Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “demand side”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5

Bundling measures for food systems transformation: a global, multimodel assessment

Background Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models. Methods In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT–Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously. Findings Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO 2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices). Interpretation This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.

Sundiang, Marina [Cornell Univ., Ithaca, NY (Unite↗

Optimal Demand Response Incorporating Distribution LMP with PV Generation Uncertainty

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multiperiod bilevel optimization problem to find the ODR strategy. Here, the objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Energy Efficiency Under Alternative Carbon Policies. Incentives, Measurement, and Interregional Effects

In this report, we examine and compare how tradable mass-based polices and tradable rate-based policies create different incentives for energy efficiency investments. Through a generalized demonstration and set of examples, we show that as a result of the output subsidy they create, traditional rate-based policies, those that do not credit energy savings from efficiency measures, reduce the incentive for investment in energy efficiency measures relative to an optimally designed mass-based policy or equivalent carbon tax. We then show that this reduced incentive can be partially addressed by modifying the rate-based policy such that electricity savings from energy efficiency measures are treated as a source of zero-carbon generation within the framework of the standard, or equivalently, by assigning avoided emissions credit to the electricity savings at the rate of the intensity target. These approaches result in an extension of the output subsidy to efficiency measures and eliminate the distortion between supply-side and demand-side options for GHG emissions reduction. However, these approaches do not address electricity price distortions resulting from the output subsidy that also impact the value of efficiency measures. Next, we assess alternative approaches for crediting energy efficiency savings within the framework of a rate-based policy. Finally, we identify a number of challenges that arise in implementing a rate-based policy with efficiency crediting, including the requirement to develop robust estimates of electricity savings in order to assess compliance, and the requirement to track the regionality of the generation impacts of efficiency measures to account for their interstate effects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy savings modelling of re-tuning energy conservation measures in large office buildings

Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS’s capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This paper investigates the energy savings potential of several common HVAC system re-tuning measures on a typical large office building, using the Department of Energy’s building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply-air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated – each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All the individual measures and combinations were simulated in 16 climate locations representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual total HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy savings for most cities for all measures). Combining many of the re-tuning measures revealed deep savings potential. Some of the more aggressive combinations revealed 35-75% reductions in annual HVAC energy consumption, depending on climate and building vintage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Adaptive Transmission Planning: Implementing a New Paradigm for Managing Economic Risks in Grid Expansion

The problem of whether, where, when, and what type of transmission facilities to build in terms of minimizing costs and maximizing net economic benefits has been a challenge for the power industry from the beginning-ever since Thomas Edison debated whether to create longer dc distribution lines (with their high losses) or build new power stations in expanding his urban markets. Today's planning decisions are far more complex, as grids cover the continent and new transmission, generation, and demand-side technologies are emerging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrification Futures Study: Power Systems Operation with Newly Electrified and Flexible Loads

The Electrification Futures Study (EFS) is a multi-year study designed to analyze the impacts of widespread electrification in the U.S. energy system. In this webinar we present the detailed power systems operational analysis from the final report in the EFS series. For this analysis, we simulate multiple 2050 power systems for the conterminous United States to assess how variations in the magnitude and shape of electricity demand driven by electrification, and the extent of load participation to more-actively provide grid services, might impact the hourly operation, operational costs, and emissions of various power systems in 2050. The impacts of electrification and demand flexibility are overlayed across systems with significantly greater penetrations of variable renewable energy than today. Overall, we find that the high electrification scenarios envisioned in the EFS with significant VRE penetration (66% of annual national generation) can be operated to meet future increased levels of electrified demand. We also find that demand-side flexibility can enhance operational efficiency and reduce overall annual production costs by $5-$10 billion. The complementary relationship between flexible electric vehicle charging loads and solar generation is particularly pronounced, but in the absence of demand-side flexibility electrification can lead to increased wind and solar curtailment. By helping to reduce renewable curtailment, flexibility can also reduce power sector CO2 emissions. The analysis highlights the value of increased integration and coordination of demand- and supply-side resources in future electric system planning and operations—particularly under high electrification futures.

43 PARTICLE ACCELERATORS↗

Evaluating Demand Response Impacts on Capacity Credit of Renewable Distributed Generation in Smart Distribution Systems

Environmental concerns and depletion of traditional energy lead to the booming development of renewable distributed generation (RDG) in the past decade. However, due to intermittent nature of renewable energy sources, to what extent RDG could provide capacity to power systems becomes a critical issue to the utility company when implementing long-term system strategic (generation expansion) planning. On the other hand, in a smart-grid frame, the popularization of different varieties of demand-side resources enables the system to operate at more flexible modes ever before. The potential variability in load demand not only introduces additional dynamics and uncertainties to the system, but could also affect the reliability benefits of RDG. Therefore, in practice, to effectively estimate the reliability value of RDG in power systems, the potential interaction between generation- and demand-side must be properly captured. In this paper, a study to assess the capacity credit (CC) of RDG in a context of distributed generation system is performed with consideration of the impacts of demand response (DR). A compound reliability model for DR is presented, which considers the uncertainties involved in both instant response and follow-on load recovery processes. On this basis, an assessment framework for the CC of RDG based on sequential Monte Carlo simulation is developed by which the inter-temporal characteristics of DR resources can be fully captured. The numerical study is implemented based on the IEEE-38 bus test case. The calculation results demonstrate that the CC of RDG would depend on a variety of factors, including penetration level, responsiveness of load demand and the correlations between RDG and DR availability. Also, it is shown that accounting for the underlying effect of DR is of absolute importance, otherwise the CC of RDG might be estimated erroneously in real practices.

capacity credit↗

Potential Roles For Demand Response in More-Electrified Futures

Power systems, both supply- and demand-side, are rapidly evolving due to technological change and various policy goals. This talk will describe potential roles for demand response in future power systems serving more electrified loads (including transport) and with higher shares of variable renewable generation. Starting from a broad definition of demand response as any change imposed on demand-side end-use operations meant to support power grid functionalities, we draw on a number of past and ongoing research topics to provide insight into the value of different kinds of demand response in different kinds of power systems.

demand response↗

AC Power Flow Based DLMP Calculation and Decomposition Method to Smooth Power Fluctuation of Distributed Renewable Energy Sources

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

AC optimal power flow↗

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗

Customer enrollment and participation in building demand management programs: A review of key factors

Increasing the efficiency and flexibility of electricity demand is necessary for ensuring a cost-effective and reliable transition to zero-carbon electricity systems. Such demand-side management (DSM) resources have been procured by utilities for decades via energy efficiency and demand response programs; however, the key drivers of program enrollment and customer participation levels remain poorly understood — even as governments and grid planners seek to scale up the deployment of DSM assets to meet climate targets. Here we systematically review the evidence on multiple factors that may influence customer enrollment and participation in building DSM programs, focusing primarily on residential and commercial buildings. We examine the contexts in which relationships between DSM factors and outcomes are most often explored and with which methods; we also score the strength, direction, and internal consistency of each factor's reported impact on the enrollment and participation outcomes. We find that studies most commonly assess the effects of economic incentives for load flexibility on program participation levels, often using simulation-based methods in lieu of measured data. Few studies focus on program enrollment outcomes or regulatory drivers of either enrollment or participation, and gaps are also evident in the coverage of emerging DSM opportunities like load electrification. Removal of structural barriers (e.g., the lack of controls infrastructure) and the use of third party services (e.g., load aggregators) are the factors with the largest positive impacts on DSM outcomes, but no single factor emerges as clearly most impactful. For a given factor, the range of reported impacts typically varies widely across the relevant studies reviewed. Our findings provide a snapshot of the state of knowledge about building DSM and customer decision-making, and they expose key gaps in understanding that must be filled if building DSM is to expand as a critical resource for operating clean power grids.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Intelligent Energy Optimizer for Residential Buildings

Demand-side management in the buildings is essential for meeting grid flexibility needs in a highly renewable energy scenario. Appliance load monitoring helps decision making for demand-side management by providing the information on operation status/power consumption from different appliances in the buildings. Nonintrusive load monitoring (NILM) is an attractive option for appliance load monitoring using because it has lower cost for sensors and helps mitigate privacy concerns. In this study, the team used an event detection technique followed by two different methods for event classification. The results from k-means clustering showed that the events from a single appliance are often distributed in multiple clusters. Thus, the unsupervised method of NILM using k-means clustering used in this study was not very suitable for load disaggregation. The results from NILM showed that the F1 score for event classification was 0.77 for a heat pump water heater and very low for other appliances using the rule-based classification.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Techno-economic analysis of the impact of dynamic electricity prices on solar penetration in a smart grid environment with distributed energy storage

This study investigates the technical and economic feasibility of using high levels of solar energy penetration up to 400 MW into a smart grid system of 60,000 smart houses. A novel non-cooperative Stackelberg game is introduced that incorporates the profitability of the supply-side and helps in solving problems related to overgeneration and photovoltaic curtailment. The non-cooperative game is intended to find the optimal dynamic prices that would leverage distributed storage through the demand-side to stabilize the power grid operation. Ten cases are studied with five photovoltaic plant sizes and two battery designs. Here, a novel quantitative analysis of high levels of solar penetration as a percentage of the total electricity demand is introduced to evaluate the technical feasibility of the studied cases. To evaluate the economic viability of the proposed smart grid system, four metrics were used: the levelized cost of energy, the levelized cost of storage, the payback period, and the net present value. Two out of ten studied cases were concluded to be the most promising cases, one with a solar photovoltaic plant size of 200 MW and the other with 300 MW. The case with 300 MW solar plant is preferred as it paves the way for more solar energy deployment with a solar penetration percentage up to 67.78%. This case had a payback period of 10.72 years and a net present value of $\$51.44$ M for the solar plant and a payback period of 12.06 years and a net present value of $\$40.75$ M for the demand-side.

14 SOLAR ENERGY↗

Integrating Demand Response and Distributed Resources in Planning for Large-scale Renewable Energy Integration

The electricity grid is transitioning from a centralized and uncoordinated set of large generators and loads to a framework that also includes decentralized and coordinated "distributed energy resources" (DER). Advances in renewable generation, energy storage, efficiency, and controls technology present a significant opportunity for demand-side investment that is matched to the needs of the future grid infrastructure and operations, but the complex interplay of controls technology and grid operations makes estimating and realizing the potential of DER a significant challenge. Supply curves for conserved energy have long been used to synthesize energy efficiency opportunities for electricity system planners and show how demand side resources compete with building new power plants. We have developed a similar approach for supporting policymakers who now face a range of technology options for DER, with a focus on describing the potential for demand response (DR) to provide flexibility to the grid. We describe our modeling approach using supply curves for demand response across four key dimensions: reshaping with rates, shedding at critical time, shifting to capture renewables, and fast-response "shimmy" to balance the grid. In a California-focused study, we find a significant potential for DR to support the grid, and a need for integration between DR and energy efficiency. The combined efficiency benefits from a better-controlled and commissioned facility can lead to significant reductions in the cost of DR, increasing the quantity that is cost competitive by 5-200%. The benefit stream from DR can alternatively be framed to "buy down" the cost of EE investment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SunDial – An Integrated SHINES System to Enable High-penetration Feeder-level PV

The Project Team of Fraunhofer USA, National Grid, and IPKeys developed and conducted a pilot deployment of the SunDial system, a virtual power plant platform that enables high-penetrations of solar PV to be integrated into the distribution grid. The pilot was conducted over a 15-month period from August 2018 through October 2019 on a National Grid distribution feeder in Shirley, MA. A vendor-agnostic control platform (the “Global Scheduler”) optimally shaped the net load for a virtual portfolio of non-co-located DERs based on user-defined policy objectives. The goal of the SunDial project was to simplify and reduce the risk associated with the deployment of solar in high-penetration environments by: (1) Developing an open-source, vendor-agnostic dispatch platform that can be readily adapted to optimize control of DERs over a variety of use cases; (2) Developing auto-calibrating load and solar prediction methodologies that can be readily implemented and scaled to new deployments; (3) Developing a methodology to use demand-side management with traditional electrochemical energy storage to provide “load shaping” services in high solar penetration environments; (4) Using grid-scale storage to minimize short-term intermittency association with PV production; and (5) Deploying on the National Grid distribution system to gain experience on the potential for (and limits of) integrated storage with demand-side management.

14 SOLAR ENERGY↗

Scaling Demand Flexibility: Building on 30 Years of Energy Efficiency Success

With electricity consumption across the United States (US) and Canada anticipated to grow, energy efficiency program administrators have a key role to play in helping to ensure energy affordability and reliability in support of the broader economic systems utilities and grid support. Connected, demand side load balancing solutions, such as load shifting heating, ventilation and air conditioning (HVAC) systems and managed charging for electric vehicles (EVs), can dynamically manage energy, allowing for more volumetric electricity consumption without incurring the expense of upgraded transmission and distribution capabilities. When combined, or aggregated, many small loads can be managed to have meaningful impact on energy demand on the grid. Utilities and their partners have an opportunity to leverage decades of experience and the infrastructure needed to assess, design, implement, and measure programs to scale up the adoption of equipment with built-in load flexibility capabilities. Current efforts among a wide variety of electricity system service providers, utilities, standards agencies, regulators, national labs and private industry stakeholders aim to identify common standards, metrics, and methodologies for valuing grid services offered by demand side equipment. By combining those efforts with decades of proven energy efficiency resources, utilities are poised to effectuate a scaling up of equipment with energy management capabilities installed in homes and businesses across the US and Canada. This paper will provide an overview of how utilities are approaching this era of load growth and new peak demands across the United States and Canada. It will highlight the specific strategies that program administrators are employing to advance market transformation for grid-enabled products and devices that have the greatest potential to reduce energy use and increase load flexibility.

Grant, Peter↗

Estimating customer electricity savings from projects installed by the U.S. ESCO industry

The U.S. energy service company (ESCO) industry has a well-established track record of delivering substantial energy and dollar savings in the public and institutional facilities sector, typically through the use of energy savings performance contracts (ESPC) (Larsen et al. 2012; Goldman et al. 2005; Hopper et al. 2005, Stuart et al. 2013). This ~$6.4 billion industry, which is expected to grow significantly over the next five years, may play an important role in achieving demand-side energy efficiency under local/state/federal environmental policy goals. To date, there has been little or no research in the public domain to estimate electricity savings for the entire U.S. ESCO industry. Estimating these savings levels is a foundational step in order to determine total avoided greenhouse gas (GHG) emissions from demand-side energy efficiency measures installed by U.S. ESCOs. We introduce a method to estimate the total amount of electricity saved by projects implemented by the U.S. ESCO industry using the Lawrence Berkeley National Laboratory (LBNL) /National Association of Energy Service Companies (NAESCO) database of projects and LBNL’s biennial industry survey. We report two metrics: incremental electricity savings and savings from ESCO projects that are active in a given year (e.g., 2012). Overall, we estimate that in 2012 active U.S. ESCO industry projects generated about 34 TWh of electricity savings—15 TWh of these electricity savings were for MUSH market customers who did not rely on utility customer-funded energy efficiency programs (see Figure 1). This analysis shows that almost two-thirds of 2012 electricity savings in municipal, local and state government facilities, universities/colleges, K-12 schools, and healthcare facilities (i.e., the so-called “MUSH” market) were not supported by a utility customer-funded energy efficiency program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗