检索结果-南通市图书馆

Factors Affecting electricity Demand in Jordan

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy and Power Engineering 2013年第1期5卷 50-58页

作者： Mohammad Awad Momani Electrical Power Engineering Department Hijjawi Faculty for Engineering Technology Yarmouk University Irbid Jordan

1) The paper examines the relationship between electricity demand and climate/non-climate related factors using statistical regression analysis. 2) It focuses on the environmental, demographic, policy (energy pricing) and technological factors as the main factors affecting the consumption pattern in Jordan. 3) The paper also presents the variations occurred in the electricity demand over the period 1994-2008. The variations that are observed during the period of study are: Shifting of the peak load occurrence from evening to morning period, Modification in the annual daily load curve especially in winter season, Variation in relationship between space temperature and demand especially in winter, and dramatic increase in electric generation after year 2003. The shift in peak load from evening to morning period is mainly due to technological factor as a result of wide use of the air conditions in houses, services and government offices for cooling in summer instead of ordinary air fans. The variations in consumption pattern between 2000 and 2007 are mainly associated with economic, social and demographic factors. The high demand at lower space temperature is governed by introducing new appliances for heating in winter as a result of low electricity pricing comparing with gasoline price. The dramatic increase in electric generation after 2003 is probably due to demographic factors as a result of high growth of population after the Gulf war II. 4) The correlation between the daily maximum loads in morning and evening periods with the differential temperature (ΔT) above 20?C threshold in summer and below 15?C threshold in winter, shows pronounced changes in 2007 compared with year 2000. The regression tests show that a decrease of 1?C below 15?C threshold in winter 1) increases the morning demand by only 2 MW/?C in 2000 and 16.7 MW/?C in 2007, 2) decreases the evening peak by ?2.6 MW/1?C in 2000 and increases the evening peak by 22.9 MW/1?C in 2007. Results show that the demographic, technological, environmental and n

关键词： electricity Demand Demographic Factor Tariff Ambient Temperature Jordan

Forecasting the Impact of CCGT-CCS on the UK’s electricity Market by LCOE

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy and Power Engineering 2017年第4期9卷 198-203页

作者： Tianxiang Luan Kwoklun Lo Jianfeng Lu Department of Electronic and Electrical Engineering University of Strathclyde Glasgow United Kingdom

To achieve the target for building a low-carbon economy, the UK will have to build more low-carbon power plants to reduce carbon dioxide emissions from electricity generation. However, renewable energy is difficult to meet the increasing energy demand and keep lights on. This limitation of renewable could be solved by coal and gas-fired power station fitted with carbon capture storage (CCS) technology. CCS technology could capture up to 90% of carbon dioxide from emissions and allow fossil fuel power station to provide continuous low-carbon electricity power. This paper presents the levelised cost of electricity of CCGT with CCS and compared with renewable technology to forecast the impact of CCGT with CCS on the UK’s electricity market.

关键词： Levelised Cost of electricity Carbon Capture and Storage electricity Market

Comparison of ARIMA and ANN Models Used in electricity Price Forecasting for Power Market

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy and Power Engineering 2017年第4期9卷 120-126页

作者： Gao Gao Kwoklun Lo Fulin Fan Department of Electronic and Electrical Engineering University of Strathclyde Glasgow UK

In power market, electricity price forecasting provides significant information which can help the electricity market participants to prepare corresponding bidding strategies to maximize their profits. This paper introduces the models of autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) which are applied to the price forecasts for up to 3 steps 8 weeks ahead in the UK electricity market. The half hourly data of historical prices are obtained from UK Reference Price Data from March 22nd to July 14th 2010 and the predictions are derived from a sliding training window with a length of 8 weeks. The ARIMA with various AR and MA orders and the ANN with different numbers of delays and neurons have been established and compared in terms of the root mean square errors (RMSEs) of price forecasts. The experimental results illustrate that the ARIMA (4,1,2) model gives greater improvement over persistence than the ANN (20 neurons, 4 delays) model.

关键词： electricity Markets electricity Prices ARIMA Models ANN Models Short-Term Forecasting

The Development of electricity Grid, Smart Grid and Renewable Energy in Taiwan

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Smart Grid and Renewable Energy 2017年第6期8卷 163-177页

作者： Hwa Meei Liou Graduate Institute of Technology Management National Taiwan University of Science and Technology Taipei Taiwan

The grid has played a vital role in the evolution of the electricity market;from traditional to smart grids;from fossil fuel power generated electricity grid connections to the integration of other renewable energy forms such as solar and wind power;the grid has played a key role in each step in Taiwan’s move towards energy transition. This study includes Taiwan’s construction of its transmission and distribution network, the recently passed newly revised version of the electricity Act with its revisions to its transmission and distribution related content, and policies promoting the smart grid as well as issues that the renewable energy grid has raised in both the technical and legal aspects. Taiwan’s electricity supply system is made up of the northern, central and southern systems. The Transmission and distribution grid have been defined as a common carrier, maintaining state-owned monopoly. The smart grid has 6 main facets to promote, including smart generation and dispatch, smart transmission, smart consumers, smart grid electricity grid industry and the establishment of a smart grid environment. Due to the possible effects of the integration of renewable energy generated electricity, there is a vital need for the regulation of the grid’s management and skills.

关键词： electricity Grid Smart Grid Renewable Energy

Cost Control of the Transmission Congestion Management in electricity Systems Based on Ant Colony Algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy and Power Engineering 2011年第1期3卷 17-23页

作者： Bin Liu Jixin Kang Nan Jiang Yuanwei Jing 不详

This paper investigates the cost control problem of congestion management model in the real-time power systems. An improved optimal congestion cost model is built by introducing the congestion factor in dealing with the cases: opening the generator side and load side simultaneously. The problem of real-time congestion management is transformed to a nonlinear programming problem. While the transmission congestion is maximum, the adjustment cost is minimum based on the ant colony algorithm, and the global optimal solu-tion is obtained. Simulation results show that the improved optimal model can obviously reduce the adjust-ment cost and the designed algorithm is safe and easy to implement.

关键词： electricity Systems Congestion Management Ant Colony Algorithm Minimax Adjustment Cost

A Review of Price Forecasting Problem and Techniques in Deregulated electricity Markets

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Power and Energy Engineering 2015年第9期3卷 1-19页

作者： Nitin Singh S. R. Mohanty Department of Electrical Engineering Motilal Nehru National Institute of Technology Allahabad Allahabad India

In deregulated electricity markets, price forecasting is gaining importance between various market players in the power in order to adjust their bids in the day-ahead electricity markets and maximize their profits. electricity price is volatile but non random in nature making it possible to identify the patterns based on the historical data and forecast. An accurate price forecasting method is an important factor for the market players as it enables them to decide their bidding strategy to maximize profits. Various models have been developed over a period of time which can be broadly classified into two types of models that are mainly used for electricity Price forecasting are: 1) Time series models;and 2) Simulation based models;time series models are widely used among the two, for day ahead forecasting. The presented work summarizes the influencing factors that affect the price behavior and various established forecasting models based on time series analysis, such as Linear regression based models, nonlinear heuristics based models and other simulation based models.

关键词： electricity Price Forecasting Time Series Models ARIMA GARCH ANN Fuzzy ARTMAP

Smart Grid Distribution Management System (SGDMS) for Optimised electricity Bills

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Power and Energy Engineering 2018年第8期6卷 49-62页

作者： Weixian Li Chonghao Ng Thillainathan Logenthiran Van-Tung Phan Wai Lok Woo School of Electrical and Electronic Engineering Newcastle University Singapore Campus Singapore

This paper presents the use of proposed Smart Grid Distribution Management System (SGDMS) for Singapore contestable and non-contestable consumers. The SGDMS is a distributed management system proposed using Multi-Agent System (MAS) technology. This system can optimise the distribution of renewable energy while minimizing electricity bills for consumers. The entire system was developed using Java with the extension of JADE which is an IEEE FIPA compliant multi-agent system platform. This decentralised platform allows agents to interact and communicate using energy sources from different sectors and control them intelligently to minimise the cost of electricity for the consumers. Simulation studies were carried out on the proposed system to show its potential for providing solutions through intelligent distribution techniques and how it influences the cost of electricity.

关键词： Smart Grid Multi-Agent System electricity Bill

Modelling the Impact and Effects of Climatic Variability on electricity Energy Consumption in the Yendi Municipality of Ghana

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Open Journal of Energy Efficiency 2020年第1期9卷 1-13页

作者： Wahab A. Iddrisu Sampson T. Appiah Khalid Abdul-Mumin Abdul-Rahman Abdul-Samed Department of Mathematics and Statistics University of Energy and Natural Resources Sunyani Ghana Department of Statistics Tamale Technical University Tamale Ghana

One of the cherished assets of every economy is electricity since it has proven to be the major source of energy for industrialization. Developing economies like Ghana have suffered the downside of poor management of the already inadequate electrical energy at its disposal. This is as a result of limited research into factors that influences electricity energy consumption, most importantly, the effects of climatic variables on electricity energy consumption. This research work explores the causal connection between climatic variables and electricity energy consumption, and develops a Vector Auto Regression (VAR) model to determine the influence of the climatic variables in forecasting electricity energy consumption in Yendi Municipality in the northern region of Ghana. The climatic factors considered in this work are;Rainfall (Rain), maximum temperature (Tmax), Sunshine (Sun), Wind (wind) and Relative Humidity (RH). The Granger causality tests employed in this work revealed that aside from Relative Humidity, the end energy consumption is affected by the other four climatic factors under consideration. The impulse response was used to ascertain the active interaction among electricity energy consumption and the climatic variables. The impulse response of electricity energy consumption to the climatic variables indicates a maximum positive effect of Temperature and Sunshine on electricity energy consumption in March and September respectively. The VAR model was also used in forecasting future consumption of electricity energy. The results indicate excellent forecasts of electricity energy consumption for the first four months of 2019.

关键词： electricity Energy Consumption Vector Autoregression Climatic Variables

Dynamic correlative effect between urbanization and electricity consumption

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Ecological Economy 2015年第2期8卷 118-129页

作者： CAO Zi CHEN Hong-bo Institute of Urban Development and Environment Chinese Academy of Social Sciences

Energy especially for rapid electricity consumption increasing is an obvious problem during the process of urbanization and economic growth. It is also an important research field to explore intrinsic regular pattern of electricity consumption and provide solving approaches. Firstly, this paper studies the relationship between electricity consumption and urbanization via GMM model by stages and regions. The results show that the most obvious stage of urbanization on electricity consumption is the stage between 1992-2000. The residents' income has an evident infl uence on electricity consumption of east region and industry also has generated stronger driving force in central and west regions. Then the paper analyzes the relationship between urbanization and electricity consumption by impulse function and gray correlation, and the variables of urbanization and industrialization both have various positive impulse effect. Estimating the gray correlation, central provinces with high population density and large shares of industry have high correlation degree in urbanization and electricity consumption.

关键词： urbanization electricity consumption impulse function gray correlation