Reliability evaluation of power system considering voltage stability and continuation power flow

This article describes the methodology for evaluation of the reliability of an composite electrical power system considering voltage stability and continuation power flow, which takes into account the peak load and steady state stability limit. The voltage stability is obtained for the probable outage of transmission lines and removal of generators along with the combined state probabilities. The loss of load probabilities (LOLP) index is evaluated by merging the capacity probability with load model. State space is truncated by assuming the limits on total numbers of outages of generators and transmission lines. A prediction correction technique has been used along with one dimensional search method to get optimized stability limit for each outage states. The algorithm has been implemented on a six-bus test system

Wide Area Monitoring and Control

Today\u27s interconnected power system is deregulated for wholesale power transfers. In 1996 Federal Energy Regulatory Commission provided open access of the transmission network to utilities. Since then utilities are transferring power over long distances to bring reliable and economical electric supply to their customers. As the number of wholesale power transactions taking place over an interconnected system are increasing, system operators in control areas are forced to monitor the grid on a large scale to operate it reliably. Before scheduling such a large scale power transactions, it is necessary to make sure that such transaction will not violate system operating steady state security limits such as transmission line-flow limits and bus voltage limits. The ideal solution to this problem is to consider entire interconnected system as one system to monitor it. However, this solution is technically expensive if not impossible and hindered by confidentiality issues. This research aims to develop tools that help the system operators to operate the deregulated power grid reliably. State estimation is the tool used by today\u27s energy control centers to develop a base case of the system in real-time, which is further used to study the impact of disturbances and power transactions on static and dynamic security limits of the system. In order to monitor the deregulated power system, a wide area state estimator is required. In this dissertation a two-level approach to achieve such a solution is presented. This way, individual areas are allowed to run their own state estimator, without exchanging any real-time data with neighbor areas. The central coordinator then coordinates state estimator results available from individual areas to bring them to a global reference. This dissertation also presents the application of measurements from GPS synchronized phasor measurement units to improve accuracy of two-level state estimator. In addition to monitoring, system operators also need to determine that if they can allow the scheduled transaction to take place. This requires them to determine transfer capability of the system in real-time. This dissertation presents new iterative transfer capability algorithm which can be used in real-time. As an interconnected system is deregulated and the power transactions are taking place through many control areas, a system wide solution of transfer capability is required. This dissertation presents a two-level framework similar to one used for state estimation to achieve multi-area transfer capability solution. In general, the research work carried out would help in improving power system reliability and operation

Reliability Evaluation of Power System Considering Voltage Stability and Continuation Power Flow

JES Journal of Electrical Systems This article describes the methodology for evaluation of the reliability of an composite electrical power system considering voltage stability and continuation power flow, which takes into account the peak load and steady state stability limit. The voltage stability is obtained for the probable outage of transmission lines and removal of generators along with the combined state probabilities. The loss of load probabilities (LOLP) index is evaluated by merging the capacity probability with load model. State space is truncated by assuming the limits on total numbers of outages of generators and transmission lines. A prediction correction technique has been used along with one dimensional search method to get optimized stability limit for each outage states. The algorithm has been implemented on a six-bus test system

Analysis and management of security constraints in overstressed power systems

Management of operational security constraints is one of the important tasks performed by system operators, which must be addressed properly for secure and economic operation. Constraint management is becoming an increasingly complex and challenging to execute in modern electricity networks for three main reasons. First, insufficient transmission capacity during peak and emergency conditions, which typically result in numerous constraint violations. Second, reduced fault levels, inertia and damping due to power electronic interfaced demand and stochastic renewable generation, which are making network more vulnerable to even small disturbances. Third, re-regulated electricity markets require the networks to operate much closer to their operational security limits, which typically result in stressed and overstressed operating conditions. Operational security constraints can be divided into static security limits (bus voltage and branch thermal limits) and dynamic security limits (voltage and angle stability limits). Security constraint management, in general, is formulated as a constrained, nonlinear, and nonconvex optimization problem. The problem is usually solved by conventional gradient-based nonlinear programming methods to devise optimal non-emergency or emergency corrective actions utilizing minimal system reserves. When the network is in emergency state with reduced/insufficient control capability, the solution space of the corresponding nonlinear optimization problem may be too small, or even infeasible. In such cases, conventional non-linear programming methods may fail to compute a feasible (corrective) control solution that mitigate all constraint violations or might fail to rationalize a large number of immediate post-contingency constraint violations into a smaller number of critical constraints. Although there exists some work on devising corrective actions for voltage and thermal congestion management, this has mostly focused on the alert state of the operation, not on the overstressed and emergency conditions, where, if appropriate control actions are not taken, network may lose its integrity. As it will be difficult for a system operator to manage a large number of constraint violations (e.g. more than ten) at one time, it is very important to rationalize the violated constraints to a minimum subset of critical constraints and then use information on their type and location to implement the right corrective actions at the right locations, requiring minimal system reserves and switching operations. Hence, network operators and network planners should be equipped with intelligent computational tools to “filter out” the most critical constraints when the feasible solution space is empty and to provide a feasible control solution when the solution space is too narrow. With an aim to address these operational difficulties and challenges, this PhD thesis presents three novel interdependent frameworks: Infeasibility Diagnosis and Resolution Framework (IDRF), Constraint Rationalization Framework (CRF) and Remedial Action Selection and Implementation Framework (RASIF). IDRF presents a metaheuristic methodology to localise and resolve infeasibility in constraint management problem formulations (in specific) and nonlinear optimization problem formulations (in general). CRF extends PIDRF and reduces many immediate post-contingency constraint violations into a small number of critical constraints, according to various operational priorities during overstressed operating conditions. Each operational priority is modelled as a separate objective function and the formulation can be easily extended to include other operational aspects. Based on the developed CRF, RASIF presents a methodology for optimal selection and implementation of the most effective remedial actions utilizing various ancillary services, such as distributed generation control, reactive power compensation, demand side management, load shedding strategies. The target buses for the implementation of the selected remedial actions are identified using bus active and reactive power injection sensitivity factors, corresponding to the overloaded lines and buses with excessive voltage violations (i.e. critical constraints). The RASIF is validated through both static and dynamic simulations to check the satisfiability of dynamic security constraints during the transition and static security constraints after the transition. The obtained results demonstrate that the framework for implementation of remedial actions allows the most secure transition between the pre-contingency and post-contingency stable equilibrium points

Vulnerability Assessment of Electric Power Supply under Extreme Weather Conditions

This thesis analyses and models the vulnerability of the electricity power supply under extreme weather conditions. The system under study is the electric supply system that includes major power plants to main load centers. Extreme weather conditions can cause common mode contingencies (CMCs) of overhead power lines, which endanger the security of electricity supply. Planning and operation of transmission systems are subject to N-1 criterion, which requires that all single failures of network elements do not cause a breach of safety limits. This criterion does not guarantee the security of electricity supply at the time of extreme weather conditions. The objective of this research is to identify critical and plausible CMCs, taking into account space-time correlations of extreme weather conditions and possible states of the network. The most vulnerable zones are focused on to determine appropriate countermeasures for reducing vulnerability. In the past, extreme weather events have caused major disruptions. For example, the blackout in New York in 1977 was initiated by three impacts of lightning on high voltage lines. In 1999, hurricane Lothar caused damage to power grids in several countries, leaving hundreds of thousands of people in darkness. These examples demonstrate the vulnerability of power systems to CMCs. Current transmission networks are expected to undergo significant changes in response to developments such as increases in consumption and newly installed capacity. These changes provide an opportunity to strengthen the security of electricity supply in the perspective of extreme weather conditions and even improve the resilience of electric supply systems. The use of the proposed methodology allows reducing the level of vulnerability by reinforcing only few points or change of the topology of the network. Faced with uncertainties about the evolution of networks and plausible extreme weather conditions, a methodology based on scenarios has been selected. The methodology allows the modeler to reproduce the complexity of the problem while still encouraging the learning process. The core of the methodology is founded on a scenario of electric supply systems and a scenario of extreme weather events. The first scenario includes three models: electric, geographic, and reliability. The electric model comprises components of the network compatible with load flow calculations. The geographic model contains a representation of each power line in a geographic information system, and each of these lines is divided into segments that are associated with a reliability model. The reliability model evaluates failure rates related to exposure to extreme weather conditions. Scenarios of extreme weather events are built on data from weather stations or by numerical simulations implemented in a geographic information system. A vulnerability level index is calculated on the basis of probability and severity indices of a priori possible CMCs. These probabilities are evaluated by a simulation of the interaction between the scenario of transmission network and scenario of extreme weather event. They are a subjective and temporal measure of plausibility of CMCs stemming from interactions in space and time of the two systems previously mentioned. The severity index of CMCs is calculated by a contingency analysis that involves the evaluation of security limit violations. A matrix of vulnerability is constructed as a projection of the vulnerability level in two dimensions, including the lines involved in overload and those being overloaded. This matrix allows the identification of the infrastructures involved in the vulnerability and the determination of major zones of vulnerability. Countermeasures are then proposed to reduce the vulnerability of these zones, and these measures may include additions or retirement of lines or other network topology changes. This methodology is applied to the Swiss transmission network in 2018 subject to summer thunderstorms. A reference case from 2006 is compared in terms of vulnerability to a plausible scenario of transmission network 2018. The latter includes an increased consumption of 20%, around 3 GW of pumped-storage power plants, and network changes proposed by the electricity sector plan supported by the Swiss Federal Office of Energy. On another level, two scenarios of extreme weather events were constructed. The first is an intense thunderstorm occurring in the past, where lightning strikes were recorded by a tracking system. The second case stems from a simulation of a thunderstorm event composed of six cells passing over the Swiss territory. The vulnerability of both scenarios of electric supply system impacted by both scenarios of extreme weather events was evaluated. Two major zones of vulnerability were detected both in the reference case 2006 and the plausible scenario 2018. They are in mountainous regions near major centers of production. The network changes between 2006 and 2018 did not decrease the vulnerability. This is due to the installation of large generation capacity and the difficulty of building lines as a result of the topography in these regions. To reduce vulnerability, the addition of a 380 kV overhead line is proposed for the plausible scenario 2018. This line allows draining off the new hydro generation by offering a new route to major consumption centers and drastically reduces the vulnerability of the two zones mentioned. This measure illustrates the methodology's ability to identify areas of vulnerability and propose actions to increase network resilience. One of the major contributions and innovative points of this research is the consideration of the spatiotemporal correlations of extreme weather conditions for the geographical distribution and structural resistance of transmission lines. In the application of the Swiss 2018 scenario of transmission network, the concept of major zones of vulnerability was useful in identifying the weakest zones and in finding a measure capable of increasing network resilience

An integrated approach incorporating dynamic and static security limits in optimum power dispatch

Optimum power dispatch is performed in a power system to determine the most economic power dispatch condition for a certain system loading. In this thesis the main focus is on the investigation of this problem and its improved application by including both dynamic security and static security limits in its solution. The aim is to develop an efficient and practical on-line method of optimum power dispatch with due regard to the necessary security requirements. A critical review of the current practices of security and optimization in power system operation shows that they are essential elements in Energy Management System computer softwares. Since optimality and security present conflicting requirements on system operation, it is both logical and beneficial to develop an integrated approach to satisfy all the security limits in optimum dispatch. The classical approach to consider only the static security limits in optimum dispatch calculation is found to be insufficient in providing the essential informations on the dynamic security performance. This problem is causing increasing concern with the recent trend to load power systems more closer to their stability limits in order to achieve maximum economy. A new formulation of the security constrained optimum dispatch problem with an integrated approach to consider both dynamic and static security limits is thus proposed in this thesis. The Optimum Power Flow ( OPF ) formulation uses a Recursive Quadratic Programming algorithm applied in the compact modelling of the system. This formulation consists of a decoupling process of the active and reactive power optimizations. The investigation into on-line security control shows that insufficient attention on dynamic security in present practice could endanger the system integrity in the contingency state. This leads to the development of a new scheme to integrate both dynamic and static security assessments. Direct application of classical transient stability assessment methods using numerical integration of swing equations is found to be too slow and a new method based on reduced dynamic equivalent is investigated. The method is based on an efficient dynamic security assessment scheme which assesses the on-line operating state of the system. A dynamic security margin is defined to measure the robustness of the system when it is subjected to a selected scenario of dynamic contingency. The method also identifies the critical machine or cluster of machines that would cause transient instability, and proposes preventive control strategies to improve the dynamic security performance. This is integrated in the approach as a preventive control module. The module aims to prevent the system from reaching probable system collapse due to contingency that could cause cascading tripouts in the system. Extensive simulation tests are performed using the approach in several example networks together with validation case studies compared to full load flow and transient stability tests. The results demonstrate that the approach is fast and reliable with good potential for on-line application in stability limited power systems.Optimum power dispatch is performed in a power system to determine the most economic power dispatch condition for a certain system loading. In this thesis the main focus is on the investigation of this problem and its improved application by including both dynamic security and static security limits in its solution. The aim is to develop an efficient and practical on-line method of optimum power dispatch with due regard to the necessary security requirements. A critical review of the current practices of security and optimization in power system operation shows that they are essential elements in Energy Management System computer softwares. Since optimality and security present conflicting requirements on system operation, it is both logical and beneficial to develop an integrated approach to satisfy all the security limits in optimum dispatch. The classical approach to consider only the static security limits in optimum dispatch calculation is found to be insufficient in providing the essential informations on the dynamic security performance. This problem is causing increasing concern with the recent trend to load power systems more closer to their stability limits in order to achieve maximum economy. A new formulation of the security constrained optimum dispatch problem with an integrated approach to consider both dynamic and static security limits is thus proposed in this thesis. The Optimum Power Flow ( OPF ) formulation uses a Recursive Quadratic Programming algorithm applied in the compact modelling of the system. This formulation consists of a decoupling process of the active and reactive power optimizations. The investigation into on-line security control shows that insufficient attention on dynamic security in present practice could endanger the system integrity in the contingency state. This leads to the development of a new scheme to integrate both dynamic and static security assessments. Direct application of classical transient stability assessment methods using numerical integration of swing equations is found to be too slow and a new method based on reduced dynamic equivalent is investigated. The method is based on an efficient dynamic security assessment scheme which assesses the on-line operating state of the system. A dynamic security margin is defined to measure the robustness of the system when it is subjected to a selected scenario of dynamic contingency. The method also identifies the critical machine or cluster of machines that would cause transient instability, and proposes preventive control strategies to improve the dynamic security performance. This is integrated in the approach as a preventive control module. The module aims to prevent the system from reaching probable system collapse due to contingency that could cause cascading tripouts in the system. Extensive simulation tests are performed using the approach in several example networks together with validation case studies compared to full load flow and transient stability tests. The results demonstrate that the approach is fast and reliable with good potential for on-line application in stability limited power systems