Bibliografie tematiche / Electric power consumption – united states – forecasting

Letteratura scientifica selezionata sul tema "Electric power consumption – united states – forecasting"

Autore: Grafiati

Pubblicato: 27 luglio 2024

Ultima modifica: 29 luglio 2024

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Articoli di riviste sul tema "Electric power consumption – united states – forecasting"

Ma, Xin, Yubin Cai, Hong Yuan e Yanqiao Deng. "Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States". Sustainability 15, n. 9 (23 aprile 2023): 7086. http://dx.doi.org/10.3390/su15097086.

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Energy forecasting based on univariate time series has long been a challenge in energy engineering and has become one of the most popular tasks in data analytics. In order to take advantage of the characteristics of observed data, a partially linear model is proposed based on principal component analysis and support vector machine methods. The principal linear components of the input with lower dimensions are used as the linear part, while the nonlinear part is expressed by the kernel function. The primal-dual method is used to construct the convex optimization problem for the proposed model, and the sequential minimization optimization algorithm is used to train the model with global convergence. The univariate forecasting scheme is designed to forecast the primary energy consumption of the electric power sector of the United States using real-world data sets ranging from January 1973 to January 2020, and the model is compared with eight commonly used machine learning models as well as the linear auto-regressive model. Comprehensive comparisons with multiple evaluation criteria (including 19 metrics) show that the proposed model outperforms all other models in all scenarios of mid-/long-term forecasting, indicating its high potential in primary energy consumption forecasting.

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Meng, Ming, Lixue Wang e Qu Chen. "Quota Allocation for Carbon Emissions in China′s Electric Power Industry Based Upon the Fairness Principle". Energies 11, n. 9 (27 agosto 2018): 2256. http://dx.doi.org/10.3390/en11092256.

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As an essential measure to mitigate the CO2 emissions, China is constructing a nationwide carbon emission trading (CET) market. The electric power industry is the first sector that will be introduced into this market, but the quota allocation scheme, as the key foundation of market transactions, is still undetermined. This research employed the gross domestic product (GDP), energy consumption, and electric generation data of 30 provinces from 2001 to 2015, a hybrid trend forecasting model, and a three-indicator allocation model to measure the provincial quota allocation for carbon emissions in China′s electric power sector. The conclusions drawn from the empirical analysis can be summarized as follows: (1) The carbon emission peak in China′s electric power sector will appear in 2027, and peak emissions will be 3.63 billion tons, which will surpass the total carbon emissions of the European Union (EU) and approximately equal to 2/3 of the United States of America (USA). (2) The developed provinces that are supported by traditional industries should take more responsibility for carbon mitigation. (3) Nine provinces are expected to be the buyers in the CET market. These provinces are mostly located in eastern China, and account for approximately 63.65% of China′s carbon emissions generated by the electric power sector. (4) The long-distance electric power transmission shifts the carbon emissions and then has an impact on the quotas allocation for carbon emissions. (5) The development and effective utilization of clean power generation will play a positive role for carbon mitigation in China′s electric sector.

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Manigandan, Palanisamy, MD Shabbir Alam, Majed Alharthi, Uzma Khan, Kuppusamy Alagirisamy, Duraisamy Pachiyappan e Abdul Rehman. "Forecasting Natural Gas Production and Consumption in United States-Evidence from SARIMA and SARIMAX Models". Energies 14, n. 19 (22 settembre 2021): 6021. http://dx.doi.org/10.3390/en14196021.

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Research on forecasting the seasonality and growth trend of natural gas (NG) production and consumption will help organize an analysis base for NG inspection and development, social issues, and allow industrials elements to operate effectively and reduce economic issues. In this situation, we handle a comparison structure on the application of different models in monthly NG production and consumption forecasting using the cross-correlation function and then analyze the association between exogenous variables. Moreover, the SARIMA-X model is tested for US monthly NG production and consumption prediction via the proposed method for the first time in the literature review in this study. The performance of that model has been compared with SARIMA (p, d, q) * (P, D, Q)s. The results from RMSE and MAPE indicate that the superiority of the best model. By applying this method, the US monthly NG production and consumption is forecast until 2025. The success of the proposed method allows the use of seasonality patterns. If this seasonal approach continues, the United States’ NG production (16%) and consumption (24%) are expected to increase by 2025. The results of this study provide effective information for decision-makers on NG production and consumption to be credible and to determine energy planning and future sustainable energy policies.

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Dounis. "Special Issue “Intelligent Control in Energy Systems”". Energies 12, n. 15 (5 agosto 2019): 3017. http://dx.doi.org/10.3390/en12153017.

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The editor of this special issue on “Intelligent Control in Energy Systems” have made an attempt to publish a book containing original technical articles addressing various elements of intelligent control in energy systems. The response to our call had 60 submissions, of which 27 were published submissions and 33 were rejections. This book contains 27 technical articles and one editorial. All have been written by authors from 15 countries (China, Netherlands, Spain, Tunisia, United States of America, Korea, Brazil, Egypt, Denmark, Indonesia, Oman, Canada, Algeria, Mexico, and Czech Republic), which elaborated several aspects of intelligent control in energy systems. It covers a broad range of topics including fuzzy PID in automotive fuel cell and MPPT tracking, neural network for fuel cell control and dynamic optimization of energy management, adaptive control on power systems, hierarchical Petri Nets in microgrid management, model predictive control for electric vehicle battery and frequency regulation in HVAC systems, deep learning for power consumption forecasting, decision tree for wind systems, risk analysis for demand side management, finite state automata for HVAC control, robust μ-synthesis for microgrid, and neuro-fuzzy systems in energy storage.

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Hamza, Sakar Hasan, e Qingna Li. "The Dynamics of US Gasoline Demand and Its Prediction: An Extended Dynamic Model Averaging Approach". Energies 16, n. 12 (19 giugno 2023): 4795. http://dx.doi.org/10.3390/en16124795.

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This study contributes to the body of literature on modeling and predicting gasoline demand by using nonlinear econometric techniques. For this purpose, dynamic model averaging (DMA) and Bayesian model averaging (BMA) combined with Artificial Bee Colony (ABC) are used to forecast gasoline consumption in the United States. The article’s independent variables include demographic characteristics, economic activity, income, driving expenditures, automobile price, and road availability for annual data from 1960 to 2020. In the proposed model, not only may the coefficients and elasticity of a predictor of gasoline demand change over time, but other sets of predictors can also emerge at different periods. Moreover, this study aims to automate the process of picking two forgotten variables of the DMA model using the ABC model. Our findings indicate that dynamic model averaging significantly improves forecasting performance when compared to basic benchmark techniques and advanced approaches. Additionally, integrating it with an Artificial Bee Colony (ABC) may result in improved outcomes when time-varying forgetting variables are present. The findings of this research provide policymakers in the fields of energy economics and the environment with helpful tools and information.

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Cai, Yubin, Xin Ma, Wenqing Wu e Yanqiao Deng. "Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model". Mathematical Problems in Engineering 2021 (11 novembre 2021): 1–11. http://dx.doi.org/10.1155/2021/5541650.

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Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.

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Drews, Elizabeth, Cedric Ireland e Neil Yallabandi. "Addressing Wind Power Intermittency in the Ercot and SPP Regions". Texas A&M Journal of Property Law 1, n. 3 (marzo 2014): 365–90. http://dx.doi.org/10.37419/jpl.v1.i3.2.

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This Article explores efforts to address challenges involving wind power intermittency in two United States power regions: the South- west Power Pool (“SPP”) and the Electric Reliability Council of Texas (“ERCOT”). SPP and ERCOT are good case studies regarding these issues because each has among the strongest wind resources in the country, most of which are in isolated, sparsely populated areas and need long transmission lines to reach major load (electricity consumption) centers. Those circumstances increase the challenge of integrating intermittent wind generation into the electric system (grid).

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Prodjinotho, Ulrich, Patrice Chetangny, Macaire Agbomahena, Victor Zogbochi, Laurent Medewou, Gerald Barbier e Didier Chamagne. "Long Term Forecasting of Peak Demand and Annual Electricity Consumption of the West African Power Pool Interconnected Network by 2032". International Journal of Energy and Power Engineering 13, n. 2 (2 aprile 2024): 21–31. http://dx.doi.org/10.11648/j.ijepe.20241302.11.

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The uneven distribution of primary sources of electric power generation in Economic Community of West African States (ECOWAS) compelled the heads of states to create the West African Power Pool (WAPP). The vision of this system is to set up a common electrical energy market to satisfy the balance between supply and demand at an affordable price using the interconnected network. Forecasting maximum power demand and energy consumption is essential for planning and the coordination of new power plant and transmission lines building. This work consists of predicting maximum power demand and total energy that must transit through the WAPP interconnected network by the year 2032. We compare the performances of three time series models namely the Long Short-Term Memory (LSTM), Auto-Regressive Integrated Moving Average (ARIMA) and Fb Facebook Prophet. Electric power and energy data used for training the systems comes from the WAPP authorties. The results show that, for monthly peaks, the Facebook (Fb) Prophet model is the best, with a MAPE (mean absolute error percentage) of 3.1% and a low RMSE (root mean square error) of 1.225 GW. For energy prediction, ARIMA performances are the best compared to others with (RMSE 1.20 TWh, MAPE 1.00%). Thus, the forecast for total annual energy consumption and annual peak demand will be, respectively, 96.85TWh and 13.6 GW in 2032.

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Oyinbo, Oyakhilomen, Grace ZibahRekwot e Hassan OnipeSaliu. "Assessment of the suitability of grafted model in forecasting rice consumption trend in nigeria." Journal of Management and Science 1, n. 1 (30 giugno 2013): 114–18. http://dx.doi.org/10.26524/jms.2013.15.

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This paper was designed to examine the predictive power of grafted polynomial functional form in forecasting rice consumption in Nigeria with a linear model used as bench mark. Data on rice consumption trend in Nigeria from 1961 to 2011 elicited from the United States department of Agriculture foreign Agricultural services were utilized in this study. It was observed that rice consumption did not correlate linearly with trend over the entire sample period and this necessitatedthe grafting of a Linear – Quadratic – Linear model. The ex-post forecasts of the grafted model had lesser forecast error and were closer to the observed values than that of the linear model which had greater forecast error. Therefore, the predictive performance of the grafted model is more reliable in forecasting future trend of rice consumption in Nigeria for planning purposes.

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Chen, Xinbo, Jian Zhong, Feng Sha e Zaimin Zhong. "Research on innovative plug-in hybrid electric vehicle comprehensive energy consumption evaluation method based on statistic energy consumption". Science Progress 104, n. 4 (ottobre 2021): 003685042110502. http://dx.doi.org/10.1177/00368504211050284.

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The plug-in hybrid electric vehicle not only has the advantages of low emissions from electric vehicles, but also takes advantage of the high specific energy and high specific power of petroleum fuels, which can significantly improve the emissions and fuel economy of traditional vehicles. Studying its comprehensive energy consumption evaluation method is an important part of analyzing the economics of plug-in hybrid electric vehicles. This paper first puts forward the concept of statistical energy consumption and then proposes an innovative calculation method of plug-in hybrid electric vehicle energy consumption based on statistical energy consumption by referring to and analyzing the energy consumption test regulations of the United States, the European Union, and China. Given the two use case assumptions of charge depleting mode priority and charge sustaining mode only, considering the fuel consumption and the energy consumption that converts electrical energy consumption to fuel consumption, the probability density function of travel mileage distribution and energy consumption is derived. Finally, the interpretation and analysis of statistical energy consumption evaluation results are carried out.

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Più fonti

Tesi sul tema "Electric power consumption – united states – forecasting"

Sapp, James Christopher. "Electricity Demand Forecasting in a Changing Regional Context: The Application of the Multiple Perspective Concept to the Prediction Process". PDXScholar, 1987. https://pdxscholar.library.pdx.edu/open_access_etds/574.

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In 1982, the Bonneville Power Administration (BPA), a marketer of hydroelectric power in the Pacific Northwest, found itself in a new role which required it to acquire power resources needed to meet the demands of the region's utilities. In particular, it had to deal with the Washington Public Power Supply System's nuclear plant cost escalations. In response, BPA prepared its first independent regional power forecast. The forecast development process was intricate and multidimensional and involved a variety of interested parties. Application of the Multiple Perspective Concept uncovers strengths and weaknesses in this process by illuminating its technical, organizational and personal dimensions. Examination of the forecast from the technical perspective revealed an elaborate set of interlinked models used to develop baseline, high, and low forecasts. The organizational perspective revealed BPA to be in a transitional stage. Internally, ratemaking, forecasting, conservation, resource acquisition, and financial management swelled as new organizational functions. Interorganizationally, environmentalists, ratepayer groups, and the region's utilities all had strong interests in the decision regarding WPPSS plants. The personal perspective revealed that each of the Administrators heading BPA since the early 1980s defined the agency's approach to the resource planning problem differently, first as an engineering problem, then as a political problem, and, finally, as a business problem. Taken together, the Multiple Perspectives yielded the following conclusions about BPA's 1982 forecast. (1) BPA's range forecast constituted a major improvement over the point forecasts preceding it, but left important classes of uncertainty unexplored. (2) BPA's models were better suited to address rate and conservation issues important at the time of the 1982 forecast than their predecessors. The model of the national economy, however, remained a black box, potentially significant feedbacks were not represented, and the sheer size of the modeling system placed practical limits on its use. (3) A stronger method of dealing with forecast uncertainty is needed which utilizes a disaster-avoidance strategy and plans for high impact/low probability events. This method need not involve the use of large models, but should incorporate qualitative insights from persons normally outside the technical sphere.

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Contreras, Sergio. "Regional electricity demand in the United States". To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Libri sul tema "Electric power consumption – united states – forecasting"

M, Bolet Adela, e Georgetown University. Center for Strategic and International Studies., a cura di. Forecasting U.S. electricity demand: Trends and methodologies. Boulder: Westview Press, 1985.

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Resources, United States Congress Senate Committee on Energy and Natural. Electric power: potential for shortages in the 1990's: Hearings before the Committee on Energy and Natural Resources, United States Senate, Ninety-ninth Congress, first session, on the potential for serious regional shortages of electric power in the United States by the early 1990's. July 23 and 25, 1985. Washington: U.S. G.P.O., 1985.

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United States. Congress. Senate. Committee on Energy and Natural Resources. Electric power: Potential for shortages in the 1990's : hearings before the Committee on Energy and Natural Resources, United States Senate, Ninety-ninth Congress, first session ... July 23 and 25, 1985. Washington: U.S. G.P.O., 1985.

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United States. Congress. Senate. Committee on Energy and Natural Resources. U.S. electricity supply and demand--the northeastern region: Hearing before the Committee on Energy and Natural Resources, United States Senate, One Hundred First Congress, first session ... April 13, 1989. Washington: U.S. G.P.O., 1989.

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Resources, United States Congress Senate Committee on Energy and Natural. U.S. electricity supply and demand--the northeastern region: Hearing before the Committee on Energy and Natural Resources, United States Senate, One Hundred First Congress, first session ... April 13, 1989. Washington: U.S. G.P.O., 1989.

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Atti di convegni sul tema "Electric power consumption – united states – forecasting"

Nguyen, Thanh-Lam, Ying-Fang Huang, Ming-Hung Shu e Bi-Min Hsu. "Forecasting model for the solar photovoltaics consumption in United States of America". In 2012 10th International Power & Energy Conference (IPEC). IEEE, 2012. http://dx.doi.org/10.1109/asscc.2012.6523279.

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Buonamici, Gianfranco. "Hybrid Electric Drive Systems in the United States Navy". In ASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gt2021-03523.

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Abstract With an increasing instability and cost fluctuation in the world energy markets, it has become more important to increase the US Navy fleet’s overall fuel efficiency. The Navy’s Energy Program for Security and Independence sets forth goals to reduce its overall consumption of energy and decrease its reliance on petroleum. One way that helps accomplish these goals is through the use of hybrid electric drive systems to replace gas turbine engines to accomplish lower ship speeds. Although gas turbines are power dense and fairly efficient at full load, their fuel efficiency decreases drastically at the lower power levels used when slower speeds are required to accomplish the ship’s mission. It is in this lower speed range where operating gas turbine generators closer to their optimum efficiency levels and powering an electric motor saves a significant amount of fuel. This paper will discuss two in-service systems developed for various US Navy ships: the Hybrid Electric Drive (HED) system for DDG 103 and the Auxiliary Propulsion System (APS) for LHD 8 and LHA 7. It will describe each of the two configurations and their histories, how they are implemented and increase the capability of the ship, and the resulting fuel efficiencies that have been realized with their use.

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Lezhniuk, Petro D., e Kateryna O. Povstianko. "Operational management of the balance of power and electric energy in the electrical power system with renewable energy sources". In 16th IC Measurement and Control in Complex Systems. Vinnytsia: VNTU, 2022. http://dx.doi.org/10.31649/mccs2022.12.

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This work demonstrates the effects of the active use of renewable energy sources (RES) in the unified energy system (UES) of Ukraine, in particular, maintaining the balance in the network for its reliable and high-quality operation. In the energy strategy for the development of renewable energy sources in Ukraine until 2035, a rapid increase of the installed RES capacity is planned, i.e. the task of maintaining balance sheet reliability in the conditions of an increase in the share of RES in the UES of Ukraine is quite urgent. Forecasting of the electricity balance is based on the generation forecast, electricity consumption in a given period of time, as well as fuel reserves and the volume of generating capacity reserves. Renewable energy sources have a non-uniform nature of generation, and therefore endanger aspects of balance reliability. This problem is key for Ukraine in light of the integration of Ukraine's energy system into the European ENTSO-E network. As a result of the conducted research, it can be stated that the improvement of the situation is possible only with an integrated approach and the implementation of appropriate technologies, namely: technical, economic and institutional technologies. The introduction of technologies will make it possible to improve monitoring and management of energy systems; economic implementations will contribute to the reform of retail pricing and taxation of electricity supplies, taking into account the payment they supply for electricity and covering part of the cost of the general infrastructure; institutional innovations will change the functions and responsibilities of management subjects. Improving coordination between transmission and distribution network operators will become a priority.

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Barrett, Jasmine, Alexis Gyselinck e Gopal Singh. "The Journey to Carbon Neutrality: A Case Study Through China and the United States". In ASME Power Applied R&D 2023. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/power2023-117882.

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Abstract There is no doubt that the world is in the midst of an energy crisis. The volatile political landscape and globally increasing CO2 emissions demand that every country consolidate its resources in search of clean and reliable energy. China is no stranger to this crisis as the country has pledged to be carbon neutral by 2060. Leading the world in CO2 emissions, energy demand, coal consumption, and fossil fuel imports, China’s reliance on coal and other polluting energy sources seems to be the backbone of its very society. Moving away from these established practices will take time, investment, and focus. Despite promising to peak carbon emissions in the next 20 years, their emissions and energy use patterns continue to trend upwards. The country is already responsible for a quarter of the world’s CO2 emissions, yet it continues to build new coal-based power plants at a greater pace than the combined rest of the world. As the world’s leading manufacturer of solar panels and electric vehicles, its development of the renewable energy sector is indeed substantial. However, it must be considered whether this progress will impact the country on a large enough scale to combat their current energy trends. So the question remains: how will China combat its CO2 emissions and take the necessary steps toward clean energy in order to fulfill its ambitious promises? This paper will introduce the physical, social, and economic environment of China and discuss its current uses of energy. Second, it will compare and contrast the energy profiles of China and the United States. Lastly, the paper will discuss the progress of China in recent years and introduce several recommendations for actions that can be taken to combat carbon emissions on its journey toward clean energy and carbon neutrality.

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Carter, Thomas P., James W. Furlong, Sean P. Bushart e Jessica Shi. "Power Plant Heat Rejection System Modeling and Comparison". In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64446.

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As noted in a Summer 2007 EPRI Journal article entitled Running Dry At The Power Plant, “Securing sufficient supplies of fresh water for societal, industrial, and agricultural uses while protecting the natural environment is becoming increasingly difficult in many parts of the United States. Climate variability and change may exacerbate the situation through hotter weather and disrupted precipitation patterns that promote regional drought.” [1] Currently, in the United States, thermoelectric power production accounts for approximately 41% of freshwater withdrawals [2] and 3% of overall fresh water consumption. [3] The Electric Power Research Institute, EPRI, as part of its Technology Innovation (TI) program, is collaborating with Johnson Controls to conduct a feasibility study comparing the performance of a water saving Thermosyphon Cooling Hybrid System (TCHS) with other heat rejection systems for power plant applications. The TCHS employs a sensible heat rejection device, a thermosyphon cooler (TSC) in conjunction with an evaporative heat rejection device, an open cooling tower, to satisfy the annual cooling requirements of a given power plant. By reducing the evaporative heat load, the TCHS can significantly reduce the annual water consumed for cooling while still maintaining peak power plant output on the hottest summer days. Details of the interactive simulation program developed to compare various power plant heat rejection systems on an annual 8,760 hourly basis are discussed. Examples of the types of results and comparisons that can be made from the data obtained from the simulation program are presented.

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Barnes, William. "When East Meets West: New Technology From Romania Reduces Fuel Consumption and Emissions With Virtually No Capital Costs". In ASME 2006 Power Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/power2006-88223.

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Wouldn’t it be nice to have plug and play technology for your boilers just like on your home computer? Wouldn’t it be great if this technology could give you instant and measurable reductions of 5 percent or more in fuel consumption? Well, in the modern era, this technology has arrived. A small Romanian company has developed a technology that treats combustion air that significantly increases fuel efficiency and lowers emissions on furnaces and boilers by interacting with the fuel at the combustion stage. This technology has the potential to reduce emissions of CO2 by 2–20%, NOx by 5–30%, SOx by 20–60% and emissions that negatively affect human health like acid mists (SO3), dioxins, benzenes, and VOC by as much as 90%. With over a million hours of testing on over 100 boilers and furnaces this economical technology holds great promise. The best part of the technology is that there is limited capital investment or operational costs, and use of the specialty aerosol injection will reduce wear and corrosion in your combustion box regardless of the fuel burned. It reduces costs across the board. Avogadro Environmental Corporation in Easton, PA is working with our partners, Opris Engineering and Kubik in Romania to make this technology available in the United States. The technology has a long proven record of performance and has been fully tested in the U.S. for efficiency improvements and emissions reductions. The technology has received the support of USEPA and state agencies. We are looking for plant operators interested in reducing their emissions and at the same time saving 5–25% in operating and maintenance costs. We just completed two full scale tests of the technology here in the US. The first site was a 90-day test at a 450 MMBtu/hr waste coal-fired electric utility boiler in Pennsylvania. The second site was a 60-day test at a 1,500 MMBtu/hr coal-fired electric utility boiler in the Southeast US.

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Carter, Thomas P., James W. Furlong, Sean P. Bushart e Jessica Shi. "Thermosyphon Cooler Hybrid System for Water Saving Power Plant Heat Rejection". In ASME 2013 Power Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/power2013-98206.

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As noted in a Summer 2007 EPRI Journal article entitled Running Dry At The Power Plant, “Securing sufficient supplies of fresh water for societal, industrial, and agricultural uses while protecting the natural environment is becoming increasingly difficult in many parts of the United States. Climate variability and change may exacerbate the situation through hotter weather and disrupted precipitation patterns that promote regional drought.” Currently, in the United States, thermoelectric power production accounts for approximately 39% of freshwater withdrawals and 3% of overall fresh water consumption. The Electric Power Research Institute, EPRI, as part of its Technology Innovation (TI) program, is collaborating with Johnson Controls to conduct a feasibility study comparing the performance of a water saving Thermosyphon Cooler Hybrid System (TCHS) with other heat rejection systems for power plant applications. The TCHS employs a sensible heat rejection device, a thermosyphon cooler (TSC) in conjunction with an evaporative heat rejection device, an open cooling tower, to satisfy the annual cooling requirements of a given power plant. By reducing the evaporative heat load, the TCHS can significantly reduce the annual water consumed for cooling while still maintaining peak power plant output on the hottest summer days. Operational details of the Thermosyphon Cooler Hybrid System are presented. Additionally an overview of the cooling system simulation program, based on an 8,760 hourly analysis, used in the feasibility study is discussed. Results comparing the water use and additional fan power requirements between power plants employing a traditional all evaporative system and the TCHS are discussed for two different climatic locations. The concept of incorporating the cost of water, cost of power, the current plant operating conditions, and the current ambient dry bulb temperature into the TSC fan control strategy are also explored. The simulation program performance model is currently being validated with testing of a 1MW prototype TCHS at the Water Research Center near Cartersville, GA. Finally, a conceptual design for a power plant scale TCHS is presented.

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Dranuta, Diego, e Derek Johnson. "Analysis on Combined Heat and Power and Combined Heat and Power Hybrid Systems for Unconventional Drilling Operations". In ASME 2021 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/icef2021-67492.

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Abstract The United States (U.S.) has experienced a natural gas “boom” due to the development of unconventional shale plays, but well development is energy intensive. Operations use electric drilling rigs typically powered by either three high-horsepower diesel engines (HHPDE) or three dedicated natural gas engines (DNGE) and associated generators. From a first law analysis, HHPDEs peak at about 42% efficient at full load, while DNGE peak at about 30%. Most fuel energy is lost as heat rejected by the exhaust and radiators. Concurrently, during cold seasonsor or in cold regions rigs utilize boilers to provide steam throughout the rig to prevent freezing and provide comfort. Our analysis focused on a combined heat power (CHP) approach to improve the utilization factor (UF) of fossil energy consumed during unconventional drilling operations. Engine activity, boiler fuel consumption, and exhaust gas temperatures were recorded during winter drilling of an entire well in the Marcellus shale. Four characteristic activity cycles were extracted from recorded activity to represent four energy consumption scenarios. Exhaust and jacket water heat exchangers (E-HEX, JW-HEX) were designed and simulated, and results were analyzed in 0-D models for the four case scenarios. A 584-kWh hybrid energy management system (HEMS) was also designed and simulated into the model as another method to reduce fossil energy fuel consumption during well development. HHPDE UF improved on average from 35.7% to 55.7% if only E-HEX were used and improved to 72.7% if JW-HEX were also used. DNGE average UF increased from 19.0% to 34.9% using E-HEX only. HEMS utilization improved UF up to an average of 76.9% and 39.1% for HHPDE CHP and DNGE CHP systems, respectively.

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Twomey, Kelly M., Susan Conover e Michael E. Webber. "Reducing Residential and Commercial Energy Consumption in the US: The Role of Water Heaters". In ASME 2012 6th International Conference on Energy Sustainability collocated with the ASME 2012 10th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/es2012-91209.

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Residential and commercial water heating in the United States consumed nearly 3,700 trillion British Thermal Units (BTUs) of primary energy in 2010. Nearly half of this primary energy was lost as waste heat at the point of power generation to provide electricity for electric water heaters. In the residential sector alone, water heating accounted for 17% of total 2010 on-site energy, use or about 1,960 trillion BTUs. Of this amount, about 22%, or 440 trillion BTUs, was consumed by residential electric water heaters. However, 1,380 trillion BTUs of primary energy was required to produce this retail electric power at the power station, indicating that electricity generation is much less efficient than directly burning fuels for water heating. This study analyzes 2010 baseline primary energy consumption for water heating in the US by considering energy conversions and end-use efficiencies in the residential and commercial sectors. In order to assess more energy and carbon-efficient means of heating water, we defined four additional scenarios in order to quantify potential energy savings by replacing electric water heaters with more efficient, commercially available technologies. The scenarios ranged in scope and technology deployment, and resulted in energy savings of 10–25% and carbon dioxide emission reductions of 10–20%. Although future deployment of water heating technologies is not likely to replicate any specific scenario, the conclusions drawn from this study are useful in guiding policy incentives and consumer behavior in regards to choosing between water heating technologies.

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Kialashaki, Arash, e John Reisel. "Transport Energy Demand Modeling of the United States Using Artificial Neural Networks and Multiple Linear Regressions". In ASME 2014 8th International Conference on Energy Sustainability collocated with the ASME 2014 12th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/es2014-6447.

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In 2009, the transportation sector was the second largest consumer of primary energy in the United States, following the electric power sector and followed by the industrial, residential, and commercial sectors. The pattern of energy use varies by sector. For example, petroleum provides 96% of the energy used for transportation but its share is much less in other sectors. While the United States consumes vast quantities of energy, it has also pledged to cut its greenhouse gas emissions by 2050. In order to assist in planning for future energy needs, the purpose of this study is to develop a model for transport energy demand that incorporates past trends. This paper describes the development of two types of transportation energy models which are able to predict the United States’ future transportation energy-demand. One model uses an artificial neural network technique (a feed-forward multilayer perceptron neural network coupled with back-propagation technique), and the other model uses a multiple linear regression technique. Various independent variables (including GDP, population, oil price, and number of vehicles) are tested. The future transport energy demand can then be forecast based on the application of the growth rate of effective parameters on the models. The future trends of independent variables have been predicted based on the historical data from 1980 using a regression method. Using the forecast of independent variables, the energy demand has been forecasted for period of 2010 to 2030. In terms of the forecasts generated, the models show two different trends despite their performances being at the same level during the model-test period. Although, the results from the regression models show a uniform increase with different slopes corresponding to different models for energy demand in the near future, the results from ANN express no significant change in demand in same time frame. Increased sensitivity of the ANN models to the recent fluctuations caused by the economic recession may be the reason for the differences with the regression models which predict based on the total long-term trends. Although a small increase in the energy demand in the transportation sector of the United States has been predicted by the models, additional factors need to be considered regarding future energy policy. For example, the United States may choose to reduce energy consumption in order to reduce CO2 emissions and meet its national and international commitments, or large increases in fuel efficiency may reduce petroleum demand.

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Rapporti di organizzazioni sul tema "Electric power consumption – united states – forecasting"

Mai, Trieu T., Paige Jadun, Jeffrey S. Logan, Colin A. McMillan, Matteo Muratori, Daniel C. Steinberg, Laura J. Vimmerstedt, Benjamin Haley, Ryan Jones e Brent Nelson. Electrification Futures Study: Scenarios of Electric Technology Adoption and Power Consumption for the United States. Office of Scientific and Technical Information (OSTI), giugno 2018. http://dx.doi.org/10.2172/1459351.

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