Climate change, environmental impact and the limited natural resources urge scientific research and novel technical solutions. The monograph series Green Energy and Technology serves as a publishing platform for scientific and technological approaches to "green" i.e. environmentally friendly and sustainable technologies. While a focus lies on energy and power supply, it also covers "green" solutions in industrial engineering and engineering design. Green Energy and Technology addresses researchers, advanced students, technical consultants as well as decision makers in industries and politics. Hence, the level of presentation spans from instructional to highly technical. **Indexed in Scopus**.

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Green Energy and Technology

This paper shortly surveys existing and proposed methods for voltage instability detection. The emphasis is on methods relying on real-time measurements as well as on long-term voltage instability. Methods are classified according to the required measurement configuration: local vs. wide-area, standard SCADA-type vs. synchronized phasor measurements, etc. In the various categories, some of the features are summarized, and what appears to the authors as advantages or limitations is shortly discussed. An important feature is the ability to anticipate instability. Some tracks for further work on the subject are also outlined.

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A short survey of methods for voltage instability detection

This paper develops a novel online fast load shedding strategy aimed at shedding the most effective load to mitigate fault-induced delayed voltage recovery (FIDVR). Induction motor kinetic energy deviation has been shown to be identical to the integral of power imbalance. Instead of using voltage as an indicator, the proposed strategy applies a centralized scheme making use of equivalent motor kinetic energy to identify the most effective loads to shed. In order to derive kinetic energy, the equivalent inertia and the speed of the induction motor are needed. A methodology is proposed to obtain these variables through online measurements. Simulations on a sample power system illustrate the novel load shedding strategy and its effectiveness. The proposed strategy is compared with conventional four-stage under-voltage load shedding (UVLS) scheme. The results have validated that the proposed strategy can effectively mitigate fault-induced delayed voltage recovery and require much less load to be shed.

A Novel Online Load Shedding Strategy for Mitigating Fault-Induced Delayed Voltage Recovery

Recent investments in the Synchrophasor technology have energized the industry and a significant number of Phasor Measurement Units (PMUs) are being deployed. By some estimates, just in North America, the number of PMU installations is expected to grow five-fold — from approximately 200 today to over a 1000. The first step in PMU deployment is a clear roadmap of the process for selecting the location of the additional PMU devices and establishing guidelines to assist with this decision-making process. Many of the existing optimal PMU placement approaches are mainly focused on a particular application (such as improving State Estimation). This paper proposes a more comprehensive, holistic set of criteria for optimizing PMU placement based on sound practical solutions by experienced industry practitioners. The methodology offers the flexibility for considering multiple, diverse factors that can influence the PMU siting decision-making process, including incorporating several practical implementation aspects (e.g. communications infrastructure, prohibitive deployment cost, etc). Application needs, reliability requirements, and infrastructure challenges that drive the overall solution for optimal PMU location selection are formulated and described.

PMU placement considerations — A roadmap for optimal PMU placement

With the deployment of phasor measurement units (PMUs), machine learning based data-driven methods have been applied to online power system stability assessment. This article proposes a novel temporal-adaptive intelligent system (IS) for post-fault short-term voltage stability (STVS) assessment. Unlike existing methods using a single learning algorithm, the proposed IS incorporates multiple randomized learning algorithms in an ensemble form, including random vector functional link networks and extreme learning machine, to obtain a more diversified machine learning outcome. Moreover, under a multi-objective optimization programming framework, the STVS is assessed in an optimized temporal-adaptive way to balance STVS accuracy and speed. The simulation results on New England 39-bus system and Nordic test system verify its superiority over a single learning algorithm and its excellent accuracy and speed without increased computational efficiency. In particular, its real-time assessment speed is 27.5–37.3% faster than the single algorithm based methods. Given such faster assessment speed, the proposed method can enable earlier and more timely stability control (load shedding) for less load shedding amount and stronger effectiveness.

A Hybrid Randomized Learning System for Temporal-Adaptive Voltage Stability Assessment of Power Systems

In this paper, a new relay algorithm is proposed for under-voltage load shedding (UVLS) based on rate of voltage recovery and predicted time to recover above a preset voltage threshold Simulation experience in the Southern Electric System has shown that conventional UVLS relay logic is ill-suited to the task of mitigating delayed voltage recovery and fast voltage collapse situations while maintaining compliance with existing NERC Reliability Standards The proposed scheme continuously monitors both voltage magnitude and rate-of-change of voltage magnitude and uses these values to determine a projected voltage recovery time following a contingency event If the projected recovery time is such that resultant system conditions are unacceptable (eg, major load loss, loss of generation, or voltage collapse), the relay will operate to shed load at the distribution feeder level This unique scheme has been implemented in a commercially-available programmable relay and is presently installed and active in a number of substations in Georgia Power Company

Slope-Permissive Under-Voltage Load Shed Relay for Delayed Voltage Recovery Mitigation

As a result of a multiple contingency fault and breaker failure event at two Metro Atlanta 230 kV substations in 1999, Southern Company experienced a wide area voltage depression lasting around 15 seconds. The event resulted in a 1900 MW load loss. Dynamic simulations utilizing standard static stability load models were not successful in replicating the event. However, the actual response of the transmission system was replicated utilizing dynamic simulations with aggregate load models that included the effect of induction motors and distribution system impedances. Since the event in 1999, load has grown exceptionally in the North Georgia region. As a result of the load growth, capital projects are being implemented in Southern Company to appropriately manage the exposure to both NERC reliability standard category B and D fault induced delayed voltage recovery events. Therefore, it is critical that the load models used in dynamic studies correctly represent the behavior of actual load. This is necessary to ensure that the timing and effectiveness of capital projects are appropriately quantified. Both the formulation of the aggregate load models used to replicate the 1999 event, and ongoing efforts to refine the load model used to assess future exposure to fault induced delayed voltage recovery are discussed in this paper.

Development of load models for fault induced delayed voltage recovery dynamic studies

In this paper, a new method for steady-state screening of buses to identify possible fault-induced delayed-voltage recovery problems is presented. The method is particularly useful for (1) prioritizing substation relaying and breaker maintenance, (2) evaluating impacts of system improvement alternatives, (3) identifying most-effective locations for undervoltage load shedding, and (4) locating voltage (reactive) support equipment. The method is based on a single index value for each bus that is determined by considering the amount of load impacted by a fault at that bus using a weighted summation. The steady-state screening algorithm has been validated using dynamic simulations and has been used to successfully identify as a potentially severe contingency the location of an actual event that occurred on the Southern Electric System in the summer of 1999.

R.A. Jones

Papers

Slope-Permissive Under-Voltage Load Shed Relay for Delayed Voltage Recovery Mitigation

Development of load models for fault induced delayed voltage recovery dynamic studies

The MVA-Volt Index: A Screening Tool for Predicting Fault-Induced Low Voltage Problems on Bulk Transmission Systems