Search results for: renewable energy forecasting

Authors: Rolf Katzenbach, Frithjof Clauss, Jie Zheng

Abstract:

The final energy use can be divided mainly in four sectors: commercial, industrial, residential, and transportation. The trend in final energy consumption by sector plays as a most straightforward way to provide a wide indication of progress for reducing energy consumption and associated environmental impacts by different end use sectors. According to statistics the average share of end use energy for residential sector in the world was nearly 20% until 2011, in Germany a higher proportion is between 25% and 30%. However, it remains less studied than energy use in other three sectors as well its impacts on climate and environment. The reason for this involves a wide range of fields, including the diversity of residential construction like different housing building design and materials, living or energy using behavioral patterns, climatic condition and variation as well other social obstacles, market trend potential and financial support from government. This paper presents an extensive and in-depth analysis of the manner by which projects researched and operated by authors in the fields of energy efficiency primarily from the perspectives of both technical potential and initiative energy saving consciousness in the residential sectors especially in social housing buildings.

Keywords: energy efficiency, renewable energy, retro-commissioning, social housing, sustainability

Procedia PDF Downloads 442

Authors: Daniel Fulus Fom, Gau Patrick Damulak

Abstract:

In this study, the Autoregressive Fractional Integrated Moving Average (ARFIMA) and Jordan Recurrent Neural Network (JRNN) models were employed to model the forecasting performance of the daily turbidity flow of White Clay Creek (WCC). The two methods were applied to the log difference series of the daily turbidity flow series of WCC. The measurements of error employed to investigate the forecasting performance of the ARFIMA and JRNN models are the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The outcome of the investigation revealed that the forecasting performance of the JRNN technique is better than the forecasting performance of the ARFIMA technique in the mean square error sense. The results of the ARFIMA and JRNN models were obtained by the simulation of the models using MATLAB version 8.03. The significance of using the log difference series rather than the difference series is that the log difference series stabilizes the turbidity flow series than the difference series on the ARFIMA and JRNN.

Keywords: auto regressive, mean absolute error, neural network, root square mean error

Procedia PDF Downloads 268

Authors: Aleksandr A. Gajour, Vladimir G. Merzlikin, Vladimir I. Veselov

Abstract:

This paper refers to the analysis of the characteristics of industrial and lifestyle facilities heat- energy objects as a part of the thermal envelope of Earth's surface for inclusion in any database of economic forecasting. The idealized model of the Earth's surface is discussed. This model gives the opportunity to obtain the energy equivalent for each element of terrain and world ocean. Energy efficiency criterion of comfortable human existence is introduced. Dynamics of changes of this criterion offers the possibility to simulate the possible technogenic catastrophes with the spontaneous industrial development of the certain Earth areas. Calculated model with the confirmed forecast of the Gulf Stream freezing in the polar regions in 2011 due to the heat-energy balance disturbance for the oceanic subsurface oil polluted layer is given. Two opposing trends of human development under limited and unlimited amount of heat-energy resources are analyzed.

Keywords: Earth's surface, heat-energy consumption, energy criteria, technogenic catastrophes

Procedia PDF Downloads 402

Authors: Anita Setianingrum, Oki S. Jaya, Zuherman Rustam

Abstract:

Forecasting stock price is a challenging task due to the complex time series of the data. The complexity arises from many variables that affect the stock market. Many time series models have been proposed before, but those previous models still have some problems: 1) put the subjectivity of choosing the technical indicators, and 2) rely upon some assumptions about the variables, so it is limited to be applied to all datasets. Therefore, this paper studied a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) time series model based on Support Vector Regression (SVR) for forecasting the stock market. In order to evaluate the performance of proposed models, stock market transaction data of TAIEX and HIS from January to December 2015 is collected as experimental datasets. As a result, the method has outperformed its counterparts in terms of accuracy.

Keywords: ANFIS, fuzzy time series, stock forecasting, SVR

Procedia PDF Downloads 247

Authors: B. Elshafei, X. Mao

Abstract:

The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

Procedia PDF Downloads 136

Authors: Yousef Abu Nahleh, Arun Kumar, Fugen Daver, Reham Al-Hindawi

Abstract:

Despite the availability of natural disaster related time series data for last 110 years, there is no forecasting tool available to humanitarian relief organizations to determine forecasts for emergency logistics planning. This study develops a forecasting tool based on identifying probability of disaster for each country in the world by using decision tree modeling. Further, the determination of aggregate forecasts leads to efficient pre-disaster planning. Based on the research findings, the relief agencies can optimize the various resources allocation in emergency logistics planning.

Keywords: decision tree modeling, forecasting, humanitarian relief, emergency supply chain

Procedia PDF Downloads 484

Authors: Tarun Kumar Dalakoti, Debajyoti Majumder, Aditya Prasad Das, Samir Chandra Saxena

Abstract:

India’s ambitious target to achieve a 50 percent share of energy from non-fossil fuels and the 500-gigawatt (GW) renewable energy capacity before the deadline of 2030, coupled with the global pursuit of sustainable development, will compel the nation to embark on a rapid clean energy transition. As a result, electricity market reforms will emerge as critical policy instruments to facilitate this transition and achieve ambitious environmental targets. This paper will present a comprehensive analysis of the various electricity market reforms to be introduced in the Indian Electricity sector to facilitate the integration of clean energy sources and will assess their impact on the overall energy landscape. The first section of this paper will delve into the policy mechanisms to be introduced by the Government of India and the Central Electricity Regulatory Commission to promote clean energy deployment. These mechanisms include extensive provisions for the integration of renewables in the Indian Electricity Grid Code, 2023. The section will also cover the projection of RE Generation as highlighted in the National Electricity Plan, 2023. It will discuss the introduction of Green Energy Market segments, the waiver of Inter-State Transmission System (ISTS) charges for inter-state sale of solar and wind power, the notification of Promoting Renewable Energy through Green Energy Open Access Rules, and the bundling of conventional generating stations with renewable energy sources. The second section will evaluate the tangible impact of these electricity market reforms. By drawing on empirical studies and real-world case examples, the paper will assess the penetration rate of renewable energy sources in India’s electricity markets, the decline of conventional fuel-based generation, and the consequent reduction in carbon emissions. Furthermore, it will explore the influence of these reforms on electricity prices, the impact on various market segments due to the introduction of green contracts, and grid stability. The paper will also discuss the operational challenges to be faced due to the surge of RE Generation sources as a result of the implementation of the above-mentioned electricity market reforms, including grid integration issues, intermittency concerns with renewable energy sources, and the need for increasing grid resilience for future high RE in generation mix scenarios. In conclusion, this paper will emphasize that electricity market reforms will be pivotal in accelerating the global transition towards clean energy systems. It will underscore the importance of a holistic approach that combines effective policy design, robust regulatory frameworks, and active participation from market actors. Through a comprehensive examination of the impact of these reforms, the paper will shed light on the significance of India’s sustained commitment to a cleaner, more sustainable energy future.

Keywords: renewables, Indian electricity grid code, national electricity plan, green energy market

Procedia PDF Downloads 43

Authors: Kaushal Kishore

Abstract:

Immense amount of imported fuels are used in Fiji for electricity generation, transportation and for carrying out miscellaneous household work. To alleviate its dependency on fossil fuel, paramount importance has been given to instigate the utilization of renewable energy sources for power generation and to reduce the environmental dilapidation. Amongst the many renewable energy sources, wind has been considered as one of the best identified renewable sources that are comprehensively available in Fiji. In this study the wind resource assessment for three locations in Rakiraki, Fiji has been carried out. The wind resource estimation at Rokavukavu, Navolau and at Tuvavatu has been analyzed. The average wind speed at 55 m above ground level (a.g.l) at Rokavukavu, Navolau, and Tuvavatu sites are 5.91 m/s, 8.94 m/s and 8.13 m/s with the turbulence intensity of 14.9%, 17.1%, and 11.7% respectively. The moment fitting method has been used to estimate the Weibull parameter and the power density at each sites. A high resolution wind resource map for the three locations has been developed by using Wind Atlas Analysis and Application Program (WAsP). The results obtained from WAsP exhibited good wind potential at Navolau and Tuvavatu sites. A wind farm has been proposed at Navolau and Tuvavatu site that comprises six Vergnet 275 kW wind turbines at each site. The annual energy production (AEP) for each wind farm is estimated and an economic analysis is performed. The economic analysis for the proposed wind farms at Navolau and Tuvavatu sites showed a payback period of 5 and 6 years respectively.

Keywords: annual energy production, Rakiraki Fiji, turbulence intensity, Weibull parameter, wind speed, Wind Atlas Analysis and Application Program

Procedia PDF Downloads 189

Authors: Jane Osei, Kerry Brown, Mehran Nejati

Abstract:

Numerous studies have established that solar energy is the second most prevalent form of alternative renewable energy globally, particularly in regions with abundant sunlight. The adoption and ongoing sustainability of solar technology are pivotal for the transition to renewable energy sources. However, the literature indicates that some countries, especially in the developing world, may impede this transition. Despite various policy initiatives aimed at supporting the adoption of solar technology, the long-term effectiveness of these policies remains uncertain. This study investigates the current policy drivers influencing the success or failure of solar energy technology adoption and sustainability. It employs a qualitative review approach to compare strategies for implementing the net-metering policy incentive in both developing and developed countries, identifying successful and unsuccessful strategies and drawing conclusions on the lessons learned. The study's findings reveal that the effective implementation of net metering depends on regional variations in solar radiation and differing levels of electricity demand across regions. Further, the study found that the implementation of net metering has faced challenges in some countries due to regulatory barriers and bottlenecks that hinder private sector involvement and business sustainability. Economic stability also significantly impacts net metering implementation. This study concludes that governments should strive to balance benefit-sharing to attract more private-sector investment in solar technology while ensuring the viability of government energy regulatory bodies.

Keywords: solar energy technology, adoption, sustainability, net-metering

Procedia PDF Downloads 35

Authors: Nazanin Naderi, Milton Smith

Abstract:

Since worldwide demand for renewable energy is increasing rapidly because of the climate problem and the limitation of fossil fuels, technologies of alternative energy sources have been developed and the electric power network now includes renewable energy resources such as wind energy. Because of the huge advantages that wind energy has, like reduction in natural gas use, price pressure, emissions of greenhouse gases and other atmospheric pollutants, electric sector water consumption and many other contributions to the nation’s economy like job creation it has got too much attention these days from different parts of the world especially in the United States which is trying to provide 20% of the nation’s energy from wind by 2030. This study is trying to evaluate the effect of splitting wind farms on power output. We are trying to find if we can get more output by installing wind turbines in different sites rather than installing all wind turbines in one site. Five potential sites in Texas have been selected as a case study and two years wind data has been gathered for these sites. Wind data are analyzed and effect of correlation between sites on power output has been evaluated. Standard deviation and autocorrelation effect has also been considered for this study. The paper has been organized as follows: After the introduction the second section gives a brief overview of wind analysis. The third section addresses the case study and evaluates correlation between sites, auto correlation of sites and standard deviation of power output. In section four we describe the results.

Keywords: auto correlation, correlation between sites, splitting wind farms, power output, standard deviation

Procedia PDF Downloads 586

Authors: Jitka Hroudova, Jiri Zach

Abstract:

The majority of contemporary insulation materials commonly used in the building industry is made from non-renewable raw materials; furthermore, their production often brings high energy costs. A long-term trend as far as sustainable development is concerned has been the reduction of energy and material demands of building material production. One of the solutions is the possibility of using easily renewable natural raw material sources which are considerably more ecological and their production is mostly less energy-consuming compared to the production of normal insulations (mineral wool, polystyrene). The paper describes the results of research focused on the development of thermal and acoustic insulation materials based on natural fibres intended for floor constructions. Given the characteristic open porosity of natural fibre materials, the hygrothermal behaviour of the developed materials was studied. Especially the influence of relative humidity and temperature on thermal insulation properties was observed.

Keywords: Green thermal and acoustic insulating materials, natural fibres, technical hemp, flax, floor construction

Procedia PDF Downloads 334

Authors: Tehreem Fatima, Enjun Xia

Abstract:

The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

Procedia PDF Downloads 283

Authors: Gökçen A. Çiftçioğlu, M. A. Neşet Kadırgan, Figen Kadırgan

Abstract:

Solar energy, since it is available every day, is seen as one of the most valuable renewable energy resources. Thus, the energy of sun should be efficiently used in various applications. The most known applications that use solar energy are heating water and spaces. High efficiency solar collectors need appropriate selective surfaces to absorb the heat. Selective surfaces (Selektif-Sera) used in this study are applied to flat collectors, which are produced by a roll to roll cost effective coating of nano nickel layers, developed in Selektif Teknoloji Co. Inc. Efficiency of flat collectors using Selektif-Sera absorbers are calculated in collaboration with Institute for Solar Technik Rapperswil, Switzerland. The main cause of high energy consumption in industry is mostly caused from low temperature level processes. There is considerable effort in research to minimize the energy use by renewable energy sources such as solar energy. A feasibility study will be presented to obtain the potential of solar thermal energy utilization in the textile industry using these solar collectors. For the feasibility calculations presented in this study, textile dyeing and finishing factory located at Kahramanmaras is selected since the geographic location was an important factor. Kahramanmaras is located in the south east part of Turkey thus has a great potential to have solar illumination much longer. It was observed that, the collector area is limited by the available area in the factory, thus a hybrid heating generating system (lignite/solar thermal) was preferred in the calculations of this study to be more realistic. During the feasibility work, the calculations took into account the preheating process, where well waters heated from 15 °C to 30-40 °C by using the hot waters in heat exchangers. Then the preheated water was heated again by high efficiency solar collectors. Economic comparison between the lignite use and solar thermal collector use was provided to determine the optimal system that can be used efficiently. The optimum design of solar thermal systems was studied depending on the optimum collector area. It was found that the solar thermal system is more economic and efficient than the merely lignite use. Return on investment time is calculated as 5.15 years.

Keywords: energy, renewable energy, selective surface, solar collector

Procedia PDF Downloads 207

Authors: Yathreb Sabsaby

Abstract:

Energy efficiency retrofitting of existing buildings was long ignored by public authorities who favored energy efficiency policies in new buildings, which are easier to implement. Indeed, retrofitting is more complex and difficult to organize because of the extreme diversity in existing buildings, administrative situations and occupation. Energy efficiency retrofitting of existing buildings has now become indispensable in all economies—even emerging countries—given the constraints imposed by energy security and climate change, and because it represents considerable potential energy savings. Addressing energy efficiency in the existing building stock has been acknowledged as one of the most critical yet challenging aspects of reducing our environmental footprint on the ecosystem. Tripoli, Lebanon chosen as case study area is a typical Mediterranean metropolis in the North Lebanon, where multifamily residential buildings are all around the city. This generally implies that the density of energy demand is extremely high, even the renewable energy facilities are involved, they can just play as a minor energy provider at the current technology level in the single family house. It seems only the low energy design for buildings can be made possible, not the zero energy certainly in developing country. This study reviews the latest research and experience and provides recommendations for deep energy retrofits that aim to save more than 50% of the energy used in a typical Tripoli apartment building.

Keywords: energy-efficiency, existing building, multifamily residential building, retrofit

Procedia PDF Downloads 455

Authors: Vijayendra Anil Menon, Ashwath Narayan Murali

Abstract:

The present day vehicles do not reuse the energy expelled in running the vehicle. The energy used to run the vehicle is expelled immediately.This has remained a constant for many decades. With all the vehicles running on non-renewable resources like fossil fuels, there is an urgent need to improve efficiency of the vehicles until a reliable replacement for fossil fuels is found.Our design is based on the concept of Kinetic energy recovery systems. Though our design lies in principle with the KERS, our design can be used in day-to-day driving. With our design, efficiency of vehicles increases and fuel conservation is possible thereby reducing the carbon footprint.

Keywords: KERS, Battery, Wheels, Efficiency.

Procedia PDF Downloads 393

Authors: Ming-Hong Chen

Abstract:

In the study, the mechanical and financial feasibility for the compressed air energy storage (CAES) system in the porous media reservoir in Taiwan is evaluated. In 2035, Taiwan aims to install 16.7 GW of wind power and 40 GW of photovoltaic (PV) capacity. However, renewable energy sources often generate more electricity than needed, particularly during winter. Consequently, Taiwan requires long-term, large-scale energy storage systems to ensure the security and stability of its power grid. Currently, the primary large-scale energy storage options are Pumped Hydro Storage (PHS) and Compressed Air Energy Storage (CAES). Taiwan has not ventured into CAES-related technologies due to geological and cost constraints. However, with the imperative of achieving net-zero carbon emissions by 2050, there's a substantial need for the development of a considerable amount of renewable energy. PHS has matured, boasting an overall installed capacity of 4.68 GW. CAES, presenting a similar scale and power generation duration to PHS, is now under consideration. Taiwan's geological composition, being a porous medium unlike salt caves, introduces flow field resistance affecting gas injection and extraction. This study employs a program analysis model to establish the system performance analysis capabilities of CAES. The finite volume model is then used to assess the impact of porous media, and the findings are fed back into the system performance analysis for correction. Subsequently, the financial implications are calculated and compared with existing literature. For Taiwan, the strategic development of CAES technology is crucial, not only for meeting energy needs but also for decentralizing energy allocation, a feature of great significance in regions lacking alternative natural resources.

Keywords: compressed-air energy storage, efficiency, porous media, financial feasibility

Procedia PDF Downloads 66

Authors: Youssef Mazloum, Haytham Sayah, Maroun Nemer

Abstract:

The penetration of renewable energy sources into the electric grid is significantly increasing. However, the intermittence of these sources breaks the balance between supply and demand for electricity. Hence, the importance of the energy storage technologies, they permit restoring the balance and reducing the drawbacks of intermittence of the renewable energies. This paper discusses the modeling and the cost-effectiveness of an isobaric adiabatic compressed air energy storage (IA-CAES) system. The proposed system is a combination among a compressed air energy storage (CAES) system with pumped hydro storage system and thermal energy storage system. The aim of this combination is to overcome the disadvantages of the conventional CAES system such as the losses due to the storage pressure variation, the loss of the compression heat and the use of fossil fuel sources. A steady state model is developed to perform an energy and exergy analyses of the IA-CAES system and calculate the distribution of the exergy losses in the latter system. A sensitivity analysis is also carried out to estimate the effects of some key parameters on the system’s efficiency, such as the pinch of the heat exchangers, the isentropic efficiency of the rotating machinery and the pressure losses. The conducted sensitivity analysis is a local analysis since the sensibility of each parameter changes with the variation of the other parameters. Therefore, an exergoeconomic study is achieved as well as a cost optimization in order to reduce the electricity cost produced during the production phase. The optimizer used is OmOptim which is a genetic algorithms based optimizer.

Keywords: cost-effectiveness, Exergoeconomic analysis, isobaric adiabatic compressed air energy storage (IA-CAES) system, thermodynamic modeling

Procedia PDF Downloads 246

Authors: Kholik

Abstract:

Nowadays, the demand of renewable energy in general is increasing due to the crisis of fossil fuels. Biohydrogen is an alternative fuel with zero emission derived from renewable resources such as banana pseudo stem of agricultural residues. Banana plant can be easily found in tropical and subtropical areas, so the resource is abundant and readily available as a biohydrogen substrate. Banana pseudo stem has not been utilised as a resource or substrate of biohydrogen production and it mainly contains 45-65% cellulose (α-cellulose), 5-15% hemicellulose and 20-30% Lignin, which indicates that banana pseudo stem will be renewable, sustainable and promising resource as lignocellulosic biomass. In this research, biohydrogen is derived from banana pseudo stem by dark fermentation. Dark fermentation is the most suitable approach for practical biohydrogen production from organic solid wastes. The process has several advantages including a fast reaction rate, no need of light, and a smaller footprint. 321 million metric tonnes banana pseudo stem of 428 million metric tonnes banana plantation residues in worldwide for 2013 and 22.5 million metric tonnes banana pseudo stem of 30 million metric tonnes banana plantation residues in Indonesia for 2015 will be able to generate 810.60 million tonne mol H2 and 56.819 million tonne mol H2, respectively. In this paper, we will show that the banana pseudo stem is the renewable, sustainable and promising resource to be utilised and to produce biohydrogen as energy generation with high yield and high contain of cellulose in comparison with the other substrates.

Keywords: banana pseudo stem, biohydrogen, dark fermentation, lignocellulosic

Procedia PDF Downloads 351

Authors: Sreto Boljevic

Abstract:

In the absence of considerable investment in electricity generation, transmission and distribution network (DN) capacity, the demand for electrical energy will quickly strain the capacity of the existing electrical power network. With anticipated growth and proliferation of Electric vehicles (EVs) and Heat pump (HPs) identified the likelihood that the additional load from EV changing and the HPs operation will require capital investment in the DN. While an area-wide implementation of EVs and HPs will contribute to the decarbonization of the energy system, they represent new challenges for the existing low-voltage (LV) network. Distributed energy resources (DER), operating both as part of the DN and in the off-network mode, have been offered as a means to meet growing electricity demand while maintaining and ever-improving DN reliability, resiliency and power quality. DN planning has traditionally been done by forecasting future growth in demand and estimating peak load that the network should meet. However, new problems are arising. These problems are associated with a high degree of proliferation of EVs and HPs as load imposes on DN. In addition to that, the promotion of electricity generation from renewable energy sources (RES). High distributed generation (DG) penetration and a large increase in load proliferation at low-voltage DNs may have numerous impacts on DNs that create issues that include energy losses, voltage control, fault levels, reliability, resiliency and power quality. To mitigate negative impacts and at a same time enhance positive impacts regarding the new operational state of DN, CHP system integration can be seen as best action to postpone/reduce capital investment needed to facilitate promotion and maximize benefits of EVs, HPs and RES integration in low-voltage DN. The aim of this paper is to generate an algorithm by using an analytical approach. Algorithm implementation will provide a way for optimal placement of the CHP system in the DN in order to maximize the integration of RES and increase in proliferation of EVs and HPs.

Keywords: combined heat & power (CHP), distribution networks, EVs, HPs, RES

Procedia PDF Downloads 202

Authors: Nazaitul Idya Hamzah, Muhammad Syafiq Mazli, Maszatul Akmar Mustafa

Abstract:

The peak demand forecast is crucial to identify the future generation plant up needed in the long-term capacity planning analysis for Peninsular Malaysia as well as for the transmission and distribution network planning activities. Currently, peak demand forecast (in Mega Watt) is derived from the generation forecast by using load factor assumption. However, a forecast using this method has underperformed due to the structural changes in the economy, emerging trends and weather uncertainty. The dynamic changes of these drivers will result in many possible outcomes of peak demand for Peninsular Malaysia. This paper will look into the independent model of peak demand forecasting. The model begins with the selection of driver variables to capture long-term growth. This selection and construction of variables, which include econometric, emerging trend and energy variables, will have an impact on the peak forecast. The actual framework begins with the development of system energy and load shape forecast by using the system’s hourly data. The shape forecast represents the system shape assuming all embedded technology and use patterns to continue in the future. This is necessary to identify the movements in the peak hour or changes in the system load factor. The next step would be developing the peak forecast, which involves an iterative process to explore model structures and variables. The final step is combining the system energy, shape, and peak forecasts into the hourly system forecast then modifying it with the forecast adjustments. Forecast adjustments are among other sales forecasts for electric vehicles, solar and other adjustments. The framework will result in an hourly forecast that captures growth, peak usage and new technologies. The advantage of this approach as compared to the current methodology is that the peaks capture new technology impacts that change the load shape.

Keywords: hourly load profile, load forecasting, long term peak demand forecasting, peak demand

Procedia PDF Downloads 172

Authors: Harshit Vallecha, Prabha Bhola

Abstract:

‘Energy for all’, is a global issue of concern for the past many years. Despite the number of technological advancements and innovations, significant numbers of people are living without access to electricity around the world. India, an emerging economy, tops the list of nations having the maximum number of residents living off the grid, thus raising global attention in past few years to provide clean and sustainable energy access solutions to all of its residents. It is evident from developed economies that centralized planning and electrification alone is not sufficient for meeting energy security. Implementation of off-grid and consumer-driven energy models like Decentralized Renewable Energy (DRE) systems have played a significant role in meeting the national energy demand in developed nations. Cases of DRE systems have been reported in developing countries like India for the past few years. This paper attempts to profile the status of DRE projects in the Indian context with their scope and relevance to ensure universal electrification. Diversified cases of DRE projects, particularly solar, biomass and micro hydro are identified in different Indian states. Critical factors affecting the sustainability of DRE projects are extracted with their interlinkages in the context of developers, beneficiaries and promoters involved in such projects. Socio-techno-economic indicators are identified through similar cases in the context of DRE projects. Exploratory factor analysis is performed to evaluate the critical sustainability factors followed by regression analysis to establish the relationship between the dependent and independent factors. The generated EFA-Regression model provides a basis to develop the sustainability and replicability framework for broader coverage of DRE projects in developing nations in order to attain the goal of universal electrification with least carbon emissions.

Keywords: climate change, decentralized generation, electricity access, renewable energy

Procedia PDF Downloads 124

Authors: Mohammed Alaa Alwafaie, Bela Kovacs

Abstract:

With the rapid emergence and evolution of renewable energy sources like wind and solar power, there is an increasing demand for effective energy harvester architectures. This paper focuses on investigating the concept of energy harvesting using a wheel-motion energy source. The proposed method involves the placement of magnets and copper coils inside the hubcap rod of a wheel. When the wheel is set in motion, following Faraday's Law, the movement of the magnet within the coil induces an electric current. The paper includes an experiment to measure the output voltage of electromagnetics, as well as a numerical simulation to further explore the potential of this energy harvesting approach. By harnessing the rotational motion of wheels, this research aims to contribute to the development of innovative techniques for generating electrical power in a sustainable and efficient manner.

Keywords: harvesting energy, electromagnetic, hubcap rod wheel, magnet movement inside coil, faraday law

Procedia PDF Downloads 77

Authors: N. Ouslimani, N. Hakimi, H. Aksas

Abstract:

The reduction of oil reserves in the world makes that many countries are directed towards the study and the use of local and renewable energies. For this purpose, wood energy represents the material of choice. The energy production is primarily thermal and corresponds to a heating of comfort, auxiliary or principal. Wood is generally conditioned in the form of logs, of pellets, even of plates. In Algeria, this way of energy saving could contribute to the safeguarding of the environment, as to the recovery of under wood products (branches, barks and various wastes on the various transformation steps). This work is placed within the framework general of the search for new sources of energy starting from the recovery of the lignocellulosic matter. In this direction, we proposed various sources of products (biomass, under product and by-products) relating to the ‘Eucalyptus species’ being able to be developed, of which we carried out a preliminary physicochemical study, necessary to the development of the densified products with high calorific value.

Keywords: biomass, calorific value, combustion, energy recovery

Procedia PDF Downloads 290

Authors: Aswathi Thrivikraman, S. Advaith

Abstract:

The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

Procedia PDF Downloads 156

Authors: Kehinde Damilola Ilesanmi, Dev Datt Tewari

Abstract:

South Africa is in its post-industrial era moving from the primary and secondary sector to the tertiary sector. The study investigated the impact of the disaggregated energy consumption (coal, oil, and electricity) on the primary, secondary and tertiary sectors of the economy between 1980 and 2012 in South Africa. Using vector error correction model, it was established that South Africa is an energy dependent economy, and that energy (especially electricity and oil) is a limiting factor of growth. This implies that implementation of energy conservation policies may hamper economic growth. Output growth is significantly outpacing energy supply, which has necessitated load shedding. To meet up the excess energy demand, there is a need to increase the generating capacity which will necessitate increased investment in the electricity sector as well as strategic steps to increase oil production. There is also need to explore more renewable energy sources, in order to meet the growing energy demand without compromising growth and environmental sustainability. Policy makers should also pursue energy efficiency policies especially at sectoral level of the economy.

Keywords: causality, economic growth, energy consumption, hypothesis, sectoral output

Procedia PDF Downloads 470

Authors: Sayed Amir Hamzeh Mirkheshti

Abstract:

Offshore wind energy as a strategic renewable energy, has been growing rapidly due to availability, abundance and clean nature of it. On the other hand, budget of this project is incredibly higher in comparison with other renewable energies and it takes more duration. Accordingly, precise estimation of time and cost is needed in order to promote awareness in the developers and society and to convince them to develop this kind of energy despite its difficulties. Occurrence risks during on project would cause its duration and cost constantly changed. Therefore, to develop offshore wind power, it is critical to consider all potential risks which impacted project and to simulate their impact. Hence, knowing about these risks could be useful for the selection of most influencing strategies such as avoidance, transition, and act in order to decrease their probability and impact. This paper presents an evaluation of the feasibility of 500 MV offshore wind project in the Persian Gulf and compares its situation with uncertainty resources and risk. The purpose of this study is to evaluate time and cost of offshore wind project under risk circumstances and uncertain resources by using Monte Carlo simulation. We analyzed each risk and activity along with their distribution function and their effect on the project.

Keywords: wind energy project, uncertain resources, risks, Monte Carlo simulation

Procedia PDF Downloads 352

Authors: Javier Carroquino, Nieves García-Casarejos, Pilar Gargallo, F. Javier García-Ramos

Abstract:

The energy used in agriculture is a source of global emissions of greenhouse gases. The two main types of this energy are electricity for pumping and diesel for agricultural machinery. In order to reduce these emissions, the European project LIFE REWIND addresses the supply of this demand from renewable sources. First of all, comprehensive data on energy demand and available renewable resources have been obtained in several case studies. Secondly, a set of simulations and optimizations have been performed, in search of the best configuration and sizing, both from an economic and emission reduction point of view. For this purpose, it was used software based on genetic algorithms. Thirdly, a prototype has been designed and installed, that it is being used for the validation in a real case. Finally, throughout a year of operation, various technical and economic parameters are being measured for further analysis. The prototype is not connected to the utility grid, avoiding the cost and environmental impact of a grid extension. The system includes three kinds of photovoltaic fields. One is located on a fixed structure on the terrain. Another one is floating on an irrigation raft. The last one is mounted on a two axis solar tracker. Each has its own solar inverter. The total amount of nominal power is 44 kW. A lead acid battery with 120 kWh of capacity carries out the energy storage. Three isolated inverters support a three phase, 400 V 50 Hz micro-grid, the same characteristics of the utility grid. An advanced control subsystem has been constructed, using free hardware and software. The electricity produced feeds a set of seven pumps used for purification, elevation and pressurization of water in a drip irrigation system located in a vineyard. Since the irrigation season does not include the whole year, as well as a small oversize of the generator, there is an amount of surplus energy. With this surplus, a hydrolyser produces on site hydrogen by electrolysis of water. An off-road vehicle with fuel cell feeds on that hydrogen and carries people in the vineyard. The only emission of the process is high purity water. On the one hand, the results show the technical and economic feasibility of stand-alone renewable energy systems to feed seasonal pumping. In this way, the economic costs, the environmental impacts and the landscape impacts of grid extensions are avoided. The use of diesel gensets and their associated emissions are also avoided. On the other hand, it is shown that it is possible to replace diesel in agricultural machinery, substituting it for electricity or hydrogen of 100% renewable origin and produced on the farm itself, without any external energy input. In addition, it is expected to obtain positive effects on the rural economy and employment, which will be quantified through interviews.

Keywords: drip irrigation, greenhouse gases, hydrogen, renewable energy, vineyard

Procedia PDF Downloads 343

Authors: Hülya Kuru Mutlu, Mustafa Kulakcı, Uğur Serincan

Abstract:

The sun is one of the latest developments in renewable energy sources, which has a variety of application. Solar energy is the most preferred renewable energy sources because it can be used directly, it protects the environment and it is economic. In this work, we investigated that important parameter of GaAs-based solar cells with respect to the growth temperature. The samples were grown on (100) oriented p-GaAs substrates by solid source Veeco GEN20MC MBE system equipped with Ga, In, Al, Si, Be effusion cells and an Arsenic cracker cell. The structures of the grown samples are presented. After initial oxide desorption, Sample 1 and Sample 2 were grown at about 585°C and 535°C, respectively. From the grown structures, devices were fabricated by using the standard photolithography procedure. Current-voltage measurements were performed at room temperature (RT). It is observed that Sample 1 which was grown at 585°C has higher efficiency and fill factor compared to Sample 2. Hence, it is concluded that the growth temperature of 585°C is more suitable to grow GaAs-based solar cells considering our samples used in this study.

Keywords: molecular beam epitaxy, solar cell, current-voltage measurement, Sun

Procedia PDF Downloads 473

Authors: Huashan Tai, Chien-Hui Lung

Abstract:

Nowadays people use massive fossil fuels which not only cause environmental impacts and global climate change, but also cause the depletion of non-renewable energy such as coal and oil. Bioenergy is currently the most widely used renewable energy, and agricultural waste is one of the main raw materials for bioenergy. In this study, we use orange peel residue, which is easier to collect from agricultural waste to produce bio-coal by torrefaction. The orange peel residue (with 25 to 30% moisture) was treated by torrefaction, and the experiments were conducted with initial temperature at room temperature (approximately at 25° C), with heating rates of 10, 30, and 50°C / min, with terminal temperatures at 150, 200, 250, 300, 350℃, and with residence time of 10, 20, and 30 minutes. The results revealed that the heating value, ash content and energy densification ratio of the solid products after torrefaction are in direct proportion to terminal temperatures and residence time, and are inversely proportional to heating rates. The moisture content, solid mass yield, energy yield, and volumetric energy density of the solid products after torrefaction are inversely proportional to terminal temperatures and residence time, and are in direct proportion to heating rates. In conclusion, we found that the heating values of the solid products were 1.3 times higher than those of the raw orange peels before torrefaction, and the volumetric energy densities were increased by 1.45 times under operating parameters with terminal temperature at 250°C, residence time of 10 minutes, and heating rate of 10°C / min of torrefaction. The results indicated that the residue of orange peel treated by torrefaction improved its energy density and fuel properties, and became more suitable for bio-fuel applications.

Keywords: biomass energy, orange, torrefaction

Procedia PDF Downloads 291

Authors: Weidong Fu, Qingsong Wang, Wei Hua, Ming Cheng, Giuseppe Buja

Abstract:

A single-phase transformerless electric energy router (TL-EER) is proposed for renewable energy management and power quality improvement in smart homes. The proposed TL-EER only contains four semiconductor switching devices, which reduces costs greatly compared to traditional electric energy routers. TL-EER functions as intelligent systems that optimize the flow and distribution of energy within a grid, enabling seamless interaction between generation, storage, and consumption. In addition, TL-EER operates in multiple modes and could be converted to diverse topologies by changing the states of relays. As for power quality, voltage and current compensating methods are adapted. Thus, high-quality electrical energy could be transferred to the load, and the grid-side power factor could be improved. Finally, laboratory prototypes are established to validate the effectiveness of the system.

Keywords: transformerless, electric energy router, power flow, power quality, power factor

Procedia PDF Downloads 10