Search results for: electricity demand

Authors: Hussain Ali Bekhet, Tuan Ab Rashid Bin Tuan Abdullah, Tahira Yasmin

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It is very important for electric utility to determine dominant sectors which have more impacts on electricity consumption in national economy system. The aim of this paper is to examine the electricity demand multipliers in Malaysia for (2005-2014) period. Malaysian Input-output tables, 2005 and 2010 are used. Besides, a new concept, electricity demand multiplier (EDM), is presented to identify key sectors imposing great impacts on electricity demand quantitatively. In order to testify the effectiveness of the Malaysian energy policies, it notes that there is fluctuation of the ranking sectors between 2005 and 2010. This could be reflected that there is efficiency with pace of development in Malaysia. This can be good indication for decision makers for designing future energy policies.

Keywords: input-output model, demand multipliers, electricity, key sectors, Malaysia

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Authors: Xian Li, Qing-Guo Wang, Jiangshuai Huang, Jidong Liu, Ming Yu, Tan Kok Poh

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In power industry, accurate electricity demand forecasting for a certain leading time is important for system operation and control, etc. In this paper, we investigate the modeling and forecasting of Singapore’s electricity demand. Several standard models, such as HWT exponential smoothing model, the ARMA model and the ANNs model have been proposed based on historical demand data. We applied them to Singapore electricity market and proposed three refinements based on simulation to improve the modeling accuracy. Compared with existing models, our refined model can produce better forecasting accuracy. It is demonstrated in the simulation that by adding forecasting error into the forecasting equation, the modeling accuracy could be improved greatly.

Keywords: power industry, electricity demand, modeling, forecasting

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Authors: Ioana Neamtu

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This paper investigates the potential for demand-side management for the system price in the Nordic electricity market and the price effects of introducing wind-power into the system. The model proposed accounts for the micro-structure of the Nordic electricity market by modeling each hour individually, while still accounting for the relationship between the hours within a day. This flexibility allows us to explore the differences between peak and shoulder demand hours. Preliminary results show potential for demand response management, as indicated by the price elasticity of demand as well as a small but statistically significant decrease in price, given by the wind power penetration. Moreover, our study shows that these effects are stronger during day-time and peak hours,compared to night-time and shoulder hours.

Keywords: structural model, GMM estimation, system of equations, electricity market

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Diyono Harun

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Indonesia aims to reduce carbon emissions from energy generation by reaching 23% and 31% of the national energy supply from renewable energy sources (RES) in 2025 and 2030. The potential for RES in Indonesia is enormous, but not all province has the same potential for RES. Yogyakarta, one of the most travel-destinated provinces in Indonesia, has less potential than its neighbour, Central Java. Consequently, Yogyakarta must meet its electricity demand by importing electricity from Central Java if this province only wants to use electricity from RES. Thus, achieving the objective is balancing the electricity supply between an importer (Yogyakarta) and an exporter province (Central Java). This research aims to explore the RES potential and the current capacity of RES for electricity generation in both provinces. The results show that the present capacity of RES meets the annual domestic electricity demand in both provinces only with an extension of the RES potential. The renewable energy mixes in this research also can lower CO2 emissions compared to gas-fired power plants. This research eventually provides insights into exploring and using the domestic RES potentials between two areas with different RES capacities.

Keywords: energy mix, renewable energy sources, domestic electricity, electricity generation

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Authors: Renata Konadu

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In Ghana, electricity has become the main form of energy which all sectors of the economy rely on for their businesses. Therefore, as the economy grows, the demand and consumption of electricity also grow alongside due to the heavy dependence on it. However, since the supply of electricity has not increased to match the demand, there has been frequent power outages and load shedding affecting business performances. To solve this problem and advance policies to secure electricity in Ghana, it is imperative that those factors that cause consumption to increase be analysed by considering the three classes of consumers; residential, industrial and non-residential. The main argument, however, is that, export of electricity to other neighbouring countries should be included in the electricity consumption model and considered as one of the significant factors which can decrease or increase consumption. The author made use of multivariate time series data from 1980-2010 and econometric models such as Ordinary Least Squares (OLS) and Vector Error Correction Model. Findings show that GDP growth, urban population growth, electricity exports and industry value added to GDP were cointegrated. The results also showed that there is unidirectional causality from electricity export and GDP growth and Industry value added to GDP to electricity consumption in the long run. However, in the short run, there was found to be a directional causality among all the variables and electricity consumption. The results have useful implication for energy policy makers especially with regards to electricity consumption, demand, and supply.

Keywords: electricity consumption, energy policy, GDP growth, vector error correction model

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Authors: Migael van Zyl, Stefanie Visser, Awelani Phaswana

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The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system.

Keywords: electricity demand forecasting, load shedding, demand side management, data science

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Authors: Timothy J. Considine, Edward J. M. Manderson

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This paper develops an econometric forecasting system of energy demand coupled with engineering-economic models of energy supply. The framework is used to quantify the impact of state-level renewable portfolio standards (RPSs) achieved predominately with solar generation on electricity rates, electricity consumption, and environmental quality. We perform the analysis using Arizona’s RPS as a case study. We forecast energy demand in Arizona out to 2035, and find by this time the state will require an additional 35 million MWh of electricity generation. If Arizona implements its RPS when supplying this electricity demand, we find there will be a substantial increase in electricity rates (relative to a business-as-usual scenario of reliance on gas-fired generation). Extending the current regime of tax credits can greatly reduce this increase, at the taxpayers’ expense. We find that by 2025 Arizona’s RPS will implicitly abate carbon dioxide emissions at a cost between $101 and $135 per metric ton, and by 2035 abatement costs are between $64 and $112 per metric ton (depending on the future evolution of nature gas prices).

Keywords: electricity demand, renewable portfolio standard, solar, carbon dioxide

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Authors: Saurabh Chanana, Monika Arora

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Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand.

Keywords: demand response, home energy management, programmable communicating thermostat, thermostatically controlled appliances

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Authors: Sheikh Saeed Ahmad

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Electricity is vital for any state’s development that needs policy for planning the power network extension. This study is about simulation modeling for electricity in Balochistan province. Baseline data of electricity consumption was used of year 2004 and projected with the help of LEAP model up to subsequent 30 years. Three scenarios were created to run software. One scenario was baseline and other two were alternative or green scenarios i.e. solar and wind energy scenarios. Present study revealed that Balochistan has much greater potential for solar and wind energy for electricity production. By adopting these alternative energy forms, Balochistan can save energy in future nearly 23 and 48% by incorporating solar and wind power respectively. Thus, the study suggests to government planners, an aspect of integrating renewable sources in power system for ensuring sustainable development and growth.

Keywords: demand and supply, LEAP, solar energy, wind energy, households

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Authors: Isha Rathore, Peeyush Jain, Elangovan Rajasekar

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The thermal capacity of the envelope impacts the cooling and heating demand of a building and modulates the peak electricity demand. This paper presents the thermal capacity tuning of a building envelope to minimize peak electricity demand for space cooling. We consider a 40 m² residential testbed located in Hyderabad, India (Composite Climate). An EnergyPlus model is validated using real-time data. A Parametric simulation framework for thermal capacity tuning is created using the Honeybee plugin. Diffusivity, Thickness, layer position, orientation and fenestration size of the exterior envelope are parametrized considering a five-layered wall system. A total of 1824 parametric runs are performed and the optimum wall configuration leading to minimum peak cooling demand is presented.

Keywords: thermal capacity, tuning, peak demand reduction, parametric analysis

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Authors: Hasibe Berfu Demi̇r, Şakir Esnaf

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In the past decade, extensive improvements have been done in electrical grid infrastructures. It is very important to make plans on supply, demand, transmission, distribution and pricing for the development of the electricity energy sector. Based on this perspective, in this study, Stackelberg game approach is proposed for demand participation management (DRM), which has become an important component in the smart grid to effectively reduce power generation costs and user bills. The purpose of this study is to examine electricity consumption from a dynamic pricing perspective. The results obtained were compared with the current situation and the results were interpreted.

Keywords: lectricity, stackelberg, smart grid, demand response managment, dynamic pricing

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Authors: Daniel Murrant, Andrew Quinn, Lee Chapman

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A growing population has led to increasing global water and energy demand. This demand, combined with the effects of climate change and an increasing need to maintain and protect the natural environment, represents a potentially severe threat to many national infrastructure systems. This has resulted in a considerable quantity of published material on the interdependencies that exist between the supply of water and the thermal generation of electricity, often known as the water-energy nexus. Focusing specifically on the UK, there is a growing concern that the future availability of water may at times constrain thermal electricity generation, and therefore hinder the UK in meeting its increasing demand for a secure, and affordable supply of low carbon electricity. To provide further information on the threat the water-energy nexus may pose to the UK’s energy system, this paper models the regional water demand of UK thermal electricity generation in 2030 and 2050. It uses the strategically important Energy Systems Modelling Environment model developed by the Energy Technologies Institute. Unlike previous research, this paper was able to use abstraction and consumption factors specific to UK power stations. It finds that by 2050 the South East, Yorkshire and Humber, the West Midlands and North West regions are those with the greatest freshwater demand and therefore most likely to suffer from a lack of resource. However, it finds that by 2050 it is the East, South West and East Midlands regions with the greatest total water (fresh, estuarine and seawater) demand and the most likely to be constrained by environmental standards.

Keywords: climate change, power station cooling, UK water-energy nexus, water abstraction, water resources

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Authors: N. E Okoligwe, Okezie A. Ihugba

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Few scholars disagrees that electricity consumption is an important supporting factor for economy growth. However, the relationship between electricity consumption and economy growth has different manifestation in different countries according to previous studies. This paper examines the causal relationship between electricity consumption and economic growth for Nigeria. In an attempt to do this, the paper tests the validity of the modernization or depending hypothesis by employing various econometric tools such as Augmented Dickey Fuller (ADF) and Johansen Co-integration test, the Error Correction Mechanism (ECM) and Granger Causality test on time series data from 1971-2012. The Granger causality is found not to run from electricity consumption to real GDP and from GDP to electricity consumption during the year of study. The null hypothesis is accepted at the 5 per cent level of significance where the probability value (0.2251 and 0.8251) is greater than five per cent level of significance because both of them are probably determined by some other factors like; increase in urban population, unemployment rate and the number of Nigerians that benefit from the increase in GDP and increase in electricity demand is not determined by the increase in GDP (income) over the period of study because electricity demand has always been greater than consumption. Consequently; the policy makers in Nigeria should place priority in early stages of reconstruction on building capacity additions and infrastructure development of the electric power sector as this would force the sustainable economic growth in Nigeria.

Keywords: economic growth, electricity consumption, error correction mechanism, granger causality test

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Authors: Jianlin Wang, Jiajia Zhao

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This paper applies the theory and empirical method to examine the relationship between electricity price and coal price, as well as electricity and industry output, for China during Jan 1999-Dec 2012. Our results indicate that there is no any causality between coal price and electricity price under other factors are controlled. However, we found a bi-directional causality between electricity consumption and industry output. Overall, the electricity price set by China’s NDRC is inefficient, which lead to the electricity supply shortage after 2004. It is time to reform electricity price system for China’s reformers.

Keywords: electricity price, coal price, power supply, China

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Authors: Aparna Viswanath

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Electricity spot prices are highly volatile under optimal generation capacity scenarios due to factors such as non-storability of electricity, peak demand at certain periods, generator outages, fuel uncertainty for renewable energy generators, huge investments and time needed for generation capacity expansion etc. As a result market participants are exposed to price and volume risk, which has led to the development of risk management practices. This paper provides an overview of risk management practices by market participants in electricity markets using financial derivatives.

Keywords: financial derivatives, forward, futures, options, risk management

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Authors: Paul Kipchumba

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Kenya is an East African Country lying at the Equator. It had a population of 46 million in 2015 with an annual growth rate of 2.7%, making a population of at least 65 million in 2030. Kenya’s GDP in 2015 was about 63 billion USD with per capita GDP of about 1400 USD. The rural population is 74%, whereas urban population is 26%. Kenya grapples with not only access to energy but also with energy security. There is direct correlation between economic growth, population growth, and energy consumption. Kenya’s energy composition is at least 74.5% from renewable energy with hydro power and geothermal forming the bulk of it; 68% from wood fuel; 22% from petroleum; 9% from electricity; and 1% from coal and other sources. Wood fuel is used by majority of rural and poor urban population. Electricity is mostly used for lighting. As of March 2015 Kenya had installed electricity capacity of 2295 MW, making a per capital electricity consumption of 0.0499 KW. The overall retail cost of electricity in 2015 was 0.009915 USD/ KWh (KES 19.85/ KWh), for installed capacity over 10MW. The actual demand for electricity in 2015 was 3400 MW and the projected demand in 2030 is 18000 MW. Kenya is working on vision 2030 that aims at making it a prosperous middle income economy and targets 23 GW of generated electricity. However, cost and non-cost factors affect generation and consumption of electricity in Kenya. Kenya does not care more about CO2 emissions than on economic growth. Carbon emissions are most likely to be paid by future costs of carbon emissions and penalties imposed on local generating companies by sheer disregard of international law on C02 emissions and climate change. The study methodology was a simulated application of carbon tax on all carbon emitting sources of electricity generation. It should cost only USD 30/tCO2 tax on all emitting sources of electricity generation to have solar as the only source of electricity generation in Kenya. The country has the best evenly distributed global horizontal irradiation. Solar potential after accounting for technology efficiencies such as 14-16% for solar PV and 15-22% for solar thermal is 143.94 GW. Therefore, the paper recommends adoption of solar power for generating all electricity in Kenya in order to attain zero carbon electricity generation in the country.

Keywords: co2 emissions, cost factors, electricity generation, non-cost factors

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Authors: Merieleen Engtipi

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India's total share of global population is nearly 18%; however, its per capita energy consumption is only one-third of global average. The demand and supply of electricity are uneven in the country; around 240 million of the population have no access to electricity. However, with India's trajectory for modernisation and economic growth, the demand for energy is only expected to increase. India is at a crossroad, on the one hand facing the increasing demand for energy and on the other hand meeting the Paris climate policy commitments, and further the struggle to provide efficient energy. This paper analyses the policies to meet India’s need for energy, as the per capita energy consumption is likely to be double in 6-7 years period. Simultaneously, India's Paris commitment requires curbing of carbon emission from fossil fuels. There is an increasing need for renewables to be cheaply and efficiently available in the market and for clean technology to extract fossil fuels to meet climate policy goals. Fossil fuels are the most significant generator of energy in India; with the Paris agreement, the demand for clean energy technology is increasing. Finally, the U.S. decided to withdraw from the Paris Agreement; however, the two countries plan to continue engaging bilaterally on energy issues. The U.S. energy cooperation under Trump administration is significantly vital for greater energy security, transfer of technology and efficiency in energy supply and demand.

Keywords: energy demand, energy cooperation, fossil fuels, technology transfer

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Authors: Zaid Jamal Saeed Almahmoud

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Our increasing reliance on electricity, with inefficient consumption trends, has resulted in several economical and environmental threats. These threats include wasting billions of dollars, draining limited resources, and elevating the impact of climate change. As a solution, the smart grid is emerging as the future power grid, with smart techniques to optimize power consumption and electricity generation. Minimizing the peak power consumption under a fixed delay requirement is a significant problem in the smart grid. In addition, matching demand to supply is a key requirement for the success of the future electricity. In this work, we consider the problem of minimizing the peak demand under appliances constraints by scheduling power jobs with uniform release dates and deadlines. As the problem is known to be NP-Hard, we propose two versions of a heuristic algorithm for solving this problem. Our theoretical analysis and experimental results show that our proposed heuristics outperform existing methods by providing a better approximation to the optimal solution. In addition, we consider dynamic pricing methods to minimize the peak load and match demand to supply in the smart grid. Our contribution is the proposal of generic, as well as customized pricing heuristics to minimize the peak demand and match demand with supply. In addition, we propose optimal pricing algorithms that can be used when the maximum deadline period of the power jobs is relatively small. Finally, we provide theoretical analysis and conduct several experiments to evaluate the performance of the proposed algorithms.

Keywords: heuristics, optimization, smart grid, peak demand, power supply

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Authors: Roya Moradifar, Bijan Honarvar, Masoumeh Zabihi

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The personal residential camps of South Pars gas complex are one of the few places where electric energy is used for the bath water heating. The widespread use of these devices is mainly responsible for the high peak of the electricity demand in the residential sector. In an attempt to deal with this issue, to reduce the electricity usage of the hot water, as an option, solar hot water systems have been proposed. However, despite the high incidence of solar radiation on the Assaloyeh about 20 MJ/m²/day, currently, there is no technical assessment quantifying the economic benefits on the region. The present study estimates the economic impacts resulting by the deployment of solar hot water systems in residential camp. Hence, the feasibility study allows assessing the potential of solar water heating as an alternative to reduce the peak on the electricity demand. In order to examine the potential of using solar energy in Bidkhoon residential camp two solar water heater packages as pilots were installed for restaurant and building. Restaurant package was damaged due to maintenance problems, but for the building package, we achieved the result of the solar fraction total 83percent and max energy saving 2895 kWh, the maximum reduction in CO₂ emissions calculated as 1634.5 kg. The results of this study can be used as a support tool to spread the use solar water heaters and create policies for South Pars Gas Complex.

Keywords: electrical energy, hot water, solar, South Pars Gas complex

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Authors: Abdulla Rahil, Rupert Gammon, Neil Brown

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The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data.

Keywords: hydrogen filling station off-peak electricity, renewable energy, off-peak electricity, electrolytic hydrogen

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Authors: Madia Safdar, G. Amjad Hussain, Mashhood Ahmad

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One of the major challenges of today’s era is peak demand which causes stress on the transmission lines and also raises the cost of energy generation and ultimately higher electricity bills to the end users, and it was used to be managed by the supply side management. However, nowadays this has been withdrawn because of existence of potential in the demand side management (DSM) having its economic and- environmental advantages. DSM in domestic load can play a vital role in reducing the peak load demand on the network provides a significant cost saving. In this paper the potential of demand response (DR) in reducing the peak load demands and electricity bills to the electric users is elaborated. For this purpose the domestic appliances are modeled in MATLAB Simulink and controlled by a module called energy management controller. The devices are categorized into controllable and uncontrollable loads and are operated according to real-time tariff pricing pattern instead of fixed time pricing or variable pricing. Energy management controller decides the switching instants of the controllable appliances based on the results from optimization algorithms. In GAMS software, the MILP (mixed integer linear programming) algorithm is used for optimization. In different cases, different constraints are used for optimization, considering the comforts, needs and priorities of the end users. Results are compared and the savings in electricity bills are discussed in this paper considering real time pricing and fixed tariff pricing, which exhibits the existence of potential to reduce electricity bills and peak loads in demand side management. It is seen that using real time pricing tariff instead of fixed tariff pricing helps to save in the electricity bills. Moreover the simulation results of the proposed energy management system show that the gained power savings lie in high range. It is anticipated that the result of this research will prove to be highly effective to the utility companies as well as in the improvement of domestic DR.

Keywords: controllable and uncontrollable domestic loads, demand response, demand side management, optimization, MILP (mixed integer linear programming)

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Authors: Ali Hashemifarzad, Jens Zum Hingst

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The structure of the world’s energy systems has changed significantly over the past years. One of the most important challenges in the 21st century in Germany (and also worldwide) is the energy transition. This transition aims to comply with the recent international climate agreements from the United Nations Climate Change Conference (COP21) to ensure sustainable energy supply with minimal use of fossil fuels. Germany aims for complete decarbonization of the energy sector by 2050 according to the federal climate protection plan. One of the stipulations of the Renewable Energy Sources Act 2017 for the expansion of energy production from renewable sources in Germany is that they cover at least 80% of the electricity requirement in 2050; The Gross end energy consumption is targeted for at least 60%. This means that by 2050, the energy supply system would have to be almost completely converted to renewable energy. An essential basis for the development of such a sustainable energy supply from 100% renewable energies is to predict the energy requirement by 2050. This study presents two scenarios for the final energy demand in Germany in 2050. In the first scenario, the targets for energy efficiency increase and demand reduction are set very ambitiously. To build a comparison basis, the second scenario provides results with less ambitious assumptions. For this purpose, first, the relevant framework conditions (following CUTEC 2016) were examined, such as the predicted population development and economic growth, which were in the past a significant driver for the increase in energy demand. Also, the potential for energy demand reduction and efficiency increase (on the demand side) was investigated. In particular, current and future technological developments in energy consumption sectors and possible options for energy substitution (namely the electrification rate in the transport sector and the building renovation rate) were included. Here, in addition to the traditional electricity sector, the areas of heat, and fuel-based consumptions in different sectors such as households, commercial, industrial and transport are taken into account, supporting the idea that for a 100% supply from renewable energies, the areas currently based on (fossil) fuels must be almost completely be electricity-based by 2050. The results show that in the very ambitious scenario a final energy demand of 1,362 TWh/a is required, which is composed of 818 TWh/a electricity, 229 TWh/a ambient heat for electric heat pumps and approx. 315 TWh/a non-electric energy (raw materials for non-electrifiable processes). In the less ambitious scenario, in which the targets are not fully achieved by 2050, the final energy demand will need a higher electricity part of almost 1,138 TWh/a (from the total: 1,682 TWh/a). It has also been estimated that 50% of the electricity revenue must be saved to compensate for fluctuations in the daily and annual flows. Due to conversion and storage losses (about 50%), this would mean that the electricity requirement for the very ambitious scenario would increase to 1,227 TWh / a.

Keywords: energy demand, energy transition, German Energiewende, 100% renewable energy production

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Authors: Maria Luiza D. Ramiento, Maria Lissette D. Lucas

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Electricity is said to serve as the backbone of modern technology. Considering this, electricity consumption has dynamically grown due to the continuous demand. An alternative producer of energy concerning electricity must therefore be given focus. Microbial fuel cell wholly characterizes a new method of renewable energy recovery: the direct conversion of organic matter to electricity using bacteria. Electricity is produced as fuel or new food is given to the bacteria. The study concentrated in determining the feasibility of electricity production from local benthic zones. Microbial fuel cells were constructed to harvest the possible electricity and to test the presence of electricity producing microorganisms. Soil samples were gathered from Calumpang River, Palawan Mangrove Forest, Rosario River and Batangas Port. Eleven modules were constructed for the different trials of the soil samples. These modules were made of cathode and anode chambers connected by a salt bridge. For 85 days, the harvested voltage was measured daily. No parameter is added for the first 24 days. For the next 61 days, acetic acid was included in the first and second trials of the modules. Each of the trials of the soil samples gave a positive result in electricity production.There were electricity producing microbes in local benthic zones. It is observed that the higher the organic content of the soil sample, the higher the electricity harvested from it. It is recommended to identify the specific species of the electricity-producing microorganism present in the local benthic zone. Complement experiments are encouraged like determining the kind of soil particles to test its effect on the amount electricity that can be harvested. To pursue the development of microbial fuel cells by building a closed circuit in it is also suggested.

Keywords: microbial fuel cell, benthic zone, electricity, reduction-oxidation reaction, bacteria

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Authors: Cem Isik Dogru, Salih Tekin, Kursad Derinkuyu

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Electric vehicle (EV) carsharing is an alternative method to tackle urban transportation problems. This method can be applied by several options. One of the options is the one-way carsharing, which allow an EV to be taken at a designated location and leaving it on another specified location customer desires. Although it may increase users’ satisfaction, the issues, namely, demand dissatisfaction, relocation of EVs and charging schedules, must be dealt with. Also, excessive electricity has to be stored in batteries of EVs. To cope with aforementioned issues, two-step mixed integer programming (MIP) model is proposed. In first step, the integer programming model is used to determine amount of electricity to be sold to the grid in terms of time periods for extra profit. Determined amounts are provided from the batteries of EVs. Also, this step works in day-ahead electricity markets with forecast of periodical electricity prices. In second step, other MIP model optimizes daily operations of one-way carsharing: charging-discharging schedules, relocation of EVs to serve more demand and renting to maximize the profit of EV fleet owner. Due to complexity of the models, heuristic methods are introduced to attain a feasible solution and different price information scenarios are compared.

Keywords: electric vehicles, forecasting, mixed integer programming, one-way carsharing

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Authors: Muhammad Shahid, Kafait Ullah, Kashif Imran, Arshad Mahmood, Maarten Arentsen

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Poor planning and governance in the power sector of Pakistan have generated several issues ranging from gradual reliance on thermal-based expensive energy mix, supply shortages, unrestricted demand, subsidization, inefficiencies at different levels of the value chain and resultantly, the circular debt. This situation in the power sector has also hampered the growth of allied economic sectors. This study uses the Long-range Energy Alternative Planning (LEAP) system for electricity modelling of Pakistan from the period of 2016 to 2040. The study has first time in Pakistan forecasted the electricity demand at the provincial level. At the supply side, five scenarios Business as Usual Scenario (BAUS), Coal Scenario (CS), Gas Scenario (GS), Nuclear Scenario (NS) and Renewable Scenario (RS) have been analyzed based on the techno-economic and environmental parameters. The study has also included environmental externality costs for evaluating the actual costs and benefits of different scenarios. Contrary to the expectations, RS has a lower output than even BAUS. The study has concluded that the generation from RS has five times lesser costs than BAUS, CS, and GS. NS can also be an alternative for the sustainable future of Pakistan. Generation from imported coal is not a good option, however, indigenous coal with clean coal technologies should be promoted. This paper proposes energy planners of the country to devise incentives for the utilization of indigenous energy resources including renewables on priority and then clean coal to reduce the energy crises of Pakistan.

Keywords: economic evaluation, externality cost, penetration of renewable energy, regional electricity supply-demand planning

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Authors: Christo Nicholls

Abstract:

The National Electricity Grid (NEG) in South Africa has been under strain for the last five years. This overburden of the NEG led Eskom (the State-Owned Entity responsible for the NEG) to implement a blunt methodology to assist them in reducing the maximum demand (MD) on the NEG, when required, called Loadshedding. The challenge of this methodology is that not only does it lead to immense technical issues with the distribution network equipment, e.g., transformers, due to the frequent abrupt off and on switching, it also has a broader negative fiscal impact on the distributors, as their key consumers (commercial & industrial) are now grid defecting due to the lack of Electricity Security Provision (ESP). This paper provides a pragmatic alternative methodology utilizing specific functionalities embedded within direct-connect single and three-phase Advanced Meter Infrastructure (AMI) Solutions deployed within the distribution network, in conjunction with a Multi-Agent Systems Based AI implementation focused on Automated Negotiation Peer-2-Peer trading. The results of this research clearly illustrate, not only does methodology provide a factual percentage contribution towards the NEG MD at the point of consideration, it also allows the distributor to leverage the real-time MD data from key consumers to activate complex, yet impact-measurable Demand Response (DR) programs.

Keywords: AI, AMI, demand response, multi-agent

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Authors: Endang Jati Mat Sahid, Hussain Ali Bekhet

Abstract:

Ability to supply reliable and secure electricity has been one of the crucial components of economic development for any country. Forecasting of electricity production is therefore very important for accurate investment planning of generation power plants. In this study, we aim to examine and analyze the factors that affect electricity generation. Multiple regression models were used to find the relationship between various variables and electricity production. The models will simultaneously determine the effects of the variables on electricity generation. Many variables influencing electricity generation, i.e. natural gas (NG), coal (CO), fuel oil (FO), renewable energy (RE), gross domestic product (GDP) and fuel prices (FP), were examined for Malaysia. The results demonstrate that NG, CO, and FO were the main factors influencing electricity generation growth. This study then identified a number of policy implications resulting from the empirical results.

Keywords: energy policy, energy security, electricity production, Malaysia, the regression model

Procedia PDF Downloads 121

Authors: Fatemeh Behrouzi, Adi Maimun, Mehdi Nakisa

Abstract:

The growth of population, rising fossil fuel prices which the fossil fuels are limited and decreased day by day, pollution problem due to use of fossil fuels and electrical demand are important role to encourage of using the green energy and renewable technologies. Among different renewable energy technologies, hydro power generation (large and small scale) is the prime choice in terms of contribution to the world's electricity generation by using water current turbines. Nowadays, researchers focus on design and development of different kind of turbines to capture hydro-power electricity generation as clean and reliable energy. This article is review about statues of water current turbines carried out to generate electricity from hydro-kinetic energy especially places that they do not have electricity, but they have access to the current water.

Keywords: water current turbine, renewable energy, hydro-power, mechanic

Procedia PDF Downloads 428

Authors: Victor Siahaan

Abstract:

Coal still become the most important energy source for electricity generation known for its contribution which take the biggest portion of energy mix that a country has, for example Indonesia. The low cost of electricity generation and quite a lot of resources make this energy still be the first choice to fill the portion of base load power. To realize its significance to produce electricity, it is necessary to know the amount of coal (volume) needed to ensure that all coal power plants (CPP) in a country can operate properly. To secure the volume of coal, in this study, discussion was carried out regarding the identification of coal mining sources in Indonesia, classification of coal typical from each coal mining sources, and determination of the port of loading. By using data above, the sources of coal mining are then selected to feed certain CPP based on the compatibility of the coal typical and the lowest transport cost.

Keywords: merit order, Indonesian coal mine, electricity, power plant

Procedia PDF Downloads 122