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DOE OSTI2025

A Review of Quantum Computing Technologies in Power System Optimization

As modern power grids increasingly integrate variable renewable generation, distributed energy resources, and energy storage systems, classical optimization techniques are facing unprecedented challenges. This review examines the emerging application of quantum computing to overcome these challenges in power system optimization, including optimal power flow (OPF), unit commitment (UC), economic dispatch (ED), and intelligent switching and topology optimization (IS-TO). Recent research has introduced various quantum methodologies—such as gate-based, annealing-based, variational algorithms, and quantum-inspired algorithms—to address the combinatorial complexity inherent in grid reconfiguration and energy management. The review summaries the quantum algorithms, quantum devices and the power system test cases, highlighting hybrid quantum–classical strategies that leverage the complementary strengths of both paradigms. Some quantum advantages have been observed, including theoretical speedup, accurate simulation results, scalable qubit usage, efficient QUBO mapping. In particular, the review emphasizes the importance of integrating quantum optimization techniques with classical control frameworks, these hybrid approaches demonstrate the potential to improve real-time grid management and operational reliability. A significant portion of the analysis is devoted to the practical limitations of current quantum devices. Present-day quantum hardware, operating in the noisy intermediate-scale quantum (NISQ) era, remains highly sensitive to noise and limited in qubit connectivity, which constrains the scale and accuracy of implemented algorithms. The review delves into specific challenges such as the need for qubit-efficient encoding techniques and error mitigation strategies that are critical for handling real-world grid optimization problems. In addition, the work draws attention to the performance discrepancies between theoretical quantum speedups and experimental validations, underscoring the importance of rigorous benchmark studies using representative power grid test cases. In summary, this review highlights both the promise and limitations of quantum computing for power system optimization. It provides a comprehensive overview of the state-of-the-art technologies, categorizes recent advancements in algorithm design, and discusses practical considerations for implementation, and serves as an informative resource on current research. Future research directions include developing robust hybrid frameworks, advancing qubit-efficient formulations, and scaling up experimental demonstrations to confirm the theoretical advantages of quantum methods in large-scale power system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Optimal Power System Black start using Inverter-Based Generation

Power system black start readiness is part of the system planning. Utility planners perform periodic studies to assess if their power system is capable of total restoration following a black out. Hydro and diesel generators are the most commonly used black start capable resources by power utilities. However, with increasing penetration of solar generation, inverter-based resources can be considered to provide black start capability. Since the solar inverters can be located at multiple locations throughout the power system, and in view of their unique characteristics, an optimal real-time capable plan is helpful for system operators for faster black start. Black start optimization is a multi stage mixed-integer non-linear optimization which is extremely hard to solve. In this paper, we propose an optimal black start methodology that is easier to solve and scalable in real-time. We demonstrate the proposed methodology on two test systems and illustrate how inverter-based resources can contribute and improve power system restoration.

power system restoration, blackstart, Inverter-bas↗
DOE OSTI2024

Decomposable Formulation of Transmission Constraints for Decentralized Power Systems Optimization

One of the most complicating factors in decentralized solution methods for a broad range of power system optimization problems is the modeling of power flow equations. Existing formulations for direct current power flows either have limited scalability or are very dense and unstructured, making them unsuitable for large-scale decentralized studies. Here, in this work, we present a novel sparsified variant of the injection shift factors formulation, which has a decomposable block-diagonal structure and scales well for large systems. We also propose a decentralized solution method, based on the alternating direction multiplier method, that efficiently handles transmission line outages in N-1 security requirements. Benchmarks on multizonal security-constrained unit commitment problems show that the proposed formulation and algorithm can reliably and efficiently solve interconnection-level test systems with up to 6,515 buses with no convergence or numerical issues.

Alternating-method of multipliers (ADMM)↗
DOE OSTI2022

Quantitative Metrics for Grid Resilience Evaluation and Optimization

Power system resilience has become a critical topic in recent years because of the increasing trend of extreme events and the growing integration of intermittent renewable energy sources. To enhance grid resilience against high-impact, low-frequency events, two questions should be answered: how to quantify the resilience of a given grid and how to incorporate the quantification into power system planning, operation, and restoration. Here this paper develops a new set of quantitative metrics with clear physical interpretation to comprehensively evaluate power system resilience. Using microgrids as an example, an event-based corrective scheduling (ECS) model and an online model predictive control (OMPC) model are developed to integrate the proposed quantitative resilience metrics into power system optimization models for resilience enhancement. The ECS model employs extreme event data to investigate the optimal restoration solution and to help microgrid operators prepare to respond to similar events. The OMPC model provides online decision-making support for operators to handle ongoing outages in the most resilient fashion. The effectiveness and superiority of the proposed quantitative resilience metrics and the resilience enhancement models are demonstrated through simulations and comparative studies on an IEEE test feeder and a real distribution feeder in Southern California.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Comparative Investigation of System-Level Optimized Power Conversion System Architectures to Reduce LCOE for Large-Scale PV-Plus-Storage Farms

PV-plus-storage (PVS) has become a prevalent configuration for newly commissioned large-scale solar projects. However, the optimal power conversion system (PCS) architecture has not been investigated yet. This paper first validates the limited impact of inverter cost on LCOE and then explores a system-level optimized PCS architecture with extended LCOE reduction to proliferate large-scale dispatchable solar energy. Two state-of-the-art architectures including central inverters (CI), traditional 480/600 V string inverters (SI) are compared with newly proposed medium voltage string inverters (MVSI) and multiport DC transformer (MDCT). With verified layouts and single line diagrams (SLDs) of 20 MW PVS plants, the losses and costs breakdown of different architectures are extracted and the PCS related LCOEs are derived. In this analysis, all electrical bill of materials (EBOS) elements, inverters, battery storage and its associated components, are included, whose losses and costs are obtained from markets, manufacturers, and literature. Besides, the sensitivities of PCS-related LCOEs to Inverter-Loading-Ratio (ILR) are also investigated. Here, the results show that compared with CI and SI with 1.5 kV PV, 4 kV MVSI and 34 kV MDCT present an extended LCOE reduction across all ILR from 1.0 to 3.0, making them economically favorable candidates for PVS farms.

14 SOLAR ENERGY↗
DOE OSTI2022

Optimizing power system restoration with damaged communications

Utility procedures for power system blackstart and restoration typically assume that energization decisions can be reliably communicated across the grid. In reality, the communications and control network would likely also be affected in power outages, such as those caused by extreme weather events or cyber-attacks. This paper studies the effect of damage to the power system communications and control infrastructure on restoration operations following a blackout. We model the communications infrastructure as a graph, overlaying the power grid, and imposing the requirement that every energized element in the power grid be observable from a control center. We expand on a specialized branch-and-bound algorithm from the literature to optimize the restoration process and devise an initialization heuristic and a rounding heuristic to improve solution speed. We perform numerical experiments on synthetic systems for Illinois and Texas with outages based on a solar flare or hurricane. We compare the results of our specialized branch-and-bound algorithm to the results from (i) the initialization heuristic alone, (ii) a variation of this heuristic that we use as a baseline, and (iii) the restoration optimization for the power system without communications constraints. Here, we find that damage to the communications infrastructure significantly increases the time required to re-energize the grid. Moreover, by simultaneously optimizing communications repairs and grid energization decisions, we are able to re-energize the grid significantly faster than if communications repairs and energization decisions were made independently or with partial coordination, motivating improvements to current industry practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A Pulsar-Inspired Timing Framework for Power System: Optimization and Performance Evaluation

Due to their excellent stability, neutron pulsar stars are considered promising candidate timing sources for power system applications. However, the complexity of pulsar signals necessitates advanced processing algorithms to provide accurate timing references. This paper presents the foundational framework for pulsar signal processing, serving as the basis for further optimization. To enhance the timing accuracy and computation efficiency in pulsar period searches, three algorithms are proposed as the initial optimization step: wavelet de-noising, fast folding, and cross-correlation for profile evaluation. Wavelet de-noising improves signal-to-noise ratio (SNR) by 36%–70%. Fast folding reduces computation time from hundreds of seconds to mere milliseconds. Cross-correlation works better than traditional SNR-based methods by effectively identifying the optimal period. The performance of the proposed algorithms is evaluated using observation data from telescopes. Together, these algorithms significantly improve pulsar timing performance, reducing the error of the Pulse Per Second (PPS) signal from hundreds to tens of microseconds.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗
DOE OSTI2022

Recent advances and challenges in optimization models for expansion planning of power systems and reliability optimization

Optimization models for expansion planning of power systems aim to determine capacities, investment timing, and location of power systems to satisfy the power demands while minimizing the total cost. The models have become complex in recent years to reflect both regulations on conventional energy sources and the increasing penetration of renewable energy sources (RES). This paper reviews the basic concepts and optimization models for expansion planning of power systems. We first explain the definition and features of generation expansion planning (GEP), transmission expansion planning (TEP), and generation and transmission expansion planning (GTEP). To address the computational challenges of large-scale expansion planning problems, we review several simplifications including temporal and spatial aggregation, and decomposition methods. This paper also addresses power system reliability defined as the probability of satisfying the load demand while withstanding failures of components. Finally, the goal of this paper is to provide a research overview, discuss trends in expansion planning of power systems, and suggest directions for future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗