Dissertations / Theses on the topic 'Time-Of-Use tariffs of electricity'

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics<br>This work project consists on the proposal of a product/service – Variable Time of Use Tariff – to enhance the innovativeness of the portfolio of EDP Comercial. This product/service is dependent on the simultaneous use of a smart meter, a home energy manager and a set of smart domestic appliances. To sustain my proposal I resorted to data about the wind energy, the use of smart meters together with time of use tariffs and the general characteristics of tariff structures in Europe. A SWOT analysis follows the description of the product/service, with one threat and one opportunity standing as major issues. The feasibility of the implementation of the tariff I propose depends entirely the future of these two factors, thus making this work project a future looking one.

L'industrie est le plus grand consommateur d'énergie dans le monde et la majeure partie de sa consommation est électrique. Pour moduler la consommation et équilibrer les périodes creuses et de pic, les producteurs d'électricité dans de nombreux pays pratiquent une tarification différenciée, en anglais "time-of-use (TOU) policy", afin d’encourager les industriels et les particuliers à adapter leur consommation. Cette stratégie incite les gros consommateurs industriels, en particulier le secteur semi-conducteur où la fabrication se fait souvent par lots, à réduire leurs factures d’électricité en adaptant leur production.Dans ce travail, nous étudions plusieurs problèmes d’ordonnancement de production par lots avec tarification différenciée d'électricité. Nous nous intéressons d’abord à l’ordonnancement d’une machine par lots pour minimiser le coût total d’électricité et le makespan. Le deuxième problème étudié généralise le premier en considérant le coût d’électricité pendant les périodes inactives de la machine telles que les périodes de réglage ou d'attente. Enfin, nous traitons l’ordonnancement sur machines parallèles par lots avec des pièces non identiques. Pour chacun de ces problèmes, nous construisons des modèles mathématiques appropriés, et évaluons sa complexité. Pour la résolution, nous proposons plusieurs méthodes de ɛ-contrainte dans lesquelles des sous-problèmes sont transformés en problèmes de sac-à-doc, de sacs-à-doc multiples et ou de bin packing. Nous développons aussi une méthode itérative à deux étapes. Les performances des méthodes développées sont évaluées à l'aide d'un grand nombre d'instances représentatives générées au hasard. Les résultats numériques montrent l'efficacité de ces méthodes par rapport au logiciel commercial CPLEX<br>The industrial sector is the largest consumer of the world's total energy and most of its consumption form is electricity. To strengthen the grid's peak load regulation ability, time-of-use (TOU) electricity pricing policy has been implemented in many countries to encourage electricity users to shift their consumption from on-peak periods to off-peak periods. This strategy provides a good opportunity for manufacturers to reduce their energy bills, especially for energy-intensive ones, where batch scheduling is often involved. In this thesis, several bi-objective batch scheduling problems under TOU tariffs are studied. We first investigate a single machine batch scheduling problem under TOU tariffs with the objectives of minimizing total electricity cost and makespan. This primary work is extended by further considering machine on/off switching. Finally, a parallel batch machines scheduling problem under TOU tariffs with non-identical job sizes to minimize total electricity cost and number of enabled machines is studied. For each of the considered problems, appropriate mathematical models are established, their complexities are demonstrated. Different bi-objective resolution methods are developed, including knapsack problem heuristic based ɛ-constraint method, multiple knapsack problem heuristic based ɛ-constraint method, bin packing heuristic based ɛ-constraint method and two-stage heuristic based iterative search algorithm. The performance of the proposed methods is evaluated by randomly generated instances. Extensive numerical results show that the proposed algorithms are more efficient and/or effective for the studied problems than the commercial software CPLEX

The thesis investigates the application of ice thermal storage technology to situations where the price of electricity varies continuously with instantaneous network demand. A central hypothesis is postulated in chapter 1, which states: "A variable electricity pricing structure, in which unit price continuously varies in response to instantaneous network demand, enhances the opportunities and benefits of ice thermal storage. The benefits both financial and environmental are dependent on the establishment of control and design strategies which optimise performance by matching refrigeration load with the instantaneous electricity price. " For ease of reference, the form of pricing described above is referred to in the thesis as 'real time' electricity pricing. The 'pool price' which is used to facilitate the competitive electricity awkct in England and Wales, is one of the foremost examples of real time pricing. The thesis therefore uses the electricity supply industry in the UK as its research vehicle. Notwithstanding this, the work contained in the thesis can be applied to any country which applies real time electricity pricing mechanisms. The validity of the hypothesis is assessed in the thesis through the development of a variety of numerical and computer models. These models fall into two distinct categories; those concerned with predicting and optimising the financial benefits of ice thermal storage, and those concerned with predicting and optimising the environmental benefits of ice thermal storage. Chapters 2,3 and 4 should be treated as support chapters, which equip the reader with the prerequisite knowledge necessary to understand the research work contained in the later chapters. As such, these chapters contain, respectively, a description of the electricity supply industry in the UK, a discussion of demand side management in the UK, and a description of the technology involved in ice thermal storage. The parametric study contained in chapter 4 is however an original piece of research work by the author. The models developed to evaluate and optimise the economic benefits of ice thermal storage are presented in chapters 5 and 6, and are applied to contrasting theoretical case study applications, namely an office building and a dairy. In chapter 5a 'long hand' numerical analysis technique is used. In chapter 6 this technique is rationalised and developed into a computer model for optimising both the design and control of ice storage installations in real time electricity pricing applications. The environmental studies are presented in chapter 7. These concentrate on the ability of ice thermal storage to reduce carbon dioxide emissions. Although the overall objective of the chapter is to evaluate the carbon dioxide emissions associated with ice thermal storage, the bulk of the chapter is concerned with the development of a model for predicting the carbon dioxide emissions per kWh of delivered electrical energy in England and Wales on a time related basis. The development of this 'time of day' carbon dioxide model is one of the main objectives of the thesis. Having established this model, it is then used to analyse the carbon dioxide emissions associated with the dairy case study.

Residential demand is a large and important factor of the utility load during the system peak period. And the control of residential demand can make a significant change to the system load of the utility. This research is designed to study the residential end-use appliances under various direct load control schemes. These appliances are water heaters, air conditioners, and space heaters which are the major electrical demand of the residential load. The study will apply the LOADSIM, an Electrical Power Research Institute (EPRI) load simulation program, to conduct load control strategies of these residential appliances. The LOADSIM program can be applied both for cycling and shedding control strategies during a specified control period. In this study, the cycling control is done on an air conditioner and space heater. The water heating control is performed under shedding strategy. The research has studied the appliance use of four house types under the same weather and control conditions. A total of 100,000 houses have been used in the study. These houses have the same dwelling and appliance characteristics but their house insulations are different. Diversity in house insulations gives different results in terms of load reduction and temperature change due to the load control. For example, a better-insulated house demands less electricity for its appliance than a low-insulated house. This study also uses the EPRl-LOADSIM program to estimate the load reduction and temperature change of each house type under the load control.<br>Master of Science

The 2008 Climate Change Act set legally-binding carbon reduction targets. Demand side management (DSM) includes energy use reduction and peak shaving and offers significant potential to reduce the amount of carbon used by the electricity grid. The demand side management (DSM) schemes that have tried to meet this challenge have been dominated by engineering-based approaches and so favour tools like automation (which aims to make shifting invisible) and pricing (which requires customer response) to shift demand. These approaches tend to focus on the tools for change and take little account of people and energy-use practices. This thesis argues that these approaches are limited and therefore unlikely to produce the level of response that will be needed in future. The thesis therefore investigates the potential for time-shifting domestic energy demand but takes a different angle by trying to understand how people use energy in their daily lives, whether this use can be shifted and some of the implications of shifting it. The centrepiece of the work is an empirical study of eleven households energy-use practices. The interdisciplinary methodology involved in-house observations, interviews, photographs, metered energy data and disruptive interventions. The data was collected in two phases. Initially, a twenty-four hour observation was carried out in each household to find out how energy was implicated in everyday practices. Next, a series of three challenges were carried out, aimed at assessing the implications of disrupting practices by time-shifting food preparation, laundry and work/ leisure. A practice theory approach is used to shift the focus of attention from appliances, tools for change, behaviour or even people, to practices. The central finding of this work is that practices were flexible. This finding is nuanced, in the light of the empirical research, by an extended discussion on the nature of practices; in particular, the relationship between practices and agency and the temporal-spatial locatedness of practices. The findings demonstrate that, in this study at least, expanding the range of demand response options was possible. The research suggests numerous possibilities for extending the potential of practices to shift in time and space, shift the energy used in practices or substitute practices for other non-energy-using practices, though there are no simple technological or behavioural fixes . More profoundly, however, the thesis concludes that infrastructures of provision , such as the electricity grid and the companies that run it, underpin and facilitate energy-use practices irrespective of the time of day and year. In this context technology-led demand response schemes may ultimately contribute to the problem they purport to solve. A more fundamental interrogation of demand and the infrastructures that serve it is therefore necessary and is almost entirely absent from the demand response debate.

Master of Science<br>Department of Electrical and Computer Engineering<br>Anil Pahwa<br>With the Smart Grid trend setting in, various techniques to make the existing grid smarter are being considered. The price of electricity is one of the major factors, which affects the electric utility as well as the numerous consumers connected to the grid. Therefore deciding the right price of electricity for the time of day would be an important decision to make. Consumers’ response to this change in price will impact peak demand as well as their own annual energy bill. Owning a small wind generator under the Critical Peak Pricing (CPP) and Time of Use (TOU) price-based demand response programs could be a viable option. Economic evaluation of owning a small wind generator under the two pricing schemes, namely Critical Peak Pricing (CPP) and Time of Use (TOU), is the main focus of this research. Analysis shows that adopting either of the pricing schemes will not change the annual energy bill for the consumer. Taking into account the installed cost of the turbine, it may not be significantly economical for a residential homeowner to own a small wind turbine with either of the pricing schemes in effect under the conditions assumed.

This thesis describes the trial design and analysis of the Low Carbon London (LCL) residential dynamic Time-of-Use (dToU) trial. This trial investigated the potential for dToU tariffs to deliver residential demand response to the Supplier, where it may contribute to system balancing through Supply Following (SF) actions, and to the distribution network operator (DNO), where it may be used for network Constraint Management (CM). 5,533 households from the London area participated in the trial and their consumption was measured at 30 minute resolution. 1,119 of these received the dToU tariff, which subjected them to CM and SF price events that were designed according to the specific requirements of these respective use cases. A novel, data driven, engagement ranking index was developed that allowed stratification of subsequent results into sets of the most engaged consumers, who may be indicative of a future populace that is more experienced/engaged in home energy management. Demand response (DR) was calculated relative to baseline model that used the dToU group mean demand as an input, with aggregate response levels calculated over a range of time, socio-economic and household occupancy related variables. Taking a network perspective, the reliability of CM event response was examined and two simple linear models presented as candidate predictors of response level, which was found to be consistent with an 8% reduction in demand. The network capacity contribution of residential DR was theorised to consist of two components: 'mean response' and 'variance response', and the real impact of these was investigated using the LCL gathered data. Potential risks to the network from low price induced demand spikes were explored empirically using the SF event data and the times of highest risk were identified. The extensive metadata set gathered from trial participants was processed into some 200 numerical variables. A correlation analysis was performed which was visualised using weighted correlation network graphs. A number of parameters were found to predict response level, but responsiveness (the level of deliberate engagement) could only be reliably measured by engagement rank.

Suppliers in competitive electricity markets regularly respond to prices that change hour by hour or even more frequently, but most consumers respond to price changes on a very different time scale, i. e. they observe and respond to changes in price as reflected on their monthly bills. This thesis examines mixed complementarity programming models of equilibrium that can bridge the speed of response gap between suppliers and consumers, yet adhere to the principle of marginal cost pricing of electricity. It develops a computable equilibrium model to estimate the time-of-use (TOU) prices that can be used in retail electricity markets. An optimization model for the supply side of the electricity market, combined with a price-responsive geometric distributed lagged demand function, computes the TOU prices that satisfy the equilibrium conditions. Monthly load duration curves are approximated and discretized in the context of the supplier's optimization model. The models are formulated and solved by the mixed complementarity problem approach. It is intended that the models will be useful (a) in the regular exercise of setting consumer prices (i. e. , TOU prices that reflect the marginal cost of electricity) by a regulatory body (e. g. , Ontario Energy Board) for jurisdictions (e. g. , Ontario) where consumers' prices are regulated, but suppliers offer into a competitive market, (b) for forecasting in markets without price regulation, but where consumers pay a weighted average of wholesale price, (c) in evaluation of the policies regarding time-of-use pricing compared to the single pricing, and (d) in assessment of the welfare changes due to the implementation of TOU prices.

Thesis advisor: Scott Fulford<br>Can smart metering program and time-of-use (TOU) prices help reduce energy consumption in New York City? Being able to track electricity consumption levels and to modify consumer usage patterns are important for policy makers to efficiently manage the energy markets. Unfortunately, no reliable and up-to-date data have been brought to bear on this question. I study the effects of time-of-use (TOU) prices and smart metering for the residents of Shanghai and I investigate further what can policy makers do in order to adapt and transfer this successful DSM experience from Shanghai to the residential sector in New York City. The primary objective of my study is to characterize the realistic short-term and long-term potential for the smart metering program in New York City given my empirical findings that the smart metering program has had brought great benefits to the residents of Shanghai. People respond to incentives; if electricity is charged at different prices throughout a day, consumers are likely to shift their usage to when it is cheaper. My findings suggest that policy makers should think harder about designing a pricing scheme that can optimize the social plus<br>Thesis (BA) — Boston College, 2011<br>Submitted to: Boston College. College of Arts and Sciences<br>Discipline: College Honors Program<br>Discipline: Economics Honors Program<br>Discipline: Economics

M.Com. (Business Management)<br>The residential demand profile for electricity shows that this segment of the market has. a great demand in the morning and early evening. Due to a shortage of generation capacity during these peak consumption periods, different strategies are now needed to persuade customers to use their electricity in the periods when there is not a great demand. One way in which this can be achieved is to give the customers a time differentiated tariff i.e. a time-of-use (TOU) tariff, whereby the customer will pay a high energy rate in the peak periods, and lower energy rates in the off-peak and standard periods. The overall goal of this study was to determine to what extent residential customers would respond to such a tariff The study covered three consumption groups i.e. customers using more than 1500 kWh per month, between 600 and 1000 kWh per month, and between 300 and 600 kWh per month. All the customers taking part in the study were direct Eskom customers. Once the customers had agreed to participate in the study, they had TOU measuring equipment installed in their homes, which measured their consumption according to the time of day it was consumed.

One way of energy conservation and Greenhouse Gases (GHG) reduction is a more rational energy consumption. However, increased energy efficiency does not always leads to the desired outcomes regarding the reduction of consumption and consequently the reduction of GHG. The effect that makes it impossible to obtain the totality of benefits due to increasing energy efficiency is known as the rebound effect. This study aims to focus on rebound effect, controlling them by setting different prices according to the consumption period. A family production function is developed incorporating the electricity consumption, dividing them between peak and off-peak periods. The function for the direct rebound effect is calculated through the elasticity of electricity service comparing to the increased energy efficiency. The consumption variations are thus obtained in each of the periods that are associated with a particular direct rebound effect. In this perspective, a new Time-of-Use tariff (TOU) dual tariff is defined wherein the prices vary in order to cancel the full rebound effect. This way, the increased energy efficiency causes a further decrease of consumption in the critical period (peak period), promoting the smooth of the load diagram. It is proposed a partial sectioning of the dispatch priority of renewables based electricity in a special regime (SR). This procedure allows freeing resources to promote greater energy efficiency. Increased energy efficiency will be accompanied by the TOU tariff we are proposing, making these actually effective efficiency gains, since the proposed tariff ensures the control of RE.<br>Uma das formas de conservação de energia e de redução dos Gases de Efeito Estufa (GEE) é a utilização mais racional no consumo. No entanto, nem sempre o aumento da eficiência conduz à diminuição do consumo e consequentemente à diminuição dos GEE. O efeito da não obtenção da totalidade dos benefícios decorrentes do aumento da eficiência da energia é conhecido como rebound effect. Assim, este trabalho tem como objetivo focar-se no rebound effect, controlando-o através da definição de preços diferenciados consoante o período de consumo. É desenvolvida uma função de produção familiar que incorpora o consumo de eletricidade, diferenciando-o nos períodos em pico e em fora de pico. Calcula-se a função para o rebound effect direto através da elasticidade do serviço em eletricidade em relação ao aumento da eficiência de energia. Obtém-se as variações de consumo, em cada um dos períodos, que estão associadas a determinado rebound effect direto. Nesta perspetiva, é definida uma nova tarifa time-of-use (TOU) (bi-horária) sendo que os preços variam com o objetivo de anular o rebound effect total. Desta forma, o aumento da eficiência em energia provoca uma maior diminuição do consumo no período mais crítico (período de pico), promovendo a suavização do diagrama de carga. Propõe-se corte parcial da prioridade de despacho da eletricidade de base renovável em regime especial libertando assim recursos para promover maior eficiência de energia. O aumento da eficiência em energia será acompanhado pela nova tarifa TOU, tornando esses ganhos de eficiência efetivamente eficazes, uma vez que a tarifa proposta assegura o controlo dos RE.

碩士<br>大同大學<br>電機工程學系(所)<br>99<br>Since the energy price fluctuates significantly and many countries face economic crisis, it will be an important issue to reduce expense and conserve the energy. Regarding energy conservation, including the improvement of electric equipment efficiency, it has the significant achievement. There are many successful cases and well-developed technologies of the load reduction in the peak period and the load shifting to the off-peak period. However, the study on the target value’s optimization of the controlling electric expense is very rare. In modern power system, beside the time-of-use tariff, the hardware facilities of Hi-Tech are the essential condition. The intelligent meter which is so-called smart meter has a great deal of functions, such as measurement, computation, memory, control and communication, etc. By combining the wireless communication and the information management system, the advanced metering infrastructure (AMI) has been developed successfully and adopted in many countries. This study, based on the AMI environment mentioned above, precedes electricity bill management. The factors of the usable electricity bill and the acceptable delay time should be considered. By using fuzzy theory to coordinate the cheaper electricity price and rescheduling the appliances, the electricity bill can be achieved to the expectable budget. Therefore, the advantage not only can conserve the energy and reduce the carbons, but also can achieve saving the electricity bill without sacrificing users’ comfort and convenience.

This thesis proposes equilibrium models to link the wholesale and retail electricity markets which allow for reconciliation of the differing time scales of responses of producers (e.g., hourly) and consumers (e.g., monthly) to changing prices. Electricity market equilibrium models with time of use (TOU) pricing scheme are formulated as large-scale variational inequality (VI) problems, a unified and concise approach for modeling the equilibrium. The demand response is dynamic in these models through a dependence on the lagged demand. Different market structures are examined within this context. With an illustrative example, the welfare gains/losses are analyzed after an implementation of TOU pricing scheme over the single pricing scheme. An approximation of the welfare change for this analysis is also presented. Moreover, break-up of a large supplier into smaller parts is investigated. For the illustrative examples presented in the dissertation, overall welfare gains for consumers and lower prices closer to the levels of perfect competition can be realized when the retail pricing scheme is changed from single pricing to TOU pricing. These models can be useful policy tools for regulatory bodies i) to forecast future retail prices (TOU or single prices), ii) to examine the market power exerted by suppliers and iii) to measure welfare gains/losses with different retail pricing schemes (e.g., single versus TOU pricing). With the inclusion of linearized DC network constraints into these models, the problem size grows considerably. Dantzig-Wolfe (DW) decomposition algorithm for VI problems is used to alleviate the computational burden and it also facilitates model management and maintenance. Modification of the DW decomposition algorithm and approximation of the DW master problem significantly improve the computational effort required to find the equilibrium. These algorithms are applied to a two-region energy model for Canada and a realistic Ontario electricity test system. In addition to empirical analysis, theoretical results for the convergence properties of the master problem approximation are presented for DW decomposition of VI problems.

碩士<br>國立臺中科技大學<br>企業管理系碩士班<br>107<br>The electricity cost accounts for about 4% of the annual turnover of Company F. According to the study, the saved electricity cost has been over 10 million NTD accumulatively in recent 8 years. The current total charge of Taiwan Power Company consists of 5 parts including basic charge, energy charge, power factor clause, penalty charge and others. Based on the actual electricity consumption data of Company F, this study conducted regression and variation analyses with SPSS statistical software and found out the effects of optimized contract capacity and time-of-use on electricity cost. The results show that: contract capacity is positively related to basic charge, unrelated to energy charge, negatively related to power factor clause, inversely proportional to penalty charge and quadratically related to payable total charge. The lowest position is found out, namely, the optimized contract capacity and the minimum payable total charge. The payable total charge has significant effects on contract capacity and basic charge and penalty charge. It is more advantageous for Company F to choose 3-secion time-of-use than the 2-secion time-of-use, but affected by the policy of “one regular leave day and one rest day”, the difference of time-of-use becomes insignificant. Because the optimized contract capacity is stable in recent 3 years, Company F is suggested to reduce the original contract capacity of 2,880 KW to 2,500 KW. In this way, the basic charge of about NTD 847,000 may be reduced, but the penalty charge may be occured in summer. It is expected that this study can be helpful for enterprises to optimize contract capacity and choose time-of-use.

Through the Smart Metering Initiative in the Canadian province of Ontario, all residential electricity customers will be converted from a tiered rate regime to a time-of-use (TOU) rate regime by the year 2010. Although TOU rates are designed to be cost-neutral for the average consumer, research suggests that TOU rates may affect consumers differently depending on their socioeconomic characteristics. In an effort to better understand the effects of TOU rates on lower-income and senior-headed households, a case-study in Milton was conducted between June and December of 2007. The overarching thesis question is: What are the behavioural responses to, and financial impacts of, TOU electricity rates on lower-income and senior-headed households? Nine expert interviews were conducted with Ontario professionals working in government, environmental non-profit groups, citizen advocacy organizations and affordable housing associations in order to provide context for the study. Time-differentiated electricity consumption data were then collected from 199 households from two senior housing complexes and two affordable housing complexes in Milton, Ontario between June and December 2007. A questionnaire was also sent to each household to determine some socio-economic and structural characteristics of the households. The electricity consumption data collected from the four sites suggest that the households would not benefit financially from TOU rates given electricity consumption behaviour during the period prior to the implementation of TOU rates in June 2007. Thus, they would have to change their behaviour in order to benefit financially from TOU rates. During this pre-TOU period, Site A, Site B and Site C would have paid more, on average, for their electricity under TOU rates than on tiered rates ($0.34, $0.61 and $0.15 per week, respectively). While Site D, on average, would have seen no change under TOU rates. A conservation effect was detected by comparing the electricity consumption from billing periods in 2006 to corresponding billing periods in 2007 after the implementation of TOU rates. Site A saw a conservation effect during the first corresponding billing period (35%); while Site B saw a conservation effect for three corresponding billing periods (21%, 24% and 9%). Site C saw a conservation effect for the first five corresponding billing periods (ranging from 8% to 21%), while Site D saw a conservation effect for all corresponding billing periods (ranging from 10% to 34%). The presence of a conservation effect at Site D was unexpected, particularly because households at Site D are not responsible for paying their own electricity bills. Although a conservation effect was observed after the implementation of TOU rates, the extent to which it could be attributed to the implementation of TOU rates is unclear, and should be investigated further. There was no considerable shift in the proportion of electricity consumed during each of the peak periods during the summer TOU period for Site A and Site D after the introduction of TOU rates. There was, however, a slight reduction in the portion of electricity consumed during the summer TOU period for Site B and Site C (0.2% and 0.1% per week, respectively). Due to the change in the on-, mid- and off-peak schedule from the summer TOU period to the winter TOU period, the households consume more electricity during the off-peak periods in the winter than they do during the off-peak periods in the summer (even though their patterns of consumption do not change). Similar to the pre-TOU period, during the summer post-TOU period, Site A and Site B, and Site C, on average, paid more for electricity (commodity) under TOU rates than they would have paid if they had continued on tiered rates ($0.38, $0.51 and $0.16 more per week, respectively), while Site D would have seen no change in their electricity costs. In contrast, during the winter post-TOU period several sites paid less for electricity on TOU rates than they would have if they had continued on tiered rates. Site B, Site C and Site D paid, on average, $0.78, $0.16 and $1.76 less per week, respectively. Although Site A paid more under on TOU rates during the winter post-TOU (on average $0.18 more per week), the cost was less than during the summer post-TOU period. The change in costs expressed here does not reflect any reduced costs that may have resulted from conservation. For example, if the households were shown to have a conservation effect, they might have lower electricity costs. Additionally, the changes in costs do not reflect any additional fees or charges that might be attributed to the smart meter installation and the Smart Metering Initiative (e.g., additional fees from Milton Hydro). In conclusion, TOU rates appear to be ineffective at motivating these lower-income and senior-headed households in Milton, Ontario to shift electricity from on-peak periods to off-peak periods, however, a reduction in electricity usage may be attributed to TOU rates. Further research is required to confirm these effects. It is important to note that some of the lower-income and senior-headed households in this study appeared to see an increase in their electricity bill, particularly during the summer TOU period. Lower-income and senior-headed households are thought to be less able to shift electricity consumption, therefore it is important to develop mechanisms to identify households that are at risk of bill increases.

碩士<br>正修科技大學<br>資訊管理研究所<br>107<br>Scheduling problems can be seen everywhere in life, and the scheduling discussed in this research is to simulate manufacturing order scheduling. In the past, many dispatching companies did not consider capacity limitations, which caused the tardiness. This research explores the order acceptance scheduling problem (OAS), which considers the due day under the capacity constraints toward higher revenue. In recent years, many researchers have changed the study of environmental pollution and time-of-use electricity cost (TOU). It means that the cost of electricity has made a heavy burden on enterprises. Because no study combines the OAS with the TOU cost, it is the significant contribution of this research. We employed the model and benchmark instances from OĞUZ et al.[41], and add the TOU constraints and power consumptions into the model and instances, respectively. In order to solve this new problem, a genetic algorithm with the multi-layer perceptron (MLP) neural network is developed. We use MLP predicts the fitness function of the chromosomes and guide the evolution process. CPLEX is used to provide the upper bound value to validate the effectiveness of the proposed algorithm compared to stand genetic algorithms (SGA). We found the proposed algorithm founds better solutions than SGA in some instances, even though the computational time is higher.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in ful lment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2015<br>The work presented extends and contributes to research in Non-Intrusive Load Monitoring (NILM), focussing on steady-state and transient power measurement disaggregation techniques for circuits containing household ap- pliances. Although previous work in this area has produced and evaluated a wide range of NILM approaches, much of it has involved the use of datasets captured from real-world household implementations. In such cases, the lack of accurate ground truth data makes it di cult to assess disaggregation tech- niques. In the research presented, three NILM techniques are comparatively evaluated using measurements from typical household appliances assembled within a laboratory environment, where accurate ground truth data could be compiled to complement the measurements. This allows for the accu- racy of the various disaggregation approaches to be precisely evaluated. It is demonstrated that the correlation of transient event edges in aggregated power measurements to individual appliance transient exemplars performs better than the matching of steady-state power levels against individual ap- pliance state combinations. Furthermore, the transient approach is shown to be the most appropriate technique for further development.<br>MT2017