Hasil untuk "Electricity"

Y. Parag, Benjamin Sovacool

Hamed Mohsenian Rad, A. Leon-Garcia

C. Fischer

S. Stoft

A. Akhil, G. Huff, Aileen B. Currier et al.

Baran Yildiz, J. Bilbao, A. Sproul

Fabio Moret, P. Pinson

While power system organization has evolved from a hierarchical structure to a more decentralized model, electricity markets are still not up to date with the ongoing transformation toward more consumer-centric economies. As information and communication technologies are broadly adopted, they allow prosumers to have a more proactive role in power system operation. This work introduces the concept of energy collectives, as a community-based electricity market structure. We find that when prosumers are allowed to share energy at community level, the overall electricity procurement for the community reflects prosumers’ preferences. We show that community members can be influenced by a supervisory third-party in charge of interfacing with the market and system operator and of guaranteeing the collective common agreements. We simulate a number of test cases and apply typical principles from analysis of communication networks and distributed systems to assess community fairness.

Wenbin Wang, Yusuf Shi, Chenlin Zhang et al.

The energy shortage and clean water scarcity are two key challenges for global sustainable development. Near half of the total global water withdrawals is consumed by power generation plants while water desalination consumes lots of electricity. Here, we demonstrate a photovoltaics-membrane distillation (PV-MD) device that can stably produce clean water (>1.64 kg·m−2·h−1) from seawater while simultaneously having uncompromised electricity generation performance (>11%) under one Sun irradiation. Its high clean water production rate is realized by constructing multi stage membrane distillation (MSMD) device at the backside of the solar cell to recycle the latent heat of water vapor condensation in each distillation stage. This composite device can significantly reduce capital investment costs by sharing the same land and the same mounting system and thus represents a potential possibility to transform an electricity power plant from otherwise a water consumer to a fresh water producer. The increasing demand for energy and clean water has become a grand global challenge. Here the authors develop a membrane-distillation device that exploits sunlight and the heat dissipated by an integrated solar cell unit, enabling simultaneous efficient production of electricity and drinkable water.

Jinyue Yan, Ying Yang, Pietro Elia Campana et al.

Paul S. Albertus, J. Manser, S. Litzelman

Summary The United States electricity grid is undergoing rapid changes in response to the sustained low price of natural gas, the falling cost of electricity from variable renewable resources (which are increasingly being paired with Li-ion storage with durations up to ∼4 h at rated power), and state and local decarbonization policies. Although the majority of recent electricity storage system installations have a duration at rated power of up to ∼4 h, several trends and potential applications are identified that require electricity storage with longer durations of 10 to ∼100 h. Such a duration range lies between daily needs that can be satisfied with technologies with the cost structure of lithium-ion batteries and seasonal storage utilizing chemical storage in underground reservoirs. The economics of long-duration storage applications are considered, including contributions for both energy time shift and capacity payments and are shown to differ from the cost structure of applications well served by lithium-ion batteries. In particular, the capital cost for the energy subsystem must be substantially reduced to ∼3 $/kWh (for a duration of ∼100 h), ∼7 $/kWh (for a duration of ∼50 h), or ∼40 $/kWh (for a duration of ∼10 h) on a fully installed basis. Recent developments in major technology classes that may approach the targets of the long-duration electricity storage (LDES) cost framework, including electrochemical, thermal, and mechanical, are briefly reviewed. This perspective, which illustrates the importance of low-cost and high-energy-density storage media, motivates new concepts and approaches for how LDES systems could be economical and provide value to the electricity grid.

Zihan Chang, Yang Zhang, Wenbo Chen

To a large extent, electricity price prediction is a daunting task because it depends on factors, such as weather, fuel, load and bidding strategies etc. Those features generate a lot of fluctuations to electricity price. As a type of RNN, LSTM has a good performance on processing time series data as well as some nonlinear and complex problems. To explore more accurate electricity price forecasting approach, in this paper, a new hybrid model based on wavelet transform and Adam optimized LSTM neural network, denoted as WT-Adam-LSTM, is proposed. After the wavelet transform, nonlinear sequence of electricity price can be decomposed and processed data will have a more stable variance, and the combination of Adam, one of efficient stochastic gradient-based optimizers, and LSTM can capture appropriate behaviors precisely for electricity price. This study presented four cases to verify the performance of the hybrid model, and the dataset from New South Wales of Australia and French were adopted to illustrate the excellence of the hybrid model. The results show that the proposed model can significantly improve the prediction accuracy.

Md. Nazmul Hasan, Rafia Nishat Toma, A. Nahid et al.

Among an electricity provider’s non-technical losses, electricity theft has the most severe and dangerous effects. Fraudulent electricity consumption decreases the supply quality, increases generation load, causes legitimate consumers to pay excessive electricity bills, and affects the overall economy. The adaptation of smart grids can significantly reduce this loss through data analysis techniques. The smart grid infrastructure generates a massive amount of data, including the power consumption of individual users. Utilizing this data, machine learning and deep learning techniques can accurately identify electricity theft users. In this paper, an electricity theft detection system is proposed based on a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) architecture. CNN is a widely used technique that automates feature extraction and the classification process. Since the power consumption signature is time-series data, we were led to build a CNN-based LSTM (CNN-LSTM) model for smart grid data classification. In this work, a novel data pre-processing algorithm was also implemented to compute the missing instances in the dataset, based on the local values relative to the missing data point. Furthermore, in this dataset, the count of electricity theft users was relatively low, which could have made the model inefficient at identifying theft users. This class imbalance scenario was addressed through synthetic data generation. Finally, the results obtained indicate the proposed scheme can classify both the majority class (normal users) and the minority class (electricity theft users) with good accuracy.

Moussa P. Blimpo, M. Cosgrove-Davies

Access to reliable electricity is a prerequisite for the economic transformation of economies in Sub-Saharan Africa (SSA), especially in a digital age. Yet the electricity access rate in the region is often substantially low, households and businesses with access often face unreliable service, and the cost of the service is often among the highest in the world. This situation imposes substantial constraints on economic activities, provision of public services, adoption of new technologies, and quality of life. Much of the focus on how to best provide reliable, affordable, and sustainable electricity service to all has been on mitigating supply-side constraints. However, demand-side constraints may be as important, if not more important. On the supply side, inadequate investments in maintenance result in high technical losses; most state-owned utilities operate at a loss; and power trade, which could significantly lower the cost of electricity, is underdeveloped. On the demand side, the uptake and willingness to pay are often low in many communities, and the consumption levels of those who are connected are limited. Increased uptake and consumption of electricity will encourage investment to improve service reliability and close the access gap. Electricity Access in Sub-Saharan Africa shows that the fundamental problem is poverty and lack of economic opportunities rather than power. The solution lies in understanding that the overarching reasons for the unrealized potential involve tightly intertwined technical, financial, political, and geographic factors. The ultimate goal is to enable households and businesses to gain access to electricity and afford its use, and utilities to recover their cost and make profits. The report makes the case that policy makers need to adopt a more comprehensive and long-term approach to electrification in the region—one centered on the productive use of electricity at affordable rates. Such an approach includes increased public and private investment in infrastructure, expanded access to credit for new businesses, improved access to markets, and additional skills development to translate the potential of expanded and reliable electricity access into substantial economic impact. Enhancing the economic capabilities of communities is the best way to achieve faster and more sustainable development progress while addressing the broad challenges of affordability, low consumption, and financial viability of utilities, as well as ensuring equitable provision between urban and rural areas.

A. Abu-Rayash, I. Dincer

This paper investigates the impact of COVID-19 and the global pandemic on the energy sector dynamics. Hourly electricity demand data was collected and analyzed for the province of Ontario. It is evident that health-related pandemics have a detrimental and direct influence on the concept of the smart city. This is manifested through various social, economic, environmental, technological and energy-related changes. The overall electricity demand of the province for the month of April of this year amidst pandemic conditions declined by 14%, totaling 1267 GW. A unique trend of reciprocating energy demand exists throughout the week. The post-COVID-19 indicates higher energy demand in the earlier part of the week and a lower demand in the latter part of the week. Pre-pandemic, the days of highest electricity demand were in the latter part of the work week (Wed-Fri) in addition to the weekend. Post-pandemic, the highest electricity demand occurred in the earlier part of the week (Mon-Tue). Hourly electricity demand shows a clear curve flattening during the pandemic, especially during peak hours of 7–11 in the morning and 5–7 in the evening, resulting in significant demand reductions during these periods. Lastly, due to COVID-19, GHG emission reductions of 40,000 tonnes of CO2e were achieved along with savings of $131,844 for the month of April.

S. Sarkodie, S. Adams

Abstract Consistent with the Sustainable Development Goal 7 of ensuring access to clean and modern energy technologies, this study examined the nexus between access to electricity, human development index, political system environment, income level, and income inequality. We employed a nonparametric regression technique with Driscoll–Kraay standard errors from 1990 to 2017 in Sub-Saharan Africa. The study revealed that income inequality has a negative effect on access to electricity whereas income level and human development have a positive impact on access to electricity. Enhancing the political system environment in Sub-Saharan Africa is crucial to ensuring access to clean and modern electricity. The negative effect of political system on income inequality means that good governance environment reduces income inequality. Income inequality is found to reduce human development, as such, social protection policies that reduce poverty are essential to minimize the vulnerability to poverty. The study highlights that the effective promotion of labor markets and the improvement of socio-economic capacity to manage unemployment, infirmity, and disability will decrease income inequality, hence, promote human development.

Fateh Bélaïd, M. Zrelli

In this article, we develop an empirical model to investigate the causal link amid renewable and non-renewable electricity consumption, GDP and carbon emissions by using a panel of 9 Mediterranean countries over the period 1980–2014. Using the PMG panel ARDL and panel econometric technics, heterogeneity and cross-sectional dependence among the panel were considered to explore the long and short-run dynamic relationships as well as the validity of a proposed model. The results provide panel empirical evidence that there is short-term bidirectional causality between GDP, renewable electricity consumption and CO2 emissions and between non-renewable electricity consumption, GDP and renewable electricity consumption. For the long-term causal relationship, the result indicates that there is bidirectional causality between non-renewable electricity consumption and CO2 emissions. However, there is evidence of unidirectional causal relationships from GDP to CO2 emissions and non-renewable electricity consumption and from renewable electricity consumption to CO2 emissions. The findings imply that non-renewable electricity consumption and economic growth stimulate CO2 emissions in southern and northern Mediterranean countries, while renewable electricity reduces them. This empirical evidence suggests that expansion of renewable energy sources is a viable strategy for addressing energy security and reducing carbon emissions to protect the environment for future generations.

Fengji Luo, Z. Dong, Gaoqi Liang et al.

The prevalence of distributed energy resources encourages the concept of an electricity “Prosumer (Producer and Consumer)”. This paper proposes a distributed electricity trading system to facilitate the peer-to-peer electricity sharing among prosumers. The proposed system includes two layers. In the first layer, a multi-agent system is designed to support the prosumer network, and an agent coalition mechanism is proposed to enable the prosumers to form coalitions and negotiate electricity trading. In the second layer, a Blockchain based transaction settlement mechanism is proposed to enable the trusted and secure settlement of electricity trading transactions formed in the first layer. Simulations are conducted based on the java agent development environment to validate the proposed electricity trading process.

Zhuoyi Li, Xu Ma, Danke Chen et al.

Though evaporation‐driven electricity generation has emerged as a novel eco‐friendly energy and attracted intense interests, it is typically demonstrated in pure water or a very low salt concentration. Integrating evaporation‐driven electricity generation and solar steam desalination simultaneously should be more promising. Herein, a polyaniline coated metal‐organic frameworks (MOFs) nanorod arrays membrane is synthesized which inherits the merits of both polyaniline and MOFs, demonstrating nice stability, good interfacial solar steam desalination, and evaporation‐driven electricity generation. Moreover, an integrated system based on this hybrid membrane achieves good interfacial solar‐heating evaporation and prominently enhanced evaporation‐driven electricity generation under one sun. Notably, the realization of effective seawater desalination and efficient evaporation‐driven electricity generation simultaneously by the non‐carbon‐based materials is reported for the first time, which provides a new alternative way for cogenerating both freshwater and electricity by harvesting energy from seawater and solar light.

Pishdar Mahsa

Transition to renewable electricity faces diverse challenges, the systemic interdependencies of which are still underexplored. This study applies a Pythagorean Fuzzy Cognitive Map (PFCM) to analyze and prioritize challenges of transitioning to the electricity sustainability across five dimensions of economic, technological, policy, social, and geopolitical. The analysis is based on experts’ opinions from Iran’s energy domain. Results indicate that geopolitical constraints such as sanctions and water scarcity, and social challenges like public acceptance and skills gaps are more influential than conventional economic and technological challenges. The analysis reveals that sanctions (C51) and water stress (C52) have cascading effects, disrupting financing (C11), technology imports (C21–C22), and governance coherence (C31–C33). Meanwhile, low public trust (C41) and fossil fuel subsidies (C13) emerge as secondary but pivotal bottlenecks. The study shows that economic or infrastructural improvement alone cannot drive transition. Instead, it argues that geopolitical solutions such as sanctions relief and social preparedness are prerequisites for starting progress in other domains. These findings suggest that policymakers should prioritize diplomatic engagement and social-centric energy campaigns alongside technical investments.

Christian Truitt Lüddeke, Birger Hagemann, Leonhard Ganzer

The energy transition is a long-term strategy dedicated to achieving carbon neutrality in Germany by 2045. This process includes the development of renewably generated electricity from wind and solar power. As these energy sources are dependent on weather conditions, imbalances in availability and demand might result in a deficit or excess of renewable energy. In times of excessive availability, hydrogen can be generated and stored in subsurface storage sites from which it can be withdrawn when the demand increases. Using subsurface storage sites is a viable option as those currently store natural gas. Considering the properties of hydrogen, converting existing storage sites poses many challenges, including the total stored energy content and the amount of extractable working gas. Using an exemplary storage formation, a numerical simulation model is set up in an open-source software and used to calculate and compare the stored volumes and energy contents for natural gas and hydrogen. Storage withdrawal and pressure profiles for both cases are developed. A pseudo gas is defined with individually alternating compressibility, density and viscosity behavior to independently assess the influence of these properties on the withdrawal rates. A sensitivity analysis of various storage, bottom-hole flowing pressures and the skin factor on the extraction rates is also performed. The results show that a larger volume of natural gas and a resulting higher energy content can be stored in the storage site compared to hydrogen. Changes in extraction rates occur earlier and pressure decrease is greater for stored hydrogen. The compressibility factor has the largest influence on the extraction behavior of the gas, leading to a steeper decline in hydrogen withdrawal rates and a quicker pressure depletion. The levels of the storage and the bottom-hole flowing pressure impact the slope of the decline and the level of withdrawal rates.