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Results for “co-optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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194 records · Page 11

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration: Preprint

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗

Optimizing DER Deployment for Climate, Health, Resilience, and Energy Bill Benefits Using the REopt Model

Climate change, public health, and resilience to power outages are of critical concern to local governments, federal agencies, and the private sector, and are increasingly motivating investments in distributed energy resources (DERs). However, designing a solar-plus-storage system to co-optimize for climate, health, resilience, and energy bill benefits requires complex trade-offs. To address this need, the National Renewable Energy Laboratory has integrated climate and health impacts of grid-purchased electricity and on-site fuel consumption into the publicly-available REopt web tool and API - a techno-economic model that determines the cost-optimal DER system sizes and dispatch strategy. This presentation will provide an overview of the tool's methodology, datasets, and capabilities, including costing emissions into system sizing and dispatch and setting emissions reductions targets. Results of previous work will demonstrate the use of new emissions accounting capabilities by quantifying the impact of including climate and health costs on the optimal resilient microgrid configurations for a hospital, school, and warehouse across 14 U.S. cities.

climate↗

Fuel Properties and Kinetics

The Co-Optimization of Fuels and Engines (CoOptima) program is focused on a two-pronged approach to develop new, lower net-carbon fuels and advanced engine technologies in tandem. This effort brings nine national labs and several university and industry partners together to simultaneously identify new fuel candidates and to further engine technology development in the light-, medium-, and heavy-duty vehicle sectors with a focus on fuel economy and emission reduction. The fuel properties and kinetics project is aimed at achieving a better understanding of fuel property kinetics and how they impact engine performance such that more efficient and lower emitting engines can be made a reality. Several promising biofuel candidates were identified through tiered screening approaches and were evaluated utilizing unique bench-scale measurement techniques. Kinetic models were developed to describe autoignition and soot pre-cursor formation mechanisms to identify the most promising candidates that advanced various combustion strategies.

ADVANCED PROPULSION SYSTEMS↗

Managing Uncertainty and Flexibility in Day-Ahead Electricity Markets

Net load imbalances from day ahead forecasts can lead to significant grid operations costs and are expected to increase as variable renewable energy adoption grows. We propose a new wholesale market product to manage the risk of net load imbalances called Flexibility Options. This product relies on probabilistic forecasts to estimate flexibility demand and would be co-optimized in the day-ahead market. We also propose stochastic methods that enable DER and flexible load aggregators to participate in flexibility markets while considering the uncertainty in weather and occupant behavior.

day-ahead market↗

Hydrogen Systems for PERformance-Based Value Stacking

The proposed technology (HYPER-V: HYdrogen Systems for PERformance based Value-stacking) represents a co-optimized control framework to dispatch hydrogen systems for serving complex commercial energy demands. HYPER-V aims at integrating hydrogen systems for a variety of use-cases in all energy markets including (but not limited to) grid services, transportation, and fuels. This presentation is the end-of-the-project merit review describing the outcomes.

grid services↗

Estimating the value of jointly optimized electric power generation and end use: a study of ISO-scale load shaping applied to the residential building stock

A generation-to-load simulation estimated the impact, in terms of production costs and CO2 emissions, attributable to the joint optimization of electric power generation and flexible end uses to support increasing penetrations of renewable energy. Newly conceived, evaluated, and foundational in developing a U.S. National Standard was a transaction-less yet continuous demand response system based on a day-ahead optimum load shape (OLS) designed to encourage Internet-connected devices to autonomously and voluntarily explore options to favour lowest cost generators - without requiring two-way communications, personally identifiable information, or customer opt-in. Boundary conditions used for model calibration included historical weather, residential building stock construction attributes, home appliance and device empirical operating schedules, prototypical power distribution feeder models, thermal generator heat rates, startup and ramping constraints, and fuel costs. Results of an hourly-based annual case study of Texas indicate a 1/3 reduction in production costs and a 1/5 reduction in CO2 emissions are possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comparing the economic performance of ice storage and batteries for buildings with on-site PV through model predictive control and optimal sizing

Integrating renewable energy and energy storage systems provides a way of operating the electrical grid system more energy efficiently and stably. Thermal storage and batteries are the most common devices for integration. However, it is not clear which integrated storage system performs better in terms of overall economics. Ice storage has low initial and maintenance costs, but there is an efficiency penalty for charging of storage and it can only shift electrical loads associated with building cooling requirements. A battery's round-trip efficiency, on the contrary, is quite consistent and batteries can be used to shift both HVAC and non-HVAC loads. However, batteries have greater initial costs and a shorter life. Finally, this research presents a tool, using model predictive control and optimal sizing, and provides a case study for comparing life-cycle economics of battery and ice storage systems for commercial buildings that have chillers for cooling and an on-site photovoltaic system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Systematic Review on Coordinated Restoration Strategies for Power Distribution Grids

Power distribution grids are increasingly exposed to High-Impact Low-Probability (HILP) events, which cause widespread disruptions with severe societal and economic impacts. The growing complexity of modern grids, driven by the integration of distributed energy resources and smart grid technologies, has introduced new challenges to effective service restoration. While significant research has explored individual restoration strategies, such as network reconfiguration and microgrid formation, limited attention has been given to methods in which they can be effectively coordinated. Furthermore, the absence of systematic review papers addressing this issue hampers the development of cohesive restoration frameworks capable of addressing the operational complexities of modern grids. This paper presents a systematic review synthesizing existing knowledge on power grid restoration, identifying key limitations, and highlighting opportunities for coordinated strategies. By addressing research gaps and emphasizing the integration of diverse approaches, this study provides critical insights for advancing grid resiliency and recovery, offering a foundation for future research and practical applications in the face of HILP events.

Systematic review↗

Graphene-Based Interconnect Exploration for Large SRAM Caches for Ultrascaled Technology Nodes

Graphene-based interconnects are considered promising replacements for traditional copper (Cu) interconnect due to their great electric properties. In this article, an interconnect-memory co- design framework is developed to efficiently optimize various graphene-based interconnect technologies. Four interconnect materials and heterogeneous design schemes are benchmarked against their traditional Cu counterparts to optimize large cache-level SRAM performance in terms of delay and energy per access, energy-delay product (EDP), and energy-delay-area product (EDAP). Here, a large design space exploration is performed based on realistic subarray design and device technology. Various interconnect- and array-level design parameters are studied to quantify the true potential of graphene-based wires for optimal memory performance.

42 ENGINEERING↗

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Utilizing energy storage solutions to reduce the need for traditional transmission investments has been recognized by system planners and supported by federal policies in recent years. This work demonstrates the need for detailed reliability assessment for quantitative comparison of the reliability benefits of energy storage and traditional transmission investments. First, a mixed-integer linear programming expansion planning model considering candidate transmission lines and storage technologies is solved to find the least-cost investment decisions. Next, operations under the resulting system configuration are simulated in a probabilistic reliability assessment which accounts for weather-dependent forced outages. The outcome of this work, when applied to TPPs, is to further equalize the consideration of energy storage compared to traditional transmission assets by capturing the value of storage for system reliability.

co-optimization↗

Scheduler Modeling of Distributed Energy Resources for Providing Ancillary Services

Distribution energy resources (DERs) have been integral components of modern power systems, and their capability to provide grid services has been widely studied. To promote the deployment of these resources in providing grid services in real-world utility operations, this paper proposes a day-ahead scheduler model for a distribution system connected DER plant. A certain amount of generation capacity of this DER plant is reserved for frequency services, and some ancillary services for the distribution system-including peak load reduction, voltage regulation, and power factor control-are integrated into the model. The model is tested on a real-world distribution system. From the simulation results, the energy and reserve schedule of the solar photovoltaic (PV) unit and battery energy storage system (BESS) can be determined, and voltage and power factor are well maintained. Additionally, in order to demonstrate the specific characteristics of the co-located and hybrid operation modes for the PV and BESS, these two modes are analyzed both theoretically and through real-time simulation. Simulation results show that most of PV's variability is transferred to the net power in the co-located mode, whereas it is transferred to the BESS in the hybrid mode. This proposed scheduler model and the comparison of co-located and hybrid modes can provide practical guidance for the applications of DER plant in the real-world utility.

14 SOLAR ENERGY↗

To What Extent Will Decarbonization Deepen the Conversation Between Industry and the Grid?

Decarbonization - the transition away from un-mitigated fossil fuel combustion throughout the economy - requires big changes from both power and process systems. On the power system side, those changes are expected to include large increases in variable generation, e.g., from wind and solar, which has near-zero marginal costs and at large shares can produce infrequent but consequential energy droughts. On the process systems side, industries are investigating their options for direct and indirect electrification, the latter exemplified by replacing fossil fuel inputs with zero-carbon, energy-carrying chemicals like hydrogen and ammonia produced via electrochemical processes. The economic features of these changes within the larger context of power and process systems suggest that their realization could be accompanied by a paradigm shift in how industrial facilities interact with the grid. For example, the dominant type of demand participation in power markets could change from today's focus on load reductions at peak times to a new focus on shifting electricity use, enabled in part by large-scale product storage, to take advantage of renewable energy that would otherwise be curtailed and to avoid consumption during high-price energy droughts. This talk will describe these and other possible design and operational approaches from grid and industrial economic perspectives, culminating in an enumeration of open problems that lie at the interface of today and tomorrow's power and process systems.

co-design↗