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Results for “PEAK LOAD”

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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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Formation of stored heat by means of bled steam during times of load reduction and its use in peak load times

Technical possibilities and economic advantages of integrating hot water storage systems into power plants fired with fossil fuels are discussed. The systems can be charged during times of load reduction and then used for back-up during peak load periods. Investment costs are higher for such systems than for gas turbine power plants fired with natural gas or light oil installed to meet peak load demand. However, by improving specific heat consumption by about 1,000 kcal/k ohm, which thus reduces the related costs, investment costs will be compensated for, so that power production costs will not increase.

Bitterlich, E.↗
DOE OSTI2013

Minimization of Impact from Electric Vehicle Supply Equipment to the Electric Grid Using a Dynamically Controlled Battery Bank for Peak Load Shaving

This research presents a comparison of two control systems for peak load shaving using local solar power generation (i.e., photovoltaic array) and local energy storage (i.e., battery bank). The purpose is to minimize load demand of electric vehicle supply equipment (EVSE) on the electric grid. A static and dynamic control system is compared to decrease demand from EVSE. Static control of the battery bank is based on charging and discharging to the electric grid at fixed times. Dynamic control, with 15-minute resolution, forecasts EVSE load based on data analysis of collected data. In the proposed dynamic control system, the sigmoid function is used to shave peak loads while limiting scenarios that can quickly drain the battery bank. These control systems are applied to Oak Ridge National Laboratory s (ORNL) solar-assisted electric vehicle (EV) charging stations. This installation is composed of three independently grid-tied sub-systems: (1) 25 EVSE; (2) 47 kW photovoltaic (PV) array; and (3) 60 kWh battery bank. The dynamic control system achieved the greatest peak load shaving, up to 34% on a cloudy day and 38% on a sunny day. The static control system was not ideal; peak load shaving was 14.6% on a cloudy day and 12.7% on a sunny day. Simulations based on ORNL data shows solar-assisted EV charging stations combined with the proposed dynamic battery control system can negate up to 89% of EVSE load demand on sunny days.

Battery Management Systems↗
DOE OSTI2015

Research, Development and Demonstration of Peak Load Reduction on Distribution Feeders Using Distributed Energy Resources for the City of Fort Collins

This project titled “Research, Development and Demonstration of Peak Load Reduction on Distribution Feeders Using Distributed Energy Resources for the City of Fort Collins” evolved in response to the Department of Energy’s (DOE) Funding Opportunity Announcement (FOA) Number DE-PS26-07NT43119. Also referred to as the Fort Collins Renewable and Distributed System Integration (RDSI) Project, the effort was undertaken by a diverse group of local government, higher education and business organizations; and was driven by three overarching goals: I. Fulfill the requirements of the DOE FOA’s Area of Interest 2: Renewable and Distributed System Integration; most notably, to demonstrate the ability to reduce electric system distribution feeder peak load by 15% or more through the coordinated use of Distributed Energy Resources (DER). II. Advance the expertise, technologies and infrastructure necessary to support the long term vision of the Fort Collins Zero Energy District (FortZED) and move towards creating a zero energy district in the Fort Collins “Old Town” area. III. Further the goals of the City of Fort Collins Energy Policy, including the development of a Smart Grid-enabled distribution system in Fort Collins, expanded use of renewable energy, increased energy conservation, and peak load reduction. Through the collaborative efforts of the partner organizations, the Fort Collins RDSI project was successful in achieving all three of these goals. This report is organized into two distinct sections corresponding to the two phases of the project: • Part 1: Feeder Peak Load Reduction and the FortZED Initiative. • Part 2: Forming and Operating Utility Microgrids and Managing Load and Production Variability The original project scope addressed the Part 1 feeder peak load reduction. That work took place from 2009 through 2011 and was largely complete when the project scope was amended to include a demonstration of microgrid operations. While leveraging the assets, partner relationships, and lessons learned from Part 1, Part 2 was managed and executed as a distinct and substantially independent sub-project during the spring and summer of 2013. Both Parts 1 and 2 of the overall RDSI project can be viewed as cohesive stand-alone bodies of work and are presented as such within this report. In addition to the narratives, this document includes two Appendices that were compiled to supplement information about the various aspects of activities performed during Parts 1 and 2 of the project. Moreover, these Appendices are organized (as outlined below) so as to directly relate to the narratives in Part 1 and 2 of this report. • Appendix - Part 1: describes the roles of each project participant in regards to the feeder peak load reduction effort, and • Appendix - Part 2: deals with the microgrid research/demonstration.

14 SOLAR ENERGY↗
DOE OSTI2023

Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data

In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS-based on real-time optimal power flow-controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources: Preprint

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS—based on real-time optimal power flow—controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Design of Phase-Change Thermal Storage Device in a Heat Pump for Building Electric Peak Load Shaving: Preprint

Replacing carbon-intensive fossil fuel heating systems with electric heat pumps powered by renewables is a promising approach to decarbonize the building sector. However, one of the technical barriers of this approach is the large scale of heat demand, which will put excessive stress on the electricity grid. Integrating thermal energy storage (TES) into the heating systems can help alleviate this problem, by shifting thermal load and thus shaving peaks in the building electric load. Therefore, it is critical to understand how to design a thermal storage device in a heat pump for peak load shaving. In this study, we developed a numerical model for a cascaded vapor compression heat pump system integrating a phase change thermal storage device. This novel system can control the net thermal charging and discharging rate of the TES independently from the building's thermal load, which allows for precise control of electric power use. In the current study, we controlled the system to shave building electric peak load during a cold winter morning, and to charge TES during the relatively warm afternoon while still providing space heating. We used the model to evaluate the system performance with and without peak shaving. We also investigated the effect of PCM transition Tt on the peak reduction and electric energy saving potentials. The results show that peak shaving scheme effectively reduces the peak electric power consumption during a predefined discharge time window. When comparing to the no shaving case, for PCM Tt = 10 degrees C, the peak electric load reduction is 23.5%. When comparing to an air-source heat pump with back up electric heater, as Tt increases from 0 to 20 degrees C, the peak reduction increases from 46.1% to 50.9%. Integrating PCM Tt = 10 degrees C with peak shaving leads to the 45.5% of electric energy saving, which is the highest among the three transition temperatures.

electric energy saving↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2019

Method and apparatus for measuring a peak load

The present subject matter discloses a method of measuring a peak load, including the steps of placing an indenter between a first surface and a second surface, exerting a load on at least one of the first and second surfaces, measuring at least one of a width, depth, radial chord length, and cross-sectional area of an indentation formed by the indenter in at least one of the first and second surfaces; and converting the measured parameter into a load value. Certain methods further include the steps of converting the measured parameter into a load per length value and obtaining a load value by integrating along a circumferential length of the indentation. In still other methods, the exerted load is a compressive load.

Bullen, David A.↗
DOE OSTI2017

Impacts of Using Distributed Energy Resources to Reduce Peak Loads in Vermont

To help the United States develop a modern electricity grid that provides reliable power from multiple resources as well as resiliency under extreme conditions, the U.S. Department of Energy (DOE) is leading the Grid Modernization Initiative (GMI) to help shape the future of the nation's grid. Under the GMI, DOE funded the Vermont Regional Initiative project to provide the technical support and analysis to utilities that need to mitigate possible impacts of increasing renewable generation required by statewide goals. Advanced control of distributed energy resources (DER) can both support higher penetrations of renewable energy by balancing controllable loads to wind and photovoltaic (PV) solar generation and reduce peak demand by shedding noncritical loads. This work focuses on the latter. This document reports on an experiment that evaluated and quantified the potential benefits and impacts of reducing the peak load through demand response (DR) using centrally controllable electric water heaters (EWHs) and batteries on two Green Mountain Power (GMP) feeders. The experiment simulated various hypothetical scenarios that varied the number of controllable EWHs, the amount of distributed PV systems, and the number of distributed residential batteries. The control schemes were designed with several objectives. For the first objective, the primary simulations focused on reducing the load during the independent system operator (ISO) peak when capacity charges were the primary concern. The second objective was to mitigate DR rebound to avoid new peak loads and high ramp rates. The final objective was to minimize customers' discomfort, which is defined by the lack of hot water when it is needed. We performed the simulations using the National Renewable Energy Laboratory's (NREL's) Integrated Energy System Model (IESM) because it can simulate both electric power distribution feeder and appliance end use performance and it includes the ability to simulate multiple control strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a two-agent soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak demand reduction. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operations to enhance control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment and reduce peak load demand from feeder's head.

deep reinforcement learning↗
DOE OSTI2023

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management: Preprint

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak load demand shaving. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operation to enhance the control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment for peak demand reduction.

deep reinforcement learning↗
DOE OSTI2017

Impacts of Commercial Building Controls on Energy Savings and Peak Load Reduction

Commercial buildings in the United States use about 18 Quadrillion British thermal units (Quads) of primary energy annually . Studies have shown that as much as 30% of building energy consumption can be avoided by using more accurate sensing, using existing controls better, and deploying advanced controls; hence, the motivation for the work described in this report. Studies also have shown that 10% to 20% of the commercial building peak load can be temporarily managed/curtailed to provide grid services. Although many studies have indicated significant potential for reducing the energy consumption in commercial buildings, very few have documented the actual savings. The studies that did so only provided savings at the whole building level, which makes it difficult to assess the savings potential of each individual measure deployed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

Molten salt thermal energy storage for utility peaking loads

This paper considers the use of thermal energy storage (TES) in molten salts to increase the capacity of power plants. Five existing fossil and nuclear electric utility plants were selected as representative of current technology. A review of system load diagrams indicated that TES to meet loads over 95% of peak was a reasonable goal. Alternate TES heat exchanger locations were evaluated, showing that the stored energy should be used either for feedwater heating or to generate steam for an auxiliary power cycle. Specific salts for each concept are recommended. Design layouts were prepared for one plant, and it was shown that a TES tube/shell heat exchanger system could provide about 7% peaking capability at lower cost than adding steam generation capacity. Promising alternate heat exchanger concepts were also identified.

Ferrara, A.↗
DOE OSTI2019

How Solar and Storage Can Reduce Coincident Peak Loads and Payments: A Case Study in Austin, TX

This study builds a generalized tool to forecast the change of 4 coincident peak (4CP) loads and payments based on varying amounts of solar, storage capacity, and population estimates over a 10-year period for utilities within the Electric Reliability Council of Texas (ERCOT). It also incorporates an optimization model for the energy storage systems (ESSs) that maximizes the sum of the revenue earned from their operation as well as the net 4CP payments received by the utility by attempting to arbitrage the ERCOT energy market. Here, the tool is illustrated by using empirical data from the municipally-owned utility in Austin, TX (Austin Energy). 4CP payments can be on the order of tens of millions of dollars. Results indicate that solar and storage capacity can substantially lower these payments. For example, a 20 MW increase in solar capacity in 2018 would reduce Austin Energy’s payment by an estimated $200,000 for each subsequent year. By using the novel approach of incorporating coincident peak demand charge reductions at the DSP level, this study highlights the economic value of local generation and storage.

14 SOLAR ENERGY↗
DOE OSTI2020

Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy

Reducing peak power demand in a building can reduce electricity expenses for the building owner and contribute to the efficiency and reliability of the electrical power grid. For the building owner, reduced expenses come from the reduction or elimination of peak power charges on electricity bills. For the power system operator, reducing peak power demand leads to a more predictable load profile and reduces stress on the electric grid system. Herein we present a computationally inexpensive, dynamic, and retrofit-deployable control strategy to effect peak load reduction and load shaping. The effectiveness of the control strategy is examined in a simulation with 80 air-conditioning units and 40 refrigeration units. The results show that a peak demand reduction of 60 kW can be achieved relative to peak demand in a typical set point–based approach. The proposed strategy was deployed in a gymnasium building with four rooftop HVAC units, where it showed over 15% peak demand (kW) reduction savings while maintaining or lowering energy consumption (in kilowatt-hours) relative to the set point–based thermostat controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗