Decentralized state estimation and remedial control action for minimum wind curtailment using distributed computing platform

Remedial Action Schemes (RAS) provide automatic control action with high impact on system performance. In order to improve the resilience of the RAS against any single node failure and to guarantee the secured and reliable operation of the power systems, distributed implementations of the RAS is researched upon. The input data to such a distributed RAS must be of high quality. In addition, RAS operation must be fast. Traditional centralized state estimation, which feeds data to RAS is slow and cannot meet the requirements of RAS. New approach needs to be developed to provide the fast and accurate data to RAS. In order to solve this problem, distributed state estimation is developed as an alternative strategy to feed data to the RAS. This paper discusses the implementation of Distributed Linear State Estimation (DLSE) in a decentralized platform called Resilient Information Architecture Platform for Smart Grid (RIAPS). The DLSE algorithm is fully implemented in RIAPS platform and validated on a real-time testbed consisting of Real Time Digital Simulator, Phasor Measurement Units and BeagleBones. The effectiveness of the proposed approach is validated through online simulations on IEEE 14-bus test system under various cyber failures.

Guest Editorial: Situational awareness of integrated energy systems

Environmental concerns about global warming and climate change have led to the large-scale integration of renewable sources such as wind energy in power systems. However, this integration has resulted in a reduction in the level of network inertia. Network inertia is responsible for controlling the stability of the network during a disturbance. Therefore, the increase in the integration of wind energy has led to stability concerns in the network. In this work, a Remedial Action Scheme (RAS) to provide the optimum value of wind power injection for specific network inertia has been proposed. To achieve this objective, a Linear Programming (LP) problem has been framed for maximizing the amount of wind power injection into the network with network inertia as the constraint. The proposed method is tested for the WSCC 9-bus network using PSCAD/EMTDC simulations and the results highlight the performance of the method.

The Remedial Action Scheme (RAS) is designed to take corrective actions after detecting predetermined conditions to maintain system transient stability in large interconnected power grids. However, since RAS is usually designed based on a few selected typical operating conditions, it is not optimal in operating conditions that are not considered in the offline design, especially under frequently and dramatically varying operating conditions due to the increasing integration of intermittent renewables. The deep learning-based RAS is proposed to enhance the adaptivity of RAS to varying operating conditions. During the training, a customized loss function is developed to penalize the negative loss and suggest corrective actions with a security margin to avoid triggering under-frequency and over-frequency relays. Simulation results of the reduced United States Western Interconnection system model demonstrate that the proposed deep learning–based RAS can provide optimal corrective actions for unseen operating conditions while maintaining a sufficient security margin.

Contingency analysis (CA) is a well-known function in power system planning and operation. In accordance with CA results, the system operator dispenses information regarding static security of the power system (overloads and/or voltage outside tolerable limits). However, classic CA with remedial action schemes cannot distinguish safe operating regimes from potentially dangerous ones in terms of voltage (in)stability. In fact, voltage instability is considered as one of the major threats leading to power system insecurity. Therefore, in this study an enhanced contingency analysis (ECA) is presented where the classical CA is extended with static voltage analysis based on the modal analysis. The article presents a dedicated methodology for the proposed ECA tool, with special emphasis on the analysis of corrective measures provided by the system operator, intended for enhancing power system security (regulation transformer action, distributed generation and energy storage). Also the influence of the load model was analyzed by simulation and the main conclusions are presented. The study demonstrated the advantages that distributed generation resources and energy storage can provide in the context of voltage stability. Also, the simulations acknowledged the importance of correct load modeling, since over or under estimation of a certain load-type component can result in too optimistic or too pessimistic power system operation limits.

Enabling renewable generation integration to the power grids has become an essential element of the smart grid roadmap. As electric utilities prepare to meet the Renewable Portfolio Standard goals, advanced sensing and communication technologies can be used to facilitate renewable integration. The Remedial Action Scheme (RAS) is becoming an attractive mitigation approach to maintain transmission system reliability and security, while deferring transmission capital investment. Besides, RAS can bring in valuable operation information for generation analytical model development. In this paper, the role of RAS in the mitigation of renewable integration issues is presented. A need for an effective centralized RAS implementation strategy under the framework of Wide-Area Monitoring, Protection, and Control methodology is also discussed.

A new mechanism for remedial action schemes design in a multi-area power system considering competitive participation of multiple electricity market players

The integration of ICT into power systems has increased the interdependencies between the two systems. The operation of power system depends on several ICT-enabled grid services which manifest the interdependencies. ENTSO-E system state classification is a tool that is widely used by operators to determine the current operational state of the power system. However, it does not adequately describe the impact of ICT disturbances on the operation of the power system. Despite their interconnections, the operational states of both systems have been described separately so far. This paper bridges the well-established ENTSO-E systems state classification with an ICT system state classification, forming a new model considering the state classification of the ICT-enabled grid services. The model is developed by first identifying the ICT-enabled services, remedial actions and the respective performance requirements that are required by the power system. Then the states of these services are specified based on the supporting ICT system. The resulting joint state description shows how performance degradation of ICT-enabled services (introduced by disturbances) can affect the operation of the interconnected power system. Two case studies of such ICT-enabled services, namely state estimation and on-load tap changer control, are investigated in terms of how their operational states affect the states of the power system. A third case study highlights the interdependencies that exist between the services. These case studies demonstrate the interdependencies that exist between power and ICT systems in modern cyber-physical energy systems, thus highlighting the usage of a unified system state description.

Several major blackouts in the past have shown the need for advanced wide‐area monitoring and control (WAMC) techniques. Advanced synchrophasor visualization and monitoring can be realized with time‐referenced power system data that are collected by phasor measurement units (PMUs) using synchronized clocks. Presently, PMUs are being deployed around the world at a rapid rate for various power system applications. When a necessary number of PMUs are installed at optimal locations throughout the network, the complete state of the system can be observed. PMUs take real‐time measurements to determine the state of the power system and can be used to enhance state estimation efficiency. With PMUs in place, there are many control and protection schemes that can be implemented successfully to take preventive and corrective actions. These remedial action schemes (RASs) are classified by the IEEE Power System Relaying Committee (PSRC) as system integrity protection schemes (SIPSs). This work involved the development of a real‐time hardware test bed in order to analyze the transient stability of a simulated power system by using synchrophasors to visualize system stress across a transmission line with and without load‐shedding schemes. The real time digital simulator (RTDS®) was used to model the power system in real time. PMUs, a satellite‐synchronized clock, and a synchrophasor vector processor (SVP) were used to test the synchrophasor application. Copyright © 2010 John Wiley & Sons, Ltd.

When VSC HVDC is applied to the meshed power system, if the appropriate operating point is not determined, it is adversely affected to the total power system. To avoid the side effects of HVDC operation, this paper proposes a method to determine the proper operating point of VSC HVDC. Especially, the control of the VSC HVDC can be a burden for the system operator. In order to alleviate this burden, preventive control should be applied to reduce the burden on system operators. The danger of overloading of the AC line is predicted in advance, so that the operating point at which overload does not occur after an accident is determined as the operating point of VSC HVDC. The typical conventional VSC HVDC control methods are constant active/reactive power control and remedial action scheme. In the former case, there is no control after the contingency, which can cause AC overload or overvoltage problems. The latter controls the operating point for system reliability, but it can be a burden for the system operator and can cause problems in the system in case of communication failure. On the other hand, when applying the preventive control, it is possible to determine an operating range in which the AC load and the overvoltage do not occur even after N − 1 contingency in the operating range of VSC HVDC. In addition, in this paper, we proposed an operating point that minimizes the system’s total losses in the area. The proposed control strategy can reduce the burden on the VSC HVDC operation and can also provide economic benefits by reducing losses. This will be one of the VSC HVDC operation plans that can be selected by the system operator in the future.

Cyber attacks and extreme events can cause severe consequences to the grid that require immediate response. Conventional remedial action schemes (RAS) use offline calculations to determine corrective control actions to deploy for a predetermined set of credible contingencies. Yet, cyber attacks cannot be sufficiently represented in a look‐up table approach; such contingencies are highly dynamic and unpredictable. Online RAS with real‐time calculation of corrective controls provides the most suitable and effective response. To achieve rapid computation and reduce the search space to only the most effective candidate control(s), the analytic corrective control selection method using clustering and factorisation techniques is developed based on controllability analysis. The resulting critical controls comprise a minimum set that is most effective in reducing the violations in the stressed areas of the system. While this study focuses on generators as the critical control mechanism, this methodology is broadly applicable to any corrective control for which a sensitivity matrix in relation to the violated components can be derived. The algorithm is evaluated with the IEEE 24‐bus and IEEE 118‐bus systems under compromised generator outage scenarios, and the identified critical control set is shown to be highly effective for reducing violations and improving RAS computation time.

This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.

Power systems are subjected to a wide range of disturbances during daily operations. Severe disturbances, such as a loss of a large generator, a three-phase bolted fault on a generator bus, or a loss of a transmission line, can lead to the loss of synchronism of a generator or group of generators. The ability of a power system to maintain synchronism during the few seconds after being subjected to a severe disturbance is known as transient stability. Most of the modern methods of controlling transient stability involve special protection schemes or remedial action schemes. These special protection schemes sense predetermined system conditions and take corrective actions, such as generator tripping or generation re-dispatch, in real time to maintain transient stability. Another method is the use of a real-time feedback control system to modulate the output of an actuator in response to a signal. This paper provides a fundamental evaluation of the use of feedback control strategies to improve transient stability in a power system. An optimal feedback control strategy that modulates the real power injected and absorbed by distributed energy-storage devices is proposed. Its performance is evaluated on a four-machine power system and on a 34-machine reduced-order model of the Western North American Power System. The result shows that the feedback control strategy can increase the critical fault clearing time by 60%, thereby improving the transient stability of the power system.

Deployment of Remedial Action Schemes (RAS) is a cost-effective alternative when taking pre-contingency actions or building new infrastructure are not desirable. However, if not modeled adequately in operation and planning studies, RAS can impose a risk to systems reliability by unintended activation or interactions with other protection systems. In this paper, we explain the implementation and testing procedure of RAS models for real-time transient stability assessment tool at Peak Reliability. First, we implemented 11 RAS models in Western Interconnection using user-defined models (UDM) and tested their functionality through off-line and online studies. Then, we performed a one-day study to evaluate the impact of adding RAS models on transient stability limits and limiting contingencies. Our study demonstrates that incorporating RAS models in transient stability analysis provide a more accurate representation of system operating conditions. This can enhance operators situational awareness and their ability to take timely, effective actions.

In recent years there have been many improvements in the reliability of critical infrastructure systems. Despite these improvements, the power systems industry has seen relatively small advances in this regard. For instance, power quality deficiencies, a high number of localized contingencies, and large cascading outages are still too widespread. Though progress has been made in improving generation, transmission, and distribution infrastructure, remedial action schemes (RAS) remain non-standardized and are often not uniformly implemented across different utilities, ISOs, and RTOs. Traditionally, load shedding and islanding have been successful protection measures in restraining propagation of contingencies and large cascading outages. This paper proposes a novel, algorithmic approach to selecting RAS policies to optimize the operation of the power network during and after a contingency. Specifically, we use policy-switching to consolidate traditional load shedding and islanding schemes. In order to model and simulate the functionality of the proposed power systems protection algorithm, we conduct Monte-Carlo, time-domain simulations using Siemens PSS/E. The algorithm is tested via experiments on the IEEE-39 topology to demonstrate that the proposed approach achieves optimal power system performance during emergency situations, given a specific set of RAS policies.