[pt] O uso da representação de modelos completos em estudos de sistemas de potência pode levar a indesejados níveis de esforço computacional e imprecisão devido às incertezas e complexidade dos sistemas modernos. Para endereçar este problema de tratabilidade, métodos de redução de redes buscam criar um modelo simplificado, com dimensão reduzida, de um dado sistema de potência. As técnicas atuais consideram apenas um ponto de operação no processo de redução falhando em desempenho para uma grande variedade de condições operativas. Adicionalmente, a solução para o fluxo de potência CA (não linear) apresenta pior performance computacional, mas melhor precisão quando comparada à sua contraparte linear (solução para fluxo de potência CC). Infelizmente, a aproximação do fluxo de potência CC desconsidera a perda de energia nas linhas e os efeitos das não linearidades devido as mudanças nos níveis de tensão e potências reativas no sistema. Neste contexto, um novo modelo de fluxo de potência equivalente baseado em otimização é proposto. Assim, para superar as limitações relativas a performance computacional e as imprecisões para multiplos cenários operativos, utilizamos o modelo proposto para produzir um método de redução baseado no fluxo CC, que apresenta bom desempenho em variados pontos operativos. Neste caso, a solução de um problema de otimização linear, que considera múltiplos cenários de fluxo CA ou medições do sistema, determina os parâmetros da rede equivalente. Para garantir a precisão do modelo, consideramos um conjunto de cargas artificiais para representar o desbalanço entre os cenários observados e a resposta da rede equivalente. Estas cargas artificiais são funções polinomiais do ponto operativo do sistema, e seus coeficientes são cootimizados com os parâmetros da rede reduzida. A Analise de Componentes Pincipais é utilizada para extrair as componentes relevantes do vetor de cargas que define um ponto operativo, reduzindo a dimensão do modelo, e melhorarando o desempenho out–of–sample. A metodologia é testada contra o equivalente Ward para diferentes condições operativas. Casos de estudo com dados gerados são apresentados com o objetivo de analisar a capacidade de generalização do modelo para diferentes níveis de ruído. Por fim, um caso de estudo com perfís de carga realísticos oriundos de uma companhia de distribuição brasileira é conduzido no sistema de teste IEEE 118–Bus. / [en] The use of full model representation in power system studies may lead to undesirable levels of computational burden and inaccuracy due to modern system complexities and uncertainties. To address the tractability issue, network reduction methods aim to create a simplified model, with reduced dimension, of a given power system. Current techniques consider only one operating point in their reduction process, falling short in properly performing for a wide range of operating conditions. Additionally, a nonlinear AC power flow solution features worse computation performance, but better accuracy when compared against its linearized counterpart (DC power flow solution). Unfortunately, the DC power flow approximation disregards the line losses and nonlinear effects due to changes in voltage levels and reactive power. In this context, we propose a novel optimization–based framework to create equivalent power flow models. Thus, to overcome the computational performance limitations and imprecision for multiple operating scenarios, we use the proposed framework to produce a DC–based network reduction method that performs well in many operating points. The solution of a linear optimization problem, which considers multiple AC power flow scenarios or network measurements, determines the equivalent network parameters. To ensure modeling accuracy, we consider a set of artificial dynamic loads to represent the mismatch between observed scenarios and the response of the equivalent. These artificial loads are polynomial functions of the operating point, and their coefficients are co-optimized with the reduced network parameters. Principal Component Analysis (PCA) is used to extract the relevant components of the load vector defining the operating point, reducing the equivalent model dimensionality, and improving out–of–sample performance. We test the methodology against traditional Ward equivalent for different operating conditions. We present case studies with generated data to investigate the model generalization capability for different noise levels. Finally, we conduct a case study based on realistic load profiles from a Brazilian distribution company within the IEEE 118–Bus test system.

Yes / In this paper, a stochastic method for active distribution networks planning within a distribution market environment considering multi-configuration of wind turbines is proposed. Multi-configuration multi-scenario market-based optimal power flow is used to maximize the social welfare considering uncertainties related to wind speed and load demand and different operational status of wind turbines (multiple-wind turbine configurations). Scenario-based approach is used to model the abovementioned uncertainties. The method evaluates the impact of multiple-wind turbine configurations and active network management schemes on the amount of wind power that can be injected into the grid, the distribution locational marginal prices throughout the network and on the social welfare. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system. It was shown that multi-wind turbine configurations under active network management schemes, including coordinated voltage control and adaptive power factor control, can increase the amount of wind power that can be injected into the grid; therefore, the distribution locational marginal prices reduce throughout the network significantly.

No / This chapter proposes a novel method for the operation of active distribution networks within a distribution market environment taking into account multi-configuration of wind turbines. Multi-configuration multi-scenario market-based optimal power flow is used to maximise the social welfare considering uncertainties related to wind speed and load demand. Scenario based approach is used to model the uncertainties. The method assesses the impact of multiple-wind turbine configurations on the amount of wind power that can be injected into the grid and the distribution locational marginal prices throughout the network. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.

Yes / In this paper, a novel deterministic approach for the planning of active distribution networks within a distribution market environment considering multi-configuration of wind turbines (WTs) and photovoltaic (PV) cells is proposed. Multi-configuration multi-period market-based optimal power flow is utilized for maximizing social welfare taking into account uncertainties associated with wind speed, solar irradiance and load demand as well as different operational status of WTs and PVs. Multi-period scenarios method is exploited to model the aforementioned uncertainties. The proposed approach assesses the effect of multiple-configuration of PVs and WTs on the amount of wind and solar power that can be produced, the distribution locational marginal prices all over the network and on the social welfare. The application of the proposed approach is examined on a 30-bus radial distribution network. / This work was supported in part by the Royal Academy of Engineering Distinguished Visiting Fellowship Grant DVF1617/6/45 and by the University of Bradford, UK under the CCIP grant 66052/000000.

The electricity demand increases rapidly, and in order to mitigate climate change the power production needs to be renewable and free from green house gas emissions. When solar and wind power are introduced in the system, voltage instability might become a problem. This study aims to investigate voltage stability and the effects of reactive power compensation. It is done by performing power flow analysis on a simulated power system model in Jämtland, Sweden, with a large share of wind power and a relatively small share of sun power. The simulations are made in MATPOWER (MATLAB). The results reveal that the voltage levels in this study remain stable, with the reactive power being the limiting factor. The use of passive reactive power compensators, like shunt reactors, does not keep reactive power levels in the system within set limits. This study shows that in order to achieve that, active reactive power compensators are required. / Efterfrågan av elektricitet ökar snabbt, och för att kunna mildra klimatförändringarna behöver kraftproduktionen vara förnybar och fri från växtusgasutsläpp. När sol- och vindkraft introduceras kan spänningsstabilitet bli ett problem. Denna studie ämnar att undersöka spänningsstabilitet och effekterna av reaktiv effekt-kompensering. Det görs genom att utföra belastningsfördelningsberäkningar på en simulerad kraftsystem-modell i Jämtland i Sverige, med en stor andel vindkraft och en relativt liten andel solkraft. Simuleringarna görs i MATPOWER (MATLAB). Resultaten visar att spänningsnivåerna i denna studie hålls stabila, där reaktiv effekt är den begränsande faktorn. Användning av passiva reaktiv effekt-kompensatorer så som shuntreaktorer, håller inte de reaktiva effektnivåerna inom önskade gränser. Denna studie visar att, för att kunna uppnå det, så krävs det aktiv reaktiv effekt-kompensering. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

För att uppnå optimal resursdelning och öka hållbar energiförsörjning, stiger behovet av gränsöverskridande kraftöverföring ständigt. Därför frekventa utbyta information med detaljerade galler uppgifter krävs. För att standardisera sådant utbyte och därigenom främja gemensam kraftsystemstudier i Europa, Common Grid Model Exchange Standard (CGMES) grundar sig på IEC CIM (Common Information Models) utfärdats av ENTSO-E (European Network of Transmission Operators for Electricity) i 2013. En CGMES bedömning av överensstämmelse processen också inrättats att uppmuntra och undersöka antagandet av CGMES med relevanta kraftsystemtillämpningar. Huvudsyftet med denna avhandling är att validera att Network Manager produkten av ABB har genomfört CGMES ordentligt. Effektflödesberäkningar utförs baserat på ENTSO-Es provnäten och erhållna lösningarna jämförs med standard resultat samt resultaten från Power Factory (ett kraftsystem analysverktyg från DIgSILENT som redan har passerat bedömningen av överensstämmelse med framgång). Jämförelse resultaten analyseras alltså för att identifiera orsakerna till eventuella avvikelser från standardeffektflödeslösningar och ge förslag på framtida utveckling av Network Manager. / To achieve optimal resource sharing and enhance the sustainability of energy supply, the need for cross-border power transmission is continuously growing. Therefore, frequent information exchange with detailed grid data is required. To standardize such exchange and thus to facilitate common power system studies in Europe, the Common Grid Model Exchange Standard (CGMES) based on IEC CIM (Common Information Models) was issued by ENTSO-E (European Network of Transmission Operators for Electricity) in 2013. A CGMES conformity assessment process was also set up to encourage and examine the adoption of CGMES with relevant power system applications. The main purpose of this thesis is to validate that the Network Manager product of ABB has implemented CGMES properly. Power flow calculations are performed based on ENTSO-E’s test networks and the solutions obtained are compared with the standard results as well as the results from Power Factory (a power system analysis tool from DIgSILENT that has already passed the conformity assessment successfully).  The comparison results are analyzed thus to identify causes of any variation from the standard power flow solutions and to give suggestions for future development of Network Manager.

The aim of this project was to analyze howthe voltage magnitudes of an electrical grid is affectedwhen wind power production varies in an area aroundthe river of Ångermanälven. The goal of the project wasto keep the voltage deviation within 10 % from the setbase value. A secondary goal was to make a profitabilityassessment between power losses and costs related tothe power grid.A transmission grid model was built around Ångermanälven and simulations were made in MATLAB,with the open-source tool package called MATPOWER,to simulate the properties of the grid. Thesesimulations included real hourly historical data fordemand and power generation. Voltage deviation andlosses in the transmission grid for the system was thendetermined with power flow analysis.For the base case, the voltage deviation was keptwithin the limit of a maximum deviation of 10 %. Thebase case was thereafter upgraded to improve transmissionefficiency and resiliency. Increasing the basevoltage resulted in lower losses and voltage deviationsbelow 5 %. To make the grid more resilient and fulfillthe N-1 and N-2 criteria, additional transmission lineswere added. However, these were deemed necessary fora reliable grid, even though the upgrades increased thetotal cost of the system. / Strävan med detta projekt varatt analysera hur spänningsnivån för ett elnätpåverkas av varierande vindkraftsproduktion för ettområde kring Ångermanälven. Målet med projektetvar hålla spänningen inom 10 % från den sattabasspänningen. Ett sekundärt mål var att göra enlönsamhetsbedömning mellan effektförluster och kostnaderrelaterade till elnätet.En model av transmission nätet byggdes kring Ångermanälven och simuleringar utfördes i MATLAB,med hjälp av ett open-source verktyg kallat MATPOWER,för att simulera nätets egenskaper. Simuleringarnainkluderade verklig historisk timvis data förbehov och kraftproduktion. Spänningsavvikelser ochförluster i transmissionsnätet fastställdes med belastningsfördelning.För basfallet hölls spänningsavvikelserna inom denmaximala gränsen på 10 %. Basfallet uppgraderasdärefter för att förbättra transmissionseffektivitet ochtillförlitlighet. Ökning av basspänningen resulterade ilägre andel förluster och spänningsavvikelser på under5 %. För ett mer tillförlitligt nät och för att kunnauppfylla N-1 och N-2 kriterierna, installerades extraledningar. Dessa ledningar ansågs nödvändiga för attuppnå ett tillförlitligt elnät, även om det innebar ettkrav på ökade investeringskostnader för systemet. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

With the advent of distributed energy resources (DERs), electric vehicles, and demand-response programs, grid operators are in dire need of new monitoring and design tools that help improve efficiency, reliability, and stability of modern power networks. To this end, the work in this thesis explores a generalized modeling and analysis framework for two pertinent tasks: i) learning loads via grid probing, and; ii) optimizing power grid topologies for stability. Distribution grids currently lack comprehensive real-time metering. Nevertheless, grid operators require precise knowledge of loads and renewable generation to accomplish any feeder optimization task. At the same time, new grid technologies, such as solar panels and energy storage units are interfaced via inverters with advanced sensing and actuation capabilities. In this context, we first put forth the idea of engaging power electronics to probe an electric grid and record its voltage response at actuated and metered buses to infer non-metered loads. Probing can be accomplished by commanding inverters to momentarily perturb their power injections. Multiple probing actions can be induced within a few tens of seconds. Load inference via grid probing is formulated as an implicit nonlinear system identification task, which is shown to be topologically observable under certain conditions. The analysis holds for single- and multi-phase grids, radial or meshed, and applies to phasor or magnitude-only voltage data. Using probing to learn non-constant-power loads is also analyzed as a special case. Once a probing setup is deemed topologically observable, a methodology for designing probing injections abiding by inverter and network constraints to improve load estimates is provided. The probing task under noisy phasor and non-phasor data is tackled using a semidefinite-program relaxation. As a second contribution, we also study the effect of topology on the linear time-invariant dynamics of power networks. For a variety of stability metrics, a unified framework based on the H2-norm of the system is presented. The proposed framework assesses the robustness of power grids to small disturbances and is used to study the optimal placement of new lines on existing networks as well as the design of radial topologies for new networks. / Doctor of Philosophy / Increased penetration of distributed energy resources such as solar panels, wind farms, and energy storage systems is forcing utilities to rethink how they design and operate their power networks. To ensure efficient and reliable operation of distribution networks and to perform any grid-wide optimization or dispatch tasks, the system operator needs to precisely know the net load (energy output) of every customer. However, due to the sheer extent of distribution networks (millions of customers) and low investment interest in the past, distribution grids have limited metering infrastructure. Nevertheless, data from grid sensors comprised of voltage and load measurements are readily available from a subset of customers at high temporal resolution. In addition, the smart inverters found in solar panels, energy storage units, and electric vehicles can be controlled within microseconds. The work in this thesis explores how the proliferation of grid sensors together with the controllability of smart inverters can be leveraged for inferring the non-metered loads i.e., energy output of customers that are not equipped with smart inverters/sensors. In addition to the load learning task, this thesis also presents a modeling and analysis framework to study the optimal design of topologies (how customers are electrically inter-connected) for improving stability of our power networks.

The restructuring of the electric energy market and the proliferation of intermittent renewable-energy based power generation have introduced serious challenges to power system operation emanating from the uncertainties introduced to the system variables (electricity prices, congestion levels etc.). In order to economically operate the system and efficiently run the energy market, a statistical analysis of the system variables under uncertainty is needed. Such statistical analysis can be performed through an estimation of the statistical moments of these variables. In this thesis, the Point Estimate Methods (PEMs) are applied to the optimal power flow (OPF) problem to estimate the statistical moments of the locational marginal prices (LMPs) and total generation cost under system uncertainty. An extensive mathematical examination and risk analysis of existing PEMs are performed and a new PEM scheme is introduced. The applied PEMs consist of two schemes introduced by H.P. Hong, namely, the 2n and 2n+1 schemes, and a proposed combination between Hong's and M. E Harr's schemes. The accuracy of the applied PEMs in estimating the statistical moments of system LMPs is illustrated and the performance of the suggested combination of Harr's and Hong's PEMs is shown. Moreover, the risks of the application of Hong's 2n scheme to the OPF problem are discussed by showing that it can potentially yield inaccurate LMP estimates or run into unfeasibility of the OPF problem. In addition, a new PEM configuration is also introduced. This configuration is derived from a PEM introduced by E. Rosenblueth. It can accommodate asymmetry and correlation of input random variables in a more computationally efficient manner than its Rosenblueth's counterpart. / Master of Science

Electric vehicles (EVs) are increasing in popularity and play an important role in decarbonizing the transport sector. However, a growing EV fleet can cause problems for power grids as the grids are not initially designed for EV charging. The potential of a power grid to accommodate EV loads can be assessed through hosting capacity (HC) analysis. The HC is grid specific and varies, therefore it is necessary to conduct analysis that reflects local conditions and covers uncertainties and correlations over time. This theses aims to investigate the HC for EVs in existing residential power grids, and to gain a better understanding of how it varies based on how the EVs are implemented and charged. The work is in collaboration with a distribution system operator (DSO) and is based on two case studies using real-life data reflecting conditions in Swedish grids. Combinations of different HC assessment methods have been used and the HC is evaluated based on cable loading, transformer loading and voltage deviation. Additionally, the study investigated three distinct charging strategies: charging on arrival, evenly spread charging over whole connection period, and charging at the lowest spot price.  The results show that decisions on acceptable voltage deviation limit can have a large influence on the HC as well as the charging strategy used. A charging strategy based on energy prices resulted in the lowest HC, as numerous EVs charging simultaneously caused high power peaks during low spot price periods. Charging on arrival was the second worst strategy, as the peak power coincided with household demand. The best strategy was to evenly spread out the charging, resulting in fewer violations for 100% EV implementation compared to the other two strategies for 25% EV implementation.  The findings underscore the necessity for coordinated charging controls for EV fleets or diversified power tariffs to balance power on a large scale in order to use the grids efficiently.