scholarly journals The Effects of Social Distancing on Electricity Demand Considering Temperature Dependency

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 473
Author(s):  
Mohannad Alkhraijah ◽  
Maad Alowaifeer ◽  
Mansour Alsaleh ◽  
Anas Alfaris ◽  
Daniel K. Molzahn
Keyword(s):  
Power System ◽  
Social Activity ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Electric Grid ◽  
Temperature Changes ◽  
Social Distancing ◽  
Novel Coronavirus ◽  
Time Required

To mitigate the spread of the Novel Coronavirus (COVID-19), governments around the world have imposed social distancing policies ranging from minor social activity suspensions to full curfews. These social distancing policies have altered electricity consumption behaviors in numerous countries. Many governments imposed strict social distancing policies during a temperature transition season where the impacts of temperature variations are particularly important for the operation of the electric grid. This paper studies how strict social distancing policies affect the relationship between electricity demand and ambient temperature. We first review the expected short- and long-term impacts of social distancing on the electricity demand. We then present a case study on the electricity demand of the Kingdom of Saudi Arabia during strict social distancing policies. The results of this case study suggest that strict social distancing policies result in a stronger correlation between temperature and electricity demand compared to previous years. Additionally, we observe a reduction in the time required for the electricity demand to respond to temperature changes. Power system regulators can use the results in this paper to better design energy policies. The results can also be used by power system operators to more accurately forecast electricity demands and avoid inefficient and insecure operation of the electric grid.

scholarly journals Econometric Model for Forecasting Electricity Demand of Industry and Construction Sectors in Vietnam to 2030

2020 ◽  
Vol 3 (1) ◽  
pp. First
Author(s):  
Viết Cường Võ ◽  
Phuong Hoang Nguyen ◽  
Luan Le Duy Nguyen ◽  
Van-Hung Pham
Keyword(s):  
Power System ◽  
Econometric Model ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Master Plan ◽  
Base Scenario ◽  
Leading Position ◽  
Long Term Forecasting ◽  
High Scenario

An accurate forecasting for long-term electricity demand makes a major role in the planning of the power system in any country. Vietnam is one of the most economically developing countries in the world, and its electricity demand has been increased dramatically high of about 15%/y for the last three decades. Contribution of industry and construction sectors in GDP has been increasing year by year, and are currently holding the leading position of largest consumers with more than 50% sharing in national electricity consumption proportion. How to estimate the electricity consumption of these sectors correctly makes a crucial contribution to the planning of the power system. This paper applies an econometric model with Cobb Douglas production function - a top-down method to forecast electricity demand of the industry and construction sectors in Vietnam to 2030. Four variables used are the value of the sectors in GDP, income per person, the proportion of electricity consumption of the sectors in total, and electric price. Forecasted results show that the proposed method has a quite low MAPE of 7.66% for long-term forecasting. Variable of electric price does not affect the demand. This is a very critical result of the study for authority governors in Vietnam. In the base scenario of the GDP and the income per person, the forecasted electricity demands of the sectors are 112,853 GWh, 172,691 GWh, and 242,027 GWh in 2020, 2025, 2030, respectively. In high scenario one, the demands are 115,947 GWh, 181,591 GWh, and 257,272 GWh, respectively. The above values in the high scenario are less than from 9.0% to 15.8 % of that of the based on in the Revised version of master plan N0. VII.

scholarly journals The Impact of COVID-19 on Electricity Demand Profiles: A Case Study of Selected Business Clients in Poland

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5332 ◽  
Author(s):  
Marcin Malec ◽  
Grzegorz Kinelski ◽  
Marzena Czarnecka
Keyword(s):  
Energy Consumption ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Energy Prices ◽  
Total Change ◽  
Rapid Changes ◽  
Sales Company ◽  
Energy Companies ◽  
The Impact

The COVID-19 pandemic has caused changes in electricity demand and, consequently, electricity consumption profiles. Given the rapid changes in energy prices, it is significant from the perspective of energy companies, and forecasting consumed energy volume. A necessity for accurate energy volume planning forces the need for analyzing consumers’ behaviors during the pandemic, especially under lockdowns, to prepare for the possibility of another pandemic wave. Many business clients analyzed in the paper are economic entities functioning in sectors under restrictions. That is why analyzing the pandemic’s impact on the change in energy consumption profiles and volume of these entities is particularly meaningful. The article analyzes the pandemic and restrictions’ impact on the total change of energy consumption volume and demand profiles. The analysis was conducted basing on data collected from a Polish energy trading and sales company. It focused on the energy consumption of its corporate clients. Analyzed data included aggregated energy consumption volumes for all company’s customers and key groups of economic entities under restrictions. The analysis demonstrates the influence of pandemic restrictions on energy consumption in the group of business clients. Significant differences are observable among various sectors of the economy. The research proves that the largest drops in energy consumption are related to shopping centers and offices. Altogether, the restrictions have caused a 15–23% energy consumption drop during the first lockdown and a maximum 11% during the second against expected values.

Electricity Demand as a High-Frequency Economic Indicator: A Case Study of the COVID-19 Pandemic and Hurricane Harvey

FEDS Notes ◽  
2020 ◽  
Vol 2020 (2792) ◽  
Author(s):  
Joshua Blonz ◽  
◽  
Jacob Williams ◽  
Keyword(s):  
United States ◽  
Natural Disaster ◽  
High Frequency ◽  
Electricity Consumption ◽  
Economic Indicator ◽  
The United States ◽  
Electricity Demand ◽  
Economic Conditions ◽  
Economic Shocks

Electricity is used by all businesses in the United States. During quickly moving economic shocks—for example, a pandemic or natural disaster—changes in electricity consumption can provide insight to policymakers before traditional survey-based metrics, which can lag weeks or months behind economic conditions and typically only show a snapshot of when the survey was conducted.

A Rapid Automatic Life Cycle Assessment Tool for Eco-Design

2017 ◽  
Author(s):  
Yongxian Zhu ◽  
Fu Zhao
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Assessment Tool ◽  
Electricity Consumption ◽  
Resource Depletion ◽  
Design Decisions ◽  
Manufacturing Enterprises ◽  
Environmental Footprints ◽  
Time Required

Increasing concerns about global warming, resource depletion, and ecosystem degradation are pushing manufacturing enterprises to consider environmental impacts of the products they make. Tools such as Life Cycle Assessment (LCA) has been developed to quantify environmental performance of a product, yet the implementation of LCA requires a significant amount of time/resources and its potential in assisting eco-design has been limited. Research has been done to conduct automatic LCA using the simplified database for electronics or to investigate the environmental impact of electricity consumption in a manufacturing process. However, a comprehensive and automated approach is in need to perform LCA analysis for a product considering all related materials and manufacturing processes. In this research, a framework for automating LCA analysis for eco-friendly product design has been developed and implemented with a computer program. A case study has been conducted using the proposed automatic LCA tool to perform life cycle analysis in the design process. The result of the tool can, with minimal time required, provide detailed distribution of life cycle impact indicators among direct inputs and assist in making design decisions to reduce the environmental footprints.

scholarly journals Application of LEAP model on long-term electricity demand forecasting in Indonesia, period 2010-2025

2018 ◽  
Vol 49 ◽  
pp. 02007 ◽  
Author(s):  
Jaka Windarta ◽  
Bambang Purwanggono ◽  
Fuad Hidayanto
Keyword(s):  
Demand Forecasting ◽  
Electricity Consumption ◽  
Electricity Demand ◽  
Planning System ◽  
Large Country ◽  
Electricity Demand Forecasting ◽  
Electricity Planning ◽  
Business As Usual

Electricity demand forecasting is an important part in energy management especially in electricity planning. Indonesia is a large country with a pattern of electricity consumption which continues to increase, therefor need to forecasting electricity demand in order to avoid unbalance demand and supply or deficit energy. LEAP (Long-range Energy Alternative Planning System) as a tool energy model and Indonesia as a case study. Basically, electricity demand is influenced by population, economy and electricity intensity. The purpose of this study is to provide understanding and application of electricity demand forecasting by using LEAP. The base year is 2010 and end year projection is 2025. The scenarios of simulated model consist of two scenarios. They are Business as Usual (BAU) and Government policy scenario. Results of both scenarios indicate that end year electricity demand forecasting in Indonesia increased more than two fold compared to base year.

scholarly journals Is Urbanisation Rate a Feasible Supplemental Parameter in Forecasting Electricity Consumption in China?

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Biao Yang ◽  
Yingcheng Li ◽  
Haokun Wei ◽  
Huan Lu
Keyword(s):  
Regression Models ◽  
Electricity Consumption ◽  
Forecast Model ◽  
Electricity Demand ◽  
Shaanxi Province ◽  
Average Error ◽  
Demand Forecast ◽  
Valid Predictor ◽  
The Government

Traditional method of forecasting electricity consumption based only on GDP was sometimes ineffective. In this paper, urbanisation rate (UR) was introduced as an additional predictor to improve the electricity demand forecast in China at provincial scale, which was previously based only on GDP. Historical data of Shaanxi province from 2000 to 2013 was collected and used as case study. Four regression models were proposed and GDP, UR, and electricity consumption (EC) were used to establish the parameters in each model. The model with least average error of hypothetical forecast results in the latest three years was selected as the optimal forecast model. This optimal model divides total EC into four parts, of which forecasts can be made separately. It was found that GDP was only better correlated than UR on household EC, whilst UR was better on the three sectors of industries. It was concluded that UR is a valid predictor to forecast electricity demand at provincial level in China nowadays. Being provided the planned value of GDP and UR from the government, EC in 2015 were forecasted as 131.3 GWh.

scholarly journals A Practical Formulation for Ex-Ante Scheduling of Energy and Reserve in Renewable-Dominated Power Systems: Case Study of the Iberian Peninsula

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1939 ◽  
Author(s):  
Miguel Carrión ◽  
Rafael Zárate-Miñano ◽  
Ruth Domínguez
Keyword(s):  
Stochastic Programming ◽  
Power Systems ◽  
Power System ◽  
Iberian Peninsula ◽  
Ad Hoc ◽  
Computational Time ◽  
Operational Practices ◽  
Mathematical Programming Problems ◽  
Time Required

Scheduling energy and reserve in power systems with a large number of intermittent units is a challenging problem. Traditionally, the reserve requirements are assigned after clearing the day-ahead energy market using ad hoc rules or solving computationally intense mathematical programming problems to co-optimize energy and reserve. While the former approach often leads to costly oversized reserve provisions, the computational time required by the latter makes it generally incompatible with the daily power system operational practices. This paper proposes an alternative deterministic formulation for computing the energy and reserve scheduling, considering the uncertainty of the demand and the intermittent power production in such a way that the resulting problem requires a lower number of constraints and variables than stochastic programming-based formulations. The performance of the proposed formulation has been compared with respect to two standard stochastic programming formulations in a small-size power system. Finally, a realistic case study based on the Iberian Peninsula power system has been solved and discussed.

Exponential growth impact of COVID-19 pandemic-world scenario, preventive measures and drug preferences (Preprint)

2020 ◽  
Author(s):  
Aneesh Kumar K V
Keyword(s):  
Exponential Growth ◽  
World Health ◽  
The Novel ◽  
Social Distancing ◽  
Infected People ◽  
The Public ◽  
The World ◽  
Novel Coronavirus ◽  
Health Organization

BACKGROUND The World Health Organization (WHO) declared 2019-20 coronavirus outbreak as a Public Health Emergency of International Concern (PHEIC) on 30 January 2020 and pandemic on 11 March 2020. As of today, 17 May 2020 around 3,16,520 death and 47,99,266 coronavirus infected cases are reported worldwide. There is about 26,25,463 active cases are now under treatment and several lakhs of people are under quarantine. Therefore, an attempt has been made to explain briefly about the characteristics of the virus, current review, COVID-19 symptoms, precautions, available vaccines etc. In addition, a case study was also conducted to provide the dangerous picture of drastic growth of infected people around the world during the span of time. OBJECTIVE World Health Organization (WHO) has announced the COVID-19 outbreak as a global public health emergency and pandemic, spreading fast with an increasing number of infected patients worldwide. At present, no vaccines are available for the treatment of patients with COVID_19 disease. A case study was conducted to provide the dangerous picture of exponential growth of infected people around the world to inculcate the awareness of maintaining social distancing and hand hygiene. This effort is made in view of providing awareness to the public effectively to understand and deal with the novel coronavirus situation worldwide. It is also anticipated to provide a reference to future advances in medical anti-virus related studies. METHODS A case study was conducted to provide the dangerous picture of exponential growth of infected people around the globe. For our study, we preferred five most coronavirus effected countries in the world viz., China, Itali, USA, Spain, India in the month of February and March 2020, and later extended to 17 May 2020. Based on the current published evidence, we precisely summarize the disease, characteristics of the virus, current world scenario, available treatment options and preventive measures to be taken against COVID-19. RESULTS Effort is made in view of providing awareness to the public effectively to understand and deal with the novel coronavirus situation worldwide.The medicines like Remdesivir, Chloroquine and Hydroxychloroquine, Ritonavir/Lopinavir and combined with Interferon beta are the experimental treatments currently being researched. Treatment with Lopinavir and Ritonavir or Chloroquine should be recommended in older patients with serious symptoms. The main risk factor of COVID-19 is travel and exposure to the virus. Lockdown, quarantine and thereby maintaining the ‘social distancing’ are the suitable method for controlling the out spread of coronavirus. Moreover, it is individual’s responsibility to take prompt measures to control the fast spreading of this virus disease. CONCLUSIONS The COVID-19 disease is spreading fast uncontrolled with an increasing number of infected patients worldwide. Our case study details the dangerous picture of exponential growth of infected people around the globe. The exact source, characteristics of the virus is unknown and no suitable drugs have been developed as of today. Symptomatic treatments are available and the list is provided, no need to panic. Conclusion is to inculcate the awareness of maintaining social distancing and hand hygiene. Anticipated to provide a reference to future advances in medical antivirus related studies.

Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan

2021 ◽  
Author(s):  
Miao Yu ◽  
Zhongsheng Hua
Keyword(s):  
Close Contact ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Social Distancing ◽  
Infected People ◽  
Epidemic Curve ◽  
Specific Effects ◽  
Lag Effect ◽  
Novel Coronavirus

Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.

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