Electricity in the marketplace: Reconfiguring the consumption of essential resources

This paper critically examines how privatisation and liberalisation of electricity provision is reconstructing energy consumption practices. The paper discusses the commercial restructuring of the electricity industry in the UK over the last four years, illustrating how a reconfiguration of production and consumption interests is transforming the utility marketplace: differentiating the value of resource units, distinguishing between infrastructure suppliers and stratifying utility customers. This process is shown to be resulting in differential forms of service provision as utility companies actively engage with more lucrative customers, presenting opportunities for environmental innovation, while disengaging from unprofitable customers and heightening social polarisation.     

Grey relation analysis of carbon dioxide emissions from industrial production and energy uses in Taiwan

This study aims to identify key factors affecting energy-induced CO₂emission changes from 34 industries in Taiwan, in order to have an integrated understanding of the industrial environmental-economic-energy performance and to provide insights for relevant policy making in Taiwan. Grey relation analysis was used in this paper to analyse how energy-induced CO₂emissions from 34 industries in Taiwan are affected by the factors: production, total energy consumption, coal, oil, gas and electricity uses. The methodology was modified by taking account of the evolutionary direction among relevant factors. Furthermore, tests of sensitivity and stability, which are seldom discussed in most grey relation analyses, were conducted to ensure the reliability of outcomes. We found that values ranging from 0·3 to 0·5 are appropriate, and the analytical results with value of 0·5 offer moderate distinguishing effects and good stability. Results indicate that industrial production has the closest relationship with aggregate CO₂emission changes; electricity consumption the second in importance. It reveals that the economy in Taiwan relied heavily on CO₂intensive industries, and that electricity consumption had become more important for economic growth. The relational order of fuels is electricity, coal, oil then gas, accordant with their CO₂emission coefficients in Taiwan. The positive relational grade of aggregate production implies that the aggregate industrial CO₂intensity tended to decline. The total energy consumption had a smaller and negative relational grade with CO₂emissions, and implies an improvement on aggregate energy intensity, while the CO₂emission coefficient increased. For industries with significant influence on CO₂emissions, the total energy consumption had the largest relational grades. It is important to reduce the energy intensity of these industries. Nevertheless, it is also critical to decouple energy consumption and production to reduce the impacts of CO₂mitigation on economic growth.     

Potential for electricity savings by reducing potable water consumption in a city scale

Nowadays, it is very important that water and energy resources are used appropriately as this is a challenge to promote sustainable development. In some sectors, such as water and sewerage utilities, energy consumption depends on water consumption. The main objective of this work is to estimate the potential for electricity savings in a water and sewerage utility by reducing potable water consumption in the residential, commercial and public sectors in the city of Florianópolis, southern Brazil. These three sectors account for 98.9% of the total water consumption in the city. By using data related to energy consumption and costs that apply to the local water utility for water and sewage treatment, and also the potential for potable water savings over the three sectors, it is possible to estimate the potential for energy savings by reducing potable water consumption and sewage treatment. Potable water savings were estimated by using data available in the literature about water end-uses for different types of buildings located in Florianópolis. Three options were considered: installing dual-flush toilets, reusing greywater and using rainwater. The average potential for potable water savings were 30.0%, 53.4% and 60.3%, respectively, for the residential, commercial and public sectors. Thus, the average potable water savings amount to about 10,153,835 m³/year, and the electricity savings amount to 4.4 GW h/year, which would be enough to supply 1217 houses or flats in Florianópolis, with an average energy consumption of 300 kW h/month.     

Accuracy improvement of various short-term load forecasting models by a novel and unified statistical data-filtering method

ABSTRACT

Time-series and machine-learning methods are being strongly exploited to improve the accuracy of short-term load forecasting (STLF) results. In developing countries, power consumption behaviors could be suddenly changed by different customers, e.g. industrial customers, residential customers, so the load-demand dataset is often unstable. Therefore, reliability assessment of the load-demand dataset is obviously necessary for STLF models. Hence, this paper proposes a novel and unified statistical data-filtering method with the best confidence interval to eliminate unexpected noises/outliers of the input dataset before performing various short-term load forecasting models. This proposed novel data-filtering method, so-called the data pre-processing method, is also compared to other existing data-filtering methods (e.g. Kalman filter, Density-Based Spatial Clustering of Applications with Noise, Wavelet transform, and Singular Spectrum Analysis). By using an SCADA system?-based database of a typical 22kV distribution network in Vietnam, NYISO database, and PJM-RTO database, case studies of short-term load forecasting have been conducted with a conventional ARIMA model, an ANN forecasting model, an LSTM-RNN model, an LSTM-CNN combined model, a deep auto-encoder (DAE) network, a Wavenet-based model, a Wavenet and LSTM hybrid model, and a Wavelet Neural Network (WNN) model, which are to validate the novel and unified statistical data-filtering method proposed. The achieved numerical results demonstrate which the accuracy of the aforementioned STLF models can be significantly improved due to the proposed statistical data-filtering method with the best confidence interval of the input load dataset. The proposed statistical data-filtering method can considerably outperform the existing data-filtering methods.     

The discursive framework of sustainability in UK food policy: the marginalised environmental dimension

ABSTRACT

In the context of food policy, sustainability functions as a normative principle but also constitutes a highly contested arena. The study presented in this paper establishes how discursive dynamics amongst professionals involved in matters of food distribution, retail, consumption and waste lead to food policy themes being framed as issues of sustainability. Analysing varied UK-based data (trade magazine articles, policy documents and interviews with retail, non-profit and consultancy representatives), three interpretative frames of sustainability are identified: consumer sovereignty, economic rationality and stewardship. Focusing on three themes of food sustainability – organic consumption, protein diversity and waste reduction – it is shown how these interpretative frames constitute the discursive framework relevant to food policy. Based on these findings, it is shown how in the analysed debates environmental concerns are sidelined.     

Changes in fuelwood use and selection following electrification in the Bushbuckridge lowveld, South Africa

Fuelwood is the primary energy source for domestic purposes throughout the developing world, in both urban and rural environments. Due to the detrimental impacts of biomass use on human and environmental health, many governments have sought to reduce its use through provision of potentially cleaner energies, of which electricity is the dominant form. Yet there are surprisingly few studies of changes in fuelwood use following the introduction of electricity, especially in rural areas of Africa. This paper reports on a longitudinal study of fuelwood use, using identical approaches, in five rural villages in the Bushbuckridge region of South Africa, spanning the period over which electricity became widely available. Almost a decade after the introduction of electricity, over 90% of households still used fuelwood for thermal purposes, especially cooking, and the mean household consumption rates over the 11-year period had not changed, even with a policy of 6 kWh per month of free electricity. The proportion of households purchasing fuelwood had increased, probably in response to a number of factors, including (i) increased fuelwood scarcity in the local environment as reflected by increased fuelwood collection times, changes in fuelwood species preferences, and ranking of scarcity by local collectors, and (ii) increases in the price of fuelwood well below that of other fuels and the prevailing inflation rate. Overall, there was an increase in the number of species harvested over the 11-year period. The implications of these findings for rural energy provision are discussed.     

Thinking Habits into Action: The role of knowledge and process in questioning household consumption practices

Despite occupying a central place in the sustainable development paradigm, calls for individuals in high-income countries to adopt patterns of sustainable consumption have failed to gain ground in the past decade. The low uptake of public messages that emphasise links between the environment and the home are caused by a plethora of 'barriers to action', which range from individual circumstances to public norms and structures. This article argues that in addition to these barriers, consideration of how individuals read and react to sustainable consumption information is important. Based on interviews with participants of a sustainable behaviour change programme called Action at Home, this article considers both how, and in what form, knowledge is mobilised when individuals rethink their personal practices. Using Giddens' structuration theory, a framework is presented. This framework emphasises the importance of 'known' or 'local' information, as well as discursive processes, in addressing individual consumption practices and argues that a 'cultural politics' of sustainable consumption needs to be factored into on-going academic and policy debates.     

居民生活用电碳排放交易机制研究

个人排放交易被认为可以促进居民参与碳减排,但是因其减排收益难以覆盖高昂的建立和运行成本,降低了公众接受度。本文提出除了考虑碳减排的收益外,更需要关注个人排放交易机制的教育价值、形成正确的激励以及鼓励创新的价值,并提出可以基于当前国内多地实行的阶梯电价制度,利用电力系统现有的用户网络和账户系统,建立居民生活用电碳排放交易机制,以降低成本并实现上述价值。在此基础上,就居民生活用电碳排放交易机制的配额设定与分配、配额交易以及清缴问题做了细致的分析,并提出绿色电力作为补充电力可以免费获得碳配额以促进绿色消费。同时,比较分析了在居民生活用电交易机制和阶梯电价制度下,不同居民家庭以及电力公司的用电成本(收益),指出了其在形成正确的激励方面的作用。最后指出在条件成熟的情况下,居民生活用电碳排放交易机制可以扩展到居民的其他能源消费领域,以实现更为全面的个人排放交易。     

Modeling Hydraulic and Thermal Electricity Production Based on Genetic Algorithm-Time Series (GATS)

Abstract

This study deals with the estimation of electricity production from hydraulic and thermal sources using the Genetic Algorithm (GA) with time series (TS) approach. Two forms of the mathematical models are developed, of which one is exponential and the second is polynomial. The power form of the Genetic Algorithm-Time Series (GATS) model is used for the thermal electricity production. The polynomial form of the GATS is used for the electricity production from the hydraulic sources. The GATS weighting parameters are obtained by minimizing the Sum of Squared Error (SSE) between observed and estimated electricity production from both sources. Therefore, the fitness function adapted is the minimization of the SSE for use in the GA process. The application of the GATS model is correspondingly presented. Some future scenarios are made to increase the electricity production from hydraulic sources. Variations of the electricity production from thermal and hydraulic energy sources are analyzed. Future prospects of electricity production are dealt with in terms of policy changes. The GATS models are used for making scenarios for future electricity planning policy. Results also show if current trend continues, the thermal electricity production amounts to 75% of the total electricity production, which is undesirable for environmental concerns. Results also shows that if new policy is to move from the thermal to hydraulic electricity production, the hydraulic sources will meet the demand until 2020.     

Mitigation of power sector environmental emissions through energy efficiency improvements: the case of Pakistan

This paper assesses the potential of selected efficient electrical appliances for avoiding power generation and for mitigation of selected air pollutants from the power sector in Pakistan from technical as well as national, utility and user perspectives. The study shows that about 14, 21 and 35% of the total CO₂, SO₂and NO_xemissions in the business as usual (BAU) case could be avoided by the adoption of selected efficient appliances during 1997–2015 from the national perspective, while the corresponding figures from the user perspective are 12, 17 and 29%, respectively. All selected efficient appliances would be cost effective to the users if electricity prices were set at the long-run marginal cost of supply.1998 Academic Press     

Automated energy management in distributed electricity systems: An EEPOS approach

The increasing capacity of distributed electricity generation brings new challenges in maintaining a high security and quality of electricity supply. New techniques are required for grid support and power balance. The highest potential for these techniques is to be found on the part of the electricity distribution grid.

This article addresses this potential and presents the EEPOS project’s approach to the automated management of flexible electrical loads in neighborhoods. The management goals are (i) maximum utilization of distributed generation in the local grid, (ii) peak load shaving/congestion management, and (iii) reduction of electricity distribution losses. Contribution to the power balance is considered by applying two-tariff pricing for electricity.

The presented approach to energy management is tested in a hypothetical sensitivity analysis of a distribution feeder with 10 households and 10 photovoltaic (PV) plants with an average daily consumption of electricity of 4.54 kWh per household and a peak PV panel output of 0.38 kW per plant. Energy management shows efficient performance at relatively low capacities of flexible load. At a flexible load capacity of 2.5% (of the average daily electricity consumption), PV generation surplus is compensated by 34–100% depending on solar irradiance. Peak load is reduced by 30% on average. The article also presents the load shifting effect on electricity distribution losses and electricity costs for the grid user.     

Hybrid input-output analysis to evaluate economic impacts of biomass energy

ABSTRACT

The introduction of the new biomass industry exerts influences that change the interactions among economic sectors by drawing the resources for generating electricity, pricing alterations from the existing market and competitively selling electricity to the power grid. These influences should be described and identified to ensure the benefits to the local economy. In this article, we deem to test the potential of hybrid I-O analysis to analyze the economic impacts and address the change in characteristics of the economic impacts of the biomass power plant. The resource utilization data from the existing biomass power plant located in Kochi Prefecture (Japan) is collected and then analyzed by a hybrid input-output (I-O) analysis. We found that (1) the use of cutoff function could determine the new economy’s structure included the biomass power plant where the allocation of resource in the economy is changed according to the consumption and production of the biomass power plant, (2) The power plant increases the total production of Kochi prefecture’s economy, and this benefit overthrows the negative effect of the loss of resource demand of the existing economic sectors. The use of the hybrid I-O to forecast the economic impacts on the local economy could enhance the decision made by the policymaker.     

Cost-benefit analysis of central softening for production of drinking water

Softening drinking water before distribution yields advantages with environmental impact, such as lower household products consumption, less scaling in piping and machines, and the avoidance of decentralized, domestic softeners. Central softening is under consideration in Flanders by the largest water supplier, VMW (Dutch acronym for “Flemish Company for Water Supply”), to deliver soft (15 °F) water to their customers. A case study is presented for a region with hard water (47 °F). The chosen technique is the pellet reactor, based on precipitation of CaCO₃ by NaOH addition. This softening operation has possibly large impact on the environment and the water consumption pattern.A cost-benefit analysis has been made to estimate the added value of central softening, by investigating the impact on the drinking water company, on their customers, on employment, on environment, on health, etc. The analysis for the region of study revealed benefits for customers which were higher than the costs for the drinking water company. However, pricing of drinking water remains an important problem.A sensitivity analysis of these results has also been made, to evaluate the impact of important hypothesis, and to be able to expand this study to other regions. The conclusions for this part show that softening is beneficial if water hardness is to be decreased by at least 5 °F.     

Smart meters for enhanced water supply network modelling and infrastructure planning

To design water distribution network infrastructure, water utilities formulate daily demand profiles and peaking factors. However, traditional methods of developing such profiles and peaking factors, necessary to carry out water distribution network modelling, are often founded on a number of assumptions on how top-down bulk water consumption is attributed to customer connections and outdated demand information that does not reflect present consumption trends; meaning infrastructure is often unnecessarily overdesigned. The recent advent of high resolution smart water meters allows for a new novel methodology for using the continuous ‘big data’ generated by these meter fleets to create evidence-based water demand curves suitable for use in network models. To demonstrate the application of the developed method, high resolution water consumption data from households fitted with smart water meters were collected from the South East Queensland and Hervey Bay regions in Australia. Average day (AD), peak day (PD) and mean day maximum month (MDMM) demand curves, often used in water supply network modelling, were developed from the herein created methodology using both individual end-use level and hourly demand patterns from the smart meters. The resulting modelled water demand patterns for AD, PD and MDMM had morning and evening peaks occurring earlier and lower main peaks (AD: 12%; PD: 20%; MDMM: 33%) than the currently used demand profiles of the regions’ water utility. The paper concludes with a discussion on the implications of widespread smart water metering systems for enhanced water distribution infrastructure planning and management as well as the benefits to customers.     

Private sector participation in urban water and sanitation: Realising social and environmental objectives in developing countries

There has been a large increase in private sector participation (PSP) in the urban water supply and sanitation (WSS) sector in recent years. However, even with increased PSP, public authorities will still have to: ensure that the service providers do not use their market power to exploit customers; internalise public health and environmental externalities; provide mechanisms whereby water consumption is sustainable and allocated efficiently between alternative uses; and stand as a guarantor of a level of service provision that is consistent with a basic standard of living. While there is considerable literature addressing the first of these four issues, the latter three are rather less adequately addressed. Through a review of a number of case studies (Abidjan, Buenos Aires/Cordoba, Mexico City and Manila), this paper provides an overview of the issues involved and some of the mechanisms available to the authorities responsible for the regulation of the sector.     

Novel electricity-saving concept using a radio technique for indoor lighting

This study proposes a novel concept for designing a radio switch that can match workplace characteristics and personal needs by individually controlling the lighting group to save electricity. We use a microcontroller that can achieve the function of timing, turned-on and turn-off by setting the internal program to control the radio switch for convenient use, and electricity saving. As compared with the traditional mechanical switch, the radio switch reduced the electricity consumption by 38.64 kwh/week (86.25% of ideal condition or 1194.62% of practical condition), and the annual CO₂ emission can be reduced by 1032.2 kg/year. Additionally, the cost of the radio switch to replace the traditional mechanical switch can be paid back in 1.72 years.     

CO2-free paper?

Black liquor gasification–combined cycle (BLGCC) is a new technology that has the potential to increase electricity production of a chemical pulping mill. Increased electricity generation in combination with the potential to use biomass (e.g. bark, hog fuel) more efficiently can result in increased power output compared to the conventional Tomlinson-boiler. Because the BLGCC enables an integrated pulp and paper mill to produce excess power, it can offset electricity produced by power plants. This may lead to reduction of the net-CO₂ emissions. The impact of BLGCC to offset CO₂ emissions from the pulp and paper industry is studied. We focus on two different plant designs and compare the situation in Sweden and the US. The CO₂ emissions are studied as function of the share of recycled fibre used to make the paper. The study shows that under specific conditions the production of “CO₂-free paper” is possible. First, energy efficiency in pulp and paper mills needs to be improved to allow the export of sufficient power to offset emissions from fossil fuels used in boilers and other equipment. Secondly, the net-CO₂ emission per ton of paper depends strongly on the emission reduction credits for electricity export, and hence on the country or grid to which the paper mill is connected. Thirdly, supplemental use of biomass to replace fossil fuel inputs is important to reduce the overall emissions of the pulp and paper industry.     

Community-based participatory research: Changing scientific practice from research on communities to research with and for communities

The Agenda 21 treaty adopted at the 1992 United Nations Conference on Environment and Development set out new goals for the provision and management of information in a sustainable society. New information and communications technologies (ICTs) have the potential to be used as tools for managing information and consequently have a role in sustainable development. This paper considers the use of ICTs to manage local information areas and the extent to which these new technologies are compatible with the broader goals of Agenda 21 such as social inclusion and public participation in decision making. The use of the World Wide Web by local authorities in the UK to manage local information and promote Agenda 21 is explored through a critique of website contents. It is concluded that, although the use of ICTs is not incompatible with the broader aims of Agenda 21, and has many possible positive applications, current use of the World Wide Web by local government in the UK does not yet fulfil this potential.     

A disaggregated emissions inventory for Taiwan with uses in hybrid input‐output life cycle analysis (IO‐LCA)

This paper reports on a life‐cycle analysis (LCA) of Taiwan's “agriculture and forestry”, “crude petroleum, coal and natural gas extraction” and “electricity generation” sectors, revealing for the first time Taiwan's CO₂ and CH₄ emissions inventories and matching Taiwan's input‐output sectors. Integrated hybrid input‐output life cycle analysis is used to disaggregate the electricity generation sector into nuclear, hydro, gas, oil and coal, and cogeneration. Results show that the fossil‐fuel‐related electricity sub‐sectors have higher CO₂ emissions intensity than the remaining sectors in the economy and that the “paddy rice” sector is Taiwan's most CH₄‐intensive sector, making rice cultivation an important source of CH₄ emissions. This work is vital to sound policy decisions concerning power generation, coal, and agriculture and forestry at the national level.