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At least 127 records · Page 7

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Bilevel Approach for Identifying the Worst Contingencies for Nonconvex Alternating Current Power Systems

We address the bilevel optimization problem of identifying the most critical attacks to an alternating current (AC) power flow network. The upper-level binary maximization problem consists of choosing an attack that is treated as a parameter in the lower-level defender minimization problem. Instances of the lower-level global minimization problem by themselves are NP-hard due to the nonconvex AC power flow constraints, and bilevel solution approaches commonly apply a convex relaxation or approximation to allow for tractable bilevel reformulations at the cost of underestimating some power system vulnerabilities. Our main contribution is to provide an alternative branch-and-bound algorithm whose upper bounding mechanism (in a maximization context) is based on a reformulation that avoids relaxation of the AC power flow constraints in the lower-level defender problem. Lower bounding is provided with semidefinite programming (SDP) relaxed solutions to the lower-level problem. We establish finite termination with guarantees of either a globally optimal solution to the original bilevel problem, or a globally optimal solution to the SDP-relaxed bilevel problem which is included in a vetted list of upper-level attack solutions, at least one of which is a globally optimal solution to the bilevel problem. We demonstrate through computational experiments applied to IEEE case instances both the relevance of our contribution, and the effectiveness of our contributed algorithm for identifying power system vulnerabilities without resorting to convex relaxations of the lower-level problem. We conclude with a discussion of future extensions and improvements.

97 MATHEMATICS AND COMPUTING↗

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗

Intelligent Partitioning based Fully Parallel AC Security-Constrained Optimal Power Flow

Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Managing Power Systems-Induced Wildfire Risks Using Optimal Scheduled Shutoffs

The increasing demands for electricity and the increase in extreme weather conditions are putting unprecedented pressure on our electric grids. Often, this pressure leads to electrical component failures, which might ignite wildfires. This work develops a novel model to balance the reliability of power network operations and the risk of wildfire ignition by opti- mizing the operational schedule of power transmission networks considering time-varying risk measures that include exogenous and operational factors. Energy storage systems are considered to deliver power during peak wildfire hours and enable temporal load shifting. The problem is formulated as a mixed-integer linear program that maximizes a weighted sum of the served power demand and the reduction in grid-induced wildfire risk. The results demonstrate the ability of the model to significantly reduce wildfire risk without considerable load shedding.

power systems operations↗

Large Scale Bilevel Optimization for N-K SCOPF Using Adversarial Robustness

Ensuring a secure dispatch against multiple simultaneous outages has long been desired to maintain grid security in the presence of severe events, such as extreme weather phenomena. Traditionally denoted as N-k security constrained optimal power flow (N-k SCOPF), this problem is intractable to solve due to its size being combinatorial in the number of simultaneous outages and due to the non-convex nature of the AC network constraints. This hinders the use of N-k SCOPF for operating realistic-scale systems. In this paper, we introduce a methodology to scalably solve an AC-feasible dispatch that improves security over k simultaneous outages. Our methodology poses N-k SCOPF as a bilevel optimization problem and solves it using an adversarial robustness approach. We develop new efficient methods to solve each level of the bilevel optimization by employing knowledge of the physics of the underlying system. This yields significant improvements in speed and convergence that enable us to address the N-k SCOPF problem at scale. We demonstrate the effectiveness of our method by conducting a comprehensive analysis of an N-3 SCOPF for a 500-bus network. Furthermore, we emphasize the ability of our physics-driven techniques to handle larger systems by successfully scaling up to 12,000 buses.

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On the optimal sizing of power take-off systems for wave energy converters

The power take-off (PTO) system in a wave energy converter (WEC) is the means by which the energy in an ocean wave is converted into useful energy. There has been a general lack of technology convergence in the wave energy industry and PTO design has been largely device-specific with the design process determined by the WEC developer. An optimized PTO design can significantly affect the efficiency, reliability, performance, and overall cost and viability of a device. There remains a need in the marine energy industry for best practices and efficient design processes to be identified as it could greatly benefit developers and researchers in designing an optimal WEC PTO. This research utilizes the open-source Matlab-Simulink based software, WEC-Sim, which was developed by the National Renewable Energy Laboratory, and the Eagle, a high-performance computing system, to model and optimize two WECs of different archetypes and then investigates if any trends exist that can be exploited for greater efficiency in optimal PTO design. The results from this research indicate that there may be an optimal sizing for WEC PTOs for both power and PTO force rating and that substantial reductions can be made in the cost of a device without significant loss in the energy produced. Furthermore this optimal sizing may be independent of WEC type and deployment location. With an optimal, or near optimal, approach to WEC PTO sizing demonstrated, a methodology is proposed to address the challenge of nameplate ratings in the wave energy industry.

13 HYDRO ENERGY↗

A Distributionally Robust Optimization Framework for Stochastic Assessment of Power System Flexibility in Economic Dispatch

Given the complexity of power systems, particularly the high-dimensional variability of net loads, accurately depicting the entire operational range of net loads poses a challenge. To address this, recent methodologies have sought to gauge the maximum range of net load uncertainty across all buses. In this paper, we consider the stochastic nature of the net load and introduce a distributionally robust optimization framework that assesses system flexibility stochastically, accommodating a minimal extent of system violations. We verify the proposed method by solving the flexibility of the economic dispatch problem on four distinct IEEE standard test systems. Compared to traditional deterministic flexibility evaluations, our approach consistently yields less conservative flexibility outcomes.

distributionally robust optimization↗

Design Principles for Resonant Wave Energy Converters: Benchmarking Power Capture and Flow

Control co-design (CCD) in Wave Energy Converters (WECs) integrates the controller, power take-off (PTO), and buoy models during system design to optimize power output. Using the bi-conjugate impedance matching principle, this study models the PTO as a two-port network, revealing impedance matching conditions at the input and output ports as a function of the buoy, PTO, and controller. Here, this study examines the pairing of a flywheel-type pitch resonator PTO within a given buoy constrained by limited space and ballast capacity. The results show that physical constraints imposed by the buoy affect PTO performance. While controller tuning achieves optimal output impedance matching and flywheel inertia is maximized within the buoy's limitations, the PTO's input impedance remains smaller than the complex conjugate of the buoy's intrinsic impedance. This mismatch limits the PTO's ability to generate sufficient reaction torque, particularly outside the resonance frequency, resulting in narrow-band power transfer. The findings emphasize the need for PTO design modifications to improve input power transfer. Pendulum-based PTO mechanisms are proposed as alternatives to couple with multiple buoy motion modes and improve wave-to-wire efficiency while respecting system constraints.

Control Co-Design↗

Maximal nighttime electrical power generation via optimal radiative cooling

We present a systematic optimization of nighttime thermoelectric power generation system utilizing radiative cooling. We show that an electrical power density >2 W/m 2 , two orders of magnitude higher than the previously reported experimental result, is achievable using existing technologies. This system combines radiative cooling and thermoelectric power generation and operates at night when solar energy harvesting is unavailable. The thermoelectric power generator (TEG) itself covers less than 1 percent of the system footprint area when achieving this optimal power generation, showing economic feasibility. We study the influence of emissivity spectra, thermal convection, thermoelectric figure of merit and the area ratio between the TEG and the radiative cooler on the power generation performance. We optimize the thermal radiation emitter attached to the cold side and propose practical material implementation. The importance of the optimal emitter is elucidated by the gain of 153% in power density compared to regular blackbody emitters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Utilization of waste heat from a commercial GT for freshwater production, cooling and additional power: Exergoeconomic analysis and optimization

In this work, a multigeneration system is proposed for power, cooling and freshwater production. The waste heat from a SIEMENS SGT6-2000E GT is utilized to drive a supercritical CO 2 recompression Brayton cycle (SCRBC) and multi-effect desalination (MED) with thermal vapor compressor (TVC), while the waste heat from the pre-cooler of the SCRBC is utilized to drive an absorption cooling cycle. Detailed thermodynamic, exergy and exergoeconomic analyses are performed for the proposed multigeneration system using Engineering Equation Solver (EES). A sensitivity study is also performed to study the effects of the main operational parameters on the proposed system performance. Finally, multi-objective optimization using a genetic algorithm approach in EES is carried out to reach the optimal design. The proposed system can consume 34.2% less energy input and reduce CO 2 emission by 39.3% compared to the stand-alone systems for power, cooling and freshwater production. The results show that the energy utilization factor and exergy efficiency of the proposed system are improved by 33.6% and 14.3%, respectively, while the total unit product cost is reduced by 11.3% compared to the stand-alone GT cycle. Further, from exergoeconomic optimization, the proposed system can produce 132.4 MW of power, 7.09 MW of cooling and 650 kg/s of freshwater at energy utilization factor of 57.5%, exergy efficiency of 39.7% and total unit product cost of 16.3 $/GJ.

42 ENGINEERING↗

Optimization-Based Deconfliction of Distribution System Applications

Power distribution systems are transitioning towards a future with large numbers of controllable grid-edge devices and distributed generation, as well as more complex operational objectives. This evolution requires a new distribution management approach, and modular applications can play a significant role. Thus, new strategies to coordinate independent applications with diverging operational goals are necessary. In this paper, we propose a novel optimization-based deconflictor to facilitate coordination in future advanced distribution management systems.

application deconfliction, power system optimizati↗

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗

Time-Varying Feedback Optimization for Quadratic Programs with Heterogeneous Gradient Step Sizes

Online feedback-based optimization has become a promising framework for real-time optimization and control of complex engineering systems. This tutorial paper surveys the recent advances in the field as well as provides novel convergence results for primal-dual online algorithms with heterogeneous step sizes for different elements of the gradient. The analysis is performed for quadratic programs and the approach is illustrated on applications for adaptive step-size and model-free online algorithms, in the context of optimal control of modern power systems.

gradient methods↗

Enhancing the Survivability of Power Systems With Grid-Edge DERs Against DoS Attacks

Power system survivability, defined as the ability of a system to maintain steady-state functionality under varying operational conditions, reflects its resilience against disturbances. While existing research primarily focuses on physical-layer disturbances, the increasing prevalence of grid-edge DERs, which are primarily used for integrating renewable energy, has significantly expanded the cyber attack surface. As a result, operational disruptions caused by cyber threats are posing significant challenges to system survivability and cannot be overlooked. To fill this gap, we redefine system survivability to incorporate the cyber layer’s status and propose a Distributionally Robust Optimization (DRO) approach to enhance power system survivability against potential cyber-physical threats. In this paper, we first analyze the operational guidelines of systems with a high penetration of DERs under various cyber network conditions and redefine survivability in this context. Next, we focus on the most common cyber threat, Denial-of-Service (DoS) attacks, and develop a corresponding attack model. This model allows for the creation of a kernel-based ambiguity set that captures attack uncertainties using historical data. Finally, we transform the proposed DRO model as a tractable optimization problem, with its solution providing an optimal cyber redundancy plan to enhance system survivability in DoS attack scenarios. Simulation results on the IEEE 13-node and 123-node test feeders demonstrate the effectiveness of our proposed model in improving system survivability. This model can also be expanded to include other types of common attacks and serve as a comprehensive planning tool to improve overall cyber physical survival of the system.

cybersecurity↗

Spacetime pq theory for AC and DC electric power systems

The 50/60 Hz alternating current (AC) electric power has been the standard and most flexible energy source powering our modern societies for one and a half centuries since the war of the currents: AC versus direct current (DC). A reactive power concept that was introduced at the beginning of the AC power was very useful for circuit/system analysis, design, control, optimization, and ultimately for more efficient and stable generation, transmission, distribution, and consumption. The initial reactive power theory was based on single-phase sinusoidal AC power to capture inductive and capacitive power that yields to net-zero average power over one fundamental cycle. Soon it was expanded to non-sinusoidal AC power and finally to instantaneous three-phase AC power. However, these reactive power theories remain separate and limited to special cases and have never been consolidated and made valid to all cases. Today, more widespread adoption of power electronics and renewable energy is bringing back DC power into the electric grids. The reactive power concept has never been applied to DC power systems. There is no reactive power in DC power systems according to the existing reactive power theories. Do DC power systems really have no reactive power? Capacitors and inductors are widely used in DC just like in AC power systems. Are they not reactive power components? Why are they different from their AC counterparts? Furthermore, are batteries active or reactive power components? What about active devices like power converters (or inverters) with AC (or DC) on one side and DC (or AC) on the other? Do they generate or consume reactive power? Finally, what about AC and DC hybrid power systems? How to define reactive power in such a complex power system that has a multitude of loads, buses, and sources? Is there reactive power between any two loads, any two buses, or any two sources in a power system and what is the total reactive power in such a complex power system as a whole? As the motivation and goal of this paper to answer the above basic questions, to unify the existing AC reactive power theories and to ultimately provide theoretical and insightful guidance for system analysis, design, control, efficiency, optimization, and operation of complex power systems, a concept of spacetime (both spatial and temporal) active and reactive power (pq) theory—the spatiotemporal aspect of active and reactive power—is developed for both AC and DC power systems. The theoretical definitions and physical meanings of the spacetime reactive power will be developed, and real applications and thought experiments/cases/exercises will be explored and discussed. The developed mathematics to define the active (or real) and reactive (or imaginary) power— p and q respectively by dot (scalar) and cross (vector) products of multi-dimension spacetime vectors and time-space mapping principle/law can have some fundamental implications as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗