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Submitted by Maria Aparecida (cidazen@gmail.com) on 2022-09-23T13:56:48Z No. of bitstreams: 1 Louseiro Filho vec.pdf: 56541575 bytes, checksum: 2b78463407db9cb05b37d3a4a7b3f512 (MD5) Made available in DSpace on 2022-09-23T13:56:48Z (GMT). No. of bitstreams: 1 Louseiro Filho vec.pdf: 56541575 bytes, checksum: 2b78463407db9cb05b37d3a4a7b3f512 (MD5) Previous issue date: 2020-05-25 CNPq The importance of electric energy in the society imposes on utilities the need to assess the reliability of the electric power supply and to adopt measures that minimize the impact of interruptions. Regulatory agencies establish quality limits, which, if extrapolated, will result in penalties for distribution utilities. In this scenario, the reliability index estimation methods are tools that help the planning and operation of the electrical network oriented towards the fulfillment of acceptable standards. Reliability indices can measure the frequency and duration of interruptions in the distribution networks, i.e. the DEC index, which is the average annual unavailability for a group of consumers. The penalties paid by the distribution utilities depend on DEC. That is, each time the acceptable limit of DEC is violated, a penalty is paid. Thus, modifying DEC's probability density function implies a reduction in penalties. Another cost associated with the reliability indices is the customer interruption cost for the consumer classes. These costs express the economic impacts of an outage for different types of consumers based on the duration, frequency and energy not supplied due to outage. The allocation of devices in the electrical network is a low cost and very effective resource to maximize the reliability of distribution network. However, the effect of the allocation on the penalties has never been assessed. Automatic and manual switches are efficient in reducing consumers' restoration times due to the increased sectionalizing capacity of the network. Fault indicators and automatic keys are important to indicate a path closer to the fault. In this way, the consumers' restoration time is reduced due to the reduction of fault location time. Therefore, this dissertation proposes a method that aims to reduce the costs associated with penalties and interruptions through the optimal allocation of manual keys, automatic keys and fault indicators. This optimization problem was solved using multiobjective optimization techniques based on the Pareto surface theory. In addition, surrogate models have been developed to reduce the computational cost of estimating penalties. The results of the tests demonstrated that the multi-objective optimization model managed to obtain solutions with an acceptable compromise between installation / maintenance costs and reliability. Additionally, the surrogate models for estimating penalties demonstrated good accuracy and low computational cost in relation to Monte Carlo Simulation. A importância da energia elétrica na sociedade impõe para as concessionárias de energia a necessidade de avaliar a confiabilidade do fornecimento de energia elétrica e adotar medidas que minimizem o impacto das interrupções. As agências reguladoras atribuem limites de qualidade, que se forem extrapolados, serão impostas multas para as concessionárias. Neste cenário, os métodos de estimação de índices de confiabilidade são ferramentas que auxiliam o planejamento e a operação da rede elétrica orientados para o cumprimento de padrões aceitáveis. Os índices de confiabilidade podem medir a frequência e a duração das interrupções nas redes de distribuição, destacando-se o índice DEC, que é a indisponibilidade anual média para um conjunto de consumidores. As penalidades pagas pelas concessionárias de energia dependem do DEC, ou seja, a cada vez que o limite aceitável do DEC é violado, paga-se uma penalidade. Desta forma, modificando-se a função densidade de probabilidade do DEC implica em redução das penalidades. Outro custo associado aos índices de confiabilidade são os custos de interrupção de energia para as classes de consumidores. Estes custos expressam os impactos econômicos de uma interrupção para os diferentes tipos de consumidores com base na duração, frequência e potência não fornecida da interrupção. A alocação de dispositivos na rede elétrica é um recurso de baixo custo e muito eficaz para maximizar a confiabilidade da rede de distribuição. Porém, o efeito da alocação nas penalidades nunca foi avaliado. As chaves automáticas e manuais são eficientes para reduzir os tempos de restauração dos consumidores devido ao aumento na capacidade de seccionamento da rede. Os indicadores de falta e chaves automáticas são importantes para indicar um caminho mais próximo da falta. Desta forma, reduz-se o tempo de restauração dos consumidores devido a diminuição do tempo de localização da falta. Portanto, essa dissertação propõe um método que visa reduzir os custos associados as penalidades e interrupções através da alocação ótima de chaves manuais, chaves automáticas e indicadores de falta. Este problema de otimização foi solucionado usando-se técnicas de otimização multiobjetivo baseadas na Teoria da superfície de Pareto. Além disso, foram desenvolvidos modelos alternativos para reduzir o custo computacional da estimação das penalidades. Os resultados dos testes demonstraram que o modelo de otimização multiobjetivo foi capaz de obter soluções com um compromisso aceitável entre custos de instalação/manutenção e de confiabilidade. Adicionalmente, os modelos alternativos para a estimação das penalidades demonstraram boa precisão e baixo custo computacional com relação a Simulação Monte Carlo.

U disertaciji je predstavljen pristup zasnovan na algoritmu mešovitog celobrojnog linearnog programiranja (MILP) za određivanje optimalnog broja, tipa i lokacije uređaja za automatizaciju distributivne mreže. Ugradnja različitih tipova nove opreme (daljinski kontrolisani reklozeri, sekcioneri i indikatori prolaska struje kvara) kao i relokacija postojeće opreme su istovremeno razmatrani. Prilikom određivanja optimalnog scenarija za automatizaciju, predloženi pristup uvažava troškove ispada potrošača/proizvođača usled trenutnih, kratkotrajnih i dugotrajnih ispada, najčešće korišćene pokazatelje pouzdanosti (SAIFI, SAIDI, MAIFI, i ASIDI) kao i troškove distributivnog preduzeća, asocirane uređajima za automatizaciju i ekipama koje su uključene u proces rešavanja prekida napajanja. Dakle, osnovni cilj ove disertacije je, da se napravi model zasnovan na mešovitom celobrojnom linearnom programiranju koji će omogućiti određivanje najboljeg scenarija za automatizaciju distributivne mreže u slučajevima kada se ocena kvaliteta isporuke definiše preko pokazatelja pouzdanosti, preko troškova usled prekida napajanja ili kombinacijom ova dva pokazatelja. The dissertation presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both approaches (criteria) are used.

The EU has set itself ambitious short- and long-term decarbonisation targets: a reduction in greenhouse gas (GHG) emissions of 40% by 2030 and 80% by 2050, compared to 1990 levels. The power generation sector, currently responsible for around 55% of GHG emissions, is expected to contribute significantly to achieving the EU’s decarbonisation targets. Increasing the share of energy from renewable sources (RES), such as wind and solar, is an important step towards decarbonising the power generation sector. This dissertation analyses drivers, enablers, and barriers to renewable energy deployment in the EU’s electricity sector. The transition to power generation from renewable energy sources is strongly driven by targets and policies. In this dissertation, past RES deployment trajectories in selected EU Member States (MS) are studied to identify the most effective drivers to increasing deployment in the past as well as barriers that may potentially hinder its progress. A meta-analysis of previous studies shows the significant variance in projected levels of RES-E shares in the EU. While no study is expected to accurately predict future levels of RES-E, the meta-analysis showed their sensitivity to underlying data, assumptions, and methodologies. However, not all projection studies - and the energy strategies based on them – explicitly state their underlying assumptions. Technologies such as energy storage and smart grids can enable the increased penetration of variable RES by providing flexibility to the system. Here, the role and potential of large-scale electricity storage to enable higher shares of RES penetration is assessed using a combination of a long-term energy system (TIMES) and a power system model (PLEXOS). Further, the regulatory treatment of technologies such as energy storage is analysed and with suggested updates are provided to reflect their evolving role in the energy system. The thesis verifies findings in other studies that multiple benefits are required to justify battery storage in the EU until 2030. Further, this dissertation shows a clear correlation between degree of RES implementation and the value of storage. This is illustrated by the difference in feasibility of storage in the Reference scenarios and CO2 scenarios. Under current cost estimations and policy framework, there is no business case for large-scale electricity storage in the EU until 2030 with the technologies considered, but it may become feasible by 2050 in selected markets. Further studies - including how multiple benefits could be used and consideration of other storage technologies - would provide additional insights on the potential role of large-scale electricity storage. The current status of smart energy solutions - such as smart meters and demand side management – in the EU is also studied in this dissertation. The study finds that the current emphasis on smart meter roll-outs must be followed up with measures such as real-time pricing in order to achieve the full potential of smart energy solutions.Increasing the share of variable RES also brings with it significant challenges. As the EU moves towards an internal energy market, the role of cross-border interconnectors will become crucial. This dissertation highlights the role that cross-border interconnectors are expected to play - such as enabling large-scale integration of variable RES, preventing loss of load, and ensuring cost-effective power generation – through a power system model, with an hourly resolution, of the EU’s power system in 2030. Finally, the transition to a system with high shares of variable RES must be achieved while maintaining, or improving upon, the high level of reliability currently enjoyed in the EU. Valuing electricity interruptions differently between EU MS may lead to mismatched incentives to improve reliability levels through cross-border interconnectors. This dissertation, for this first time, quantifies the differences in value of lost load for households across all twenty-eight EU Member States. The EU is on track to meet its 2020 RES targets, which are legally binding at the Member State level. The targets set in the 2030 climate and energy framework are only legally binding at the EU level and this is seen as a risk since Member States may not be sufficiently incentivised to invest in RES deployment beyond 2020. This dissertation analyses selected drivers, barriers, and enablers of renewable energy deployment in the EU’s electricity sector to help achieve the EU’s stated decarbonisation targets. In particular, the potential role of large-scale electricity storage and cross-border interconnectors is highlighted as being of crucial importance. Finally, the variance in costs of electricity supply interruptions across the EU is also presented as a potential barrier to increased RES-E penetration. QC 20180507

The aim of the paper is to identify a gap between the quality dependant regulatory principles and the up-to-date Croatian approach to regulation of distribution activity. The analysis of the main principles of optimal price-quality regulation and the overview of the Croatian regulatory practice and its results are given. Finally, the paper provides recommendations on a direction which Croatian regulation should take in order to aim at optimizing distribution activity from a socio-economic point of view.

The paper presents the methodology on survey on customer power supply interruptions and the results conducted survey in order to assess the customer interruption costs (CIC) depending on the interruption duration. The survey was conducted in 2004 and 2005 on over 100 households mostly from city of Osijek and other urban and rural areas in Eastern Croatia. In addition one large industrial user has been surveyed in order to compare the results of the different type of power system customers (consumers). Customer damage functions (CDF) have been determined and calculation of expected damages, i.e. overall expected customer outage costs (COC) is presented using a developed Visual Basic algorithm for customer supply reliability analysis.

The paper presents the methodology on survey of the customer power supply interruptions and the results of the conducted survey in order to assess the customer interruption costs (CIC) depending on the interruption duration. The survey was conducted in 2004 and 2005 on over 100 households mostly from the city of Osijek and other urban and rural areas in Eastern Croatia. In addition one large industrial user has been surveyed in order to compare the results of different types of power system customers (consumers). Customer damage functions (CDF) have been determined and the calculation of expected damages, i.e. overall expected customer outage costs (COC) is presented using a developed Visual Basic algorithm for customer supply reliability analysis., Članak predstavlja metodologiju anketiranja o troškovima prekida opskrbe električnom energijom potrošača i rezultate provedene ankete s ciljem određivanja troškova prekida opskrbe potrošača (CIC) ovisnih o trajanju prekida. Anketa je provedena u 2004. i 2005. na više od 100 kućanstava uglavnom iz grada Osijeka i drugih urbanih i ruralnih područja u istočnoj Hrvatskoj. Dodatno, anketiran je jedan veliki industrijski potrošač s ciljem usporedbe rezultata različitih tipova potrošača (kupaca). Utvrđene su krivulje štete potrošača i prikazan proračun očekivanih šteta, tj. ukupnih očekivanih troškova prekida opskrbe potrošača u sustavu (COC) korištenjem razvijenog Visual Basic algoritma za analizu pouzdanosti opskrbe potrošača.

Este artigo descreve uma aplicação da simulação Monte Carlo pseudo-cronológica em estudos de impacto do gerenciamento da demanda no custo da perda de carga. A simulação pseudo-cronológica apresenta a eficiência computacional da simulação não-seqüencial e a precisão da simulação cronológica, podendo ser utilizada para representar diferentes padrões comportamentais para as cargas das diversas áreas ou barras de um sistema. O sistema SSB (Sistema Sul-Sudeste Brasileiro) é utilizado para testes, sendo avaliados os impactos obtidos por diferentes políticas de gerenciamento da carga na área Rio. This paper presents an application of pseudo-chronological Monte Carlo simulation algorithm to investigate the effects of load management on interruption cost. The pseudo-chronological simulation, which retains the computational efficiency of non-sequential simulation and the accuracy of chronological simulation, can be used to represent different load patterns per area or bus. Case studies on the Brazilian South-Southeastern System (SSB) considering the impact of different load management policies applied to the Rio de Janeiro area are presented and discussed.

It is very difficult to find pre-emptive scheduling algorithms that consider all the main characteristics of computer vision systems. Moreover, there is no generic algorithm that considers interruption costs for such systems. Taking the interruption of tasks into account scheduling results can be improved. But it is also very important to take the costs that arise from interruptions into account because they not only increase the total execution time, but also because the scheduler can evaluate whether it is adequate to interrupt certain tasks or not. Thus, the result can be more realistic. Therefore, we present an extension to the static algorithm SASEPA for computer vision which considers interruption costs.