The evolving complexity of electric power systems with higher levels of uncertainties is a new challenge faced by system operators. Therefore, new methods for power system prediction, monitoring and state estimation are relevant for the efficient exploitation of renewable energy sources and the secure operation of network assets. In order to estimate all possible operating conditions of power systems, this Thesis proposes the use of Gaussian mixture models to represent non-Gaussian correlated input variables, such as wind power output or aggregated load demands in the probabilistic load flow problem. The formulation, based on multiple Weighted Least Square runs, is also extended to monitor distribution radial networks where the uncertainty of these networks is aggravated by the lack of sufficient real-time measurements. This research also explores reduction techniques to limit the computational demands of the probabilistic load flow and it assesses the impact of the reductions on the resulting probability density functions of power flows and bus voltages. The development of synchronised measurement technology to support monitoring of electric power systems in real-time is also studied in this work. The Thesis presents and compares different formulations for incorporating conventional and synchronised measurements in the state estimation problem. As a result of the study, a new hybrid constrained state estimator is proposed. This constrained formulation makes it possible to take advantage of the information from synchronised phasor measurements of branch currents and bus voltages in polar form. Additionally, the study is extended to assess the advantages of PMU measurements in multi-area state estimators and it explores a new algorithm that minimises the data exchange between local area state estimators. Finally, this research work also presents the advantages of dynamic state estimators supported by Synchronised Measurement Technology. The dynamic state estimator is compared with the static approach in terms of accuracy and performance during sudden changes of states and the presence of bad data. All formulations presented in this Thesis were validated in different IEEE test systems.

Le Dynamic Line Rating est la modification dynamique des contraintes de courant sur une ligne électrique aérienne, en accord avec la météorologie. De telles modifications permettent alors d’avoir des réductions des phénomènes de congestion près de 99% du temps.De manière similaire aux énergies renouvelables, il est possible de générer des prévisions de ces contraintes modifiées, en accord avec des observations historiques, des prévisions météorologiques et des méthodes d’intelligence artificielle.Dans cette thèse, nous proposons le développement de modèles de prévision probabilistes à court terme du DLR. Nous nous concentrons plus particulièrement sur des méthodes fournissant des prévisions ayant de très faibles probabilités d’être surestimées. Cela passe par le développement et la comparaison de plusieurs méthodes de prévision, ainsi que des améliorations comme des modifications de prévisions à très bas quantile à l’aide de remodélisations des queues de distribution.Par la suite, une réflexion est faite sur l’utilisation en pratique de ces prévisions, d’abord par des cas d’étude simplifié, puis à l’aide de simulations de réseaux électrique. Ces approches nous permettent de développer de nouvelles stratégies d’utilisation des prévisions DLR, optimisant le bien-être social tout en maintenant les risques associés aux erreurs de prévision à un niveau faible.Finalement, nous évaluons les modèles de prévisions développés en fonction de leurs performances économiques à l’aide des modèles de réseaux électriques, et nous démontrons la valeur des améliorations des modèles de prévision que nous proposons. / Dynamic Line Rating is the modification of the maximal current capacity of an overhead electrical line, depending on weather characteristics. Such modifications allow important decreases of congestion phenomena, around 99% of the time.Similarly to renewable generation, it is possible to forecast the modified constraints, accordingly to some historic observations, weather predictions and artificial intelligence methods.In this document, the development of short-term probabilistic DLR forecast models. A focus is especially made on methods providing forecasts having a very low probability of being overestimated. This is made through the development and the comparison of several forecast methods, and some improvements such as the remodelling of very low quantile forecasts with tail density modelling.Following that, a reflection is proposed on the use of such forecasts in practice, first with some simplified test cases, then with electrical grid simulations. These approaches allow us developing new strategies for the use of the DLR forecasts, maximizing the social welfare while keeping risks associated with forecasts errors at low levels.Finally, an evaluation of the forecast models function of their economic value is made with the electrical grids models, and the value of the proposed modifications of the forecast models is then demonstrated.

In recent years, large investments have been made in wind power, and this trend is expected to continue in the coming decades. Integrating more wind power in the production mix offers great opportunities for the society, such as reducing greenhouse gas emissions and the dependence on foreign fuel. Large wind power penetration does, however, require changes in the way power systems are planned and operated. The power transfers across the electrical grid are determined by the load and the production. A secure operation of power systems requires that these power transfers stay within certain limits. Frequency control schemes are crucial for ensuring the balance between the electric demand and the production. They enable system operators to re-dispatch the production (for example via the activation of balancing bids) during real-time operations to follow the load variations. With wind power, these frequency control schemes must not only meet the variations of the load but also those of the wind. An optimal use of the frequency control reserves would allow system operators to operate the system in the most cost effective and secure manner, that is, using the cheapest available resources while taking into account the stability limits of the system and the uncertainty. With no wind power, the load is the main source of uncertainty, and it can be forecasted accurately. This enables system operators to dispatch the generation in the most cost-effective way to meet the load while keeping the system within its stability limits. Adding wind power to power systems, on the other hand, introduces a new source of uncertainty on the production side, which is more difficult to forecast. The tools used today for computing the stability limits and operating the system do not consider the whole range of possible future load and wind power production levels, but only pick a few likely values in this range. In this work, we propose a new approach which accounts for the whole uncertainty in the load and wind power, and gives the optimal re-dispatch which ensures a given level of system security given this uncertainty. The approach is a so-called Stochastic Optimal Power Flow (S-OPF) formulation, developed in the scope of this project for the optimal activation of balancing bids. It is a nonlinear optimization problem with one probabilitistic constraint ensuring a certain level of system security -- computed as the probability that the system stays within its stability limits -- and whose objective function is the minimization of the generation re-dispatch. Compared to what is done today, the S-OPF formulation enables system operators to consider the uncertainty when making decisions. An approximation of the proposed S-OPF formulation is developed to render the problem tractable. In particular, the stability boundary, defined as the set of stability limits, is approximated by second-order approximations. The accuracy of these second-order approximations are analyzed in the IEEE 9 bus system by computing the distance between the actual boundary and its approximation. The S-OPF problem is then solved in the IEEE 39 bus system using the approximated stability boundaries. Monte Carlo simulations are run in order to assess the accuracy of the approximation and check whether the optimal solution of the approximation does ensure the specified level of system security. / <p>QC 20121121</p>

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-08-15T16:36:49Z No. of bitstreams: 1 ANTONIO MARCOS DELFINO DE ANDRADE – TESE (PPGMet) 2017.pdf: 3321439 bytes, checksum: 641b9755396203a4dd27ac62503ca9e8 (MD5) / Made available in DSpace on 2018-08-15T16:36:49Z (GMT). No. of bitstreams: 1 ANTONIO MARCOS DELFINO DE ANDRADE – TESE (PPGMet) 2017.pdf: 3321439 bytes, checksum: 641b9755396203a4dd27ac62503ca9e8 (MD5) Previous issue date: 2016-02-19 / Capes / A radiação de onda longa incidente (L↓) é seguramente a componente do balanço de radiação mais difícil de ser medida. Portanto, diferentes formulações têm sido propostas para estimá-la. Desta maneira, avaliou-se neste estudo o desempenho de várias formulações para a estimativa dos fluxos de L↓ e sua a interação com outras variáveis medidas, bem como as interações da temperatura do ar e da pressão de vapor d’água junto à L↓. Neste estudo foi utilizada a análise pela transformada em ondeletas (TO) como ferramenta matemática para a análise de variações locais de energia dentro das séries temporais aqui estudadas, pela sua decomposição no tempo-frequência-espaço. Para investigar a correlação entre duas séries (L↓ com a temperatura do ar e da L↓ medida com as estimadas por cada modelo), empregou-se transformada cruzada em ondeletas e a coerência e fase em ondeletas. Os dados deste estudo compreendem o período de 01 de janeiro a 31 de dezembro de 2009, e são provenientes da torre micrometeorológica (K34) pertencente ao Experimento de Grande Escala da Biosfera Atmosfera na Amazônia (LBA) em Manaus, Amazonas. A TO revelou que no período de 36 horas, para todo período analisado, um persistente, homogêneo e forte espectro energético entre a L↓ e a temperatura do ar, onde se constatou uma sinergia entre essas variáveis. Constatou -se ainda que a precipitação e a pressão de vapor d’água exercem bastante influencia nos fluxos de L↓, principalmente na estação chuvosa. A análise através da transformada cruzada e de coerência e fase em ondeletas no período de 32 a 64 horas. Já nos modelos ajustados foram no período de 16 a 64 horas. Os modelos propostos para condições de céu claro, com o uso de seus coeficientes originais, mostraram tendência em subestimar os fluxos de L↓ medidos. Com os ajustes nos coeficientes, os modelos expuseram uma melhora nas estimativas nos fluxos de L↓.Para os modelos propostos para condições de céu nublado, estes exibiram um desempenho regular. / The downward longwave radiation (L↓) component really is difficult of the net radiation the measured. Therefore, different parameterizations have been proposed to estimate it. Thus, in this study we evaluated the performance of various parameterizations for the L↓ flows estimated and their interaction with other variables measured as well as the air temperature and water vapour pressure interactions with L↓. In this study we used by wavelet transform (WT) analysis as mathematical tool for energy of local variations analysis in the studied time series here by their frequency time-space decomposition. To investigate the correlation between two series (L↓ with air temperature and between L↓ measured with estimated), we used crosswavelet transform and coherency wavelets and phase angle. The datasets used in this study are of the January 01 to December 31 of 2009, measured from micrometeorological tower (named K34) controlled by Large Scale Biosphere Atmosphere experiment in Amazonia (LBA) from Manaus city, Amazonas. The WT showed that in 36 hours period, for the entire period analyzed, a persistent, smooth and strong energy spectrum between L↓ and the air temperature, which demonstrated a synergy between these variables. It was also found that precipitation and water vapour pressure exert enough on L↓ flows influence, especially in the wet season. The crosswavelet transform and coherency wavelets and phase angle analysis at 32 to 64 hours period. Already in adjusted models were in the 16-64 hours period. With the adjustable coefficients, according to the environmental study area conditions, the models presents an improvement in the L↓ flows estimates. The cloudy skies models proposed, they exhibited a regular performance.

Modern day power systems present an open access environment, inspiring participation from small scale and large power suppliers. With multiple players in the system driven by the market, proper monitoring and control of system becomes a major concern. This transformation is accompanied by dynamic consumption patterns and rising power demands. The expanding network encompassing EHV/AC network, HVDC and FACTS devices, along with increased penetration of renewable sources, viz. solar and wind energy at medium and low voltage levels, adds to the problem. Independent System Operators (ISO) are entrusted with ensuring smooth operation, and employing proper preventive measures to eliminate a possible cascade tripping leading to a partial or large-scale blackout. To aid the operator in the process of ensuring secure operation of the grid, there are many tools that provide required information and guidance. Power flow tracing is one such tool that aids the operator in congestion management, transmission pricing, transaction evaluation, loss allocation and reactive power optimization. In this thesis, a novel active power flow tracing approach is proposed that takes into account, the real-time operating conditions and network topology. It provides the decomposition of active power flow in a line into respective components injected by various generators in the system. It also provides the contribution of the generators to various loads in the system. The approach is simple and computationally fast, making it an ideal tool to aid preventive control decisions. Based on the proposed active power flow tracing, a congestion management approach is developed. The approach indicates the least number of generators that need to be coordinated for generation rescheduling, so as to alleviate overloading in affected transmission lines and transformers. The approach also takes into consideration the operating constraints on the system, while computing the optimal rescheduling amongst selected generators using LP technique. The thesis also presents a real power loss allocation approach based on the proposed power flow tracing. Loss allocation is an important part of tariff design as the cost associated with losses amounts to a sizable fraction of total revenue collected from the loads. The approach provides information as to how losses are distributed among loads and how much each generator is providing for the loss share of each load. The approaches developed in the thesis are illustrated on a sample 10-bus equivalent system, IEEE 30-bus, and IEEE 39-bus systems. Results for typical case studies are presented for practical systems of 72-bus equivalent and 203-bus equivalent of Indian Southern grid.

No description available.

Transmission pricing and congestion management are two important aspects of modern power sectors working under a deregulated environment or moving towards a deregulated system (open access) from a regulated environment. The transformation of power sector for open access environment with the participation of private sector and potential power suppliers under the regime of trading electricity as a commodity is aimed at overcoming some of the limitations faced by the vertically integrated system. It is believed that this transformation will bring in new technologies, efficient and alternative sources of power which are greener, self sustainable and competitive. There is ever increasing demand for electrical power due to the changing life style of human beings fueled by modernization and growth. Augmentation of existing capacity, siting of new power plants, and a search for alternate viable sources of energy that have lesser impact on environment are being taken up. With the integration of power plants into the grid depending upon the type, loca- tion and technology used, the cost of energy production also differs. In interconnected networks, power can flow from one point to other point in infinite number of possible paths which is decided by the circuit parameters, operating conditions, topology of network and the connected loads. The transmission facility provided for power transfer has to recover the charges from the entities present in the network based on the extent of utilization. Since power transmission losses account for nearly 4 to 8% of the total generation, this has to be accounted for and shared properly among the entities depending upon the connected generation/load. In this context, this thesis aims to evaluate the shortcomings of existing tracing methods and proposes a tracing method based upon the actual operating conditions of the network taking into account the network parameters, voltage gradient among the connected buses and topology of the network as obtained by the online state estimator/load flow studies. The concept proposed is relatively simple and easy to implement in a given transactional period. The proposed method is compared against one of the existing tracing technique available in literature. Both active and reactive power tracing is handled at one go. The summation of partial contributions from all the sources in any given line of the system always matches with that of the respective base case ow. The AC power flow equations themselves are nonlinear in nature. Since the sum of respective partial flows in a given branch is always equal to the original ow, these are termed as virtual flows and the effect of nonlinearity is still unknown. The virtual flows in a given line are complex in nature and their complex sum is equal to the original complex power flows as in the base case. It is required to determine whether these are the true partial flows. To answer this, a DC equivalent of the original AC network is proposed and is called as the R - P equivalent model. This model consists of only the resistances as that of original network (the resistances of transformers and lines neglecting the series reactance and the shunt charging) only. The real power injections in a AC network i.e. sources into respective buses and loads (negative real power injections) are taken as injection measurements of this R P model and the bus voltages (purely real quantities) are estimated using the method of least squares. Complex quantities are absent in this model and only real terms which are either sums or differences are present. For this model, virtual flows are evaluated and it has been verified that the virtual real power contributions from sources are in near agreement with the original AC network. This implies that the virtual flows determined for the original network can be applied for day-to-day applications. An important feature of the virtual flows is that it is possible to identify counter ow components. Counter flow components are the transactions taking place in opposite direction to the net flow in that branch. If a particular source is produces counter flow in a given line, then it is in effect reducing congestion to that extent. This information is lacking in most of the existing techniques. Counter flows are useful in managing congestion. HVDC links are integrated with HVAC systems in order to transfer bulk power and for the additional advantages they offer. The incremental cost of a DC link is zero due to the closed loop control techniques implemented to maintain constant power transfer (excluding constant voltage or constant current control). Consequently, cost allocation to HVDC is still a problem. The proposed virtual power flow tracing method is extended to HVAC systems integrated with HVDC in order to determine the extent of utilization of a given link by the sources. Before evaluating the virtual contributions to the HVDC links, the steady state operating condition of the combined system is obtained by per-forming a sequential load flow. Congestion is one of the main aspects of a deregulated system, and is a result of several transactions taking place simultaneously through a given transmission facility. If congestion is managed by providing pricing signals for the transmission usage by the parties involved. It can also be due to the non-availability of transmission paths due to line outages as a result of contingencies. In such a case, generation active power redispatch is considered as a viable option in addition to other available controls such as phase shifters and UPFCs to streamline the transactions within the available corridors. The virtual power flow tracing technique proposed in the thesis is used as a guiding factor for managing congestions occurring due to transactions/contingencies to the possible extent. The utilization of a given line by the sources present in the network in terms of real power flow is thus obtained. These line utilization factors are called as T-coefficients and these are approximately constant for moderate increments in active power change from the sources. A simple fuzzy logic based decision system is proposed in order to obtain active power rescheduling from the sources for managing network congestions. In order to enhance the system stability after rescheduling, reactive power optimization has life systems to illustrate the proposed approaches. For secure operation of the network, the ideal proportion of active power schedule from the sources present in the network for a given load pattern is found from network [FLG] matrix. The elements of this matrix are used in the computation of static voltage stability index (L-index). This [FLG] matrix is obtained from the partitioned network YBUS matrix and gives the Relative Electrical Distance (RED) of each of the loads with respect to the sources present in the network. From this RED, the ideal proportion of real power to be drawn by a given load from different sources can be determined. This proportion of active power scheduling from sources is termed as Desired Proportion of Generation (DPG). If the generations are scheduled accordingly, the network operates with less angular separation among system buses (improved angular stability), improved voltage profiles and better voltage stability. Further, the partitioned K[GL] matrix reveals information about the relative proportion in which the loads should draw active power from the sources as per DPG which is irrespective of the present scheduling. Other partitioned [Y ′ GG] matrix is useful in finding the deviation of the present active power output from the sources with respect to the ideal schedule. Many regional power systems are interconnected to form large integrated grids for both technical and economic benefits. In such situations, Generation Expansion Planning (GEP) has to be undertaken along with augmentation of existing transmission facilities. Generation expansion at certain locations need new transmission networks which involves serious problems such as getting right-of-way and environmental clearance. An approach to find suitable generation expansion locations in different zones with least requirements of transmission network expansion has been attempted using the concept of RED. For the anticipated load growth, the capacity and siting generation facilities are identified on zonal basis. Using sample systems and real life systems, the validity of the proposed approach is demonstrated using performance criteria such as voltage stability, effect on line MVA loadings and real power losses.