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At least 577 records · Page 32

Transmission-and-Distribution Dynamic Co-simulation Framework for Distributed Energy Resource Frequency Response

The rapid deployment of distributed energy resources (DERs) in distribution networks has made it challenging to balance the transmission system and stabilize frequency. DERs have the ability to provide frequency regulation services; however, existing frequency dynamic simulation tools - which were developed mainly for the transmission system - lack the capability to simulate distribution network dynamics with high penetrations of DERs. Although electromagnetic transient simulation tools can simulate distribution network dynamics, the computation efficiency limits their use for large-scale transmission-and-distribution (T&D) co-simulation. This paper presents an efficient open-source T&D dynamic co-simulation framework for DER frequency response based on the HELICS platform and off-the-shelf T&D simulators. The challenge of synchronizing the simulation time between the transmission network and the DERs in the distribution network is solved through the detailed modeling of DERs in frequency dynamic models while DER power flow models are also preserved in the distribution networks, thereby respecting local voltage constraints when dispatching DER power for frequency response. DER frequency response (primary and secondary) is simulated in case studies to validate the proposed framework. Last, the accuracy of the proposed co-simulation model is benchmarked, and a large T&D system simulation (2k transmission and 1M distribution nodes) is presented to demonstrate the efficiency and effectiveness of the overall framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Network-Aware Distributed Energy Resource Aggregation Framework for Flexible, Cost-Optimal, and Resilient Operation

To efficiently use the ubiquitous behind-the-meter distributed energy resources (DERs) in distribution systems for providing grid services, this paper presents a hierarchical control framework for DER optimal aggregation and control. We first develop a convex optimization model to evaluate the DER flexibility, and then use a convex model-predictive-control based approach to dispatch those DERs. The hierarchical control framework consists of a utility controller, community aggregators and multiple home energy management systems. The flexibility of the DERs is evaluated by each controller in the hierarchy such that the resultant flexibility is feasible given its operational domain. Based on the determined flexibility, the hierarchical controllers then compute optimal setpoints for the DERs to help the distribution system regulate node voltages and provide other distribution grid services. Numerical simulations performed on a model of a real distribution feeder in Colorado, using actual DER data in a residential community demonstrate that the proposed approach can effectively alleviate voltage issues and support resilient operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation

Aggregation of electric vehicles (EVs) is a promising technique for providing secondary frequency regulation (SFR) in highly renewable energy-penetrated power systems. Equipped with energy storage devices, EV aggregation can provide reliable SFR. However, the main challenge is to guarantee reliable intra-interval SFR capacities and inter-interval delivery following the automatic generation control (AGC) signal. Furthermore, aggregated EV SFR provision will be further complicated by the EV charging time anxiety because SFR provision might extend EV's charging time. This paper proposes a deliverable EV SFR provision with a charging-time-constrained control strategy. First, a charging-time-constrained EV aggregation is proposed to address the uncertainty of EV capacity based on the state-space model considering the charging-time restriction of EV owners. Second, a real-time economic dispatch and time domain simulation (RTED-TDS) cosimulation framework is proposed to verify financial results and the dynamic performance of the EV SFR provision. Last, the proposed charging time-constrained EV aggregation is validated on the IEEE 39-bus system. In conclusion, the results demonstrate that with charging time-constrained EV aggregation, the dynamic performance of the system can be improved with a marginal increase in total cost. More importantly, the charging time constraint can be respected in the proposed SFR provision of the EV aggregation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Microgrid Service Restoration Incorporating Unmonitored Automatic Voltage Controllers and Net Metered Loads

Islanded microgrids may experience voltage and frequency instability due to uncontrolled state changes of voltage regulation devices and inaccurate demand forecasts. Uncontrolled state changes can occur if optimal microgrid restoration and dispatch algorithms, used for generating control commands for distributed energy resources, do not incorporate the behavior of automatic controllers of voltage regulation devices. Inaccurate demand forecasts may be encountered since post-outage demand of behind-the-meter net metered (NM) loads can vary significantly from their historical NM profiles. Here, this paper proposes an optimization formulation which allows optimal control of voltage regulators and capacitor banks without remote control and communication capabilities. A generalized demand model for NM loads is proposed which incorporates the cold load pickup phenomenon and their time varying post-outage demand in accordance with the IEEE 1547 standard. The time dependent optimal control formulation and the NM demand model are integrated in a sequential microgrid restoration algorithm by linearization of the involved logic propositions. A detailed case study on the unbalanced IEEE 123-node test system in OpenDSS validates the effectiveness of the proposed approach.

30 DIRECT ENERGY CONVERSION↗

Stochastic Adaptive Droop Control in Frequency Regulation of Power Systems With Intermittent Generators

Modern power systems (MPSs), including microgrids (MGs), are increasingly incorporating multiple renewable energy sources (RESs) such as wind and solar power, as well as battery storage and controllable loads. While environmentally beneficial, these sources pose challenges for control and management due to their intermittent and stochastic nature, especially in maintaining frequency stability with multiple interconnected generators of varying capacities. Traditional droop control methods are effective in systems with generators that are dispatchable and have fixed generation capacities, but they fall short when applied to systems with RESs, where generation capacities are dynamic and affected by unpredictable environmental conditions. To address these challenges, this paper introduces a novel stochastic adaptive droop control (SADC) method for load frequency control (LFC). The proposed method adapts droop coefficients in real time, based on the measured stochastic data of power generation capacities, enabling more effective frequency regulation in systems with variable and intermittent power generation. Unlike traditional adaptive control methods, which assume constant or slowly-varying system parameters, this approach accounts for stochastic processes by modeling them as Markov chains, enabling robust performance under highly dynamic and unpredictable conditions. The key contributions of this work include the development of real-time droop coefficient adaptation algorithms, derivation of their stability and convergence properties, and the demonstration of the advantages of the method through simulations. Case studies highlight the improved performance of frequency regulation, particularly in addressing the impact of stochastic weather conditions and the benefits of reducing dependence on battery reserves in dealing with intermittency of RESs. Finally, this paper provides a comprehensive analysis of the theoretical foundations of the method, as well as practical implementation insights for future power systems with high penetration of RESs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Additional Capacity Value From Synergy of Variable Renewable Energy and Energy Storage

Current capacity markets often consider capacity credits from each resource independently, irrespective of the portfolio of resources, potentially overvaluing or undervaluing the capacity contribution of variable renewable energy (VRE) and energy storage (ES) in the grid. We propose a method for calculating the standalone and integrated capacity value of an added VRE resource with existing ES resources. The difference between the integrated and standalone value is the portfolio effect. This is the additional capacity value gained by the synergy of VRE and the existing fleet. Using chronological dispatch simulations and two different reliability metrics to estimate firm capacity, we demonstrate on a small test system that the portfolio effect can be substantial.

capacity credit↗

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗

Approximate Dynamic Programming With Enhanced Off-Policy Learning for Coordinating Distributed Energy Resources

Herein this paper proposes an innovative approximate dynamic programming (ADP) method for distributed energy resource coordination with the loss of life of battery energy storage system (BESS) explicitly modeled. The dispatch policy is designed to account for both calendrical and cyclical aging effects on BESS, explicitly modeling the impacts of ambient temperature on BESS lifespan. The proposed ADP employs an adaptive critic method and enhanced off-policy deterministic policy gradient (DPG) strategy, addressing the limitations of the on-policy gradient-based ADP approaches, including inadequate exploration, low data usage, and computational complexity. In particular, a customized policy is proposed to guide the algorithm to explore some promising decisions and thereby improve exploration capability and learning efficiency compared to conventional DPG-based learning approaches, which may struggle to find a global optimum due to random noisy action-based exploration or require expert demonstration with extra effort. The proposed method is illustrated using the IEEE 123-node system and compared with the existing ADP methods to prove solution accuracy and demonstrate the effects of incorporating degradation models into control design. Case studies showed that the proposed ADP effectively coordinates DERs with a 10 times smaller optimization gap compared to existing methods, and the incorporation of the BESS life loss model ensures the expected lifespan and results in significant cost savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hierarchical Control of Megawatt-Scale Charging Stations for Electric Trucks with Distributed Energy Resources

Electrifying medium- and heavy-duty trucks is critical to decarbonizing the transportation sector. Energy needs of electric trucks will likely require megawatt-scale charging stations, which could significantly stress the electric distribution grid. Distributed energy resources (DER) can alleviate this stress and reduce charging costs with proper management. To that end, this work develops a hierarchical predictive control algorithm for future multi-port megawatt-scale charging stations that can provide real-time energy management for stations, decide charging rates, dispatch energy storage system (ESS), and provide grid voltage support. We integrate three algorithmic components: (i) an energy management optimization (EMO) that provides supervisory control to DER assets and charging loads at minute scale, (ii) a real-time energy management system (RT-EMS) that heuristically compensates for fast disturbances at sub-second scale, and (iii) a model predictive control (MPC)-based battery management system (BMS) that communicates future charging demands to the EMO, to manage the overall megawatt-scale site. Additionally, validation in a controller hardware-in-the-loop (CHIL) environment shows that the hierarchical controller can reduce the total energy consumption from the grid by approximately 28% compared to an uncontrolled case for the station configuration in this paper, without impacting charging time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Operational Simulation of Multi-Functional Charging Station for Sustainable Transportation

As transportation systems move toward electrification and decarbonization, multifunctional charging stations (MFCS) are emerging as key infrastructure for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs). This paper presents a simulation model of an MFCS that integrates solar photovoltaic (PV), wind power, battery storage, hydrogen (\mathrm{H}_{2}) production, dual-pressure \mathrm{H}_{2} storage, fuel cells, and dynamic grid interactions. The model simulates daily operations using 5 -minute resolution data to capture realtime variability in renewable energy (RE), demand, and electricity prices. A flexible dispatch algorithm dynamically allocates energy for EV charging, \mathrm{H}_{2} production, storage, and grid transactions while respecting system constraints. Results show that the MFCS effectively prioritizes RE usage, minimizes waste, meets diverse energy demands, and achieves net operational profit. The model serves as a valuable decision-support tool for designing and optimizing integrated clean energy hubs for zero-emission transportation.

Gbadegoye, Jeremiah [University of Tennessee, Knox↗

The Potential to Improve the Value of U.S. Geothermal Electricity Generation Through Flexible Operations

Geothermal power plants have typically been operated as baseload plants. The recent expansion of wind and solar power generation creates a potential opportunity to increase the value of geothermal generation through flexible operations. In recent years, California’s wholesale electricity markets have exhibited frequent, short-term periods of negative pricing, indicating that additional flexibility would be valued in the market. Here, we examine local nodal hourly price records at all geothermal plants located in the western United States. We describe how the frequency and temporal characteristics of negative pricing episodes have changed over recent years. Based on these price series, we calculate the value of multiple strategies of flexible operations. Additionally, we use the estimates of future prices, developed through a capacity-expansion model and a dispatch model, to explore how the value of such flexible operations might change along with further penetration of variable renewable power sources. Based on the historical pricing records, we find that simple curtailment of operations during negative pricing episodes could increase the average energy value by 1–2 dollars per MWh and that allowing for increased production during limited high-priced hours, in addition to curtailment during negative priced hours, could potentially double the increase in value (up to 4 dollars per MWh). The forward-looking simulations indicate reduced values of flexibility from geothermal power despite higher penetrations of variable renewable energy. This result highlights the possibility that increasing flexibility options throughout the system may counteract the influence of increased variable renewable energy deployment.

15 GEOTHERMAL ENERGY↗

Design of a 1 MWth Supercritical Carbon Dioxide Primary Heat Exchanger Test System

A new generation of Concentrating Solar Power (CSP) technologies is under development to provide dispatchable renewable power generation and reduce the levelized cost of electricity (LCOE) to 6 cents/kWh by leveraging heat transfer fluids (HTF) capable of operation at higher temperatures and coupling with higher efficiency power conversion cycles. The U.S. Department of Energy (DOE) has funded three pathways for Generation 3 CSP (Gen3CSP) technology development to leverage solid, liquid, and gaseous HTFs to transfer heat to a supercritical carbon dioxide (sCO 2 ) Brayton cycle. Here we present the design and off-design capabilities of a 1 MWth sCO 2 test system that can provide sCO 2 coolant to the primary heat exchangers (PHX) coupling the high-temperature HTFs to the sCO 2 working fluid of the power cycle. This system will demonstrate design, performance, lifetime, and operability at a scale relevant to commercial CSP. A dense-phase high pressure canned motor pump is used to supply up to 5.3 kg/s of sCO 2 flow to the primary heat exchanger at pressures up to 250 bar and temperatures up to 715 °C with ambient air as the ultimate heat sink. Key component requirements for this system are presented in this paper.

14 SOLAR ENERGY↗

Technoeconomic Design of a Geothermal-Enabled Cold Climate Zero Energy Community

Development of a zero energy community is more costly in northern cold climates than in moderate regions. Building energy loads are higher, thanks to the colder weather, and site solar photovoltaics (PV) are less productive due to lower solar incidence and misalignment with the buildings’ energy needs (summer production, winter demands). Geothermal energy production can support a zero energy community through application of energy efficiency (demand design), geothermal production (supply design), and asset dispatch as an integrated techno-economic package. This article presents the process used to explore geothermal system integration, our findings, and technical challenges for community-scale adoption of geothermal as an electric and thermal resource. We show that under a wide range of conditions, community-scale geothermal electric power and direct-use thermal energy is economically competitive with “business-as-usual” design and construction practices for zero energy communities. Furthermore, geothermal-produced energy will be self-consumed to a much greater extent than PV, resulting in significant reductions in site energy import and export. We conclude that under appropriate conditions, community-scale geothermal can be the most economically favorable energy resource for northern-climate zero energy community developments. Ongoing geothermal research and development to improve performance and reduce costs will further enhance the value proposition for community-scale geothermal technologies. We expect that including geothermal power and thermal energy in zero energy community design can improve its cost-effectiveness and therefore enhance the benefits of zero energy in more northern climates.

15 GEOTHERMAL ENERGY↗

Design of a Compact Dry Cooler With an Aluminum Heat Exchanger Core for a Supercritical CO2 Power Cycle Is Evaluated for a Concentrating Solar Power Application

Abstract As the supercritical CO2 power cycle develops and the component technologies mature, there is still a need to reduce the associated capital and operating costs to maintain a competitive levelized cost of electricity (LCOE) in order to enter the market. When considering concentrating solar power (CSP) coupled with an sCO2 power block and sensible thermal storage, the technology presents a clean source for utility-scale power generation to support baseload or peak-load electrical demand. However, the LCOE of the technology is still considered higher than the competing technologies and should be reduced to better compete in the market; 2030 targets for dispatchable solar plants are 5¢/kWh for baseload CSP and 10¢/kWh for peaker plants, as set by the United States Department of Energy. In response to this need, this study is targeting improvements in the power cycle precooler to reduce power block contribution to LCOE. This study considers a dry cooler, as CSP plants are sensitive to water consumption because many installations are slated for remote or arid locations where solar irradiance is very high, but water is scarce. Furthermore, the power block footprint for an sCO2 system is quite compact, especially as compared to a steam cycle. Therefore, there is interest in installing a more compact dry cooler that is proportional to the reduced footprint sCO2 power block, while conventional dry coolers are an order of magnitude larger. The competing goals of size, performance, and cost were considered in this study to develop a compact dry cooler that can easily be packaged with the power block, significantly reducing the installation and transport cost compared to the current state of the art, while maintaining or improving upon the heat transfer performance and impact on plant LCOE. This paper details the high-level findings of a large dry cooler sensitivity study for design point selection, design of the compact dry cooler, expected year-round performance for the dry cooler and the power cycle, and the predicted LCOE for a 30-year plant life. It was found that an aluminum heat exchanger core can be suitably designed to meet the pressure and temperature requirements for a precooler in an sCO2 recompression Brayton cycle. The dry cooler assembly was found to have improved heat transfer performance, allowing for increased cycle efficiencies and a reduced plant LCOE. When coupled with a centrifugal blower and compact transition duct, the dry cooler assembly was able to reduce the installation footprint by over 50%.

14 SOLAR ENERGY↗

PHASE CHANGE MATERIAL FOR THERMAL ENERGY STORAGE IN BUILDINGS BASED ON SODIUM SULFATE DECAHYDRATE AND DISODIUM HYDROGEN PHOSPHATE DODECAHYDRATE

The worldwide increasing energy demand and 2050 net zero carbon target urge the globe to solve the energy challenge. Thermal Energy Storage (TES) has received significant attention in recent years as TES can be integrated into heating, ventilation, and air-conditioning systems where the energy would be stored during low-demand times and dispatched during high-demand times, resulting in controlling the peak load and improving energy savings. Material development is an integral part of TES. Salt hydrates are appealing due to cost-effectiveness, low- to no toxicity, and their high melting enthalpy, where energy is stored as latent heat. However, most salt hydrates are prone to incongruent melting (i.e., phase separation upon melting), which results in poor stability and large supercooling. In this study, we produced a highly stable novel energy storage material at a composition of 32 wt% sodium sulfate decahydrate, 52 wt% sodium phosphate dibasic dodecahydrate, 12 wt% milled expanded graphite, and 4 wt% borax. The material has a melting temperature of 28°C and an energy storage capacity of 167 kJ/kg with a supercooling of less than 3°C. The system showed no loss in energy storage performance after 150 cycles. The findings suggest that the novel energy storage material developed in this might be utilized in building heating and cooling applications.

Turnaoglu, Tugba↗

System and Component Development of Particle-Based Pumped Thermal Energy Storage

Reliable power supply from variable renewable resources requires energy storage at various scales to overcome resource intermittency. Long-duration energy storage (LDES, 10-100 hours) can improve dispatchability and grid reliability with increasing levels of renewable power supply. Thermal energy storage (TES) has siting flexibility and the ability to store a large capacity of energy, and thus has the potential to meet the LDES need and provide charging and discharging durations beyond the economic capacity of conventional batteries. TES technology has evolved from concentrating solar thermal power (CSP) generation and is recognized as an economic large-scale energy storage method. A standalone electric-thermal energy storage system supporting renewable integration of wind and solar power without CSP solar field can firm renewable generation and boost overall grid resilience and security.

concentrating solar thermal power↗

LIQUID AIR COMBINED CYCLE

Hybrid integration of thermal energy storage with gas turbines can provide compact, cost-effective, long-duration energy storage while reducing the fuel consumption of dispatchable resources needed for the reliability of renewable dominant electric grids. The Liquid Air Combined Cycle™ (LACC) is a hybrid energy storage system using cryogenic liquid air as an energy storage medium and gas turbine exhaust heat to extract stored energy. The storage tank is charged using liquefaction processes employing electric motor-driven compressors to pressurize the air, heat exchangers to reject heat of compression, and expanders to reduce the temperature and liquefy the air. Proven cryogenic refrigeration processes can be selected based on capital cost (per kg/s of liquid air produced), efficiency (kJ per kg of air produced), and operating factors including startup speed and load following capability. This paper presents results of studies undertaken for the U.S. Department of Energy to evaluate cost and performance tradeoffs for charge and discharge cycle components, optimize charge and discharge cycles, and assess the techno-economic potential of LACC technology.

Conlon, William↗