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At least 829 records · Page 46

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DOE OSTI2020

A Modular Optimal Power Flow Method for Integrating New Technologies in Distribution Grids

This work proposes a modular concept to build optimal power flow (OPF) models for distribution networks containing various emerging technologies under diverse ownership structures, to efficiently deal with evolving technology capabilities and information sharing or privacy constraints. This concept will support any typical OPF application (e.g., optimal dispatch of a given asset without violating grid constraints) by coordinating between grid module and technology module without the need to recreate various modeling elements as technology capability changes due to innovation. Moreover, the modularity of the proposed concept enables achieving system level objectives without sharing detailed information on module level objectives and constraints among modules. To achieve this, the proposed work develops a gradient-descent algorithm which builds upon the literature on the state-of-the-art power flow approximation. The proposed concept is demonstrated with two case studies of i) controllable loads and ii) battery energy storage system (BESS) on an actual large-scale distribution grid.

Hanif, Sarmad↗

DOE OSTI2021

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-Learning

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure damage in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified to help transmission and distribution system operators prepare for and prevent significant damage and subsequent loss of power. In this paper, we develop an approach that models the impact of extreme weather on the grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch to minimize the adverse impacts of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

extreme weather↗

DOE OSTI2020

Advanced Sensors & Controls FWP Overview

Fossil energy power generation is needed now and in the future, but its role is shifting from baseload operation to fulfilling dispatchable power needs in regions of the United States. Novel sensors and controls will help to increase efficiency, minimize emissions, and reduce operating costs of existing power generation technologies under this increased load following role; and help enable next generation power systems with high efficiency and greater operational flexibility.

Buric, Michael↗

DOE OSTI2020

Conceptual Design Study of a Thermal Energy Storage System Using Granular Solids for Coal-fired Boilers

Presentation for the 2020 International Pittsburgh Coal Conference held virtually from September 8-11, 2020.Abstract: As electricity from various renewable energy sources is increasingly supplied to the power grid, the grid’s stability will be challenged. Proposed grid-stability solutions will need to address variability of sources, such as solar and wind energy, in order to alleviate problems such as overgeneration and ramping. In regions where increases in solar energy are prominent, such as California, the net power demand curve often referred to as “the Duck Curve,” has caused problems for energy dispatchers, due to over-generation and fast ramping demands. In this project, we investigated a conceptual design for a Thermal Energy Storage System (TESS) integrated into a coal-fired power plant to support grid-scale storage. Implementing a TESS into power plants can allow for an increase in renewable sources, increase grid resilience, and allow conventional coal-fired plants to operate more efficiently. For this project, a TESS using granular solids as the energy-storage media is integrated into a conventional coal-fired power plant. The purpose of the TESS is to store energy from the flue gas during low demand periods and transfer the energy to steam during peak demand periods. The storage allows the stabilization of combustion and related boiler components at low loads and provides the opportunity to avoid some shutdowns. This study uses thermodynamic properties of several candidate thermal storage materials to estimate the size of storage system required for several operating scenarios.

Huckaby, E. David↗

DOE OSTI2021

Lithium Metal as an Anode in Electrochemical Energy Storage

The drastic environmental and economic costs of global warming have driven the necessity to reduce, if not eliminate, a dependency on oil and gas for energy applications. Alternative clean energy reliance has been initiated as a global investment for a more sustainable future. Part of this transitional effort is focused on energy storage via a rechargeable battery. High energy density storage is necessary for utilizing non-dispatchable green energy technologies, as well in the electric transition of our vehicle fleet. Further, understanding methods of extracting, manufacturing, and recycling lithium is necessary to lessen environmental impact. Lithium metal is often considered the “Holy Grail” of battery technology, due to its high theoretical capacity (3,860 mAh/g) and low electrochemical potential (-3.04 V vs. SHE). However, parasitic reactions lead to rapid and dangerous battery failure. Therefore, determining methods of stabilizing lithium metal is paramount for the transition to a greener future.

25 ENERGY STORAGE↗

DOE OSTI2021

Hardware-in-the-Loop Evaluation of an Advanced Distributed Energy Resource Management Algorithm

This paper presents the laboratory performance evaluation of voltage regulation under a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale real-world distribution system from a utility partner, the DERMS software controller, and power hardware photovoltaic (PV) inverters. The new DERMS algorithm is developed based on online multi-objective optimization (OMOO) algorithms that perform fast dispatch of distributed solar PV simulated in a real-time digital simulator and real physical hardware devices. Experimental tests confirm the correct functioning of the HIL platform for evaluating controller algorithms and satisfactory voltage regulation performance of the developed OMOO algorithms.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2021

Renewable Thermal Hybridization Framework for Industrial Process Heat Applications

Renewable thermal energy systems (RTES) could be hybridized with different renewable options (e.g., flat plate collectors (FPCs) with parabolic collectors), or combined with existing heat supplies (e.g., fossil fuels), to give options for targeted solar IPH applications, industrial decarbonization and the reduction of fuel consumption. Buildings and industrial thermal energy applications require different temperature ranges, quantities, and rates of thermal energy, and as such require flexible, cost competitive solutions, able to provide heat over various temperature ranges. Hybrid solutions and thermal energy storage (TES) will be important for the dispatch of heat at optimal times needed by the demand side of the buildings and industrial applications. A variety of tools and platforms, such as the System Advisor Model (SAM), can provide hourly thermal yield simulations from single renewable energy (RE) technology options, including FPCs or CSP for solar IPH. We have investigated a variety of approaches to hybrid system modeling for RTES at different temperatures or combinations of technologies and developed an initial framework. The hybridization framework starts by creating a heat stream and raising the temperature of that heat stream by various combinations of RE technologies and other sources such as fossil fuels, new fuels or electric heating in multiple stages, with options for TES and/or waste heat recovery (WHR).

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Emergency Voltage Regulation in Power Systems via Ripple-Type Control: Preprint

With increasing penetration of volatile renewable generation and cyber-physical disruptions, ensuring safe operation of bulk power systems has become unprecedentedly challenging. Since communication and computational costs restrict centralized system dispatch to be called upon every few minutes; and purely local schemes are shown to be insufficient, distributed controls have been advocated for handling unanticipated system conditions in real time. However, the applicability of distributed control schemes is fundamentally limited by their need for widespread communication and model cognizance. In this con-text, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a ‘hotline’ communication network. Under this protocol, when agents observe a constraint violation based on local measurements, they respond locally until their control resources saturate, in which case they send a beacon for assistance to peer agents. The scheme ensures that minor violations are efficiently mitigated via fast local controls, while severe violations may be handled by a collaboration of a relatively small set of agents. We evaluate the performance of this scheme via extensive numerical tests on the IEEE 14-bus test feeder, where agents act upon noisy measurements under diverse scenarios of random load variations and severe low/high voltage events.

distributed control↗

DOE OSTI2021

Coordinated Modeling of Electric Grid and Natural Gas Network Operations

Presentation based upon full report of a Colorado case study and coordination framework, which is available at https://www.nrel.gov/docs/fy20osti/77096.pdf. JISEA analysts Brian Sergi, Omar Guerra, and Bri-Mathias Hodge will present on recent JISEA work on coordination between the natural gas and electricity sectors. Power and gas are becoming increasingly interdependent but weren't designed to function together. How does greater coordination impact system operations with different levels of solar and wind penetrations? This free JISEA presentation will take place in a Webinar on Tuesday, May 11, 2021 at 12 p.m.: Learn how greater coordination between the natural gas and electricity sectors impacts system operations with different levels of solar and wind penetrations. Presentation information includes: Historical and projected data for natural gas consumption and power generation in the United States as demonstrated by 2014 East Coast Polar Vortex, 2021 Texas Winter Storm Uri. Showing coupling points, FERC identified need for better coordination, different levels of coordination (decision making and optimization control), coordination framework. Case study on Colorado Front Range, ramping requirements and gas nominations, real-time dispatch (June and December scenarios), results of analysis of impacts of coordination on unserved load. Total real-time gas offtakes by node, impacts on unserved gas, effect on CO2 emissions. Discussions on clusions drawn from Colorado Case study expanded co-simulation via HELICS, objectives of the HELICS+ natural gas use case, modeling of hydrogen blending, techno economic assessment of blending, and blending impacts on energy content and pressure.

analysis↗

DOE OSTI2021

Hardware accelerated dynamic work creation on a graphics processing unit

A processor core is configured to execute a parent task that is described by a data structure stored in a memory. A coprocessor is configured to dispatch a child task to the at least one processor core in response to the coprocessor receiving a request from the parent task concurrently with the parent task executing on the at least one processor core. In some cases, the parent task registers the child task in a task pool and the child task is a future task that is configured to monitor a completion object and enqueue another task associated with the future task in response to detecting the completion object. The future task is configured to self-enqueue by adding a continuation future task to a continuation queue for subsequent execution in response to the future task failing to detect the completion object.

Gutierrez, Anthony↗

DOE OSTI2021

Coordinated Optimal Control of PV Inverters and HVAC Loads in Distribution Systems

The increasing integration of distributed energy resources (DERs), such as photovoltaics (PVs) and smart buildings into distribution systems complicate power system operation and controls. This paper proposes a coordinated optimal control strategy for PV inverters and Heating, ventilation, and air conditioning (HVAC) loads in smart buildings to minimize the total network loss in a distribution system. For the HVAC units, we enforce minimum on and off time constraints to avoid frequent switching that can degrade the unit. The proposed control will dispatch optimal control signals of active and reactive power to PV inverters and on/off commands to HVAC units while maintaining the nodal voltage within a secure range and the temperature of HVAC units at a comfort level. The simulation results on a modified IEEE 33-node distribution system demonstrate that the proposed coordinated control scheme can reduce the network loss.

Pani, Naveen↗

DOE OSTI2021

Priority-enabled Load Balancing for Dispersed Computing

Opportunistic managed access to local in-network compute resources can improve the performance of distributed applications and reduce the dependence on shared network resources. Instead of backhauling application data to a centralized cloud data center for processing, networked services may be adaptively and continuously dispersed into shared compute resources that are closer to the source of need. While this approach has several benefits, support for mission-aware access to computation is often an afterthought, and is implemented as a brittle extension over traditional load-balancer solutions.In this work, we investigate the design of two priority-aware resource allocation strategies and two load-balancing dispatching strategies as first class citizens in an open-source dispersed computing middleware. We present a control theoretic analysis of these load-balancing primitives to identify weaknesses and strengths in our design, and recommend future directions. In parallel, we prototype two priority-aware allocation algorithms to validate our priority predictions. In initial experiments our prototype shows substantial gains in processing prioritized load. Finally, we make our source-code and experimental configurations open source.

Paulos, Aaron↗

DOE OSTI2021

Final Scientific Technical Report for "Microgrid RD&D and Testing of PIDC and PWD Systems"

Alstom Grid Inc’s (ALSTOM Grid) Research Design and Development (RD&D) project, “Microgrid RD&D and Testing for PIDC and PWD” was conducted in partnership with Philadelphia Industrial Development Corporation (PIDC) in its role as owner’s representative and manager of a vibrant commercial and industrial community, involving critical loads in one of the nation’s largest unregulated, non-military electric distribution systems. PIDC needed to develop solutions to address the planned considerable growth in Distributed Energy Resources (DER) Combined Heat Plan (CHP), Renewables, Distributed Generation (DG), Demand Response (DR) and Storage. In supporting the corporate objective, PIDC needed a new class of control systems for achieving enhanced energy resilience of their critical infrastructure operation during adverse conditions together with carbon emission reduction and optimization of the overall system operation economics through system energy efficiency during normal and emergency operating conditions. Additionally, PIDC anticipated the need to support a new class of commercial agreements with tenants, such as those for Urban Outfitters, for guaranteed one hundred percent (100%) grid resilience and electric power supply in case of utility outage conditions. The project was designed to address the challenges for the commercial & industrial (C&I) communities. But more importantly, the project included development of scalable and replicable solutions intended to target a multitude of the nation’s electric distribution communities. The project researched and developed a fully comprehensive prototype consisting of microgrid operation and control functions including islanding, synchronization and reconnection, protection, voltage, frequency, and power quality management, dispatch, and system resiliency. The project provided the foundation required to significantly enhance the overall national objectives set by the DOE for energy resilience, emission reduction and system energy efficiency improvement, including protection of critical infrastructure and public resources.

14 SOLAR ENERGY↗

DOE OSTI2021

A hub and spoke approach to optimizing energy wheeling of renewable resources

The deployment of zero carbon renewable energy sources needs to increase significantly to support the goal of net zero greenhouse gas emissions by 2050. At the same time energy end use needs to decarbonize. This will change both energy supply and energy demand patterns, requiring the energy delivery infrastructure (grid-based transmission circuits) to become increasingly flexible to maintain security of supply everywhere and always. The integration of zero carbon renewable energy requires cross-border and cross energy system coupling and a fit-for-purpose design. Nowadays, energy systems are planned, designed and operated in silos with a strong national focus. However, large-scale offshore wind production needs to be transported to deep inland locations, across country borders. The increased peak generation capacity of renewable energy sources will, at times, significantly exceed demand (Matthew Langholtz, 2020). The traditional solution of continuously reinforcing and extending the electricity grid is not sustainable from a cost and societal perspective. This paper will, however, propose a deterministic approach on how networked (interconnected grid) Points of receipt (POR) to Points of Delivery (POD) can be optimized for wheeling renewable energy resources while minimizing energy cost with a hub and spoke approach. The statistical approach will be done via using existing daily energy market clearing prices, available transmission capacity and firm daily transmission prices in open access energy markets. Renewable energy targets, including specific offshore wind targets, need to be in line with the ramp-up as implied by the Paris Agreement. These targets are required to provide industry with a secure market outlook that allows them to build up supply chains accordingly. Optimizing wheeled energy paths from carbon neutral resources such as renewables make them not only cost competitive on the unit commitment stack, but also more accessible on the dispatch stack to other carbon heavy forms of generation such as coal and natural gas turbines (Matthew Langholtz, 2020). This correlates to maximizing renewable resource inertia (wind, solar, biomass) within an interconnected grid without having to consider additional expansion of resources via land purchases and de-forestation.

Mukherjee, Srijib↗

DOE OSTI2021

Hardware-in-the-Loop Evaluation of an Advanced Distributed Energy Resource Management Algorithm: Preprint

This paper presents the laboratory performance evaluation of voltage regulation under a new distributed energy resource management system (DERMS) algorithm via an advanced hardware-in-tbe-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale real-world distribution system from a utility partner, the DERMS software controller, and power hardware photovoltaic (PV) inverters. The new DERMS algorithm is developed based on online multiobjective optimization (OMOO) algorithms that perform fast dispatch of distributed solar PV simulated in a real-time digital simulator and real physical hardware devices. Experimental tests confirm the correct functioning of the HIL platform for evaluating controller algorithms and satisfactory voltage regulation performance of the developed OMOO algorithms.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2021

A Computationally Efficient Algorithm for Computing Convex Hull Prices

Electricity markets worldwide allow participants to bid non-convex production offers. While non-convex offers can more accurately reflect a resource's capabilities, they create challenges for market clearing processes. For example, system operators may execute side payments when a participant’s cost is not covered through energy sale settlements from locational marginal pricing schemes, or when a participant incurs lost opportunity costs to follow the dispatch signal. Convex hull pricing minimizes these and other types of side payments while providing uniform (i.e., locationally and temporally consistent) prices. However, computing convex hull prices involves solving either a large-scale linear program - which in turn requires explicit descriptions of market participants’ convex hulls -or the Lagrangian dual of the corresponding non-convex scheduling problem. Here, we propose a computationally feasible and industrially scalable Benders decomposition approach to computing convex hull prices at least an order of magnitude faster than the current state-of-the-art while leveraging recent advances in convex hull formulations for thermal generating units.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Solar PV Curtailment in Changing Grid and Technological Contexts: Preprint

Solar photovoltaic (PV) systems generate electricity with no marginal costs or emissions. As a result, PV output is almost always prioritized over other fuel sources and delivered to the electric grid. At increasing levels of PV penetration situations arise where PV is curtailed, either because of local supply/demand imbalances or to maintain system flexibility. In 2018, we estimate that about 6.5 million MWh of PV output was curtailed in four key countries: Chile, China, Germany, and the United States. We find that PV curtailment peaks in the spring and fall, when PV output is relatively high but electricity demand is relatively low. Similar to the case of wind, some PV curtailment is attributable to limited transmission capacity connecting sparsely populated solar-heavy regions to load centers.Grid policies generally seek to minimize curtailment because it is viewed as an economic and environmental loss. However, we argue that changing grid and technological contexts warrant new thinking on PV curtailment. In the grid context, as grids integrate more PV and other renewable energy generation, seeking an optimal level of accepted curtailment becomes more efficient than preventing it. In the technological context, emerging technologies such as advanced inverters and low-cost battery storage are making PV systems more flexible. With flexible PV, grid operators can use withheld PV output to provide various non-generation grid services. This withheld PV output is a form of curtailment under prevailing definitions of the term. Hence, policies that aim to minimize curtailment may undercut the ability of grid operators to fully use the emerging capabilities of flexible PV systems. We argue that the changing grid and technological contexts require a re-examination of the curtailment paradigm. We argue that PV output that is withheld to provide grid services is fundamentally different from output that goes unused in response to system constraints. As a result, we propose a more exclusive definition of curtailment as unused PV output rather than the more expansive conventional definition as any reduction in system output from its technical potential. The terminological distinction is more than a question of semantics. Facilitating grid services by withholding PV output may increase the potential value of flexible PV systems to the grid. This shift in thinking may allow grid operators and policymakers to think in terms of PV curtailment management rather than minimization. Effective curtailment management may include policies that increase PV system dispatchability, alternative PV compensation schemes that decouple generator revenue from system output, and policies to increase grid flexibility.

Chile↗

DOE OSTI2021

Computational Math Problems for a Clean Energy Future

Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.

ADMM↗