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Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference
Large-scale battery energy storage systems (BESS) have found ever-increasing use across industry and society to accelerate clean energy transition and improve energy supply reliability and resilience. However, their optimal power management poses significant challenges: the underlying high-dimensional nonlinear nonconvex optimization lacks computational tractability in real-world implementation, and the uncertainty of the exogenous power demand makes exact optimization difficult. This paper presents a new solution framework to address these bottlenecks. The solution pivots on introducing power-sharing ratios to specify each cell’s power quota from the output power demand. To find the optimal power-sharing ratios, we formulate a nonlinear model predictive control (NMPC) problem to achieve power-loss-minimizing BESS operation while complying with safety, cell balancing, and power supply-demand constraints. We then propose a parameterized control policy for the power-sharing ratios, which utilizes only three parameters, to reduce the computational demand in solving the NMPC problem. This policy parameterization allows us to translate the NMPC problem into a Bayesian inference problem for the sake of 1) computational tractability, and 2) overcoming the nonconvexity of the optimization problem. We leverage the ensemble Kalman inversion technique to solve the parameter estimation problem. Concurrently, a low-level control loop is developed to seamlessly integrate our proposed approach with the BESS to ensure practical implementation. This low-level controller receives the optimal power-sharing ratios, generates output power references for the cells, and maintains a balance between power supply and demand despite uncertainty in output power. We conduct extensive simulations and experiments on a 20-cell prototype to validate the proposed approach.
Joint Planning of EV Fast Charging Stations and Power Distribution Systems With Balanced Traffic Flow Assignment
To tackle the challenges introduced by the fast-growing charging demand of electric vehicles (EVs), the power distribution systems (PDSs) and fast charging stations (FCSs) of EVs should be planned and operated in a more coordinated fashion. However, existing planning approaches generally aim to minimize investment costs in PDSs while ignoring the risk of worsening traffic conditions. To overcome this research gap, this article integrates the interests of traffic networks into PDS and FCS joint planning model to mitigate negative impacts on traffic conditions caused by installing FCSs. First, a novel microscopic method that is different from traditional assignment methods is proposed to simulate the influences of FCSs on traffic flows and EV charging loads. Then, a multiobjective joint planning model is developed to minimize both the planning costs and unbalanced traffic flows. A new bilayer Benders decomposition algorithm is designed to solve the proposed joint planning model. Numerical results on two practical systems in China validate the feasibility of our microscopic method by comparing the simulated results with real data. Compared with existing approaches, it is also demonstrated that the proposed joint planning approach helps to balance traffic flow assignments and relieve traffic congestion.
T700 power turbine rotor multiplane/multispeed balancing demonstration
Research was conducted to demonstrate the ability of influence coefficient based multispeed balancing to control rotor vibration through bending criticals. Rotor dynamic analyses were conducted of the General Electric T700 power turbine rotor. The information was used to generate expected rotor behavior for optimal considerations in designing a balance rig and a balance technique. The rotor was successfully balanced 9500 rpm. Uncontrollable coupling behavior prevented observations through the 16,000 rpm service speed. The balance technique is practical and with additional refinement it can meet production standards.
Development of a PEMFC Power System with Integrated Balance of Plant
Autonomous Underwater Vehicles (AUV s) have received increasing attention in recent years as military and commercial users look for means to maintain a mobile and persistent presence in the undersea world. Compact, neutrally buoyant power systems are needed for both small and large vehicles. Batteries are usually employed in these applications, but the energy density and therefore the mission duration are limited with current battery technology. At a certain energy or mission duration requirement, other means to get long duration power become feasible. For example, above 10 kW-hrs liquid oxygen and hydrogen have better specific energy than batteries and are preferable for energy storage as long as a compact system of about 100 W/liter is achievable to convert the chemical energy in these reactants into power. Other reactant forms are possible, such as high pressure gas, chemical hydrides or oxygen carriers, but it is essential that the power system be small and light weight. Recent fuel cell work, primarily focused on NASA applications, has developed power systems that can meet this target power density. Passive flow-through systems, using ejector driven reactant (EDR) flow, integrated into a compact balance of plant have been developed. These systems are thermally and functionally integrated in much the same way as are automotive, air breathing fuel cell systems. These systems fit into the small volumes required for AUV and future NASA applications. Designs have been developed for both a 21" diameter and a larger diameter (LD) AUV. These fuel cell systems occupy a very small portion of the overall energy system, allowing most of the system volume to be used for the reactants. The fuel cell systems have been optimized to use reactants efficiently with high stack efficiency and low parasitic losses. The resulting compact, highly efficient fuel cell system provides exceptional reactant utilization and energy density. Key design variables and supporting test data are presented. Future development activities are described.
Thermo-Hydrological Modeling of Thermal Energy Storage in a Depleted Oil Reservoir
Thermal energy storage in oil and gas reservoirs leverages the existing surface and subsurface infrastructure, which can pave the way for economic production of geothermal energy. Existing studies on geothermal energy storage are focused mostly on the use of aquifers with more homogeneous rock and fluid properties. Coupling of heat and fluid flow in a multiphase-multicomponent system, such as an oil reservoir, is imperative especially if existing oil field assets need to be repurposed as required for a sustainable energy transition. The objective is to model the subsurface thermo-hydrological processes associated with reservoir performance and operational sustainability. The model evaluates formation pressure and temperature within the reservoir and at the injection/production wells during multiple charge and discharge cycles. Hot water (approximately 200 degrees C) heated by Concentrating Solar Power (CSP) at high pressure is injected into the existing oil reservoir for storage and produced as thermal energy for power generation, which will be accompanied by enhanced oil recovery. To demonstrate the coupled fluid and heat flow during the injection/production cycle in the subsurface reservoir, TOUGH3 (developed by Berkeley Lab) is used to simulate the thermo-hydrological (TH) processes in a multiphase, multicomponent system. Two well geometries are considered within the reservoir grid: 1) a single-well huff-n-puff system (same well is used for injection and production), and 2) an isolated injection-production well doublet. Seasonal charge and discharge cycling are implemented based on the scheduling specified in the model input file. The model reports pressure, temperature, enthalpy, liquid fluxes, heat fluxes, pore velocities, and changes in porosity & permeability due to temperature and pressure variations during the cyclic Reservoir Thermal Energy Storage (RTES) operations. The results from the simulations can be used to optimize the operational parameters (such as well spacing and injection/production rates) and round-trip efficiency for surface power-plants coupled with thermal energy storage over time. They can also serve as important inputs for levelized cost of storage estimations. The research will help to design and integrate surface renewable energy sources, such as concentrating solar power (CSP), with RTES to help balance out power supply and demand on the grid.
Optimal Power Management of Battery Energy Storage Systems via Ensemble Kalman Inversion
Optimal power management of battery energy storage systems (BESS) is crucial for their safe and efficient operation. Numerical optimization techniques are frequently utilized to solve the optimal power management problems. However, these techniques often fall short of delivering real-time solutions for large-scale BESS due to their computational complexity. To address this issue, this paper proposes a computationally efficient approach. We introduce a new set of decision variables called power-sharing ratios corresponding to each cell, indicating their allocated power share from the output power demand. We then formulate an optimal power management problem to minimize the system-wide power losses while ensuring compliance with safety, balancing, and power supply-demand match constraints. To efficiently solve this problem, a parametrized control policy is designed and leveraged to transform the optimal power management problem into a parameter estimation problem. We then implement the ensemble Kalman inversion to estimate the optimal parameter set. The proposed approach significantly reduces computational requirements due to 1) the much lower dimensionality of the decision parameters and 2) the estimation treatment of the optimal power management problem. Finally, we conduct extensive simulations to validate the effectiveness of the proposed approach. The results show promise in accuracy and computation time compared with explored numerical optimization techniques.
Energy in the Balance: PV Reliability to Power the Energy Transition
We present an analysis of the effects of reliability on our ability to achieve the energy transition deployment targets. We examine three end of life modes as captured in the PV ICE tool; degradation, failures, and project lifetime. Recommendations are made for improving PV reliability for achieving energy energy transition.
A Concept for Integration of Direct Air Capture System in the Thermal Balance of an Nuclear Power Station
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Value of Nuclear Energy to the Reliability of the North American Power System: Results for Western and Eastern Interconnections
This report documents the fulfillment of a milestone for the United States (U.S.) Department of Energy Office of Nuclear Energy Light Water Reactor Sustainability Program: completing a baseline study of regional impact of nuclear power plants and hydrogen production in maintaining grid services and power quality. Models have been comprehensively demonstrated for the Western Interconnection, or Western Electric Coordinating Council area, and in the Eastern Interconnection for scenarios representative of past extreme events (e.g., drought and heat waves). Understanding the impact on the reliability of the bulk electric system of any reduction in generation capacity from nuclear power, for any reason, is the motivation of this work. Factors that might lead to the premature or unplanned closure of nuclear plants, extended outages, or repurposing of nuclear power include: • Aging infrastructure: Many nuclear power plants in the U.S. are nearing the end of their designed operating lives. Upgrading aging infrastructure can be expensive, and some utilities may choose to retire plants rather than invest in costly upgrades. • Low wholesale electricity prices: The deregulation of the electricity market in many states has led to increased competition and driven down wholesale electricity prices, causing nuclear power operators to seek other revenue sources for their heat and power such as clean hydrogen production. • Renewables growth: The rapid growth of renewable energy sources like solar and wind power is posing a challenge to traditional generation sources like nuclear. While many see renewables as a key part of the clean energy transition, their intermittent nature requires additional grid solutions for reliable power supply. • The potential for regulatory decisions to be in conflict: In its 2021 rulemaking, EPA rule (86 FR 880), the Environmental Protection Agency (EPA) set a compliance date for the ban on processing and distribution in commerce of Decabromodiphenyl Ether (DecaBDE). Since DecaBDE is in many components, particularly wiring, of nuclear power plants which are deemed safety-related or important to safety, three plants would not have been able to restart after their 2023 spring outages, and numerous others would have faced issues in the near future. Fortunately, in this case, the EPA provided relief to the nuclear energy industry. The report provides a summary of the significant role nuclear energy plays in the United States’ power generation mix, supplying around 20% of the nation’s electricity generation, spread across 28 U.S. states. Nuclear power is reliable, mostly unaffected by weather and seasonal changes, and provides a consistent source of baseload power. In terms of capacity, nuclear power plants account for as much as 26% of balancing area power generation capacity. Nuclear power also provides a substantial contribution (e.g., 10% of the inertia in the Eastern Interconnection) of the synchronous spinning mass/inertia that buffers the rate at which frequency changes when a load and generation imbalance occurs (e.g., a large plant trips or a load is suddenly shed due to a transmission outage). This contribution is critical for maintaining grid stability during sudden changes in load or generation.
Computer-assisted high-speed balancing of T53 and T55 power turbines
Standard overhaul procedures for U.S. Army helicopter engines require operational vibration acceptance testing after rebuild. Engines frequently experience vibrations which exceed allowable overhaul work requirement limits. The rework/retest cycle for these engines constitute a significant cost penalty to the overhaul center. This paper reviews both analytical and test data which indicate bending critical speeds within the operating speed range of the low-speed power turbine rotor as the cause of most test cell rejections. High-speed balancing techniques are applicable and are capable of significantly reducing this reject rate. A complete prototype computer-assisted high-speed balancing system for assembled T53 and T55 power turbine rotors is described.
H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays
This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.
Submillimeter sources for radiometry using high power Indium Phosphide Gunn diode oscillators
A study aimed at developing high frequency millimeter wave and submillimeter wave local oscillator sources in the 60-600 GHz range was conducted. Sources involved both fundamental and harmonic-extraction type Indium Phosphide Gunn diode oscillators as well as varactor multipliers. In particular, a high power balanced-doubler using varactor diodes was developed for 166 GHz. It is capable of handling 100 mW input power, and typically produced 25 mW output power. A high frequency tripler operating at 500 GHz output frequency was also developed and cascaded with the balanced-doubler. A dual-diode InP Gunn diode combiner was used to pump this cascaded multiplier to produce on the order of 0.5 mW at 500 GHz. In addition, considerable development and characterization work on InP Gunn diode oscillators was carried out. Design data and operating characteristics were documented for a very wide range of oscillators. The reliability of InP devices was examined, and packaging techniques to enhance the performance were analyzed. A theoretical study of a new class of high power multipliers was conducted for future applications. The sources developed here find many commercial applications for radio astronomy and remote sensing.
Mobility power flow analysis of an L-shaped plate structure subjected to acoustic excitation
An analytical investigation based on the Mobility Power Flow method is presented for the determination of the vibrational response and power flow for two coupled flat plate structures in an L-shaped configuration, subjected to acoustical excitation. The principle of the mobility power flow method consists of dividing the global structure into a series of subsystems coupled together using mobility functions. Each separate subsystem is analyzed independently to determine the structural mobility functions for the junction and excitation locations. The mobility functions, together with the characteristics of the junction between the subsystems, are then used to determine the response of the global structure and the power flow. In the coupled plate structure considered here, mobility power flow expressions are derived for excitation by an incident acoustic plane wave. In this case, the forces (acoustic pressures) acting on the structure are dependent on the response of the structure because of the scattered pressure component. The interaction between the structure and the fluid leads to the derivation of a corrected mode shape for the plates' normal surface velocity and also for the structure mobility functions. The determination of the scattered pressure components in the expressions for the power flow represents an additional component in the power flow balance for the source plate and the receiver plate. This component represents the radiated acoustical power from the plate structure.
Mobility power flow analysis of coupled plate structure subjected to mechanical and acoustic excitation
The mobility power flow approach that was previously applied in the derivation of expressions for the vibrational power flow between coupled plate substructures forming an L configuration and subjected to mechanical loading is generalized. Using the generalized expressions, both point and distributed mechanical loads on one or both of the plates can be considered. The generalized approach is extended to deal with acoustic excitation of one of the plate substructures. In this case, the forces (acoustic pressures) acting on the structure are dependent on the response of the structure because of the scattered pressure component. The interaction between the plate structure and the acoustic fluid leads to the derivation of a corrected mode shape for the plates' normal surface velocity and also for the structure mobility functions. The determination of the scattered pressure components in the expressions for the power flow represents an additional component in the power flow balance for the source plate and the receiver plate. This component represents the radiated acoustical power from the plate structure. For a number of coupled plate substrates, the acoustic pressure generated by one substructure will interact with the motion of another substructure. That is, in the case of the L-shaped plate, acoustic interaction exists between the two plate substructures due to the generation of the acoustic waves by each of the substructures. An approach to deal with this phenomena is described.
The Pegasus drive - A multi-megawatt nuclear electric propulsion system
Pegasus, a power generating system for use in space, is multimegawatt power system that would enable missions of almost any conceivable duration and scope. The Pegassus Drive is the coupling of this nuclear electric power system with a 6 MWe MPD thruster. The power system has a maximum power output of 8.5 MWe. The MPD thruster requires 6 MWe to provide spacecraft propulsion and 1.5 MWe are available for mission-specific tasks and experiments. The balance of power generated is used to operate the power system. The size and mass limitations of the STS are of prime consideration in the design of this system to allow the collapsed system to be placed in lower earth orbit by two Shuttle missions. The main system (19,120 kg) employing a shadow shield would require one launch and the balance of the four-pi shield (27,830 kg) would occupy the second launch. Development of this power system could be completed by the mid 1990's and the system available near the turn of the century.
Robust Predictive Control for Modular Solid-State Transformer With Reduced DC Link and Parameter Mismatch
This paper presents the analysis and implementation of a predictive control method for dc-link regulation and voltage balance in a cascaded modular reduced dc-link solid-state transformer (SST). Passive components like bulky dc links limit the power density of power converters, especially medium-voltage (MV) SST. Reduced dc-link or low-inertia converters can dramatically reduce the size, cost, and weight by tolerating larger dc-link ripples and improve the reliability with electrolytic capacitor-less dc link. However, a small dc link leads to tight coupling between the input and the output stages, which is a challenge for control design. In stacked low-inertia converters (SLIC), the low-inertia converter modules are stacked for MV applications, resulting in coupling between the modules and making the control more challenging. A new model predictive control method which can achieve deadbeat regulation on the dc link without weighting factors has been proposed to address this novel problem. This paper focuses on analyzing the condition of the low-inertia dc link up to 80% ripple, the robustness of the control under parameter mismatches, high-order terms, and important implementation issues such as model-based sampling and computation delay compensation. Significantly, the high-order terms are introduced because of the large dc-link ripple. These high-order terms are unique to the SLIC and negligible in conventional high-inertia converters. A discrete-time large-signal model is built to capture the dc-link’s nonlinear dynamics, and the eigenvalues of a small-signal Jacobian matrix are analyzed with Floquet theory to evaluate stability, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. Simulation and experimental results of an MVDC M-S4T verify the analysis and the predictive control method. Finally, the general application of the predictive control to low-inertia converters is compared against a conventional PI controller using a reduced dc-link active-front-end (AFE) rectifier as an example.