Modelling and simulation of a distributed power generation system with energy storage to meet dynamic household electricity demand

Electrical consumption in a household is not stable but changeable in one day throughout a whole year. The consumption depends on weather, seasons and users. This characteristic of demand makes it difficult to design and build a distributed power generation system to meet the demand for a household. For this reason, a stand-alone distributed power generation system (DPGS) needs to be carefully designed not only to meet the dynamic household electricity demand, but also to be economical. Hence, for a DPGS, it is essential to utilise electrical energy storage (EES) unit to store the excessive energy while power generation is running at off-peak time; and then the EES may supply the stored energy during the peak demand period. This study investigates a distributed power generation system with an electric energy storage unit to meet the dynamic electricity demand in a household. The system composes of one diesel-engine-generator (DG) running with biofuel; a fuel cell; integrated with an energy storage unit including a supercapacitor and a group of batteries. Models have been set up in Dymola software and two different system configurations are proposed and simulated. The characteristics of the integrated DPGS–EES system are presented and discussed. The results show that both configurations are working properly to meet the demand.     

Analysis of household energy demand in Vietnam

Household energy demand in Vietnam is analysed based on a recent household energy survey in four northern provinces. Energy consumption patterns by fuel type and by end use are analysed. The effects of income on these patterns are also examined for different categories of households. Widely held beliefs about energy use and behaviour have been given actual value.     

Modelling of electricity savings in the Danish households sector: from the energy system to the end-user

In this paper, we examine the value of investing in energy-efficient household appliances from both an energy system and end-user perspectives. We consider a set of appliance categories constituting the majority of the electricity consumption in the private household sector, and focus on the stock of products which need to be replaced. First, we look at the energy system and investigate whether investing in improved energy efficiency can compete with the cost of electricity supply from existing or new power plants. To assess the analysis, Balmorel, a linear optimization model for the heat and power sectors, has been extended in order to endogenously determine the best possible investments in more efficient home appliances. Second, we propose a method to relate the optimal energy system solution to the end-user choices by incorporating consumer behaviour and electricity price addition due to taxes. The model is non-exclusively tested on the Danish energy system under different scenarios. Computational experiments show that several energy efficiency measures in the household sector should be regarded as valuable investments (e.g. an efficient lighting system) while others would require some form of support to become profitable. The analysis quantifies energy and economic savings from the consumer side and reveals the impacts on the Danish power system and surrounding countries. Compared to a business-as-usual energy scenario, the end-user attains net economic savings in the range of 30–40 EUR per year, and the system can benefit of an annual electricity demand reduction of 140–150 GWh. The paper enriches the existing literature about energy efficiency modelling in households, contributing with novel models, methods, and findings related to the Danish case.     

Modelling the transport sector fuel demand for developng economies

This paper concentrates on the transport sector of six developing countries with similar common denominators, namely Turkey, Thailand, Pakistan, Morocco, Tunisia and Malaysia. By using standard econometric techniques, we analyse the evolution of oil demand for road transport in these countries in relation to independent variables such as income, population, price of gasoline and diesel etc. Unlike the treatment in the present literature on the subject, gasoline and diesel consumption are estimated separately due to the high share of diesel in the total transport sector consumption. On the basis of the estimation over the period 1970–1990, on a country by country basis, we forecast the demand for these six countries until 2010. The results of this study indicate that the transport sector will be the driving force for energy and oil demand as part of economic growth in these developing countries. Its share in the future energy market structure is expected to grow. Consequently, the (pricing) policies of oil products in this sector have a crucial role for shaping rational economic and energy strategies within the framework of rising environmental concern.     

Modelling industrial energy demand in Saudi Arabia

Between 1986 and 2016, industrial energy consumption in Saudi Arabia increased by tenfold, making it one of the largest end-use sectors in the Kingdom. Despite its importance, there appear to be no published econometric studies on aggregate industrial energy demand in Saudi Arabia. We model aggregate industrial energy demand in Saudi Arabia using Harvey’s (1989) Structural Time Series Model, showing that it is both price and income inelastic, with estimated long-run elasticities of −0.34 and 0.60, respectively. The estimated underlying energy demand trend suggests improvements in energy efficiency starting from 2010.Applying decomposition analysis to the estimated econometric equation highlights the prominent roles of the activity effect (the growth in industrial value added) and the structure effect (the shift towards energy-intensive production) in driving industrial energy demand growth. Moreover, the decomposition shows how exogenous factors such as energy efficiency helped mitigate some of that growth, delivering cumulative savings of 6.8 million tonnes of oil equivalent (Mtoe) between 2010 and 2016.Saudi Arabia implemented a broad energy price reform program in 2016, which raised electricity, fuel, and water prices for households and industry. The decomposition results reveal that, holding all else constant, higher industrial energy prices in 2016 reduced the sector’s energy consumption by 6.9 %, a decrease of around 3.0 Mtoe. Saudi policymakers could therefore build on the current policy of energy price reform and energy efficiency standards to mitigate the rate of growth of industrial energy consumption, increase economic efficiency, and maintain industrial sector competitiveness.     

Modelling future private car energy demand in Ireland

Targeted measures influencing vehicle technology are increasingly a tool of energy policy makers within the EU as a means of meeting energy efficiency, renewable energy, climate change and energy security goals. This paper develops the modelling capacity for analysing and evaluating such legislation, with a focus on private car energy demand. We populate a baseline car stock and car activity model for Ireland to 2025 using historical car stock data. The model takes account of the lifetime survival profile of different car types, the trends in vehicle activity over the fleet and the fuel price and income elasticities of new car sales and total fleet activity. The impacts of many policy alternatives may only be simulated by such a bottom-up approach, which can aid policy development and evaluation. The level of detail achieved provides specific insights into the technological drivers of energy consumption, thus aiding planning for meeting climate targets. This paper focuses on the methodology and baseline scenario. Baseline results for Ireland forecast a decline in private car energy demand growth (0.2%, compared with 4% in the period 2000–2008), caused by the relative growth in fleet efficiency compared with activity.     

The regional demand for energy by the residential sector in the United States

The residential sector is a substantial consumer of energy in the United States. The heterogeneous composition of the sector complicates modelling the demand for energy. After reflecting the particular nuances introduced by differing thermal characteristics of the various fuels, one finds an income elasticity slightly in excess of unity and a price elasticity of demand of approximately ?0·35. The results are not inconsistent with other studies done for the United States.A translog fuel share model yields some significant and interesting conclusions. Support is lent to the contention that consumers are responding to the relative changes in fuel prices by altering their energy consumption patterns.Finally, the question of stability is addressed. The results are conclusive suggesting that the demand for natural gas, oil and electrical energy have remained cirtually constant over the past three decades.     

A method for estimating non-commercial energy consumption in the household sector of developing countries

A method for estimating non-commercial energy consumption in the household sector of developing countries is presented. It has been observed that the energy demand for cooking is not income-elastic. The average requirement per person and hence the total requirement, both in useful energy terms, can be determined. The actual total commercial energy consumption for cooking is converted to useful energy terms and subtracted from this total to give a residual which is the estimated total amount of non-commercial energy used for cooking. The residual may be converted to delivered or primary energy by using an appropriate conversion factor. Using this method, the annual consumption of non-commercial energy has been estimated for selected Southeast Asian countries between 1960 and 1980.     

Determinants of energy demand in the French service sector: A decomposition analysis

This paper analyzes the changes in the energy consumption of the service sector in France over the period 1995–2006, using the logarithmic mean Divisia index I (LMDI I) decomposition method. The analysis is carried out at various disaggregation levels to highlight the specifics of each sub-sector and end-use according to their respective determinants. The results show that in this period the economic growth of the service sector was the main factor that led to the increase in total energy consumption. Structure, productivity, substitution and intensity effects restricted this growth, but with limited effect. By analyzing each end-use, this paper enables a more precise understanding of the impact of these factors. The activity effect was the main determinant of the increase in energy consumption for all end-uses except for air conditioning, for which the equipment rate effect was the main factor. Structural changes in the service sector primarily impacted energy consumption for space heating and cooking. Improvements in productivity limited the growth of energy consumption for all end-uses except for cooking. Finally, energy efficiency improvements mainly affected space-heating energy use.     

The energy demand in the manufacturing sector of Pakistan: some further results

The purpose of this study was to re-examine the role of energy in the manufacturing sector of Pakistan using a Partial Equilibrium Approach. GL restricted cost function along with the factor demand equations were estimated using Zellner’s iterative procedure. Higher energy prices do not seem to adversely affect investment in capital. Substitution possibilities between energy and non-energy inputs are very limited and therefore energy price hikes may directly affect the cost of production. Inter-fuel cross price elasticities indicate that there are substitution possibilities between electricity and gas.     

Energy-related emissions and mitigation opportunities from the household sector in Delhi

Urban centers are the major consumers of energy, which is a major source of air pollution. Therefore, an insight into energy consumption and quantification of emissions from urban areas are extremely important for identifying impacts and finding solution to air pollution in urban centers. This paper applies the Long-range Energy Alternatives Planning (LEAP) system for modeling the total energy consumption and associated emissions from the household sector of Delhi. Energy consumption under different sets of policy and technology options are analyzed for a time span of 2001–2021 and emissions of carbon dioxide (CO₂), carbon monoxide (CO), methane (CH₄), non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NO_x), nitrous oxide (N₂O), total suspended particulates (TSP) and sulfur dioxide (SO₂) are estimated. Different scenarios are generated to examine the level of pollution reduction achievable by application of various options. The business as usual (BAU) scenario is developed considering the time series trends of energy use in Delhi households. The fuel substitution (FS) scenario analyzes policies having potential to impact fuel switching and their implications towards reducing emissions. The energy conservation (EC) scenario focuses on efficiency improvement technologies and policies for energy-intensity reduction. An integrated (INT) scenario is also generated to assess the cumulative impact of the two alternate scenarios on energy consumption and direct emissions from household sectors of Delhi. Maximum reduction in energy consumption in households of Delhi is observed in the EC scenario, whereas, the FS scenario seems to be a viable option if the emission loadings are to be reduced.     

Fuel price determination in transportation sector using predicted energy and transport demand

This study determines fuel price based on estimated sectoral energy and transport demand using pumping prices. Three approaches are first used for estimating energy and transportation demand based on linear time series, polynomial time series and genetic algorithm based (GATEDE and GATDETR), as multi-parameter, models. Then, future fuel prices and marginal costs of the energy consumption are obtained. Transport demand-based energy efficiency methods are also developed. The fuel prices (FP) are analyzed under two scenarios: Linear and exponential price scenarios. Results showed that if the FP increases linearly, the marginal cost will slightly decreases from current trend, but will increases if demand increases exponentially. Results also showed that the demand-based pricing policy would help to develop a new pricing policy for fuel use in order to control fast growing demand on this sector. The exponential price increase would also help to locate financial sources to create environmentally friendly transportation systems.     

Recent development of energy supply and demand in China,and energy sector prospects through 2030

Facing multiple pressures, including its commitment to energy efficiency improvement, the current worldwide recession, and global warming concerns, China is making great efforts to maintain its continuous economic growth and reduce pollutant emissions. Many policies to encourage investing in energy efficiency and renewable energy have been issued. This article provides insights into the latest development of energy production, energy consumption and energy strategic planning and policies in China, and also describes the analysis, carried out by the authors as part of the Asian Energy Security project using the Long-range Energy Alternatives Planning (LEAP) modeling tool, of the impacts of implementing new and expected energy and environmental policies.     

Reduction potentials of energy demand and GHG emissions in China's road transport sector

Rapid growth of road vehicles, private vehicles in particular, has resulted in continuing growth in China's oil demand and imports, which has been widely accepted as a major factor effecting future oil availability and prices, and a major contributor to China's GHG emission increase. This paper is intended to analyze the future trends of energy demand and GHG emissions in China's road transport sector and to assess the effectiveness of possible reduction measures. A detailed model has been developed to derive a reliable historical trend of energy demand and GHG emissions in China's road transport sector between 2000 and 2005 and to project future trends. Two scenarios have been designed to describe the future strategies relating to the development of China's road transport sector. The ‘Business as Usual’ scenario is used as a baseline reference scenario, in which the government is assumed to do nothing to influence the long-term trends of road transport energy demand. The ‘Best Case’ scenario is considered to be the most optimized case where a series of available reduction measures such as private vehicle control, fuel economy regulation, promoting diesel and gas vehicles, fuel tax and biofuel promotion, are assumed to be implemented. Energy demand and GHG emissions in China's road transport sector up to 2030 are estimated in these two scenarios. The total reduction potentials in the ‘Best Case’ scenario and the relative reduction potentials of each measure have been estimated.     

Drivers of renewable technology adoption in the household sector

Using data from the German Socio-Economic Panel, we undertake a simultaneous assessment of the importance of factors that are individually found to be significant for the adoption of renewable energy systems by households but are not yet tested jointly. These are sociodemographic and housing characteristics, environmental concern, personality traits, and economic factors; i.e. the expected costs of and revenues from the investment. Our results suggest that household decisions to invest in photovoltaic systems and solar thermal facilities are mainly driven by economic factors. Taking account of sociodemographic and housing characteristics, environmental concern, or personality traits has comparatively little relevance, while the quantitative nexus between the decision to invest and returns on the investment is robust to their inclusion.     

Assessment of demand for natural gas from the electricity sector in India

Electricity sector is among the key users of natural gas. The sustained electricity deficit and environment policies have added to an already rising demand for gas. This paper tries to understand gas demand in future from electricity sector. This paper models the future demand for gas in India from the electricity sector under alternative scenarios for the period 2005–2025, using bottom-up ANSWER MARKAL model. The scenarios are differentiated by alternate economic growth projections and policies related to coal reforms, infrastructure choices and local environment. The results across scenarios show that gas competes with coal as a base-load option if price difference is below US $ 4 per MBtu. At higher price difference gas penetrates only the peak power market. Gas demand is lower in the high economic growth scenario, since electricity sector is more flexible in substitution of primary energy. Gas demand reduces also in cases when coal supply curve shifts rightwards such as under coal reforms and coal-by-wire scenarios. Local environmental (SO₂ emissions) control promotes end of pipe solutions flue gas de-sulfurisation (FGD) initially, though in the longer term mitigation happens by fuel substitution (coal by gas) and introduction of clean coal technologies integrated gasification combined cycle (IGCC).     

Methodologies for representing the road transport sector in energy system models

Energy system models are often used to assess the potential role of hydrogen and electric powertrains for reducing transport CO₂ emissions in the future. In this paper, we review how different energy system models have represented both vehicles and fuel infrastructure in the past and we provide guidelines for their representation in the future. In particular, we identify three key modelling decisions: the degree of car market segmentation, the imposition of market share constraints and the use of lumpy investments to represent infrastructure. We examine each of these decisions in a case study using the UK MARKAL model. While disaggregating the car market principally affects only the transition rate to the optimum mix of technologies, market share constraints can greatly change the optimum mix so should be chosen carefully. In contrast, modelling infrastructure using lumpy investments has little impact on the model results. We identify the development of new methodologies to represent the impact of behavioural change on transport demand as a key challenge for improving energy system models in the future.     

Energy efficiency improvement potentials and a low energy demand scenario for the global industrial sector

The adoption of energy efficiency measures can significantly reduce industrial energy use. This study estimates the future industrial energy consumption under two energy demand scenarios: (1) a reference scenario that follows business as usual trends and (2) a low energy demand scenario that takes into account the implementation of energy efficiency improvement measures. These scenarios cover energy demand in the period 2009–2050 for ten world regions. The reference scenario is based on the International Energy Agency World Energy Outlook (2011 edition) up to 2035 and is extrapolated by Gross Domestic Product projections for the period 2035–2050. According to the reference scenario, the industrial energy use will increase from 105 EJ in 2009 to 185 EJ in 2050 (excluding fuel use as a feedstock). It is estimated that, with the adoption of energy efficient technologies and increased recycling, the growth in industrial energy use in 2050 can be limited to 140 EJ, an annual energy use increase of 0.7 % compared with the 2009 case. The 2050 industrial energy use in the low energy demand scenario is estimated to be 24 % lower than the 2050 energy use in the reference scenario. The results of this study highlight the importance of industrial energy efficiency by providing insights of the energy savings potentials in different regions of the world.     

Modelling the UK residential energy sector under long-term decarbonisation scenarios: Comparison between energy systems and sectoral modelling approaches

The UK government has set a groundbreaking target of a 60% reduction in carbon dioxide (CO₂) emissions by 2050. Scenario and modelling assessment of this stringent target consistently finds that all sectors need to contribute to emissions reductions. The UK residential sector accounts for around 30% of the total final energy use and more than one-quarter of CO₂ emissions. This paper focuses on modelling of the residential sector in a system wide energy–economy models (UK MARKAL) and key UK sectoral housing stock models. The UK residential energy demand and CO₂ emission from the both approaches are compared. In an energy system with 60% economy-wide CO₂ reductions, the residential sector plays a commensurate role. Energy systems analysis finds this reduction is primarily driven by energy systems interactions notably decarbonisation of the power sector combined with increased appliance efficiency. The stock models find alternate decarbonisation pathways based on assumptions related to the future building stock and behavioural changes. The paper concludes with a discussion on the assumptions and drivers of emission reductions in different models of the residential energy sector.