIFIC SOCIAL NORMS, THE ELASTICITY OF ELECTRICITY DEMAND, AND CARBON EMISSION REDUCTIONS IN THE RESIDENTIAL SECTOR: EVIDENCE FROM A NATURAL EXPERIMENT IN RUSSIA

In this paper, I estimate the price elasticity of residential electricity demand using household-level panel data for Russia. The study takes advantage of the variation in tariffs across regions and over time, as well as the introduction of increasing block rate (IBR) schemes in a number of regions. I show that in those regions consumers appear to be aware of the block cut-offs, even though the latter are based on the prescribed social norms and are household and dwelling specific, to the point that there are up to a total of 31 different tier cut-offs. Based on these results, I estimate the price elasticity of electricity demand to be around −0.1. I also predict the associated changes in electricity consumption, CO2 emissions, and revenues if similar IBR policies are implemented countrywide.

Impact of demand growth on decarbonizing India's electricity sector and the role for energy storage

Global energy sector decarbonization efforts are contingent on technology choices for energy production and end-use in emerging markets such as India, where air conditioning (AC) is expected to be a major driver for electricity demand growth. Here, we assess the impact of demand and supply side-drivers on the long-term evolution of the electricity sector in India under various technology and policy scenarios. Our analysis is based on developing: (a) multiple demand scenarios produced from a bottom-up forecasting model with high temporal resolution that capture structural changes in electricity consumption resulting from (AC) and electric vehicle (EV) adoption, and (b) a multi-period power system capacity expansion model with high temporal resolution of grid operations to model supply-side evolution in response to changes in demand and technology and policy factors. Such a framework allows us to, for example, quantify the impacts of improving appliance efficiency standards for AC systems or shifts in EV charging patterns on power system decarbonization prospects. Under projected renewables and Li-ion storage cost declines, our modeling points to solar and wind generation contributing substantially (46–67%) to meet annual electricity demand in India by 2030. However, without appropriate policy measures to phase out existing coal generation, even such rapid adoption of variable renewable energy coupled with one or more technological levers such as low-cost energy storage and demand-side measures such as setting aggressive AC efficiency standards and deploying distribution level storage, are insufficient to reduce annual CO2 emissions in 2050 vs. 2020 because of the relatively higher growth rate of projected electricity demand over this period. This suggests that deep decarbonization of India's power sector will require policy measures beyond efforts related to accelerating renewables deployment.

Socio-Economic Vulnerability to Climate Change in Rural Areas in the Context of Green Energy Development-A Study of the Great Masurian Lakes Mesoregion.

Green energy production has become a common and recognized method of electricity generation. Giving up reliance on non-renewable energy sources is an important trend in the economies of many countries. The paper presents an analysis of the impact of indicators like increased green energy production on the level of vulnerability to climate change. The model of the Climate Change Vulnerability Index (VCC) recommended by the Intergovernmental Panel on Climate Change (considering three aspects: exposure, vulnerability, and adaptive capacity of the studied spatial unit/society) was applied. Sensitivity analysis, spatial heterogeneity, and temporal dynamics of indicators characterizing changes in electricity consumption, renewable energy production, greenhouse gas emissions, and variability of financial losses due to extreme weather events and their number were implemented. Several findings arose. First, the vulnerability to climate change (the level of the VCC index), does not decrease after the implementation of a single action, like the development of green energy production. The level of index of vulnerability to climate change (VCC1) from the reference year (2017) relative to VCC2 (2021) has changed slightly, despite the development of RES. The variation does not exceed a 1% reduction in the value of the VCC1 index. Second, the decrease in the level of the vulnerability requires global, coordinated action. The value of the VCC3 index, reflecting, including changes in green energy production (X15), electricity consumption/inhabitant (X38), and green-house gas emissions (X14), exhibited more favorably the impact of these indicators on vulnerability to climate change, compared to the VCC1 reference value. In eleven poviats, the VCC3 index decreased between 1 and 4%. In seven of these poviats, green energy production increased, resulting in an average 10% decrease in the X15 indicator, the X14 indicator representing green-house gas emissions decreased by an average of 7%, while the X38 indicator describing electricity consumption/per capita decreased by an average of 16%. Third, harmonized and inclusive action by the population holds the potential to be the clue to reducing vulnerability to climate change.

Analyzing Morocco’s Electricity Consumption Changes with an LMDI Decomposition Model: A Global and Sectoral Perspective

Over the past decade, Morocco has experienced a surge in electricity demand, driven by economic growth and population expansion. This study aims to delve into the factors influencing electricity consumption in Morocco from 2000 to 2020, examining both the overall national trends and sector-specific dynamics. Indeed, we employ the logarithmic mean Divisia index (LMDI) to assess changes in electricity consumption, considering various components like electricity's share, energy intensity, economic structure, economic activity, and population. At the national level, our findings indicate that economic growth has been the primary driver, contributing 66.22% to the total change in electricity consumption, followed by electricity's share effect (39.15%), population scale (29.44%), and the sectorial structure effect (10.85%). Conversely, energy intensity exhibited a declining trend, acting as a restraining factor. Among the analysed sectors, we observed distinct patterns that exhibited some degree of variation. While the agricultural, transport, and residential sectors were primarily affected by the production-per-capita effect, the industrial and commercial sectors were mainly influenced by the intensity effect. The results mentioned above highlight the significance of recent efforts to improve energy efficiency within the Moroccan economy. They also emphasize the necessity of further developing these strategies and introducing novel approaches to rationalize electricity consumption.

Analysis of the influence of the stay-at-home order on the electricity consumption in Chinese university dormitory buildings during the COVID-19 pandemic

During the COVID-19 pandemic, strict stay-at-home orders have been implemented in many Chinese universities in virus-hit regions. While changes in electricity consumption in the residential sector caused by COVID-19 have been thoroughly analysed, there is a lack of insight into the impact of the stay-at-home order on electricity consumption in university dormitory buildings. Based on questionnaire survey results, this study adopted the statistical Kaplan–Meier survival analysis to analyse the energy-use behaviours of university students in dormitories during the COVID-19 pandemic. The electricity load profiles of the dormitory buildings before and during the implementation of the stay-at-home order were generated and compared to quantitatively analyse the influence of COVID-19 pandemic on the energy-use behaviours of university students, and the proposed load forecasting method was validated by comparing the forecasting results with monitoring data on electricity consumption. The results showed that: 1) during the implementation of the stay-at-home order, electricity consumption in the university dormitory buildings increased by 41.05%; 2) due to the increased use of illuminating lamps, laptops, and public direct drinking machines, the daily electricity consumption increased most significantly from 13:00 to 18:00, with an increase rate of 97.15%; and 3) the morning peak shifted backward and the evening peak shifted forward, demonstrating the effect of implementing the stay-at-home order on reshaping load profiles.

Elektrik Tüketiminin Ekonomik Büyüme Üzerindeki Asimetrik Etkisi: NARDL ve Toda-Yamamoto Yöntemlerinden Kanıtlar

Çalışma, elektrik tüketiminin ekonomik büyüme üzerindeki asimetrik etkisini değerlendirmeyi amaçlamaktadır. Bu bağlamda, Türkiye ekonomisinin 2005-2020 dönemi verileri çalışma kapsamına dahil edilmiştir. Ekonometrik analizde, çeyreklik veriler yardımıyla iki farklı yöntem uygulanmıştır. Analizin tahmin gücünü arttırmak amacıyla sanayi üretim endeksinin bağımsız değişken olarak kullanıldığı ve ekonomik büyümenin bağımlı değişken olduğu modellerde elektrik tüketiminin asimetrik etkisi NARDL modeliyle, nedensellik ilişkisi Toda-Yamamoto testiyle yansıtılmıştır. NARDL modeli bulgularına göre, ampirik uygulamanın değişkenleri arasında uzun dönemde eşbütünleşme ilişkisi vardır ve analiz sonuçları eşbütünleşmenin varlığını doğrulamaktadır. Diğer taraftan, elektrik tüketimindeki pozitif ve negatif değişimlerin kısa ve uzun dönemdeki etkisine bakıldığında; pozitif değişimlerin büyümeyi arttırdığı, negatif değişimlerin ise büyümeyi azalttığı görülmüştür. Toda-Yamamoto nedensellik testinde elektrik tüketiminden büyümeye doğru nedensellik çıkması, NARDL modelindeki sonucu destekler niteliktedir.

Electricity Consumption in Higher Education Buildings in Thailand during the COVID-19 Pandemic

The COVID-19 pandemic forced higher education institutions to switch to online learning for most of 2020 and 2021 for the safety of their students and staff, which significantly impacted campus resource consumption. This study aims to analyze the changes in electricity consumption in higher education buildings based on comparisons of three academic years to understand more about the energy implications of the post-COVID-19 era. The electricity data were collected from 181 samples of the electricity meter records at Chulalongkorn University, Thailand. When compared to the typical academic year in 2018, the results indicate that electricity consumption in 2019 and 2020 decreased by 20.92% and 35.50%, respectively. The academic and the library-type buildings marked the biggest change in electricity reduction. The smallest change was found in the research type as its essential work remained on campus. Only electricity consumption in the residence type increased due to the long periods of online learning policies. Finally, the findings suggest that teaching and learning activities have a strong influence on electricity consumption in higher education buildings. The facilities and learning methods related to these activities should be carefully discussed as elements of an effective strategy to manage electricity demands at the university level.

The impact of COVID-19 measures on intraday electricity load curves in the European Union: A panel approach

This paper examines the impact of the intensity of government measures introduced to reduce the spread of COVID-19 on intraday electricity load curves in 23 European countries. The econometric panel model used covers the entire period from the virus outbreak in Europe up to the release of several vaccines; therefore, the estimation considers the introduction, partial lifting, and reintroduction of the interventions. Based on the results, the impacts of the different stringency measures were similar in the 23 analysed EU member states. More stringent interventions had different effects at different times of day: the morning and evening peaks were significantly affected, as was every hour of the day. The impacts were nonlinear, meaning that different measures mutually amplified each other’s impact and led to more substantial changes in electricity consumption and citizens’ lives. The morning and evening peaks are also found to have decreased, causing a flattening of the load curves. In line with this result, the partial effect of an increase in the stringency index depends on the type of day (weekday or weekend), hour of the day, and initial stringency level. Overall, the lockdown measures led to a decrease in hourly electricity consumption of between 1% and 9% on weekdays and between 1% and 13% on weekends. Total daily consumption decreased by up to 9%. Understanding how hourly electricity demand reacts to different stringency measures provides valuable information in operation scheduling and capacity planning. More accurate demand forecasts can support trading decisions and help prevent extreme market mismatches.

Mathematical modeling of power consumption based on rank analysis

In the article, based on the application of the rank analysis of the technocenosis, mathematical modeling of electricity consumption by consumers for the production of hard alloys is carried out. Two methodological levels of research in the field of energy-saving and power consumption are presented. At the same time, it was found that rank analysis allows you to streamline information, effectively predict power consumption by individual objects to identify dynamics, and visually represent objects with abnormal power consumption. The analysis of the results obtained confirms the efficiency of using the H-distribution for obtaining mathematical models of power consumption of Noah and Pointer castes in the production of hard alloys. For the first time, the regularity of changes in electricity consumption by technological equipment was established, which is described by an adequate mathematical model in the form of a damped harmonic function. The resulting model is recommended for use in an automated dispatching control system for electricity consumption for the purpose of short-term forecasting of electricity consumption.

Assessment of the Impact of the Human Coronavirus (COVID-19) Lockdown on the Energy Sector: A Case Study of Sharjah, UAE

The recent coronavirus (COVID-19) pandemic has wreaked havoc on the global economy, causing major shifts in energy use and output patterns. For some countries, this has had a significant effect on energy demand and carbon emissions, at least in the short term. Since the United Arab Emirates is currently exerting many efforts towards sustainability, it is important to assess and understand the impacts of the pandemic and the lockdown measurements on the local energy sectors. Data for this analysis were gathered by the Sharjah Electricity Water & Gas Authority (SEWA) for Sharjah City which is the capital of the Emirate of Sharjah. The changes in electricity after the implementation of quarantine and lockdown-like measures were assessed, and the results indicate that the electric power demand in Sharjah City was reduced in the commercial, industrial, and agricultural sectors, whereas the residential and government sectors witnessed a higher power demand. The overall electricity consumption in the year 2020 was reduced by 1.04% in comparison with previous years including 2016 to 2019. The results of this study indicate that the changes in electricity consumption were minimal in Sharjah City as compared to other cities around the world. However, this paper highlights the importance of governmental response during and after a pandemic, and the possible impacts that lockdowns could potentially have in the energy industry worldwide.

Effect analysis of the COVID-19 pandemic on the electricity consumption of Bangladesh

The COVID-19 pandemic has disrupted our way of life and has brought challenges on a scale never seen before. Lockdown and various other social distancing rules have been implemented in order to slow down new infections. This has led to a drastic change in people's lifestyle and has altered the pattern of electricity consumption. In this paper, the effect of lockdown on the overall electricity consumption of Bangladesh is analysed. Also, a neural network-based prediction model is developed to predict the electricity consumption during a lockdown or estimate the future consumption given a lockdown is announced in the future. Furthermore, in order to compare the change in electricity consumption for commercial, residential, and industrial areas, power measurements for the lockdown and the post lockdown period are analysed in detail. Results show a significant decline in the overall electricity consumption of Bangladesh during the period of lockdown. In addition, the commercial and industrial areas showed a considerable reduction in electricity consumption. However, the changes in electricity consumption in residential areas are found negligible. This study will aid in to provide a clearer understanding on the electricity consumption pattern in the case of further lockdowns or in the event of another outbreak in the future.

A framework for dynamic life cycle sustainability assessment and policy analysis of built environment through a system dynamics approach

Sustainability is gaining attention, particularly in the building sector, owing to its significant influence on economy, society and environment. However, most assessment methods/frameworks available for this sector focus solely or dominantly on the environmental dimension of sustainability. Hence, a sustainability assessment framework for buildings that accounts for the interdependencies amongst social, economic and environmental aspects is essential. Further, buildings also undergo several time-induced changes in their characteristics, such as changes in electricity consumption, material properties, surrounding infrastructure and energy mix that can influence their sustainability. Therefore, this paper introduces a system dynamics-based methodological framework for Dynamic Life Cycle Sustainability Assessment (D-LCSA) capable of incorporating the dynamic changes in the building characteristics with time and capturing the interactions amongst different sustainability indicators. The usability and utility of the framework is demonstrated using a case study residential project in India. The case study results show that ignoring time-dependant dynamic aspects in sustainability assessment of buildings leads to underestimating the overall sustainability impacts by about 50 per cent and specific environmental impacts by about 12 per cent. Therefore, the study reinforces the need to adopt dynamic thinking through modelling and simulation to predict sustainability performance in the built environment.

Decomposition the driving force of regional electricity consumption in Japan from 2001 to 2015

Investigating electricity consumption is vital for identifying the driving forces for national onsite energy use and pathways for mitigating greenhouse gas emissions. However, before any electricity conservation measures are implemented, a well understanding of the driving forces behind sectoral electricity consumption variation are of great importance. Therefore, this research constructed an assessment framework on how electricity consumption reflects and responds to social and natural events, and how far the Japanese electricity consumption decouples economic development by estimating the changes in electricity consumption in Japan from 2001 to 2015. The results revealed that electricity consumption intensity and economic activity effect were both dominant but obtained opposite impacts in terms of electricity consumption changes. Moreover, differences in driving forces that caused spatial variance for regional changes in electricity consumption were found during the economic recession and recovery periods. The decoupling status showed that the decoupling degree in Japan changed from an extensive negative decoupling state to a weak decoupling state during the study periods. Subsequently, the results also shed light on how to mitigate regional electricity consumption stress sustainably.

Global changes in electricity consumption during COVID-19

SummaryUnderstanding how the COVID-19 pandemic has altered electricity consumption can provide insights into society's responses to future shocks and other extreme events. We quantify changes in electricity consumption in 58 different countries/regions around the world from January-October 2020 and examine how those changes relate to government restrictions, health outcomes, GDP, mobility metrics, and electricity sector characteristics in different countries. We cluster the timeseries of electricity consumption changes to identify impact groupings that capture systematic differences in timing, depth of initial changes, and recovery rate, revealing substantial heterogeneity. Results show that stricter government restrictions and larger decreases in mobility (particularly retail and recreation) are most tightly linked to decreases in electricity consumption, although these relationships are strongest during the initial phase of the pandemic. We find indications that decreases in electricity consumption relate to pre-pandemic sensitivity to holidays, suggesting a new direction for future research.