Introduction: The global demand for renewable energy is expected to grow annually due to rising electricity consumption and economic and regulatory incentives. Efficient consumption and management of electricity consumption can support this trend (shifting from fossil resources to renewable resources) and benefit companies economically by reducing peak loads, reducing subscription costs, and protecting companies' power systems and networks. For effective and efficient electricity management that can help reduce peak electricity demand, resulting in lower demand charges and further reducing operational costs, it is necessary to understand the amount of electricity consumption and its influencing factors. Seasonal and daily variations and social behaviors influence changes in electricity consumption. Electric load variation management is essential for electricity consumers to control costs related to maximum load capacity and building electrical network equipment protection. This research presents an assessment method for describing daily electric load variations. It is applied to electricity consumption systems, but the technique is generic and can be applied to all activities where daily variations occur.Purpose: This thesis aims to show when and why peak load occurs in an office building and also to provide methods to improve the efficiency of electricity consumption during peak load.Method: This method implemented parameters like temperature, electricity consumption, and hours. It assessed a year's hourly electricity consumption in an office building to understand how load changes daily, weekly, and monthly. The case study was the AirSon office building. Data-driven from the efergy online portal was based on the hourly consumption every year.Results: The results show that the outdoor temperature, working hours, and consumption behavior can affect the overall electricity consumption and peak loads. Efficient building strategies are crucial for reducing peak loads by smartly controlling indoor temperature and managing electricity demand. The analysis offers insights into office building electricity consumption patterns and recommends strategies such as prioritizing car charging, optimizing the heat pump's operation of the HVAC system, improving the electricity management system, and using energy storage systems to reduce peak load.Discussion: The findings from this analysis carry implications for electricity consumption. It can provide some insights for reducing electricity consumption and enhancing efficiency in office buildings and similar facilities and also prioritization and rescheduling car chargers. In conclusion, it has interpreted and discussed the various electricity-saving strategies and their potential impact on electricity management.

The aim of this thesis is to describe the course of consumption of electricity. One of the feasible ways of description is statistical analysis, which enables to calculate statistically significant factors and their combinations that contributed to the course of consumption of electricity. These factors may be used for modulation of future electricity consumption, and therefore also for long-time prediction. The second chapter discusses the expansion of electricity usage in the Czech Republic from the turn of the 19th century until nowadays. The chapter describes the development of transmission system, development of electricity consumption in the sectors of the national economy, possibilities of using electric energy, and overall balance of electricity and sources of energy. The third chapter presents an overview of usage and consumption of electrical energy in the neighboring European countries as well as in the most interesting countries of the World. The fourth chapter contains statistical analysis. The first part of the chapter details a list of the analyzed quantities of individual consumptions, of the investigated factors, and the analyzed countries. Further, the chapter explains the method of statistical analysis via using simple and multiple regression and its subsequent application and evaluation for the Czech Republic and the others European countries. According to the result, it is GDP that has the main impact on the trends in the course of consumption of electricity. However, it is necessary to consider other factors influencing the consumption of electricity, too, and not rely solely on GDP in terms of long-time prediction of electricity consumption. The fifth chapter discusses the reduction of electricity consumption and savings, which can be both political and macroeconomic result. Quantification of savings is not always unequivocal and any cost-saving actions can lead to an increase in electricity consumption, which can, in effect, be bigger than any possible savings.

Thesis (MScIng)--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The Spier Estate - a wine estate in the Western Cape Province of South Africa - is engaged in a transition towards operating according to the principles of sustainable development. Besides changes in social and other environmental aspects, the company has set itself the goal to be carbon neutral by 2017. To this end, Spier is considering the on-site generation of electricity from renewable energy sources. This study was initiated to explore the technical and economic feasibility of a concentrating solar power plant for this purpose on the estate. The investigation was carried out to identify the most appropriate solar thermal energy technology and the dimensions of a system that fulfils the carbon-offset requirements of the estate. In particular, potential to offset the annual electricity consumption of the currently 5 570 MWh needed at Spier, using a concentrating solar power (CSP) system, was investigated. Due to rising utility-provided electricity prices, and the expected initial higher cost of the generated power, it is assumed that implemented efficiency measures would lead to a reduction in demand of 50% by 2017. However, sufficient suitable land was identified to allow electricity production exceeding today’s demand. The outcome of this study is the recommendation of a linear Fresnel collector field without additional heat storage and a saturated steam Rankine cycle power block with evaporative wet cooling. This decision was based on the system’s minimal impact on the sensitive environment in combination with the highest potential for local development. A simulation model was written to evaluate the plant performance, dimension and cost. The analysis was based on a literature review of prototype system behaviour and system simulations. The direct normal irradiation (DNI) data that was used is based on calibrated satellite data. The result of the study is a levelised cost of electricity (LCOE) of R2.741 per kWh, which is cost competitive to the power provided by diesel generators, but more expensive than current and predicted near-future utility rates. The system contains a 1.8 ha aperture area and a 2.0 MWe power block. Operating the plant as a research facility would provide significant potential for LCOE reduction with R2.01 per kWh or less (favourable funding conditions would allow for LCOE of R1.49 per kWh) appearing feasible, which results in cost competitiveness in comparison a photovoltaic (PV) solution. Depending on tariff development, Eskom rates are predicted to reach a similar level between 2017, the time of commissioning, and the year 2025. The downside is that the plant would not solely serve the purpose of electricity offsetting for Spier, which may result in a reduced amount of electricity that may be generated. Further studies are proposed to refine the full potential of cost reduction by local development and manufacturing as well as external funding. This includes identification of suitable technology vendors for plant construction. An EIA is required to be triggered at an early stage to compensate for its long preparation. / AFRIKAANSE OPSOMMING: Die Spier wynlandgoed in die Wes-Kaap Provinsie van Suid-Afrika is tans in ‘n oorgangsfase tot besigheids-praktyke gebaseer op volhoubare ontwikkeling. Afgesien van die sosiale en omgewingsaspekte het die groep hom ook ten doel gestel om koolstof neutraal te wees teen 2017. Ten einde hierdie doel te bereik, moet die maatskappy sy algehele elektrisiteitsverbruik vervang met hernubare bronne. Hierdie studie is dus geloods om die tegniese en ekonomiese uitvoerbaarheid van 'n gekonsentreerde sonkragstasie op die landgoed te ondersoek. Hierdie ondersoek is gedoen om die mees toepaslike sontermiese tegnologie en die grootte van 'n termiese sonkragstelsel te bepaal, wat aan die koolstof vereistes van die landgoed voldoen. Die potensiaal om die jaarlikse elektrisiteitsverbruik van 5 570 MWh met 'n gekonsentreerde elektriese sonkragstelsel te vervang, is ondersoek. Weens die toename in die elektrisiteitsprys en die verwagte hoërkoste van opgewekte elektrisiteit word aanvaar dat die implementering van voorgestelde doeltreffendheidsverbeteringe, sal lei tot 'n afname in die aanvraag na elektrisiteit van tot 50% teen die jaar 2017. Voldoende beskikbare grond is geïdentifiseer om genoeg elektrisiteit te produseer om die huidige vraag na elektrisiteit te oorskry. Die uitkoms van die studie is die aanbeveling van 'n lineêre Fresnel kollektorveld sonder addisionele warmte storing, asook 'n versadigde stoom Rankine sikluskragblok met ‘n nat-verdamping verkoelingstelsel. Die besluit is gebaseer op die stelsel se minimale impak op die omgewing, tesame met die hoogste potensiaal vir plaaslike ontwikkeling. 'n Simulasie is ontwikkel om die aanleg se werkverrigting, grootte en koste te evalueer. Die analise is gebaseer op 'n literatuuroorsig van 'n prototipe stelsel gedrag en stelsel-simulasies. Die direkte normale sonstralings data wat gebruik is, is gebaseer op gekalibreerde satelliet data. Die bevinding van die studie is 'n gebalanseerd koste van elektrisiteit van R2.74 per kWh, wat mededingend is met die koste van elektrisiteit wat deur diesel kragopwekkers verskaf word, maar is aansienlik duurder as die huidige en toekomstige voorspellings van Eskom-tariewe. Die stelsel bevat 'n 1.8 ha son kollektor oppervlakte en 'n 2.0 MWe krag-blok. Daarbenewens, sal die gebruik van die aanleg as 'n navorsingsfasiliteit die potensiaal hê om die gebalanseerd koste van elektrisiteit te verminder na R2.01 per kWh of minder (gunstig befondsing voorwaardes sal gebalanseerd koste van elektrisiteit van R1.49 per kWh tot gevolg hê), wat mededingend is met die koste van 'n fotovoltaïese alternatief. Daar word voorspel dat Eskom-tariewe dieselfde sal bly vanaf 2017, die jaar van inbedryfstelling van die aanleg, tot en met die jaar 2025. Die nadeel is dat die aanleg nie noodwendig uitsluitlik vir die opwek van elektrisiteit vir Spier gebruik sal word nie, en daarom kan dit lei tot 'n vermindering in die hoeveelheid elektrisiteit wat deur die aanleg opgewek word. Daar word voorgestel dat verdere studies onderneem word om die moontlikheid van koste-besparings vir die aanleg te ondersoek deur gebruik te maak van plaaslike ontwikkeling en vervaardiging, asook eksterne befondsing. Dit sluit die identifisering van geskikte tegnologie verskaffers vir die aanleg-kostruksie in. 'n Omgewingsimpakstudie, volgens die EIA regulasies, moet ook so gou as moontlik gedoen word aangesien dit n langsame proses is.

L’évolution de la consommation électrique est un point clé pour les choix à venir, tant pour les moyens de production d’électricité, que pour le dimensionnement du réseau à toutes ses échelles. Aujourd’hui, ce sont majoritairement des modèles statistiques basés sur les consommations passées et des tendances démographiques ou économétriques qui permettent de prédire cette consommation. Dans le contexte de la transition énergétique, des changements importants sont en cours et à venir, et la consommation future ne sera certainement pas une continuation des tendances passées. Modéliser ces changements nécessite une modélisation fine de type bottom-up de chaque contributeur de la consommation électrique. Ce type de modèle présente des challenges de modélisation, car il nécessite un grand nombre de paramètres d’entrée qui peuvent difficilement être renseignés de façon réaliste à grande échelle. En même temps, les données et informations de tout type n’ont jamais été autant disponibles. Cela représente à la fois un atout pour la modélisation, mais aussi une difficulté importante notamment à cause de l’hétérogénéité des données. Dans ce contexte, cette thèse présente une démarche de construction d’un simulateur de consommation électrique bottom-up capable de simuler différentes alternatives énergétiques à l’échelle de la France. Un travail de recensement, de classification et d’association des bases de données pour expliquer la consommation électrique a d’abord été mené. Ensuite, le modèle de consommation électrique a été présenté ; il a été validé et calibré sur une grande quantité de mesures de consommation électrique des départs HTA fournie par Enedis. Ce modèle a enfin pu être utilisé pour simuler différentes alternatives énergétiques afin d’aider au dimensionnement du réseau de distribution. / Future trend of electricity demand is a key point for sizing both the electricity network and the power plants. In order to forecast future electricity demand, current models mostly use statistical approaches based on past demand measurements and on demographic and economic trends. Because of current context of energy transition which comes along with important changes, future electricity demand is not expected to be similar to past trends. Modeling these changes requires a bottom-up modeling of each contributor to electricity demand. This kind of model is challenging because of the large number of input data required. At the same time, data and information are more and more available. Such availability can be considered both as an asset for modeling and as an important issue because of data heterogeneity. In this context, this dissertation offers an approach to build a bottom-up load curve simulator which enables to simulate prospective scenarii at the scale of France country. Firstly, an assessment, classification, and matching of the large databases explaining the electricity demand have been performed. Then, the electricity demand model has been presented. It has been validated and calibrated on Enedis’ large volumes of electricity demand measurements of medium voltage feeders. Finally, this model has been used to simulate several prospective scenarii in order to improve the electricity distribution network sizing.

Submitted by Fabricia Fialho Reginato (fabriciar) on 2015-06-30T23:58:11Z No. of bitstreams: 1 ClauberFerasso.pdf: 8384052 bytes, checksum: dc9cfb947f94d52412c3434032ae62da (MD5) / Made available in DSpace on 2015-06-30T23:58:11Z (GMT). No. of bitstreams: 1 ClauberFerasso.pdf: 8384052 bytes, checksum: dc9cfb947f94d52412c3434032ae62da (MD5) Previous issue date: 2013-08 / FINEP - Financiadora de Estudos e Projetos / A contribuição das fontes de energias alternativas, principalmente a solar térmica, para a diversificação da matriz energética brasileira é importante devido, principalmente, ao aumento da demanda do consumo de energia elétrica, ocasionado pelo progresso e desenvolvimento da população e do País. Parte deste aumento é consequência do uso simultâneo de milhares de chuveiros elétricos, na maioria das vezes no horário de ponta, considerado um dos responsáveis pelo elevado pico na curva de demanda entre 18 e 21 horas. Frente a isso, a utilização da energia solar através de sistemas de aquecimento solar para o uso doméstico, vem ao encontro deste propósito. Após análise do consumo médio mensal de energia elétrica fornecida pela concessionária AES Sul no período de um ano em um conjunto residencial na cidade de Canoas – RS, foi possível estimar o custo da utilização do chuveiro elétrico nesse local, por domicílio, que representa entre 25 a 30 % da fatura de energia elétrica. A produção de energia térmica através de sistemas de aquecimento solar para pré- aquecimento de água quente para uso doméstico foi simulada utilizando-se o software TRNSYS, para diversas configurações de sistemas (área de coletor e capacidade de armazenamento). A relação entre a demanda de energia para aquecimento de água e a energia produzida pelo SAS foi parametrizada utilizando-se o conceito de fração solar mensal e anual. Foi considerada uma temperatura mínima de consumo de água quente de 40 °C e um perfil de consumo correspondente à taxa de ocupação média dos domicílios no local. Os dados climáticos necessários para a simulação foram obtidos a partir do ano meteorológico típico (TMY) para Porto Alegre. Os resultados obtidos das diversas simulações mostraram que é possível obter uma economia direta para consumidor de até 58% de energia consumida pelo chuveiro elétrico e uma economia de energia estimada em 12.399 kWh para o sistema elétrico ao longo de 20 anos. Estes resultados podem ser melhorados com a diminuição do custo unitário do SAS ou através de incentivos decorrentes da diminuição dos custos de ampliação da capacidade da rede elétrica por parte das concessionárias, decorrentes da mudança do perfil de carga do sistema. / The contribution of alternative energy sources, particularly solar thermal, to diversify the Brazilian energy matrix is important, mainly due to increased demand of electricity consumption, caused by the progress and development of the population as well as the country. Part of this increase is a consequence of the simultaneous use of thousands of electric showers, mostly during peak hours, considered one of the chief responsible for the high peak in the demand curve between 6.00 and 9.00PM. Given this, the use of solar energy, through solar heating systems for domestic use, meets this purpose. After the analysis of the average monthly consumption of electricity provided by the supplier AES Sul in the period of one year in a residential complex in the city of Canoas – RS, it was possible to estimate the cost of using electric showers in that location, per household, which was between 25 to 30% of the electricity bill. The production of thermal energy through solar heating systems for preheating domestic hot water was simulated using the TRNSYS software for various system configurations (collector area and storage capacity). The relationship between energy demand for water heating and energy produced by SAS was parameterized using the concept of monthly and annual solar fraction, considering a minimum temperature of hot water of 40 ° C, and a profile of consumption corresponding to the average occupancy rate of households at the site. The climatic data required for the simulation were obtained from the typical meteorological year (TMY) to Porto Alegre and the results of several simulations showed that it is possible to get direct savings to the consumer up to 58% of energy consumed by electric shower and energy savings estimated at 12,399 kWh for the electricity system over a period of 20 years. These results can be improved by reducing the unit cost of SAS or through incentives from lowering the cost of expanding the capacity of the electric grid by suppliers, resulting from the change of the system load profile.

Orientador: Luiz Antonio Rossi / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola / Made available in DSpace on 2018-08-17T07:11:27Z (GMT). No. of bitstreams: 1 Laranjeira_EvandroGomes_D.pdf: 2861482 bytes, checksum: db1a70b38740eed52c118a5aff70fc1a (MD5) Previous issue date: 2010 / Resumo: O plantio em ambiente protegido é incapaz de demonstrar seu máximo potencial de produção se não for submetido a um controle climático adequado. Existem hoje diversos tipos de equipamentos e metodologias que nos permitem desenvolver controles que monitorem o estado de conforto térmico da planta com uso racional de recursos e insumos. Dessa forma, é proposta uma metodologia de controle climático com integração de lógica fuzzy, controles lógicos programáveis e utilizando o cálculo de déficit de pressão de vapor folha-ar, como forma de se estimar o conforto térmico vegetal. Esta metodologia também utilizou métodos geoestatísticos (mapas de krigagem) para avaliação dos efeitos da aplicação das ações de controle sobre o clima interno, bem como monitorar o consumo de energia elétrica dos equipamentos. Foram realizados os testes em dois tratamentos em uma casa de vegetação comercial; e os dados confrontados para avaliação de sua eficiência no que se refere ao consumo de energia e mapas de krigagem das variáveis temperatura e umidade do ar / Abstract: The protected culture is incapable to demonstrate its production maximum potential while not submitted to an adequate environment control. Nowadays, there are several equipments and methodologies which provides the control development with plant thermal comfort monitoring saving resources and inputs. This way, environment control methodology is proposed with integration of fuzzy logic, programmable logic controls and leaf-to-air deficit vapour pressure, as the way to estimate plant thermal comfort. This methodology uses geostatistics (kriging maps) to evaluate the control action effects over internal environment, as well as equipment energy consumption monitoring. The tests on two treatments was performed in commercial greenhouse; and comparing the efficiency evaluation of energy saving and kriging maps over temperature and air humidity results / Doutorado / Construções Rurais e Ambiencia / Doutor em Engenharia Agrícola

Distribution grids play an important role in delivering electricityto end users. Electricity customers would like to have a continuouselectricity supply without any disturbance. For customerssuch as airports and hospitals electricity interruption may havedevastating consequences. Therefore, many electricity distributioncompanies are looking for ways to prevent power outages.Sometimes the power outages are caused from the grid sidesuch as failure in transformers or a break down in power cablesbecause of wind. And sometimes the outages are caused bythe customers such as overload. In fact, a very high peak inelectricity consumption and irregular load profile may causethese kinds of failures.In this thesis, we used an approach consisting of two mainsteps for detecting customers with irregular load profile. In thefirst step, we create a dictionary based on all common load profileshapes using daily electricity consumption for one-monthperiod. In the second step, the load profile shapes of customersfor a specific week are compared with the load patterns in thedictionary. If the electricity consumption for any customer duringthat week is not similar to any of the load patterns in thedictionary, it will be grouped as an anomaly. In this case, loadprofile data are transformed to symbols using Symbolic AggregateapproXimation (SAX) and then clustered using hierarchicalclustering.The approach is used to detect anomaly in weekly load profileof a data set provided by HEM Nät, a power distributioncompany located in the south of Sweden.

Nous sommes intéressé par la reconstitution et la prédiction des séries temporelles multivariées à partir des données partiellement observées et/ou agrégées.La motivation du problème vient des applications dans la gestion du réseau électrique.Nous envisageons des outils capables de résoudre le problème d'estimation de plusieurs domaines.Après investiguer le krigeage, qui est une méthode de la litérature de la statistique spatio-temporelle, et une méthode hybride basée sur le clustering des individus, nous proposons un cadre général de reconstitution et de prédiction basé sur la factorisation de matrice nonnégative.Ce cadre prend en compte de manière intrinsèque la corrélation entre les séries temporelles pour réduire drastiquement la dimension de l'espace de paramètres.Une fois que le problématique est formalisé dans ce cadre, nous proposons deux extensions par rapport à l'approche standard.La première extension prend en compte l'autocorrélation temporelle des individus.Cette information supplémentaire permet d'améliorer la précision de la reconstitution.La deuxième extension ajoute une composante de régression dans la factorisation de matrice nonnégative.Celle-ci nous permet d'utiliser dans l'estimation du modèle des variables exogènes liées avec la consommation électrique, ainsi de produire des facteurs plus interprétatbles, et aussi améliorer la reconstitution.De plus, cette méthod nous donne la possibilité d'utiliser la factorisation de matrice nonnégative pour produire des prédictions.Sur le côté théorique, nous nous intéressons à l'identifiabilité du modèle, ainsi qu'à la propriété de la convergence des algorithmes que nous proposons.La performance des méthodes proposées en reconstitution et en prédiction est testé sur plusieurs jeux de données de consommation électrique à niveaux d'agrégation différents. / We are interested in the recovery and prediction of multiple time series from partially observed and/or aggregate data.Motivated by applications in electricity network management, we investigate tools from multiple fields that are able to deal with such data issues.After examining kriging from spatio-temporal statistics and a hybrid method based on the clustering of individuals, we propose a general framework based on nonnegative matrix factorization.This frameworks takes advantage of the intrisic correlation between the multivariate time series to greatly reduce the dimension of the parameter space.Once the estimation problem is formalized in the nonnegative matrix factorization framework, two extensions are proposed to improve the standard approach.The first extension takes into account the individual temporal autocorrelation of each of the time series.This increases the precision of the time series recovery.The second extension adds a regression layer into nonnegative matrix factorization.This allows exogenous variables that are known to be linked with electricity consumption to be used in estimation, hence makes the factors obtained by the method to be more interpretable, and also increases the recovery precision.Moreover, this method makes the method applicable to prediction.We produce a theoretical analysis on the framework which concerns the identifiability of the model and the convergence of the algorithms that are proposed.The performance of proposed methods to recover and forecast time series is tested on several multivariate electricity consumption datasets at different aggregation level.

In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, it is feasible and convenient to predict consumption in the short term, from a few hours to a week. The hypothesis of the study is that the method used to present time variables to a prediction system of electricity consumption affects the results.

In the process industries, cooling capacity is an important enabler for the facility to manufacture on specification product. The cooling water network is an important part of the over-all cooling system of the facility. In this research a cooling water circuit consisting of 3 cooling towers in parallel, 2 cooling water pumps in parallel, and 11 heat exchangers in parallel, is modelled. The model developed is based on first principles and captures the dynamic, non-linear, interactive nature of the plant. The modelled plant is further complicated by continuous, as well as discrete process variables, giving the model a hybrid nature. Energy consumption is included in the model as it is a very important parameter for plant operation. The model is fitted to real industry data by using a particle swarm optimisation approach. The model is suitable to be used for optimisation and control purposes. Cooling water networks are often not instrumented and actuated, nor controlled or optimised. Significant process benefits can be achieved by better process end-user temperature control, and direct monetary benefits can be obtained from electric power minimisation. A Hybrid Non-Linear Model Predictive Control strategy is developed for these control objectives, and simulated on the developed first principles dynamic model. Continuous and hybrid control cases are developed, and tested on process scenarios that reflect conditions seen in a real plant. Various alternative techniques are evaluated in order to solve the Hybrid Non-Linear Control problem. Gradient descent with momentum is chosen and configured to be used to solve the continuous control problem. For the discrete control problem a graph traversal algorithm is developed and joined to the continuous control algorithm to form a Hybrid Non-Linear Model Predictive controller. The potential monetary benefits that can be obtained by the plant owner through implementing the designed control strategy, are estimated. A powerful computation platform is designed for the plant model and controller simulations. / Thesis (PhD)--University of Pretoria, 2019. / Electrical, Electronic and Computer Engineering / PhD / Unrestricted