Impact of Price-Responsive Load and Renewables in an Emission-Aware Power Systems
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As the coincident events of extreme weather and major power outages continue to rise there is an increased need to implement resilience solutions. Many of these solutions are customer-centric, requiring the flexibility of demand, and many of the standard economic evaluations of these solutions do not include the benefits of resilience that are not easily quantified and monetized. Indoor air temperature has a large impact on the comfort and safety of building occupants during an extreme weather event. This work proposes metrics that can be used to compare the performance of resilience solutions in the context of comfort and safety.
In 2017, San Diego Gas & Electric installed a 30 MW, 120 MWh lithium-ion battery storage facility-the world's largest at the time. But, recent work demonstrates that local control can enable flexible loads to provide equivalent battery-like services to the grid. Our cost comparison shows that it is much cheaper to acquire 30 MW, 120 MWh of capacity by retro-fitting 120,000 water heaters with control hardware and telecommunications. Surprisingly, it may even be cheaper to give away 120,000 'smart' water heaters!
Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from the power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.
This paper investigates the possibility of providing aggregated regulation services with small loads, such as water heaters or air conditioners. A direct-load control algorithm is presented to aggregate the water heater load for the purpose of regulation. A dual-element electric water heater model is developed, which accounts for both thermal dynamics and users’ water consumptions. A realistic regulation signal was used to evaluate the number of water heaters needed and the operational characteristics of a water heater when providing 2-MW regulation service. Modeling results suggest that approximately 33,333 water heaters are needed to provide a 2-MW regulation service 24 hours a day. However, if water heaters only provide regulation from 6:00 to 24:00, approximately 20,000 will be needed. Because the control algorithm has considered the thermal setting of the water heater, the customer comfort is obstructed little. Therefore, the aggregated regulation service provided by water heater loads can become a major source of revenue for load-service entities when the smart grid enables the direct load control.
This article presents a real-time greedy-index dispatching policy (GIDP) for using plug-in electric vehicles (PEVs) to provide frequency regulation services. A new service cost allocation mechanism is proposed to award PEVs based on the amount of service they provided, while considering compensations for delayed-charging and reduction of battery lifetime due to participation of the service. The GIDP transforms the optimal dispatch problem from a high-dimensional space into a one-dimensional space while preserving the solution optimality. When solving the transformed problem in real-time, the global optimality of the GIDP solution can be guaranteed by mathematically proved “indexability”. Because the GIDP index can be calculated upon the PEV’s arrival and used for the entire decision making process till its departure, the computational burden is minimized and the complexity of the aggregator dispatch process is significantly reduced. Finally, simulation results are used to evaluate the proposed GIDP, and to demonstrate the potential profitability from providing frequency regulation service by using PEVs.
Demand response (DR) programs serve to reduce the consumption of electricity at times when the supply is scarce and expensive. Consumers or agents with flexible consumption profiles are recruited by an aggregator who manages the DR program. The aggregator calls on a subset of its pool of recruited agents to reduce their electricity use during DR events. Agents are paid for reducing their energy consumption from contractually established baselines. Baselines are counter-factual consumption estimates of the energy an agent would have consumed if they were not participating in the DR program. Baselines are used to determine payments to agents. This creates an incentive for agents to inflate their baselines in order to increase the payments they receive. There are several newsworthy cases of agents gaming their baseline for economic benefit. We propose a novel self-reported baseline mechanism (SRBM) where each agent reports its baseline and marginal utility. These reports are strategic and need not be truthful. Based on the reported information, the aggregator selects or calls on agents with a certain probability to meet the load reduction target. Called agents are paid for observed reductions from their self-reported baselines. Agents who are not called face penalties for consumption shortfalls below their baselines. Under SRBM, we show that truthful reporting of baseline consumption and marginal utility is a dominant strategy. Thus, SRBM eliminates the incentive for agents to inflate baselines. SRBM is assured to meet the load reduction target. To conclude, we show that SRBM is almost optimal in the metric of average cost of DR provision faced by the aggregator.
Each year, more than 20% of electricity generated in the United States is consumed for meeting the thermal demands (e.g., space cooling, space heating, and water heating) in residential and commercial buildings. Integrating thermal energy storage (TES) with building’s HVAC systems has the potential to reshape the electric load profile of the building and mitigate the mismatch between the renewable generation and the demand of buildings. A novel ground source heat pump (GSHP) system integrated with underground thermal energy storage (UTES) has been proposed to level the electric demand of buildings while still satisfying their thermal demands. This study assessed the potential impacts of the proposed system with a bottom-up approach. The impacts on the electricity demand in various electricity markets were quantified. The results show that, within the capacity of the existing electric grids, the maximum penetration rate of the proposed system in different wholesale markets could range from 51% to 100%. Altogether, about 46 million single-family detached houses can be retrofitted into the proposed system without increasing the annual peak demand of the corresponding markets. By implementing the proposed system at its maximum penetration rate, the grid-level summer peak demand can be reduced by 9.1% to 18.2%. Meanwhile, at the grid level, the annual electricity consumption would change by –12% to 2%. The nationwide total electricity consumption would be reduced by 9%.
Rising global temperatures and increasing energy demands pose significant challenges for energy management, particularly in institutional and commercial settings. As cooling needs grow, campuses must balance operational efficiency, cost control, and grid stability. Energy storage solutions, such as thermal energy storage (TES) systems, offer a promising approach to shifting energy consumption from peak to off-peak periods, alleviating peak demand, reducing utility costs, and enhancing grid resilience. When integrated with existing battery energy storage systems (BESS), TES can further optimize load management and improve energy savings, especially in buildings with diverse energy needs. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills, which already operates a BESS. We assess three TES sizing strategies—full storage, load leveling, and peak demand limiting—by modeling and simulations based on historical energy loads. Our findings show that we can control TES systems to complement BESS operation, with campus-level load leveling providing the greatest cost savings by reducing peak demands. Furthermore, the study also evaluates the long-term economic viability of TES, considering installation costs, energy savings, and payback periods under varying tariffs. This research offers practical guidance for institutions seeking to enhance energy resilience and reduce operational costs through energy storage solutions.
Although radiative cooling research is widely found in the literature, no comprehensive study has yet been conducted on the impact of novel radiant cooling (>0.91 reflectance) on the energy efficiency of warehouses. Here, in this work, we develop three building models based on a Department of Energy prototype warehouse model using trnsys, representing a typical warehouse with a black roof, a typical warehouse with a white roof, and a warehouse with novel radiative cooling (RC) paint on its roof. These models are run for 15 different cities, each representative of a different ASHRAE climate zone, to better understand the impact of RC in many different climates. It was found that an RC-coated roof in a warehouse could reduce the building's annual heating, ventilation, and air conditioning (HVAC) loads by up to 14.11 kWh/m 2 of the roof area compared to a black roof, resulting in a maximum reduction in energy costs of 0.55 $\$$/m 2 or $\$$2646/year for a large 4835 m 2 warehouse. Similarly, replacing the typical white roof coating with an RC coating could reduce the warehouse's energy consumption by up to 8.17 kWh/ m 2 of roof area, thus reducing energy costs by as much as 0.29 $\$$/m 2 or $\$$1386/year for a 4835 m 2 warehouse. In addition, applying RC paint to an unconditioned warehouse could reduce the building's ASHRAE Standard 55 indoor temperature exceedance by up to 1330 h/year compared to a black roof and up to 532 h/year compared to a white roof.
Integration of renewable resources to meet growing energy demand is becoming a global priority under decarbonization mandates. This study contributes to ongoing efforts on this key subject by assessing the feasibility of using coastal-urban renewable energy resources, namely, offshore wind and rooftop photovoltaic systems, to meet electricity demand of New York City during the intense recent heat wave period of June 2025. A unified modeling framework, based on the urbanized weather research and forecasting model, is used to simulate climate, renewable resources, and energy demand variables. Findings show significant energy load mismatch of approximately 1150 GWh over the month, between the demand and the combined renewable generation outcome. Three storage integration scenarios are analyzed to mitigate the deficits, reducing said deficits by a minimum of approximately 9% over the duration of the month. This study provides a transferable modeling framework tool for evaluating renewable integration in dense urban environments that can be used by grid operators to support grid resilience during extreme heat events.
The anticipated increase in variable generation in the Western Interconnection (WI) over the next several years has raised concerns about how to maintain system balance, especially in smaller Balancing Areas (BAs). Given renewable portfolio standards in the West, it is possible that more than 50 gigawatts (GW) of wind capacity will be installed by 2020. Significant quantities of solar generationare likely to be added as well. The consequent increase in variability and uncertainty that must be managed by the conventional generation fleet and responsive load make it attractive to consider ways in which Balancing Area Authorities (BAAs) can pool their variability and response resources, thus taking advantage of geographic and temporal diversity to increase overall operational efficiency.Our analysis considers several alternative forms of an Energy Imbalance Market (EIM) that have been proposed in the non-market areas of the WI. The proposed EIM includes two changes in operating practices that independently reduce variability and increase access to responsive resources: BAA cooperation and sub-hourly dispatch. As proposed, the EIM does not consider any form of coordinated unitcommitment; however, over time it is possible that BAAs would develop formal or informal coordination plans. This report examines the benefits of several possible EIM implementations, both separately and in concert.
The Colorado Better Buildings project intended to bring new and existing energy efficiency model programs to market with regional collaboration and funding partnerships. The goals for Boulder County and its program partners were to advance energy efficiency investments, stimulate economic growth in Colorado and advance the state’s energy independence. Collectively, three counties set out to complete 9,025 energy efficiency upgrades in 2.5 years and they succeeded in doing so. Energy efficiency upgrades have been completed in more than 11,000 homes and businesses in these communities. Boulder County and its partners received a $25 million BetterBuildings grant from the U.S. Department of Energy under the American Recovery and Reinvestment Act in the summer of 2010. This was also known as the Energy Efficiency and Conservation Block Grants program. With this funding, Boulder County, the City and County of Denver, and Garfield County set out to design programs for the residential and commercial sectors to overcome key barriers in the energy upgrade process. Since January 2011, these communities have paired homeowners and business owners with an Energy Advisor – an expert to help move from assessment to upgrade with minimal hassle. Pairing this step-by-step assistance with financing incentives has effectively addressed many key barriers, resulting in energy efficiency improvements and happy customers. An expert energy advisor guides the building owner through every step of the process, coordinating the energy assessment, interpreting results for a customized action plan, providing a list of contractors, and finding and applying for all available rebates and low-interest loans. In addition to the expert advising and financial incentives, the programs also included elements of social marketing, technical assistance, workforce development and contractor trainings, project monitoring and verification, and a cloud-based customer data system to coordinate among field advisors and across local governments and local service vendors. A portion of the BetterBuildings grant went to the Metro Mayors Caucus (MMC) who worked in partnership with the Denver Regional Council of Governments (DRCOG) to conduct a series of 10 energy efficiency workshops for local government officials and other interested parties. The workshops helped showcase lessons learned on energy efficiency and helped guide other local governments in the establishment of similar programs. The workshops covered a wide range of energy efficiency and renewable energy topics such as clean energy finance, social mobilization and communications, specific case studies of Colorado towns, energy efficiency codes, net zero buildings and solar power. Since the programs launched in January 2011, these communities have collectively spurred economic investments in energy efficiency, achieved greater than 5:1 leveraging of grant funds, saved energy and reduced greenhouse gas emissions, provided trainings for a robust local energy contractor network, and proved out viable and replicable program models that local utilities and other communities are adopting, with long lasting market transformation.
This paper is intended to help inform future technology deployment opportunities for connected thermostats (CTs), based on investigation and review of the U.S. residential housing and CT markets, as well as existing, emerging, and future use cases for CT hardware and CT-generated data. The CT market has experienced tremendous growth over the last five years — both in terms of the number of units sold and the number of firms offering competing products — and can be characterized by its rapid pace of technological innovation. Despite many assuming CTs would become powerful tools for increasing comfort while saving energy, there remains a great deal of uncertainty about the actual energy and cost savings that are likely to be realized from deployment of CTs, particularly under different conditions.
This report is one in a series of Electrification Futures Study (EFS) publications. The EFS is a multiyear research project to explore potential widespread electrification in the future energy system of the United States. Electrification is defined as the substitution of electricity for direct combustion of non-electricity-based fuels used to provide similar services. The EFS is specifically designed to examine electric technology advancement and adoption for end uses in the major economic sectors of the United States, electricity consumption growth and load profiles, future power system infrastructure development and operations, and economic and environmental implications of electrification. Because of the expansive scope and the multiyear duration of the study, research findings and supporting data will be published as a series of reports, with each report being released on its own time frame.
This slide deck summarizes a project in which NREL is providing support to the Louisville Metro Government regarding efforts to achieve a 100% renewable electricity goal for municipal operations.
The South Texas Industrial Assessment Center (ST-IAC) provides small to mid-size manufacturing companies and water treatment plants in the Rio Grande Valley of Texas, free energy assessments to help them reduce costs and stay competitive for sustainable development. The ST-IAC operates within the University of Texas Rio Grande Valley (UTRGV), and is the largest Hispanic-serving IAC in the U.S. Created in 2016, the ST-IAC, situated in the most economically disadvantaged region in the country, has been successful in training students and assessing local industries served by a predominantly Hispanic population. UTRGV, now the second largest Hispanic Serving Institution (HSI) of higher education in the U.S., has a student population of 32,000, of which 90% is Hispanic. While Covid-19 had a negative impact to our program during Budget Periods (BP) 4 and 5, the center still managed to provide opportunities for individuals, manufacturing and water industries in the local region. The program developed an energy engineering program in the region and further advanced national priorities. Those include resilience and sustainability of operations by implementing energy efficiency processes, renewable energy sources, decarbonization, battery storage, and cybersecurity in south Texas.
End-use load profiles (EULP), which quantify how and when energy is used, are critically important to utilities, public utility commissions, state energy offices, and other stakeholders. Applications of EULPs focus on understanding how efficiency, demand response, and other distributed energy resources are valued and used in R&D prioritization, utility resource and distribution system planning, and state and local energy planning and regulations. Consequently, high-quality EULPs are critical for widespread adoption of electrification, demand flexibility, and grid-interactive efficient buildings. For example, EULPs can be used to forecast energy savings in buildings or to identify energy using activities that can be shifted to different times of the day.