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At least 37 records · Page 2

Impacts of High Variable Renewable Energy Futures on Electric-Sector Decision Making: Demand-Side Effects

Previous work by the Berkeley Lab describes how high shares of variable renewable energy (VRE) such as wind and solar power could change wholesale electricity price dynamics. These include the timing of when electricity is cheap or expensive, locational differences in the cost of electricity, and the degree of regularity or predictability in those costs. Many decentralized decision-makers on the demand-side may not yet have considered the implications of these possible future changes. In this report, we evaluate the sensitivity of a set of demand-side decisions to different levels of VRE penetration ranging from a low of 5-20% to a high of 40-50%. The analysis builds on hourly wholesale energy and capacity prices in different VRE scenarios for four wholesale markets in the United States for the year 2030 (CAISO, ERCOT, NYISO, and SPP). The principal question for this exploration is whether private and public electric-sector decisions that are made based on assumptions reflecting low VRE levels still achieve their intended objective in a high VRE scenario with 40-50% wind and solar? This scoping report evaluates the impacts of changing patterns of peak system needs on the benefits of demand reductions by examining the altered value of different energy efficiency (EE) measures. Similarly, we investigate new opportunities for large energy consumers that may arise from periods with very low wholesale electricity prices. We calculate the value of new process investments (e.g., hydrogen production and other generalized electro-commodities), showcase the varying value of new product storage investments (such as reservoir extensions at a desalination plant), and estimate the benefits of increased process flexibility that uses electricity as a process-input in addition to traditional fossil fuels (e.g., district energy systems). Finally, many decentralized decision-makers and end-use customers are not directly exposed to wholesale electricity prices but instead receive price signals from their retail electricity rates. As wind and solar shares increase, we compare the economic efficiency of flat retail rates relative to more dynamic time-of-use tariffs with and without critical peak-pricing events.

14 SOLAR ENERGY↗

Wide-area Demand-side Control for Inter-area Oscillation Mitigation in Power Systems

Inter-area oscillations have severely limited maximum power transfer among different areas in large-scale interconnected power grid. If not quickly damped as soon as possible, they may cause system breakup and even lead to large cascading blackouts. To increase the damping of inter-area oscillations, both power system stabilizer~(PSS) and flexible AC transmission system~(FACTS) controller have been widely considered, which affect the real power flow indirectly. However, the effectiveness of these controllers is restricted to the neighborhood of a prescribed set of operating conditions. In this paper, wide-area demand-side control is developed to directly modulate the real power of end-user loads for oscillation mitigation. The proposed control strategy is implemented in a hierarchical manner. At the device layer, individual end-user loads independently turn ON or OFF in response to the broadcasted signals from the coordinator during the real time. At the supervisory layer, autonomous responses of end-user loads are coordinated to ensure the desired power modulation. The effectiveness of the proposed wide-area demand-side control in improving small-signal stability is illustrated by simulations on a large-scale test system.

Lian, Jianming↗

Electrification Futures Study: Scenarios for Demand-Side Adoption in the United States

Electrification - the potential for increased electricity demand due to new services and the shift from any non-electric source of energy to electricity at the point of final consumption - is a major emerging trend in energy markets around the world. Select driving forces for this trend are a collection of newly-improved electric end-use technologies, engaged consumers and manufacturers, and a variety of economic and policy objectives in different jurisdictions. NREL and partners are conducting a multi-year study of electrification scenarios, which will explore research questions related to the potential key technologies for, planning requirements for, and impacts of deep electrification of the U.S. economy. NREL recently published a report that presents scenarios with various degrees of future electrification in all major end-use sectors of the U.S. energy system, and quantifies impacts on the amount and shape of national and regional electricity demand. In addition, ongoing analysis is exploring how the U.S. electricity system could need to transform to meet changes in demand from an electrified economy, the potential role of demand-side flexibility in supporting reliable operations of a clean electricity grid, and the potential costs, benefits, and impacts of mass electrification. This talk will serve to frame some of the overall boundaries of the session and report on electrification levels and impacts under a variety of scenarios.

30 DIRECT ENERGY CONVERSION↗

A tool for assessing demand side management and operating strategies for isolated microgrids

Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Demand-Side Grid (dsgrid) Model

This presentation gives a high-level overview of the recently published demand-side grid (dsgrid) model documentation. The general modeling philosophy and technical approach of dsgrid is described, as is an initial data set covering 2012 contiguous United States (CONUS) electricity demand. The initial data set describes about 80% of electrical load at an hourly level by county, subsector and end use. Coarser models and data sets are used to describe the remainder. Model residuals are calculated at different levels of aggregation by leveraging historical electricity sector data and a model of 2012 distributed generation. Overall, the dsgrid model has been developed to support analysis of future load scenarios, including interactive effects between energy efficiency, electrification, demand response, renewable energy, battery energy (or other forms of) storage, and future grid conditions broadly construed. Planned future work includes the development of future load scenarios and physically realistic estimates of the flexible load resource.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electrification Futures Study: Operational Analysis of U.S. Power Systems with Increased Electrification and Demand-Side Flexibility

This report provides a high-resolution U.S. national-scale power systems assessment of scenarios with widespread electrification using detailed grid simulations. We find that high electrification scenarios envisioned in the Electrification Futures Study can be operated at the hourly level to meet future increased levels of electrified demand and, under the most aggressive cases, with up to 66% of generation from wind and solar technologies. The analysis also examines the value of flexibility from demand by supporting system operability under high electrification and high renewable systems. Demand-side flexibility—especially flexibility from newly electrified loads—is found to enhance the operational efficiency by reducing VRE curtailment and increasing utilization of generators with lower operating costs. It can also enhance the ability of electrification to decarbonize the energy sector.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-Driven Pricing Strategy for Demand-Side Resource Aggregators

We consider a utility who seeks to coordinate the energy consumption of multiple demand-side flexible resource aggregators. For the purpose of privacy protection, the utility has no access to the detailed information of loads of resource aggregators. Instead, we assume that the utility can directly observe each aggregator's aggregate energy consumption outcomes. Furthermore, the utility can leverage resource aggregator energy consumption via time-varying electricity price profiles. Based on inverse optimization technique, we propose an estimation method for the utility to infer the energy requirement information of aggregators. Subsequently, we design a data-driven pricing scheme to help the utility achieve system-level control objectives (e.g., minimizing peak demand) by combining hybrid particle swarm optimizer with mutation algorithm and an iterative algorithm. Case studies have demonstrated the effectiveness of the proposed approach against two benchmark pricing strategies-a flat-rate scheme and a time-of-use scheme.

data-driven optimization↗

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Array↗

Coordinating Demand-Side Efficiency Evaluation, Measurement and Verification Among Western States: Options for Documenting Energy and Non-Energy Impacts for the Power Sector

Demand-side energy efficiency (efficiency) represents a low-cost opportunity to reduce electricity consumption and demand and provide a wide range of non-energy benefits, including avoiding air pollution. Efficiency-related energy and non-energy impacts are determined and documented by implementing evaluation, measurement and verification (EM&V) systems. This technical brief describes efficiency EM&V coordination strategies that Western states can consider taking on together, outlines EM&V-related products that might be appropriate for multistate coordination, and identifies some implications of coordination. Coordinating efficiency EM&V activities can save both time and costs for state agencies and stakeholders engaged in efficiency activities and can be particularly beneficial for multiple states served by the same utility. First, the brief summarizes basic information on efficiency, its myriad potential benefits and EM&V for assessing those benefits. Second, the brief introduces the concept of multistate EM&V coordination in the context of assessing such benefits, including achievement of state and federal goals to reduce air pollutants.1 Next, the brief presents three coordination strategy options for efficiency EM&V: information clearinghouse/exchange, EM&V product development, and a regional energy efficiency tracking system platform. The brief then describes five regional EM&V products that could be developed on a multistate basis: EM&V reporting formats, database of consistent deemed electricity savings values, glossary of definitions and concepts, efficiency EM&V methodologies, and EM&V professional standards or accreditation processes. Finally, the brief discusses options for next steps that Western states can take to consider multistate coordination on efficiency EM&V. Appendices provide background information on efficiency and EM&V, as well as definitions and suggested resources on the covered topics. This brief is intended to inform state public utility commissions, boards for public and consumer-owned utilities, state energy offices and air agencies, and other organizations involved in discussions about the use of efficiency EM&V.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hierarchical Power Flow Control in Smart Grids: Enhancing Rotor Angle and Frequency Stability with Demand-Side Flexibility

Large-scale integration of renewables in power systems gives rise to new challenges for keeping synchronization and frequency stability in volatile and uncertain power flow states. To ensure the safety of operation, the system must maintain adequate disturbance rejection capability at the time scales of both rotor angle and system frequency dynamics. This calls for flexibility to be exploited on both the generation and demand sides, compensating volatility and ensuring stability at the two separate time scales. This article proposes a hierarchical power flow control architecture that involves both transmission and distribution networks as well as individual buildings to enhance both small-signal rotor angle stability and frequency stability of the transmission network. The proposed architecture consists of a transmission-level optimizer enhancing system damping ratios, a distribution-level controller following transmission commands and providing frequency support, and a building-level scheduler accounting for quality of service and following the distribution-level targets. Furthermore, we validate the feasibility and performance of the whole control architecture through real-time hardware-in-loop tests involving real-world transmission and distribution network models along with real devices at the Stone Edge Farm Microgrid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Demand-Side Opportunity: The Roles of Distributed Solar and Building Energy Systems in a Decarbonized Grid

Building energy systems represent a significant and largely untapped demand-side grid resource. Buildings use about 75% of electricity in the United States, including around 80% of peak demand, meaning that changes in building energy use have significant implications for grid operations. Building energy technologies-including energy-efficient devices, flexible loads, and energy storage-can be coordinated and aggregated to perform similar functions as centralized grid assets. Recent advances in information and communication (ICT) technologies have significantly improved building energy technology automation, coordination, and aggregation capabilities. With declining costs and technological advances, building energy systems can increasingly compete with conventional grid assets such as natural gas plants. Building energy technologies enable the deployment of distributed solar photovoltaics (DPV). Energy-efficient buildings allow DPV to meet greater shares of building load while flexible loads and energy storage can reshape building load profiles to optimize the on-site use of DPV. Optimized on-site use of DPV increases the value proposition for DPV adoption and can help utilities cost-effectively integrate higher levels of DPV penetration. Together, DPV and building energy technologies could help grids achieve deep decarbonization more quickly and cost-effectively.

14 SOLAR ENERGY↗

Coupling thermal energy storage with a thermally anisotropic building envelope for building demand-side management across various US climate conditions

Here, the thermally anisotropic building envelope (TABE) is a novel active building envelope that enhances energy efficiency and thermal comfort in buildings by transferring heat and cold between building envelopes and hydronic loops. When coupled with thermal energy storage (TES) units, the TABE + TES enables the storage of both heat and cold energy captured by the TABE roof or exterior walls. This stored energy can be later released by the TABE floor for indoor heating and cooling, benefiting both the grid and the end user. This paper evaluates the merits of TABE + TES for building demand-side management across various US climate conditions, focusing on peak load shaving, annual energy savings, and cost savings under time-of-use (TOU) electric rate schedules. Simulations were conducted by integrating time-of-day–informed, rule-based control strategies in MATLAB, TABE components and TES units in COMSOL Multiphysics, and whole-building energy analysis in EnergyPlus. A case study using the US Department of Energy’s prototype single-family detached house model in Birmingham, Alabama; Los Angeles, California; Oak Ridge, Tennessee; and Denver, Colorado, showed that the TABE + TES system achieved (1) 70 % peak load shaving in Los Angeles and Denver and 20 % in Birmingham and Oak Ridge; (2) significant peak electricity savings of 351–497 kWh, reducing peak energy consumption by 38 %–78 %; and (3) annual heating cost savings of 0.79 $\$$/m2–1.17 $\$$/m 2 and cooling cost savings of 0.60 $\$$/m 2 –1.17 $\$$/m 2 using a normal utility rate or low-TOU rate. The benefits of employing the TABE + TES system are even more significant under high TOU rates.

25 ENERGY STORAGE↗

Distributed Coordination of Demand-side Flexible Resources in Microgrid with All-Time Feasibility

The prevalence of distributed renewable generators motivates microgrid operators to exploit demand-side flexible resources (DFRs). Due to their dispersed nature, distributed DFR coordination has been a vibrant research area, while there are several issues awaiting to be addressed. On one hand, DFR power is internally coupled through power flow, while DFR usually cannot access grid information. On the other hand, in time-restricted scenarios, solution feasibility cannot be guaranteed by conventional dual-based algorithms. To fill these gaps, we propose a distributed DFR coordination framework with all-time feasibility. The proposed framework accounts for the distinct access of microgrid entities to grid information. A distributed and all-time feasible algorithm is proposed for optimal DFR coordination, which allows DFRs to make local decisions without violating constraints throughout iterations. The effectiveness of the proposed algorithm is demonstrated through case studies. The impact of peer-to-peer communication links on algorithm convergence is also investigated, which emphasizes the balance between communication investment and algorithm performance.

Li, Hongyi [Iowa State Univ., Ames, IA (United Sta↗

Residential Water Heating Demand Side Management (DSM) - South Africa

The electricity crisis in South Africa has deteriorated significantly, with the country experiencing frequent and prolonged rolling blackouts. These outages have severe economic repercussions, leading to decreased growth and productivity. Demand Side Management (DSM), particularly focusing on electric water heaters due to their significant energy consumption and peak demand contribution, is identified as a key strategy. The study aims to assess opportunities for DSM programs targeting water heating to reduce energy consumption and peak demand. It entails developing a bottom-up simulation model to establish a baseline scenario of water heating electricity load demand in 2023 and 2033, identifying technologies for energy reduction, estimating the impacts of a selected number of measures and providing recommendations to inform policy makers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scenario Evaluation and Regionalization Analysis (SERA) Model: Demand Side and Refueling Infrastructure Buildout

The National Renewable Energy Laboratory's Scenario Evaluation and Regionalization Analysis (SERA) model estimates the number, size, and locations of hydrogen refueling stations that satisfy the fuel demand from fuel cell electric vehicles (FCEVs) and the hydrogen supply requirements to meet such a demand in terms of hydrogen production plants and delivery infrastructure. SERA simulates the systemwide cost-optimal evolution of hydrogen refueling infrastructure, providing insights that reduce the informational and financial risks associated with infrastructure investment decisions and helping accelerate the adoption of FCEVs. This report describes the SERA model's demand-side and refueling infrastructure buildout algorithms, and it also illustrates use of the model for simulating hydrogen refueling stations deployment scenarios using as an example the recent H2USA national hydrogen infrastructure report.

30 DIRECT ENERGY CONVERSION↗

Optimal electric-distribution-grid planning considering the demand-side flexibility of thermal building systems for a test case in Singapore

The planning of district-scale electric grids, i.e., distribution grids, has traditionally relied on finding the most cost-effective design such that they are able to supply the peak loads in a district. With the advent of electric demand side flexibility (DSF), there is the opportunity to reshape peak loads such that the investment cost of the electric grid decreases in exchange for a minor increase in the operation cost. This paper formulates an optimal planning approach for the electric grid at the district scale, which incorporates the DSF from thermal building systems, e.g., heating ventilation and air-conditioning (HVAC) systems. The problem is formulated as a mixed-integer linear program (MILP) and aims at minimizing the investment cost for the grid along with the operation cost of the flexible loads. This is subjected to the fixed electricity demand and thermal comfort constraints of building occupants. To this end, linear models for the thermal comfort in the buildings and the power flow in electric grid are considered. The approach is tested on a district planning test case based in Singapore, where the results show up to 30.9 % reductions in investment cost and up to 3.7 % reduction in total annualized cost. Urban planning authorities, developers and utility companies can all benefit from the presented approach to make optimized investment decisions. For building operators, the results point to the need of adopting their control systems for DSF.

Troitzsch, Sebastian↗

Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)

This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api and through PyPI (pip install NREL-dsgrid-legacy-efs-api). The data format is HDF5. The API is written in Python. This initial dsgrid data set, whose description was originally published in 2018, covers electricity demand in the contiguous United States (CONUS) for the historical year of 2012. It is a proof-of-concept demonstrating the feasibility of reconciling bottom-up demand modeling results with top-down information about electricity demand to create a more detailed description than is possible with either type of data source on its own. The result is demand data that is more highly resolved along geographic, temporal, sectoral, and end-use dimensions as may be helpful for conducting electricity sector-wide "what-if" analysis of, e.g., energy efficiency, electrification, and/or demand flexibility. Although we conducted bottom-up versus top-down validation, the final residuals were significant, especially at higher geographic and temporal resolution. Please see the Executive Summary and/or Section 3 of the report to obtain an understanding of the data set limitations before deciding whether these data are suitable for any particular use case. New dsgrid datasets are under development. Please visit https://www.nrel.gov/analysis/dsgrid.html for the latest information which is also linked in the data resources.

analysis↗