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At least 307 records · Page 17

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impact of Generator Flexibility on Electric System Costs and Integration of Renewable Energy

Flexibility of traditional generators plays an important role in accommodating the increased variability and uncertainty of wind and solar on the electric power system. Increased flexibility can be achieved with changes to operational practices or upgrades to existing generation. One challenge is in understanding the value of increasing flexibility, and how this value may change given higher levels of variable generation. This study uses a commercial production cost model to measure the impact of generator flexibility on the integration of wind and solar generators. We use a system that is based on two balancing areas in the Western United States with a range of wind and solar penetrations between 15% and 60%, where instantaneous penetration of wind and solar is limited to 80%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to the development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Megawatt-Scale Power-Hardware-in-the-Loop Interface for Testing Ancillary Grid Services by Converter-Coupled Generation: Preprint

Power-hardware-in-the-loop (PHIL) is a simulation tool that can support electrical systems engineers in the development and experimental validation of novel, advanced control schemes that ensure the robustness and resiliency of electrical grids that have high penetrations of low-inertia variable renewable resources. With PHIL, the impact of the device under test on a generation or distribution system can be analyzed using a real-time simulator (RTS). PHIL allows for the interconnection of the RTS with a 7 megavolt ampere (MVA) power amplifier to test multi-megawatt renewable assets available at the National Wind Technology Center (NWTC). This paper addresses issues related to the development of a PHIL interface that allows testing hardware devices at actual scale. In particular, the novel PHIL interface algorithm and high-speed digital interface, which minimize the critical loop delay, are discussed.

17 WIND ENERGY↗

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Examination of Potential Benefits of an Energy Imbalance Market in the Western Interconnection

In the Western Interconnection, there is significant interest in improving approaches to wide-area coordinated operations of the bulk electric power system, in part because of the increasing penetration of variable generation. One proposed solution is an energy imbalance market. This study focused on that approach alone, with the goal of identifying the potential benefits of an energy imbalance market in the year 2020.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Benefit Analysis of Long-Duration Energy Storage in Power Systems with High Renewable Energy Shares

The integration of high shares of variable renewable energy raises challenges for the reliability and cost-effectiveness of power systems. The value of long-duration energy storage, which helps address variability in renewable energy supply across days and seasons, is poised to grow significantly as power systems shift to larger shares of variable generation such as wind and solar. This study explores the system-level services and associated benefits of long-duration energy storage on the 2050 Western Interconnection (WI). The operation of the future WI system with 85% renewable penetration is simulated using a two-stage production cost model. The impact of long duration energy storage on systemwide operations is examined for the 2050 WI system, using a range of round-trip efficiencies corresponding to four different energy storage technologies. The analysis projects the energy storage dispatch profile, system-wide production cost savings (from both diurnal and seasonal operation), and impacts on generation mix, and change in renewable generation curtailment.

25 ENERGY STORAGE↗

Beyond Price Taker: Conceptual Design and Optimization of Integrated Energy Systems Using Machine Learning Market Surrogates

Future electricity generation systems must be optimized to provide flexibility that counteracts the variability of non-dispatchable renewable energy sources and ensures the reliability and safety of critical infrastructure, including the electric grid. The current state-of-the-art is to co-optimize the design and operation of integrated energy systems (IES) treating historical or predicted time-series electricity prices as fixed parameters. Recent literature has shown the limitations of this price taker assumption, which neglects how IES optimization decisions influence market outcomes. As such, this paper proposes a new optimization formulation that uses machine learning surrogate models, trained from a library of annual market operation simulations, to embed IES market interactions into the co-optimization problem directly. Using a thermal generator example built in the open-source IDAES computational environment, we show that the price taker approach routinely over-predicts annual revenues by 8% or more compared to a validation simulation, where the proposed approach has a typical relative error of 1% or less.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Alternative Energy Carriers: Unique Interfaces for Electrochemical Hydrogenic Transformations

Abstract The shift toward renewable energy generation sources, characterized by their non‐carbon emitting but variable nature, has spurred significant innovation in energy storage technologies. Advancements in foundational understanding from investments in basic science and clever engineering solutions, coupled with increasing industrial adoption, have resulted in a notable reduction in the cost of storing electricity from variable energy generation sources. These developments have paved the way for the exploration of new and innovative forms of energy storage that deviate from traditional technologies. In this perspective, it is posited that the progress made in energy storage research over recent years has opened the door to the development of energy carriers for technologies that are yet to be realized. To illustrate this concept, examples of alternative energy carriers are provided within the context of unique electrochemical interfaces for electrochemical hydrogenic transformations. The unique properties of these interfaces and electrochemical systems can be leveraged in ways not yet imagined, creating new possibilities for energy storage. A perspective on the progress and challenges for each interface as well as a general outlook for the advancement of energy carrier systems are provided.

25 ENERGY STORAGE↗

Burden on hydropower units for short-term balancing of renewable power systems

There is a general need to change hydropower operational regimes to balance the growing contribution of variable renewable energy sources in power systems. Quantifying the burden on generation equipment is increasingly uncertain and difficult. Here, we propose a framework combining technical and economic indicators to analyze primary frequency control (PFC) on a timescale of seconds. We develop a model integrating hydraulic, mechanical, and electrical subsystems to characterize efficiency loss, wear and fatigue, regulation mileage, and frequency quality. We evaluate burden relief strategies under three idealized remuneration schemes for PFC, inspired by those used in Sweden, the USA, and China, respectively. We show how burden and compensation vary under future scenarios of renewable power systems. Here, our framework can be used by producers to develop favorable operation strategies that reduce burden and increase economic value, and by transmission system operators to provide insights on the relation between incentive structures and regulating performance.

13 HYDRO ENERGY↗

An Information Theoretic Approach to Identify Dominant Voltage Influencers for Unbalanced Distribution Systems

Smart distribution grid with multiple renewable energy sources can experience random voltage fluctuations due to variable generation, which may result in voltage violations. Traditional voltage control algorithms are inadequate to handle fast voltage variations. Therefore, new dynamic control methods are being developed that can significantly benefit from the knowledge of dominant voltage influencer (DVI) nodes. DVI nodes for a particular node of interest refer to nodes that have a relatively high impact on the voltage fluctuations at that node. Conventional power flow-based algorithms to identify DVI nodes are computationally complex, which limits their use in real-time applications. This paper proposes a novel information theoretic voltage influencing score (VIS) that quantifies the voltage influencing capacity of nodes with DERs/active loads in a three phase unbalanced distribution system. VIS is then employed to rank the nodes and identify the DVI set. VIS is derived analytically in a computationally efficient manner and its efficacy to identify DVI nodes is validated using the IEEE 37-node test system. It is shown through experiments that KL divergence and Bhattacharyya distance are effective indicators of DVI nodes with an identifying accuracy of more than 90%. Additionally, the computation burden is also reduced by an order of 5, thus providing the foundation for efficient voltage control.

42 ENGINEERING↗

Western Wind and Solar Integration Study Phase 3A: Low Levels of Synchronous Generation

The stability of the North American electric power grids under conditions of high penetrations of wind and solar is a significant concern and possible impediment to reaching renewable energy goals. The 33% wind and solar annual energy penetration considered in this study results in substantial changes to the characteristics of the bulk power system. This includes different power flow patterns, different commitment and dispatch of existing synchronous generation, and different dynamic behavior from wind and solar generation. The Western Wind and Solar Integration Study (WWSIS), sponsored by the U.S. Department of Energy, is one of the largest regional solar and wind integration studies to date. In multiple phases, it has explored different aspects of the question: Can we integrate large amounts of wind and solar energy into the electric power system of the West? The work reported here focused on the impact of low levels of synchronous generation on the transient stability performance in one part of the region in which wind generation has displaced synchronous thermal generation under highly stressed, weak system conditions. It is essentially an extension of WWSIS-3. Transient stability, the ability of the power system to maintain synchronism among all elements following disturbances, is a major constraint on operations in many grids, including the western U.S. and Texas systems. These constraints primarily concern the performance of the large-scale bulk power system. But grid-wide stability concerns with high penetrations of wind and solar are still not thoroughly understood. This work focuses on 'traditional' fundamental frequency stability issues, such as maintaining synchronism, frequency, and voltage. The objectives of this study are to better understand the implications of low levels of synchronous generation and a weak grid on overall system performance by: 1) Investigating the Western Interconnection under conditions of both high renewable generation (e.g., wind and solar) and low synchronous generation (e.g., significant coal power plant decommitment or retirement); and 2) Analyzing both the large-scale stability of the Western Interconnection and regional stability issues driven by more geographically dispersed renewable generation interacting with a transmission grid that evolved with large, central station plants at key nodes. As noted above, the work reported here is an extension of the research performed in WWSIS-3.

24 POWER TRANSMISSION AND DISTRIBUTION↗

2025 California Demand Response Potential Study - Charting California’s Demand Response Future. Final Report on Phase 2 Results

California’s legislative and regulatory goals for renewable energy are changing the power grid’s dynamics. Increased variable generation resource penetration connected to the bulk power system, as well as, distributed energy resources (DERs) connected to the distribution system affect the grid’s reliable operation over many different time scales (e.g., days to hours to minutes to seconds). As the state continues this transition, it will require careful planning to ensure resources with the right characteristics are available to meet changing grid management needs. Demand response (DR) has the potential to provide important resources for keeping the electricity grid stable and efficient, to defer upgrades to generation, transmission and distribution systems, and to deliver customer economic benefits. This study estimates the potential size and cost of future DR resources for California’s three investor-owned utilities (IOUs): Pacific Gas and Electric Company (PG&E), Southern California Edison Company (SCE), and San Diego Gas & Electric Company (SDG&E). Our goal is to provide data-driven insights as the California Public Utilities Commission (CPUC) evaluates how to enhance DR’s role in meeting California’s resource planning needs and operational requirements. We address two fundamental questions: 1. What cost-competitive DR service types will meet California’s future grid needs as it moves towards clean energy and advanced infrastructure? 2. What is the size and cost of the expected resource base for the DR service types?

24 POWER TRANSMISSION AND DISTRIBUTION↗

Storage Futures Study: Grid Operational Impacts of Widespread Storage Deployment

This report, the fifth in the Storage Futures Study series, uses cost-driven scenarios from the ReEDS model as a starting point to examine the operational impacts of grid-scale storage deployment and relationships between this deployment and the contribution of variable renewable energy. We use commercial production cost modeling software to evaluate hourly operation of five scenarios that reach between 210 gigawatts (GW) and 930 GW of installed storage by 2050. We find that storage plays an important role in these power systems between now and 2050 - by storing the lowest-marginal cost generation (often, overgeneration from solar or wind plants) and generating energy during the highest net load periods of the day and year. Storage helps with the integration of variable renewable energy and by providing an important resource to provide continued reliable power.

battery↗

Modeling the Value of Integrated Canadian and U.S. Power Sector Expansion

The United States and Canada power systems are not isolated. Cross-border transmission and coordination of system operation create an interconnected power system, which results in combined imports and exports of electricity of greater than 70 TWh per year [1]. Currently, over 5 GW of new international transmission lines are in various stages of permitting and development. These lines may enable greater integration and coordination of the U.S. and Canada systems, which can in turn reduce challenges associated with integration of high penetrations of variable renewables. Furthermore, low-cost Canadian resources, such as wind and hydro, could contribute to compliance with the EPA's recently released Clean Power Plan. Improving integration and coordination internationally will reduce the costs of accessing these resources. This analysis work build on previous work by Ibanez and Zinaman [2]. In this work we seek to better understand the value of additional interconnection between the U.S. and Canadian power systems. Specifically, we quantify the value of additional interconnection and coordination within the Canadian-US integrated power system under scenarios in which large reductions (>80%) in power sector CO2 emissions are achieved. We explore how the ability to add additional cross-border transmission impacts capacity investment, the generation mix, system costs, and the ability of the system to integrate variable renewable energy into the power system. This analysis uses the Regional Energy Deployment System (ReEDS) capacity expansion model [3], [4] to quantify the value of the integrated power system expansion of the United States and Canada. ReEDS is an optimization model that assesses the deployment and operation (including transmission) of the electricity sector of the contiguous United States and Canadian provinces from 2016 through 2050. It has the ability to model the integration of renewable energy technologies into the grid. ReEDS captures renewable energy resources through the use of 356 individual resource regions and 134 balancing areas across the U.S. and is able to handle renewable energy issues such as variability in wind and solar output, transmission costs and constraints, and ancillary services requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Status Report on Modelling and Simulation Capabilities for Nuclear-Renewable Hybrid Energy Systems

This report summarizes the current status of the modeling and simulation capabilities developed for the economic assessment of Nuclear-Renewable Hybrid Energy Systems (N-R HES). The increasing penetration of variable renewables is altering the profile of the net demand, with which the other generators on the grid have to cope. N-R HES analyses are being conducted to determine the potential feasibility of mitigating the resultant volatility in the net electricity demand by adding industrial processes that utilize either thermal or electrical energy as stabilizing loads. This coordination of energy generators and users is proposed to mitigate the increase in electricity cost and cost volatility through the production of a saleable commodity. Overall, the financial performance of a system that is comprised of peaking units (i.e. gas turbine), baseload supply (i.e. nuclear power plant), and an industrial process (e.g. hydrogen plant) should be optimized under the constraint of satisfying an electricity demand profile with a certain level of variable renewable (wind) penetration. The optimization should entail both the sizing of the components/subsystems that comprise the system and the optimal dispatch strategy (output at any given moment in time from the different subsystems). Some of the capabilities here described have been reported separately in [1, 2, 3]. The purpose of this report is to provide an update on the improvement and extension of those capabilities and to illustrate their integrated application in the economic assessment of N-R HES.

97 MATHEMATICS AND COMPUTING↗

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

Impact of Generator Flexibility on Electric System Costs and Integration of Renewable Energy

Flexibility of traditional generators plays an important role in accommodating the increased variability and uncertainty of wind and solar on the electric power system. Increased flexibility can be achieved with changes to operational practices or upgrades to existing generation. One challenge is in understanding the value of increasing flexibility, and how this value may change given higher levels of variable generation. This study uses a commercial production cost model to measure the impact of generator flexibility on the integration of wind and solar generators. We use a system that is based on two balancing areas in the western United States with a range of wind and solar penetrations between 15% and 60%, where instantaneous penetration of wind and solar is limited to 80%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗