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At least 19 records

Networked Microgrid Topology Reconfiguration to Promote Fairness in Proactive Load Shedding

Increasing occurrences of natural disasters and grid emergency events consistently challenge the safe and reliable operations of power systems. During such emergency situations, system operators may proactively shed load to mitigate risks. However, uncoordinated implementation of load shedding may disrupt electricity supply and even lead to cascading failures. Meanwhile, it is crucial to address potential biases affecting different customers when executing load shedding. This paper addresses the dynamic topology reconfiguration problem for networked microgrids with distributed energy resources under emergency conditions. Specifically, we propose a novel rolling-horizon optimization model that integrates fairness-aware constraints into the networked microgrid topology reconfiguration. Unlike existing approaches that focus solely on efficiency or apply fairness considerations in static settings, our method explicitly incorporates temporal fairness constraints to restrict repeated or excessive load curtailment for load blocks. Moreover, the fairness-aware constraints are specifically developed for the context of dynamic networked microgrid topology reconfiguration, and are designed to be convex or amenable to linear reformulations, which offers a more tractable alternative to traditional models with non-convex formulations. Numerical studies on a modified IEEE 13-bus system and a larger-sized SMART-DS networked microgrid system demonstrate the performance of the proposed algorithm towards more fairness-aware networked microgrid topology reconfiguration decision-making.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Real-time hybrid controls of energy storage and load shedding for integrated power and energy systems of ships

This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage systems (SCESS), in modern ship power systems poses challenges in designing an efficient energy management system (EMS). The EMS proposed in this paper aims to achieve multiple objectives. The primary objective is to minimize shed loads, while the secondary objective is to effectively manage different types of ESS. Considering the diverse ramp-rate characteristics of generators, SCESS, and BESS, the proposed EMS exploits these differences to determine an optimal long-term schedule for minimizing shed loads. Furthermore, the proposed EMS balances the state-of-charge (SoC) of ESS and prioritizes the SCESS’s SoC levels to ensure the efficient operation of BESS and SCESS. For better computational efficiency, we introduce the receding horizon optimization method, enabling real-time EMS implementation. Further, a comparison with the fixed horizon optimization (FHO) validates its effectiveness. Simulation studies and results demonstrate that the proposed EMS efficiently manages generators, BESS, and SCESS, ensuring system resilience under generation shortages. Additionally, the proposed methodology significantly reduces the computational burden compared to the FHO technique while maintaining acceptable resilience performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hydrodynamics and Load Shedding Behavior of a Variable-Geometry Oscillating Surge Wave Energy Converter (OSWEC)

In order to improve their long-term viability, wave energy converters (WECs) need to be able to shed loads when a threshold wave condition is exceeded. As shown by Tom et al. (2016) [1], provision of adjustable flaps within the body of an oscillating surge wave energy converter (OSWEC) allows wave energy to pass through the device. A control system may then be able to open and close the flaps when waves approaching the device exceed preset thresholds. The variable-geometry OSWEC (VG-OSWEC) concept studied in this paper is a bottom-hinged, rectangular wave paddle with five flaps of elliptical cross-section embedded into the face of the paddle. System ID tests were conducted on this VG-OSWEC device at a 1:14 scale in a wave basin. Free decay tests showed that the damping was distinctly nonlinear when the flaps were fully open, and the natural frequency increased by 40% when compared with the flaps in a fully closed configuration. Tests with regular wave conditions were used to develop the response amplitude operator for the rotational motion about the hinge. These response amplitude operator results when compared with numerical simulations run using WEC-Sim/WAMIT and ANSYS AQWA, show strong agreement with the flap open and closed conditions. The regular-wave condition measurements also show that the wave excitation moment about the hinge was reduced by up to 60% when the flaps were fully open. The experiments serve to demonstrate the potential of the variable geometry design to shed loads and survive harsh ocean environments.

load shedding↗

Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters

The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.

Grid-forming inverters, IBR, Inertia↗

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗

Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering

Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.

Baquedano-Aguilar, Mario D.↗

Bi-Level Linear Programming Model for Automatic Load Shedding: A Distributed Wide-Area Measurement System-based Solution

Load shedding is currently implemented as a two-step based approach. In the first step, manual load shedding is taken place, were system operators, using estimates, inform distribution utilities of predicted stressful conditions. Information provided include the potential use of energy reserves, as well as load shedding amount. In a second step, automatic load shedding is done. The latter is realized using protection relays. While considering frequency variation, pre-defined values of load to be shed and correspondent number of stages for such to be realized are transformed into relay settings. Under-frequency protection relays use only local measurements towards decision making, thus operate in a decentralized architecture. Decision making is done in milliseconds plus breaker time. While this approach has provided much system reliability, considering the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions it will generate sub-optimal solutions, such as islanding. Phasor measurement units provide a source of information which can be useful for this problem. Centralized architecture-based solutions for automatic load shedding, as present in the state-of-the-art, require though total processing times which are not acceptable for real-life implementation. In this work, considering the above, a bi-level linear programming model is presented. The model is implemented considering a distributed architecture while leveraging phasor measurement units data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model, which decision variables are the location and load value to be shed. Easy-to-implement model, built-on the classic weighted least squares solution, highlight potential aspects towards real-life applications.

Bretas, Arturo Suman↗

Machine Learning for Fairness-Aware Load Shedding: A Real-Time Solution via Identifying Binding Constraints: Preprint

Timely and effective load shedding in power systems is critical for maintaining supply-demand balance and preventing cascading blackouts. To eliminate load shedding bias against specific regions in the system, optimization-based methods are uniquely positioned to help balance between economic and fairness considerations. However, the resulting optimization problem involves complex constraints, which can be time-consuming to solve and thus cannot meet the real-time requirements of load shedding. To tackle this challenge, in this paper we present an efficient machine learning algorithm to enable millisecond-level computation for the optimization-based load shedding problem. Numerical studies on both a 3-bus toy example and a realistic RTS-GMLC system have demonstrated the validity and efficiency of the proposed algorithm for delivering fairness-aware and real-time load shedding decisions.

97 MATHEMATICS AND COMPUTING↗

ComStock Measure Documentation: Thermostat and Lighting Control for Load Shedding

This report describes the modeling methodology for an upgrade package of two end-use savings shape measures - Thermostat Control for Load Shedding and Lighting Control for Load Shedding - and briefly introduces key results. The package combines thermostat control for load shedding and lighting control for load shedding measures to reduce the HVAC and lighting load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then relaxes the thermostat setpoints and dims the lighting level from the original schedules during the peak window to reduce the peak demand. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 3%-10% daily peak demand reduction performance for applicable buildings, and 0.97% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ComStock Measure Documentation: Thermostat and Lighting Control for Load Shedding + Photovoltaics With 40% Rooftop Coverage

This report describes the modeling methodology for an upgrade package of two end-use savings shape measures - Thermostat Control for Load Shedding and Lighting Control for Load Shedding - and briefly introduces key results. The package combines thermostat control for load shedding, lighting control for load shedding, and PV with 40% rooftop coverage measures to reduce the net building load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then relaxes the thermostat setpoints and dims the lighting level from the original schedules during the peak window to reduce the peak demand, while applying the fixed rooftop PV application for onsite electricity generation. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 5%-15% daily peak demand reduction performance for applicable buildings, and around 1% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

14 SOLAR ENERGY↗

End-Use Savings Shapes Measure Documentation: Thermostat Control for Load Shedding in Large Offices

This documentation focuses on a single End-Use Savings Shape measure - thermostat control for load shedding. The thermostat control for load shedding measure applies heating and cooling temperature setpoint offsets for reducing the heating and cooling load during peak window. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the peak window, and then adjusts the thermostat cooling and/or heating setpoints by an offset value from original schedules during the peak window to reduce the HVAC or whole building daily peak load. The measure is flexible and allows users to adjust the heating and cooling offset values respectively, but for this study, the adjustment for heating and cooling setpoints are set to -2 degrees Celsius and +2 degrees Celsius by default. The measure provides options of adding rebound control period (default 2 hours) after peak windows for the setpoints to be ramped back to default values, to prevent the system from generating higher peak demand with step changes of setpoints in post-peak periods . This measure is applicable t o large offices equipped with electric HVAC system (either electric cooling only or both electric heating and cooling), which account for approximately 8.72% of the ComStock floor area. The thermostat control for load shedding measure demonstrates 2-5% daily peak demand reduction and 0.068% total site energy savings (3 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reliability Constrained Priority Load Shedding for Aerospace Power System Automation

The need for improving load shedding on board the space station is one of the goals of aerospace power system automation. To accelerate the optimum load-shedding functions, several constraints must be involved. These constraints include congestion margin determined by weighted probability contingency, component/system reliability index, generation rescheduling. The impact of different faults and indices for computing reliability were defined before optimization. The optimum load schedule is done based on priority, value and location of loads. An optimization strategy capable of handling discrete decision making, such as Everett optimization, is proposed. We extended Everett method to handle expected congestion margin and reliability index as constraints. To make it effective for real time load dispatch process, a rule-based scheme is presented in the optimization method. It assists in selecting which feeder load to be shed, the location of the load, the value, priority of the load and cost benefit analysis of the load profile is included in the scheme. The scheme is tested using a benchmark NASA system consisting of generators, loads and network.

Momoh, James A.↗

ComStock Measure Documentation: Lighting Control for Load Shedding

This report describes the modeling methodology for a single end-use savings shape measure - lighting control for load shedding - and briefly introduces key results. The lighting control for load shedding measure applies lighting dimming control to reduce the lighting load during the building's electricity peak window every weekday. The measure takes daily peak load schedule inputs generated by the method "Dispatch Schedule Generation" described in the "Supplemental Documentation: Dispatch Schedule Generation for Demand Flexibility Measures" to determine the start and end times of the predicted peak window, and then adjusts the lighting dimming level by a percentage reduction from the original schedules during the peak window to reduce the peak demand. The measure is applicable to (large, medium and small) offices, warehouses, and primary and secondary schools, which correspond to approximately 68% of the stock floor area of commercial buildings in ComStock analysis. The measure demonstrates 2%-7% daily peak demand reduction performance for applicable buildings, and 0.43% total site energy savings (0 trillion British thermal units [TBtu]) for the U.S. commercial building stock modeled in ComStock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Load Shed Recovery With Transmission Switching and Intentional Islanding Methods After (N-2) Line Contingencies

Changing power system configuration may result in load shed recovery (LSR) because topology change can provide power flow control in meshed network. Some topologies may favor generation redispatch as compared to others and can eliminate line congestion which leads to LSR. One of the known methods for topology change is called transmission switching (TS) and research conducted in the past showed that TS is an effective means of mitigating load shedding. Another method of topology control is intentional islanding (IIS). In this manuscript, we explore IIS as a potential solution for LSR. IIS based on generator coherency has been presented in literature for mitigating cascading failures. However, IIS has not been explored solely as a LSR mechanism. In this paper, we compare the LSR based on IIS with well known LSR algorithm based on TS. The comparison is performed for IEEE 39-bus system and IEEE 118- bus system. The results show that IIS has a potential to perform better than TS in terms of computational efficiency and LSR.

42 ENGINEERING↗

Resilient Distribution System Restoration with Equitable Load Shedding

A methodology is proposed for the improvement of electric distribution system resilience to high-impact, low-probability catastrophic events. An approach for dynamic network reconfiguration and coordination of distributed energy resources is introduced to assist in restoration efforts. The problem is formulated as a mixed-integer linear program that minimizes generation costs, the cost of lost load, and costs associated with equitable load shedding, while respecting operational limits of generation, loads, and the network. Constraints are imposed on binary switching variables to ensure equitable load shedding in emergency situations. Numerical validation of the proposed approach is conducted on an example distribution feeder, and case studies are performed to analyze the impact of various parameters in the optimization problem formulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Adaptive Load Shedding for Grid Emergency Control via Deep Reinforcement Learning

Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in real-world power systems under contingencies. However, existing emergency control schemes are rule-based and cannot be adaptively applied to uncertain and floating operating conditions. Here, we propose an adaptive UVLS algorithm for emergency control via deep reinforcement learning (DRL) and expert systems. We first construct dynamic components for picturing the power system operation as the environment. The transient voltage recovery criteria, which poses time-varying requirements to UVLS, is integrated into the states and reward function to advise the learning of deep neural networks. The proposed method has no tuning issue of coefficients in reward functions, and this issue was regarded as a deficiency in the existing DRL-based algorithms. Case studies illustrate that the proposed method outperforms the traditional UVLS relay in both the timeliness and efficacy for emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Review of data-driven models for quantifying load shed by non-residential buildings in the United States

Shifting and shedding power demand in buildings can be cost-effective techniques for grids to function reliably and for end users to earn compensation. Grid operators reimburse customers in proportion to the quantity of load shed. Simple data-driven methods are used to quantify this shed, which is the difference between a measured load during the event and modeled "baseline" that would have occurred in absence of the event. These methods have evolved over the years and in many cases have been integrated with building physics, to make them a hybrid between physics based and empirical models. However, there is no comprehensive analysis that provides guidance to building operators, grid operators and researchers in selecting appropriate models based on their specific needs and available data. Here, this work aims to fill this gap by critically assessing the performance of baseline models put forward from the year 2000 through 2023. The literature reviewed includes reports generated by grid operators, reports from national laboratories and academic journal articles. The work outlines modeling features like the inputs, training period, estimation method, adjustments to fine tune the predictions and metrics to evaluate the performance. A comprehensive list of 50 models has been provided. For each model, the study explores the applicability of the model to weather sensitive buildings, variability in the building profile, timing of the event, and whether the building reduces energy consumption before an event. The work identifies the situations in which a particular model works and draws lessons based on evidence of performance. Finally, recommendations to aid in model selection are given.

97 MATHEMATICS AND COMPUTING↗