Customer load characteristics provides very critical information for power system operation. The accuracy of load forecasting and the effective cases of system generation and network planning can be enhanced by the investigation of customer load characteristics. In this thesis, the intelligent meters have been used to collect the power consumption within each 15 minutes of study customers, which have been selected by stratified sampling method. The typical load patterns of each customer class have been derived. The load composition and the power system load profile of Fengshan District in Taipower have been solved by the typical load patterns and the power consumption of each custom class. To investigate the distribution system reliability, the service territory of Fengshan district is divided into six service areas. The forecasting of yearly peak loadings for each area over the future 20 years is performed by the time series method based on the historical load data and load characteristics. By using the forced outage rate ¡]FOR¡^ of main transformers in the substations, the loss of load expectation¡]LOLE¡^ which corresponds to yearly peak loading of each service area is solved. By this way, the capacity expansion planning of main transformers to meet the service reliability can therefore be derived. To further enhance the distribution system planning, the capacity transfer capability of main transformers and the tie line flow capacity between different areas are considered too. It is found that the expansion planning of main transformers by the proposed methodology can provide better cost effectiveness of transformer investment to satisfy the service reliability as well as the system peak loading.

Renewal process has been often employed as a mathematical model of the failure and repair cycle of components in power system reliability assessment. This implies that after repair, the component is assumed to be restored to be in as good as new condition in terms of reliability perspective. However, some of the components may enter an aging stage as the system grows older. This thesis describes how aging characteristics of a system may impact the calculation of commonly used quantitative reliability indices such as Loss of Load Expectation (LOLE), Loss of Load Duration (LOLD), and Expected Energy Not Supplied (EENS). To build the history of working and failure states of a system, Stochastic Point Process modeling based on Sequential Monte Carlo simulation is introduced. Power Law Process is modeled as the failure rate function of aging components. Power system reliability analysis can be made at the generation capacity level where transmission constraints may be included. The simulation technique is applied to the Single Area IEEE Reliability Test System (RTS) and the results are evaluated and compared. The results show that reliability indices become increased as the age of the system grows.

All generation facilities have to report their generator un-availabilities to their respective Independent System Operators (ISOs). The un-availability of a generator is determined in terms of its probability of failure. Generators may serve the role of two kinds, base units which operates all the time and the others are peaking units which operate only for periods of time depending on load requirement. Calculation of probability of failure for peaking units using standard formulas gives pessimistic results owing to its time spent in the reserve shut down state. Therefore the normal two state representation of a generating unit is not adequate. A four state model was proposed by an IEEE committee to calculate the forced outage rate (unavailability) of such units. This thesis examines the representation of peaking units using a four-state model and performs the analytical calculations and Monte Carlo simulations to examine whether such a model does indeed represent the peaking units properly.

Currently, major power systems almost invariably operate under interconnected conditions to transfer power in a stable and reliable manner. Multi-area reliability evaluation has thus become an invaluable tool in the planning and operation of such systems. Multi - area reliability evaluation is typically done by considering equivalent tie lines between different areas in an integrated power system. It gives approximate results for the reliability indices of a power system as it models each of the areas as a single node to which are connected the entire area generation and loads. The intratransmission lines are only indirectly modeled during the calculation of equivalent tie lines' capacities. This method is very widely used in the power industry, but the influence of the various approximations and assumptions, which are incorporated in this method, on reliability calculations has not been explored. The objective of the research work presented in this thesis is the development of a new method called Composite system based multi - area reliability model, which does multi - area reliability evaluation considering the whole composite system. It models the transmission system in detail and also takes into account the loss sharing policy within an area and no - load loss sharing policy among the areas. The proposed method is applied to standard IEEE 24 bus Reliability Test System (RTS) and the traditional equivalent tie-line method is applied to the multi-area configuration of the same test system. The results obtained by both the methods are analyzed and compared. It is found that the traditional model, although having some advantages, may not give accurate results.

Access to reliable electric power is considered by the developed world to be a minimum requirement for a reasonable standard of living. In addition to meeting a fluctuating demand, the modern electricity industry must now integrate intermittent generation sources like wind into the grid. Reserve margin allocation (RMA) for an acceptable loss of load expectation (LOLE) allows traditional generators to maintain grid reliability in the presence of small penetrations of wind energy. However, traditional RMA over-allocates the reserve capacity in the presence of short-term intermittency mitigation techniques like energy storage and demand response. For economic operation of the modern, grid better characterization techniques are needed for reserve margin reduction behavior in the presence of wind energy. This thesis addresses this challenge with a quantitative RMA analysis using real-world and simulated wind data for three different grid scenarios, with and without intermittency mitigation. The research is novel in its first-principles approach and its investigation into the practical validity of the analogy between demand response and energy response.

The North European power system (Sweden, Finland, Norway, Denmark, Estonia, Latvia and Lithuania) is facing changes in its electricity production. The increasing share of intermittent power sources, such as wind power, makes the production less predictable. The decommissioning of large plants, for environmental or market reasons, leads to a decrease of production capacity while the demand can increase, which is detrimental to the power system reliability. Investments in interconnections and new power plants can be made to strengthen the system. Evaluating the reliability becomes essential to determine the investments that have to be made. For this purpose, a model of the power system is built. The power system is divided into areas, where the demand, interconnections between areas, and intermittent generation are represented by Cumulative Distribution Functions (CDF); while conventional generation plants follow a two-state behaviour. Imports from outside the system are set equal to their installed capacity, with considering that the neighbouring countries can always provide enough power. The model is set up by using only publicly available data. The model is used for generating numerous possible states of the system in a Monte Carlo simulation, to estimate two reliability indices: the risk (LOLP) and the size (EPNS) of a power deficit. As a power deficit is a rare event, an excessively large number of samples is required to estimate the reliability of the system with a sufficient confidence level. Hence, a pre-simulation, called importance sampling, is run beforehand in order to improve the efficiency of the simulation. Four simulations are run on the colder months (January, February, March, November, December) to test the reliability of the current system (2015) and of three future scenarios (2020, 2025 and 2030). The tests point out that the current weakest areas (Finland and Southern Sweden) are also the ones that will face nuclear decommissioning in years to come, and highlight that the investments in interconnections and wind power considered in the scenarios are not sufficient to maintain the current reliability levels. If today’s reliability levels are considered necessary, then possible solutions include more flexible demand, higher production and/or more interconnections. / Det nordeuropeiska elsystemet (Sverige, Finland, Norge, Danmark, Estland, Lettland och Litauen) står inför förändringar i sin elproduktion. Den ökande andelen intermittenta kraftkällor, såsom vindkraft, gör produktionen mindre förutsägbar. Avvecklingen av stora anläggningar, av miljö- eller marknadsskäl, leder till en minskning av produktionskapaciteten, medan efterfrågan kan öka, vilket är till nackdel för kraftsystemets tillförlitlighet. Investeringar i sammankopplingar och i nya kraftverk kan göras för att stärka systemet. Utvärdering av tillförlitligheten blir nödvändigt för att bestämma vilka investeringar som behövs. För detta ändamål byggs en modell av kraftsystemet. Kraftsystemet är uppdelat i områden, där efterfrågan, sammankopplingar mellan områden, och intermittent produktion representeras av fördelningsfunktioner; medan konventionella kraftverk antas ha ett två-tillståndsbeteende. Import från länder utanför systemet antas lika med deras installerade kapaciteter, med tanke på att grannländerna alltid kan ge tillräckligt med ström. Modellen bygger på allmänt tillgängliga uppgifter. Modellen används för att generera ett stort antal möjliga tillstånd av systemet i en Monte Carlo-simulering för att uppskatta två tillförlitlighetsindex: risken (LOLP) och storleken (EPNS) av en effektbrist. Eftersom effektbrist är en sällsynt händelse, krävs ett mycket stort antal tester av olika tillstånd i systemet för att uppskatta tillförlitligheten med en tillräcklig konfidensnivå. Därför utnyttjas en för-simulering, kallad ”Importance Sampling”, vilken körs i förväg i syfte att förbättra effektiviteten i simuleringen. Fyra simuleringar körs för de kallare månaderna (januari, februari, mars, november, december) för att testa tillförlitligheten i nuvarande systemet (2015) samt för tre framtidsscenarier (2020, 2025 och 2030). Testerna visar att de nuvarande svagaste områdena (Finland och södra Sverige) också är de som kommer att ställas inför en kärnkraftsavveckling under de kommande åren. De indikerar även att planerade investeringar i sammankopplingar och vindkraft i scenarierna inte är tillräckliga för att bibehålla de nuvarande tillförlitlighetsnivåerna. Om dagens tillförlitlighetsnivåer antas nödvändiga, så inkluderar möjliga lösningar mer flexibel efterfrågan, ökad produktion och/eller fler sammankopplingar.

In the coming decades there will be an increaseof electricity consumption as the industry and transportationsectors are electrified. Electrification and the rapid expansionof renewables will have great impact on the electricity market.In order to ensure that there is enough electricity, differentcapacity mechanisms are possible solutions. In this paper, theneed of a capacity market in Sweden is studied. Simulations ofcapacity markets with convex downwards sloping demand curvesdemonstrated possible outcomes of such a market. A comparisonbetween a FCM and Sweden’s strategic reserve is also carriedout. The results of this project show that even though peakingpower plants are not profitable, there is no immediate need fora forward capacity market. / De kommande årtiondena kommerelförbruknikngen att öka till följd av elektrifieringen avindustrioch transportsektorn. Elektrifieringen och skiftettill förnybara energikällor kommer ha en stor påverkan påelmarknaden. För att se till att det finns tillräckligt med effektkan en framåtblickande kapacitetsmarknad behövas. I dettaprojekt undersöks behovet av en svensk kapacitetsmarknad. Enmodell för kapacitetsmarknader med en konvex nedåtlutandeefterfrågekurva gjordes för att undersöka möjliga utfall. Enjämförelse mellan en framåtblickande kapacitetsmarknad ochden svenska effektreserven genomförs också. Resultaten i dettaarbete visar att även fast spetskraftverk inte är lönsamma så finns det inget omedelbart behov av en framåtblickandekapacitetsmarknad. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

The first part of this dissertation presents an innovative method for the assessment of generation system reliability. In this method, genetic algorithm (GA) is used as a search tool to truncate the probability state space and to track the most probable failure states. GA stores system states, in which there is generation deficiency to supply system maximum load, in a state array. The given load pattern is then convoluted with the state array to obtain adequacy indices. In the second part of the dissertation, a GA based method for state sampling of composite generation-transmission power systems is introduced. Binary encoded GA is used as a state sampling tool for the composite power system network states. A linearized optimization load flow model is used for evaluation of sampled states. The developed approach has been extended to evaluate adequacy indices of composite power systems while considering chronological load at buses. Hourly load is represented by cluster load vectors using the k-means clustering technique. Two different approaches have been developed which are GA parallel sampling and GA sampling for maximum cluster load vector with series state revaluation. The developed GA based method is used for the assessment of annual frequency and duration indices of composite system. The conditional probability based method is used to calculate the contribution of sampled failure states to system failure frequency using different component transition rates. The developed GA based method is also used for evaluating reliability worth indices of composite power systems. The developed GA approach has been generalized to recognize multi-state components such as generation units with derated states. It also considers common mode failure for transmission lines. Finally, a new method for composite system state evaluation using real numbers encoded GA is developed. The objective of GA is to minimize load curtailment for each sampled state. Minimization is based on the dc load flow model. System constraints are represented by fuzzy membership functions. The GA fitness function is a combination of these membership values. The proposed method has the advantage of allowing sophisticated load curtailment strategies, which lead to more realistic load point indices.

[pt] A reserva girante é a parcela da geração que deve estar sincronizada, ou que seja possível sincronizar em tempo hábil, de forma a repor a perda de unidades de geração, suprir acréscimos de demanda devido aos erros de previsão, ou ainda lidar com possíveis flutuações na capacidade de geração de fontes renováveis. Desta forma, é crucial que tal parcela esteja dimensionada de modo a suprir tais necessidades de forma adequada. Para tal, deve-se considerar o perfil da demanda do sistema e também as características do sistema de geração. Estimativas imprecisas da carga elétrica podem levar a ocorrências de cortes de carga. Da mesma forma, um superdimensionamento da reserva pode ter como consequência custos excessivos para o consumidor de energia. Uma representação aceitável para carga é considerá-la como uma variável aleatória. Este tipo de modelagem permite que o valor do pico de carga estimado tenha suas incertezas intrinsecamente consideradas. Assim, considerando as variabilidades inerentes à demanda e à geração, é então possível estimar o risco de não suprimento do sistema por meio de métodos baseados em Simulação Monte Carlo (SMC). Tais métodos têm como principal vantagem uma relativa robustez para avaliação de índices que mensuram numericamente o nível de confiabilidade do sistema: e.g., LOLP (loss of load probability). Nesta dissertação será avaliado o impacto das incertezas associadas à demanda, à variabilidade das fontes renováveis e às falhas em equipamentos no dimensionamento da reserva de geração no âmbito da operação de sistemas elétricos. Serão empregadas técnicas baseadas em SMC para avaliar os níveis de confiabilidade, considerando diversas possibilidades de representação da carga em sistemas multiárea. Dentre os cenários testados e discutidos, calculam-se índices de risco para o sistema e por áreas, para avaliar se o sistema é confiável não apenas como um todo, mas também em cada uma de suas regiões operativas. Para avaliar a metodologia proposta, são realizados testes com o sistema IEEE-RTS (Reliability Test System) de modo a responder se os índices de risco por área/sistema estão dentro de níveis aceitáveis. Por fim, é avaliado também o efeito da inserção de fontes renováveis intermitentes na reserva do sistema. / [en] The spinning reserve is the generation quota that must be synchronized (or that can be synchronized in a timely manner) with the aim to restore the loss of generation units, to supply increases in demand due to forecast errors, or to cope with generation capacity fluctuations of renewable sources. Thus, it is crucial that such amount is defined so as to adequately meet the required needs. For this, the system load profile and also the generating system characteristics must be duly considered. Inaccurate estimates of electrical demand can lead to the occurrence of load shedding. Similarly, overinvestment in capacity reserve may result in excessive costs to electric energy consumers. An acceptable representation for the load profile is to consider it as a random variable. This type of modeling allows the estimated peak load value to have its uncertainties intrinsically considered. Therefore, considering the inherent variability of demand and generation, it is then possible to estimate the risk of not supplying the system load through methods based on Monte Carlo simulation (SMC). Such methods have as their main advantage a relative robustness for evaluating indices that numerically measure the reliability level of the system; e.g., LOLP (loss of load probability). In this dissertation, the impact of uncertainties associated with demand, the variability of renewable sources and equipment failures will be evaluated in order to size the amount of generating reserve, within the scope of the operation of electric systems. SMC techniques are used to evaluate the reliability levels, considering several possibilities of load representation in a multi-area system. Among different scenarios analyzed, risk indices are calculated for system and areas, in order to assess whether the grid is reliable as a whole and also for all operating regions. In order to evaluate the proposed methodology, tests are performed with the IEEE-RTS (Reliability Test System) to respond if the area/system risk indices are within acceptable levels. Finally, the effect of inserting intermittent renewable sources into the system reserve is also discussed.

[pt] A reserva girante é a parcela da reserva operativa provida por geradores sincronizados, e interligados à rede de transmissão, aptos a suprir a demanda na ocorrência de falhas de unidades de geração, erros na previsão da demanda, variações de capacidade de fontes renováveis ou qualquer outro fator inesperado. Dada sua característica estocástica, essa parcela da reserva operativa é mais adequadamente avaliada por meio de métodos capazes de representar as incertezas inerentes ao seu dimensionamento e planejamento. Por meio do risco de corte de carga é possível comparar e classificar distintas configurações do sistema elétrico, garantindo a não violação dos requisitos de confiabilidade. Sistemas com elevada penetração de fontes renováveis apresentam comportamento mais complexo devido ao aumento das incertezas envolvidas, à forte dependência de fatores energético-climáticos e às variações de capacidade destas fontes. Para avaliar as correlações temporais e representar a cronologia de ocorrência dos eventos no curto-prazo, um estimador baseado na Simulação Monte Carlo Quase Sequencial é apresentado. Nos estudos de planejamento da operação de curto-prazo o horizonte em análise é de minutos a algumas horas. Nestes casos, a ocorrência de falhas em equipamentos pode apresentar baixa probabilidade e contingências que causam corte de carga podem ser raras. Considerando a raridade destes eventos, as avaliações de risco são baseadas em técnicas de amostragem por importância. Os parâmetros de simulação são obtidos por um processo numérico adaptativo de otimização estocástica, utilizando os conceitos de Entropia Cruzada. Este trabalho apresenta uma metodologia de avaliação dos montantes de reserva girante em sistemas com participação de fontes renováveis, em uma abordagem multiárea. O risco de perda de carga é estimado considerando falhas nos sistemas de geração e transmissão, observando as restrições de transporte e os limites de intercâmbio de potência entre as diversas áreas elétricas. / [en] The spinning reserve is the portion of the operational reserve provided by synchronized generators and connected to the transmission network, capable of supplying the demand considering generating unit failures, errors in load forecasting, capacity intermittency of renewable sources or any other unexpected factor. Given its stochastic characteristic, this portion of the operating reserve is more adequately evaluated through methods capable of modeling the uncertainties inherent in its design and planning. Based on the loss of load risk, it is possible to compare different configurations of the electrical system, ensuring the non-violation of reliability requirements. Systems with high penetration of renewable sources present a more complex behavior due to the number of uncertainties involved, strong dependence of energy-climatic factors and variations in the capacity of these sources. In order to evaluate the temporal correlations and to represent the chronology of occurrence of events in the short term, an estimator based on quasi-sequential Monte Carlo simulation is presented. In short-term operation planning studies, the horizon under analysis is from minutes to a few hours. In these cases, the occurrence of equipment failures may present low probability and contingencies that cause load shedding may be rare. Considering the rarity of these events, risk assessments are based on importance sampling techniques. The simulation parameters are obtained by an adaptive numerical process of stochastic optimization, using the concept of Cross Entropy. This thesis presents a methodology for evaluating the amounts of spinning reserve in systems with high penetration of renewable sources, in a multi-area approach. The risk of loss of load is estimated considering failures in the generation and transmission systems, observing the network restrictions and the power exchange limits between the different electric areas.