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Distribution Grid Impacts of Community Solar [Slides]

Community solar (CS) projects often face uncertain interconnection costs and fees associated with distribution grid infrastructure upgrades required to connect the project. These costs can determine the economic viability of a CS project, but they are difficult to assess. Cost uncertainty can discourage new projects and prevent communities from accessing the benefits of community solar projects. At the same time, CS deployment strategies hold potential to defer or avoid some distribution costs due to new loads. To mitigate CS interconnection costs, it is important to find least-cost combinations of distribution system infrastructure solutions (transformer upgrades, reconductoring, voltage regulators, storage), and to understand how location of CS projects within a feeder impact distribution grid upgrade costs. This study aims to quantify CS impacts on the distribution grid and provide policy and regulatory insights and CS deployment strategies to address them. It is the first analysis that has systematically studied the technical impacts of community solar projects on a wide range of distribution feeders using state-of-the-art optimization and power flow tools. The analysis employs Berkeley Lab’s novel Least-cost Optimal Distribution Grid Expansion (LODGE) model, a deterministic version of the REPAIR model, that optimally upgrades hundreds or even thousands of distribution circuits or feeders. This is the first application of the LODGE model. LODGE finds the least-cost portfolio of traditional distribution system upgrades to integrate CS in combination with alternative solutions, such as utility-owned storage and downsizing CS capacity. Working with a set of least-cost solutions per feeder allows us to benchmark, compare and find techno-economic trends in CS interconnection.

14 SOLAR ENERGY↗

Enabling Grid-Aware Market Participation of Aggregate Flexible Resources

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. With the new FERC 2222 order, DER aggregations are allowed to participate in energy market. To enable market participation, these virtual power plants need to provide their generation cost curves. This paper proposes efficient optimization formulations and solution approaches for the characterization of hourly as well as multi-time-step generation cost curves for a distribution system with high penetration of DERs. Network and DER constraints are taken into account when deriving these cost curves, and they enable active distribution systems to bid into the electricity market. The problems of deriving linear and quadratic cost curves are formulated as robust optimization problems and tractable reformulation/solution algorithm are developed to facilitate efficient calculations. The proposed formulations and solution algorithm are validated on a realistic test feeder with high penetration of flexible resources.

aggregated distributed energy resources↗

Identifying Redundant Flow Limits on Parallel Lines

Many power system optimization problems constrain line flows with limits specified in terms of the magnitudes of apparent power or current flows. The set of line-flow constraints may have redundancies (i.e., the feasible space may be unchanged upon removal of a subset of the line-flow constraints), which unnecessarily complicate optimization problems. This letter describes an algorithm for identifying redundant line-flow constraints corresponding to certain parallel lines. After formulating the constraints as ellipsoids in the voltage variables, redundancies are detected from the absence of intersections between pairs of ellipsoids corresponding to parallel lines. This algorithm is demonstrated using several large test cases.

Molzahn, Daniel K. (ORCID:0000000305835376)↗

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗

Development of novel dynamic machine learning-based optimization of a coal-fired power plant

The increasing fraction of intermittent renewable energy in the electrical grid is resulting in coal-fired boilers now routinely ramp up and down. The current state-of-the-art operation for such boilers is to apply steady-state, neural network-based optimization to make control decisions in real-time, and this report demonstrates the feasibility of extending this to dynamic, neural network-based optimization using a long short-term memory neural network. A simplified numerical simulation of a t-fired coal boiler and supporting equipment is used to represent a real plant subjected to both steady-state, neural network-based optimization and dynamic, neural network-based optimization. Using the same intervals and a particle swarm optimization algorithm, the dynamic optimization outperforms the steady-state optimization and realizes up to 4.58% improvement in thermal efficiency. Dynamic optimization with a long short-term memory neural network is shown to both be feasible and beneficial for operation of a coal-fired boiler under changing load.

42 ENGINEERING↗

Study of Communication Boundaries of Primal-Dual Based Distributed Energy Resource Management Systems (DERMS)

As the coordination of distributed energy re-sources becomes more necessary to provide grid services through a distributed energy resource management system (DERMS), studying the communication requirements for suc-cessful real-world, low-cost implementation becomes increasingly important. Specifically, this paper studies the necessary communication time resolutions between the different system components for a primal-dual-based DERMS, a highly de-veloped DERMS framework. We design a metric to evaluate the functionality of a DERMS with respect to providing grid services. Using numerical simulations based on a real-world feeder in Colorado, we show that the upper bound on the time resolutions is on the order of minutes instead of the previously assumed order of seconds.

communication time resolution↗

Study of Communication Boundaries of Primal-Dual Based Distributed Energy Resource Management Systems (DERMS): Preprint

As the coordination of distributed energy resources (DERs) becomes more necessary to provide grid services through a distributed energy resources management system (DERMS), studying the communication requirements for successful real-world low-cost implementation becomes increasingly important. Specifically, this paper studies the needed communication time resolutions between the different system components for a primal-dual based DERMS which is a highly-developed DERMS framework. We design a metric to evaluate the functionality of a DERMS with respect to providing grid services. Using numerical simulations based on a real-world feeder in Colorado, we show that the upper bound on the time resolutions is on the order of minutes instead of the previously assumed order of seconds.

communication time resolution↗

Study of Communication Boundaries of Primal-Dual-Based Distributed Energy Resource Management Systems (DERMS)

As the coordination of distributed energy resources becomes more necessary to provide grid services through a distributed energy resource management system (DERMS), studying the communication requirements for successful real-world, low-cost implementation becomes increasingly important. Specifically, this paper studies the necessary communication time resolutions between the different system components for a primal-dual-based DERMS, a highly developed DERMS framework. We design a metric to evaluate the functionality of a DERMS with respect to providing grid services. Using numerical simulations based on a real-world feeder in Colorado, we show that the upper bound on the time resolutions is on the order of minutes instead of the previously assumed order of seconds.

communication time resolution↗

Optimal subinterval selection approach for power system transient stability simulation

Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modal analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MG-RAVENS: Working Group Update [Slides]

Problem Statement: Users in industry, who are planning the deployment and operation of microgrids, face a multi-domain problem that requires multiple engineering tools to solve; Existing tools lack interoperability, which requires tedious recreation and conversion of equipment models, and creates opportunities for errors in translation or through inconsistent assumptions; Microgrid modelers waste time reinventing the wheel because it is challenging to reuse existing distribution, load, generation, power flow, optimization models for new use cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CSP Plant Optimization Study for the California Power Market (“CalCSP”) (Final Technical Report)

Concentrating Solar Power (CSP) with thermal energy storage offers a unique and strategic opportunity to support California’s clean energy transition. Unlike photovoltaic (PV) systems, CSP with thermal storage can generate electricity after sunset and during periods of high demand, making it a valuable complement to intermittent renewable resources. CSP also provides synchronous, inertia-contributing generation, long-duration storage, and flexible dispatch—capabilities increasingly important as thermal plants retire. This report summarizes the findings of the CSP Plant Optimization Study for the California Power Market or “CalCSP study,” which evaluated the technical, economic, environmental, and policy factors that influence the deployment of CSP technologies in California. The CalCSP study was conducted to assess how CSP can contribute to California’s long-term decarbonization goals while enhancing grid reliability, supporting local economic development, and making efficient use of land and transmission resources. It draws on detailed modeling of CSP performance and costs, site suitability analysis, policy reviews, and stakeholder engagement across utilities, regulators, developers, and community organizations. The analysis focuses on mature molten-salt tower technology and incorporates lessons learned from the global CSP fleet, distinguishing today’s CSP from earlier first-of-a-kind projects in the U.S. The findings support a more prominent role for CSP in California’s evolving clean energy landscape. With strategic planning, targeted policy support, and continued cost improvements, CSP can complement PV and batteries to deliver reliable, around-the-clock clean electricity—especially in areas with high solar resource and constrained grid capacity.

14 SOLAR ENERGY↗

Antenna optimization of single beam microwave systems for the solar power satellite

A generalized antenna design technique is applied to the unique environmental requirements pertaining to solar power satellite (SPS) systems. Optimal illumination tapers and antenna/rectenna sizings are generated which allow increased transmit powers and lower electricity costs while minimizing sidelobe levels to meet a 0.01 mW/sq cm environmental standard. These optimal tapers also provide other advantages over the 10 dB Gaussian reference system.

Kerwin, E. M.↗

A Dual Stage Sodium Thermo-Electro-Chemical Converter

The need for reliable and distributable energy sources is evident given the current forecasting of the world’s energy demand [1]. One prominent obstacle is the lack of an efficient direct heat-to-electricity conversion technology. The sodium thermo-electro-chemical converter (Na-TECC) is a highly efficient thermally regenerative electrochemical system (TRES) that can fill this void. The advantage of the Na-TECC over other direct conversion technologies is that it is a closed device (unlike fuel cells) requiring nothing more than a heat input (similar to thermoelectrics). It also has a high power density (> 1 W/cm2) and specific power up to 0.5 kW/kg , with the potential to achieve > 45% heat to electricity conversion efficiencies [2]. Furthermore, the converter rejects heat at a temperature hot enough to make it amenable for cogeneration, potentially under air-cooled operation. This electrochemical technology uses a special ion-selective solid-electrolyte called beta-alumina (Na2O•11Al2O3), that is highly conductive to sodium cations. A more conducting variation of this compound is beta”-alumina (Na2O•MgO•5Al2O3), where the magnesium acts as a stabilizer [3]. In the device, liquid sodium enters an evaporator where it is heated isobarically and vaporizes. The vapor is then oxidized at the interface between the anode and the solid-electrolyte. The Na-TECC generates electric power by allowing the high pressure oxidized sodium vapor ions to expand isothermally through the solid-electrolyte from the anode to the cathode. The liberated electrons are simultaneously conducted through an external load and recombine with the cations at the cathode. The low pressure sodium vapor is subsequently condensed and a wick pumps the liquid into the high pressure plenum to complete the cycle. Previous Na-TECCs have achieved efficiencies of 18% due to practical losses, whereas the potential efficiencies are above 45% [4]. Thermodynamic limitations and design constraints have limited previous devices from attaining these record efficiencies. Specifically, the maximum potential voltage in these previous devices was substantially reduced by the kinetic limitations of the charge transfer in the cathode (referred to as the overpotential) and by Joule heating losses due to the solid-electrolyte resistance, electrode resistance, and current collector resistance. Moreover, previous devices experienced a steady loss in performance throughout their lifetime. The drop in performance has been attributed to the electrolyte undergoing thermal and chemical breakdown due to crack propagation, loss of sodium oxide, and the formation of molten dendrites that create electrical shorts [5]. Finally, previous designs have also had a substantial problem with proper thermal management, with some showing thermal losses as great as 50% of the heat input. To improve the efficiency, a dual stage conversion process is being explored. Rather than using one isothermal expansion step, the dual cycle will employ two separate electrolytes to allow two separate expansion steps: one at the high temperature, and another at an intermediate temperature. This new cycle is thermodynamically favorable as it allows for regeneration from the isobaric cooling of the first expansion step, and reheat to complete the expansion in the second step. This allows the engine to reach a lower condenser temperature than its single stage counterpart, thus increasing the overall efficiency. The temperature drop across each electrolyte in the dual stage device (e.g., ~ 400 K) is smaller than the temperature drop across a comparable single stage device (e.g., ~ 800 K). This is amenable for better thermal management and allows for less heat loss. This will also mitigate the thermal shock across the very thin (< 1 mm) solid electrolytes, reduce crack propagation and limit the percolation of the molten dendrites, and ultimately increase the lifetime of the device. As an additional benefit the dual stage can be designed using planer geometries, rather than tubular geometries used in previous single stage models, which can be manufactured less expensively. This modified geometry can be tailored to improve the thermal management by reducing the radiation losses, which has been the biggest source of thermal losses [2]. A dual stage concept for the Na-TECC has never been demonstrated in literature. In this presentation, the operation of a single stage device will be revisited and, by adopting concepts used for similar converters, the thermodynamic operation of the dual stage will be developed [6]. Using the dual stage approach, the efficiency and power equations have been redefined to include regeneration and reheat. Questions such as what current densities optimize the power output or which intermediate temperature maximizes the efficiency will also be answered. Initial calculations of the dual stage show that the thermal management is the most sensitive parameter. Although the ideal voltage produced by the dual stage can be higher, there are potential drawbacks. For example, by using a lower condenser temperature the dual stage device will have a higher open circuit voltage, but it will also have a larger overpotential due to the limited cathodic kinetics that occur at a lower temperature. In short, there are several trade-offs in this device that need to be balanced. It will be demonstrated that the dual stage device must have lower thermal losses than a single stage device if it is to have a higher efficiency.

14 SOLAR ENERGY↗

Study of Heating and Fusion Power Production in ITER Discharges

ITER simulations, in which the temperatures, toroidal angular frequency and currents are evolved, are carried out using the PTRANSP code starting with initial profiles and boundary conditions obtained from TSC code studies. The dependence of heat deposition and current drive on ICRF frequency, number of poloidal modes, beam orientation, number of Monte Carlo particles and ECRH launch angles is studied in order to examine various possibilities and contingencies for ITER steady state and hybrid discharges. For the hybrid discharges, the fusion power production and fusion Q, computed using the Multi-Mode MMM v7.1 anomalous transport model, are compared with those predicted using the GLF23 model. The simulations of the hybrid scenario indicate that the fusion power production at 1000 sec will be approximately 500 MW corresponding to a fusion Q = 10.0. The discharge scenarios simulated aid in understanding the conditions for optimizing fusion power production and in examining measures of plasma performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗

Optimal Litz Wire Design for High-Power Wireless Charging System

In this study, an optimized Litz wire and polyphase coil winding design is proposed for high-power wireless charging systems operating at 85 kHz frequency. Litz wire in a wireless charging system contributes to more than half of the losses of the system, making it a critical design component. Here, the Litz wire is optimized through Finite Element Analysis (FEA) considering electrical and mechanical design aspects and the design was validated through experimental tests on different Litz wires with various strand-diameters, twisting ratio, and number of strands. The proposed optimal Litz wire maximizes the system efficiency considering the tradeoff between coil resistance and mutual inductance. The optimal Litz wire shows that Litz wire constructed with the 63µm strands significantly outperform the traditionally used Litz wire with 100µm strand diameter. Additionally, the coil with optimal Litz wire design shows 60% reduction in the copper volume for the same loss, and at the same time increase the coil-to-coil efficiency by more than 2% by increasing the mutual inductance and reducing coil current. The optimized Litz wire was implemented in a 22-kW wireless charging system achieving 94.7% efficiency.

Aydin, Emrullah [ORNL]↗

Nonlinear Optimization Methods for Large-Scale Learning

Future advances in large-scale machine learning depend heavily on the availability of new and more powerful nonlinear optimization methods. The goal of this project is to address this challenge by designing new optimization algorithms that can deal with the scale, nonlinearity and stochasticity arising in machine learning models. Our research will provide the theoretical foundations for the new methods, and will involve intensive numerical testing on state-of-the-art machine learning systems. The project is organized into three interrelated projects that constitute a broad research agenda in the area of large-scale stochastic optimization for data science.

97 MATHEMATICS AND COMPUTING↗

Design and demonstration of a distributed-coupling linear accelerator structure

We present a topology for linear accelerators (linacs) in which the power is distributed to the cavities through a waveguide with periodic apertures that guarantees the correct phases and amplitudes along the structure length. Unlike conventional traveling and standing-wave linacs, the presented topology allows the cavity shapes to be designed without the constraints applied to the coupling between cells to transfer power from one cell to the next. Therefore, the topology permits more degrees of freedom for the optimization of individual cavity shapes in comparison with conventional linacs. The cavity shapes can be optimized for power consumption and efficiency, and/or the manipulation of the surface fields for high gradient operation. This topology also provides a possibility for low-temperature manufacturing techniques that prevent the annealing of the material during typical brazing processes; hence, the material could retain its original properties such as hardness. We present a design and an experimental demonstration of this linac.

43 PARTICLE ACCELERATORS↗