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At least 811 records · Page 45

Techno-economic analysis of long-duration energy storage and flexible power generation technologies to support high-variable renewable energy grids

As variable renewable energy penetration increases beyond 80%, clean power systems will require long-duration energy storage or flexible, low-carbon generation. Here, we provide a detailed techno-economic evaluation and uncertainty analysis of applicable technologies and identify challenges and opportunities to support electric grid planning. We show that for a 120-h storage duration rating, hydrogen systems with geologic storage and natural gas with carbon capture are the least-cost low-carbon technologies for both current and future capital costs. These results are robust to uncertainty for the future capital cost scenario, but adiabatic compressed air and pumped thermal storage could be the least-cost technologies in the current capital cost scenario under uncertainty. Finally, we present a new storage system using heavy-duty vehicle fuel cells that could reduce the levelized cost of energy by 13%–20% compared with the best previously considered storage technology and, thus, could help enable very high (>80%) renewable energy grids.

25 ENERGY STORAGE↗

Development Status of PEM Non-Flow-Through Fuel Cell System Technology for NASA Applications

Today s widespread development of proton-exchange-membrane (PEM) fuel cell technology for commercial users owes its existence to NASA, where fuel cell technology saw its first applications. Beginning with the early Gemini and Apollo programs, and continuing to this day with the Shuttle Orbiter program, fuel cells have been a primary source of electrical power for many NASA missions. This is particularly true for manned missions, where astronauts are able to make use of the by-product of the fuel cell reaction, potable water. But fuel cells also offer advantages for unmanned missions, specifically when power requirements exceed several hundred watts and primary batteries are not a viable alternative. In recent years, NASA s Exploration Technology Development Program (ETDP) funded the development of fuel cell technology for applications that provide both primary power and regenerative fuel cell energy storage for planned Exploration missions that involved a return to the moon. Under this program, the Altair Lunar Lander was a mission requiring fuel cell primary power. There were also various Lunar Surface System applications requiring regenerative fuel cell energy storage, in which a fuel cell and electrolyzer combine to form an energy storage system with hydrogen, oxygen, and water as common reactants. Examples of these systems include habitat modules and large rovers. In FY11, the ETDP has been replaced by the Enabling Technology Development and Demonstration Program (ETDDP), with many of the same technology goals and requirements applied against NASA s revised Exploration portfolio.

Hoberecht, Mark A.↗

An integrated power/attitude control system /IPACS/ for space vehicle application

An integrated power and attitude control system (IPACS) concept with potential application to a broad class of space missions is discussed. The concept involves the storage and supply on demand of electrical energy in rotating flywheels while simultaneously providing control torques by controlled precession of the flywheels. The system is thus an alternative to the storage batteries used on present spacecraft while providing similar capability for attitude control as that represented by a control moment gyroscope (CMG) system. Potential IPACS configurations discussed include single- and double-rotor double-gimbal IPACS units. Typical sets of control laws which would manage the momentum and energy exchange between the IPACS and a typical space vehicle are discussed. Discussion of a simulation of a typical potential IPACS configuration and candidate mission concerned with pointing capability, power supply and demand flow, and discussion of the interactions between stabilization and control requirements and power flow requirements are presented.

Anderson, W. W.↗

The VOrtex Ring Transit EXperiment (VORTEX) GAS project

Get Away Special (GAS) payload G-093, also called VORTEX (VOrtex Ring Transit EXperiment), is an investigation of the propagation of a vortex ring through a liquid-gas interface in microgravity. This process results in the formation of one or more liquid droplets similar to earth based liquid atomization systems. In the absence of gravity, surface tension effects dominate the drop formation process. The Shuttle's microgravity environment allows the study of the same fluid atomization processes as using a larger drop size than is possible on Earth. This enables detailed experimental studies of the complex flow processes encountered in liquid atomization systems. With VORTEX, deformations in both the vortex ring and the fluid surface will be measured closely for the first time in a parameters range that accurately resembles liquid atomization. The experimental apparatus will record images of the interactions for analysis after the payload has been returned to earth. The current design of the VORTEX payload consists of a fluid test cell with a vortex ring generator, digital imaging system, laser illumination system, computer based controller, batteries for payload power, and an array of housekeeping and payload monitoring sensors. It is a self-contained experiment and will be flown on board the Space Shuttle in a 5 cubic feet GAS canister. The VORTEX Project is entirely run by students at the University of Michigan but is overseen by a faculty advisor acting as the payload customer and the contact person with NASA. This paper summarizes both the technical and programmatic aspects of the VORTEX Project.

Bilen, Sven G.↗

Miniature Arcs for Synthesis of Carbon Nanotubes in Microgravity

Although many methods are available for producing single-walled carbon nanotubes (SWNTs), the conventional carbon arc process remains the most popular due to its simplicity and large production rate. In the carbon arc, SWNTs are catalytically synthesized by rapidly evaporating a graphite anode impregnated with NiN metal catalyst from which the nanotubes grow in an inert atmosphere. However, high temperatures inside the carbon arc generate strong buoyancy driven convection, and it is hypothesized that the non-uniform environment created by this flow has a large effect on the growth and morphology of the SWNTs. To study the effect of buoyancy on the arc process, a miniature carbon arc apparatus was developed to synthesize SWNTs in a microgravity environment substantially free from these strong convective flows. The reactor was operated for either 2.2 or 5 seconds during free-fall in the drop towers at the NASA Glenn Research Center. Two apparatus designs differing mainly in their production rate and power capacity were investigated. The first consisted of a miniaturized carbon arc employing a 1 mm diameter graphite anode and powered by a 0.54 F capacitor bank charged to 65 V. The second, larger apparatus employed a 4 mm diameter anode and was powered by a portable battery pack capable of providing in excess of 300 amps at 30 volts to the arc for the duration of a 5 second drop. Initial results indicated that transient heating is a very large effect in the short-duration drop tower carbon arcs, and thermal equilibrium of the arc plasma, buffer gas, and apparatus was not attained during the short microgravity periods. In addition, removal of the buoyant convection by the microgravity now allowed clear observation of large jets of evaporated carbon vapor streaming from the anode and mixing with the inert buffer gas. The initial mixing of these jets with the cold buffer gas combined with the thermal transient made it difficult to establish a uniform high temperature environment around the arc in the 2.1 to 5 second microgravity time interval, and even with a very high-powered arc, the arc region was cooler than in continuously operated arcs. Despite these difficulties, the miniature arc produced SWNTs in microgravity. However, given the large thermal transient to overcome, no dramatic difference in sample yield or composition was noted between normal gravity and q2-,andL%econd long microgravity runs.

Alford, J. M.↗

Real-time Optimal Dispatch of Behind-the-Meter DERs for Secondary Frequency Regulation

Active distribution networks (ADNs) can provide grid services such as peak load shaving, loss reduction, VoltNar control, congestion management, and frequency regulation. The fast response of inverter-based distributed energy resources (DERs) and battery storage systems enables them to provide ramping support and frequency control. This paper proposes a real-time optimization approach for behind-the-meter DERs to participate in the secondary frequency regulation. The proposed approach determines optimal set-points of output power of DERs to respond to requests from system operators (SOs) in realtime to maintain the frequency of the system at the nominal value. To satisfy the real-time requirement for the secondary frequency control, the nonlinear AC power flow model is linearized considering power losses in the system to achieve both high computational speed and acceptable accuracy. The optimization problem is rerun in a closed loop manner until the mismatch between the requested power by the system operators and actual delivered power at the substation reaches an acceptable tolerance. Furthermore, the proposed approach is validated using modified versions of the IEEE 33-bus and IEEE 69-bus distribution systems. Although the contribution of a single distribution system in the frequency regulation may not be significant, stacked and coordinated contributions from several distribution systems can provide frequency regulation and other grid services at scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗

LOCOMOTIVES - Comprehensive Impact and Cost Assessment Framework of Carbon Lowering Approaches for the US Rail Freight System

The goal of this project is to develop a tool to aid railroads and other stakeholders assess and approach the decarbonization of freight rail operations by identifying new, viable low-carbon energy storage and conversion systems for future locomotive systems and how they should be deployed on the existing US freight rail network. In the first quarter, the project focused on collecting data, establishing a simulation workflow, and engaging industry through the creation of the Industry Advisory Board (IAB). In the second quarter, the project focused on selecting fuel pathways and powertrain technologies, setting performance targets, conducting a techno-economic analyses, and developing the simulation framework that would serve as the backbone of the future toolhead. The third quarter involved developing an industry-oriented interactive dashboard powered by a five-step sequential framework, as well as holding industry advisory board meetings as per the initial technology-to-market plan. In the remaining project quarters, the NUFRIEND dashboard were fine-tuned with the help of IAB member feedback and in-depth scenario analyses were conducted to support the techno-economic analysis of energy sources. Additionally, dashboard documentation, project insights, and open-source code on GitHub were prepared and released. Throughout the project, the team completed testing and analysis of all model components, integrated all initial test scenarios, and conducted stakeholder engagement. Lower-carbon drop-in fuels can be deployed as admixtures and are considered uniform across the network at a desired penetration rate, while hydrogen and battery-electric technology deployment poses a more complex problem as they require significant investments to be made in the siting of refueling/charging facilities and the replacement of locomotive fleets. Thus, strategies for locating and sizing refueling/charging facilities on a railroad’s network to meet their energy demands were developed to inform deployment decisions. To address this challenge, the Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework presents a five-step sequential framework to select O-D paths, locate facilities, reroute flows, size facilities, and evaluate the deployment for alternative energy sources that require locomotive powertrains to be converted and new refueling infrastructure to be deployed. The NUFRIEND Framework is an industry-oriented tool for simulating the deployment of new energy technologies across the US freight rail network. The framework provides a comprehensive network-level optimization and scenario simulation tool for decarbonizing the freight rail sector, addressing the uncertainties surrounding technological developments by supporting sensitivity analyses for different operational and technological parameters through a transparent and flexible input module. It offers practical alternatives to diesel locomotives and can be applied for any railroad considering the specific network structure and freight demand, outputting evaluation metrics for the associated emissions and costs relative to diesel operations. A number of relevant simulation scenarios were run and analyzed for key insights on the value of different alternative technologies for freight rail decarbonization. The project developments and findings have been presented at numerous conferences and events.

08 HYDROGEN↗

Development of a standard connector for orbital replacement units for serviceable spacecraft

The current trend for spacecraft to be serviceable and repairable in orbit has led to a modular approach to satellite subsystem design. Spacecraft equipment, such as sensors, tape recorders, computers, transponders, batteries, etc., housed in discrete modular units, (Orbital Replacement Units(ORUs)) can be attached and detached to the spacecraft as needed. The interface between the ORU and the spacecraft is crucial. The projected use of robotics and the need for a common mechanism capable of performing several functions puts many constraints on the design of the interface. Such an interface mechanisms was designed and developed called the Standard Interface Connector (SIC) that mates the ORU to the spacecraft. The SIC also provides for the flow of fluids, data, and power between the module and spacecraft. The baseline design presented can be configured to provide various attachment schemes. Tests on SIC models have demonstrated the functionality of the design and its compatibility with current robotics.

Heath, Ellen F.↗

Data-Driven Multi-agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control with High Penetration of PVs

This paper proposes a novel model-free/data-driven centralized training and decentralized execution multi-agent deep reinforcement learning (MADRL) framework for distribution system voltage control with high penetration of PVs. The proposed MADRL can coordinate both the real and reactive power control of PVs with existing static var compensators and battery storage systems. Unlike the existing DRL-based voltage control methods, our proposed method does not rely on a system model during both the training and execution stages. This is achieved by developing a new interaction scheme between the surrogate modeling of the original system and the multi-agent soft actor critic (MASAC) MADRL algorithm. In particular, the sparse pseudo-Gaussian process with a few-shots of measurements is utilized to construct the surrogate model of the original environment, i.e., power flow model. This is a data-driven process and no model parameters are needed. Furthermore, the MASAC enabled MADRL allows to achieve better scalability by dividing the original system into different voltage control regions with the aid of real and reactive power sensitivities to voltage, where each region is treated as an agent. This also serves as the foundation for the centralized training and decentralized execution, thus significantly reducing the communication requirements as only local measurements are required for control. Comparative results with other alternatives on the IEEE 123-nodes and 342-nodes systems demonstrate the superiority of the proposed method.

14 SOLAR ENERGY↗

Thermal modeling of nickel-hydrogen battery cells operating under transient orbital conditions

An analytical study of the thermal operating characteristics of nickel-hydrogen battery cells is presented. Combined finite-element and finite-difference techniques are employed to arrive at a computationally efficient composite thermal model representing a series-cell arrangement operating in conjunction with a radiately coupled baseplate and coldplate thermal bus. An aggressive, low-mass design approach indicates that thermal considerations can and should direct the design of the thermal bus arrangement. Special consideration is given to the potential for mixed conductive and convective processes across the hydrogen gap. Results of a compressible flow model are presented and indicate the transfer process is suitably represented by molecular conduction. A high-fidelity thermal model of the cell stack (and related components) indicates the presence of axial and radial temperature gradients. A detailed model of the thermal bus reveals the thermal interaction of individual cells and is imperative for assessing the intercell temperature gradients.

Schrage, Dean S.↗

Astronaut Thermal Exposure: Re-Entry After Low Earth Orbit Rescue Mission

The STS-125 mission, launched May 11, 2009, is the final servicing mission to the Hubble Space Telescope. The repair mission's EVA tasks are described, including: installing a new wide field camera; installing the Cosmic Origins Spectrograph; repairing the Space Telescope Imaging Spectrograph; installing a new outer blanket layer; adding a Soft Capture and Rendezvous System for eventual controlled deorbit in about 2014; replacing the 'A' side Science Instrument Command and Data Handling module; repairing the Advanced Camera for surveys; and, replacing the rate sensor unit gyroscopes, fine guidance sensors and 3 batteries. Additionally, the Shuttle crew cabin thermal environment is described. A CFD model of per person CO2 demonstrates a discrepancy between crew breathing volume and general mid-deck levels of CO2. A follow-on CFD analysis of the mid-deck temperature distribution is provided. Procedural and engineering mitigation plans are presented to counteract thermal exposure upon reentry to the Earth atmosphere. Some of the procedures include: full cold soak the night prior to deorbit; modifying deck stowage to reduce interference with air flow; and early securing of avionics post-landing to reduce cabin thermal load prior to hatch opening. Engineering mitigation activities include modifying the location of the aft starboard ICUs, eliminating the X3 stack and eliminating ICU exhaust air directed onto astronauts; improved engineering data of ICU performance; and, verifying the adequacy of mid-deck temperature control using CFD models in addition to lumped parameter models. Post-mitigation CFD models of mid-deck temperature profiles and distribution are provided.

Gillis, David B.↗

Process for Upgrading Cognitive Assessment Capabilities Onboard the International Space Station

MOTIVATION: Spaceflight poses varied and unique risks to the brain and cognitive functioning including radiation exposure, sleep disturbance, fatigue, fluid shifts (increased intracranial pressure), toxin exposure, elevated carbon dioxide, and traumatic brain injury, among others. These potential threats to cognitive functioning are capable of degrading performance and compromising mission success. Furthermore, the threats may increase in severity, and new types of threats may emerge for longer duration exploration missions. This presentation will describe the process used to identify gaps in our current approach, evaluate best practices in cognitive assessment, and transition new cognitive assessment tools to operational use. OVERVIEW: Risks to brain health and performance posed by spaceflight missions require sensitive tools to assess cognitive functioning of astronauts in flight. The Spaceflight Cognitive Assessment Tool for Windows (WinSCAT) is the automated cognitive assessment tool currently deployed onboard the International Space Station (ISS). WinSCAT provides astronauts and flight surgeons with objective data to monitor neurocognitive functioning. WinSCAT assesses 5 discrete cognitive domains, is sensitive to changes in cognitive functioning, and was designed to be completed in less than 15 minutes. However, WinSCAT does not probe other areas of cognitive functioning that might be important to mission success. Researchers recently have developed batteries that may expand current capabilities, such as increased sensitivity to subtle fluctuations in cognitive functioning. Therefore, we engaged in a systematic process review in order to improve upon our current capabilities and incorporate new advances in cognitive assessment. This process included a literature review on newer measures of neurocognitive assessment, surveys of operational flight surgeons at NASA regarding needs and gaps in our capabilities, and expert panel review of candidate cognitive measures and assessment issues and procedures. SIGNIFICANCE: Our process and the results that flowed from it may be helpful to aeromedical professionals charged with transitioning research findings to operational use. Our specific findings regarding cognitive assessment tools are of significance to professionals who must assess readiness to perform in mission critical situations in environments involving threats to cognition and performance

Picano, J. J.↗

A Dataset of 3D Structural and Simulated Transport Properties of Complex Porous Media

Physical processes that occur within porous materials have wide-ranging applications including - but not limited to - carbon sequestration, battery technology, membranes, oil and gas, geothermal energy, nuclear waste disposal, water resource management. The equations that describe these physical processes have been studied extensively; however, approximating them numerically requires immense computational resources due to the complex behavior that arises from the geometrically-intricate solid boundary conditions in porous materials. Here, we introduce a new dataset of unprecedented scale and breadth, DRP-372: a catalog of 3D geometries, simulation results, and structural properties of samples hosted on the Digital Rocks Portal. The dataset includes 1736 flow and electrical simulation results on 217 samples, which required more than 500 core years of computation. This data can be used for many purposes, such as constructing empirical models, validating new simulation codes, and developing machine learning algorithms that closely match the extensive purely-physical simulation. This article offers a detailed description of the contents of the dataset including the data collection, simulation schemes, and data validation.

3D images↗

A Low-Flow Marine Hydrokinetic Turbine for a Floating Unmanned Mobile Platform

Design and fabrication of a marine hydrokinetic turbine for deployment from a floating unmanned autonomous mobile catamaran platform is described. The objective is to develop a low-flow current turbine for deployment from a floating mobile catamaran USV platform. An undershot water wheel has been selected as the turbine of choice and a WAM-V 16 catamaran has been selected as the USV platform. The concept of operation is that the USV platform would autonomously seek and navigate to a coastal location where coastal or tidal currents may be present, anchor at the location, and deploy the turbine to harness the current energy, convert it to electricity and store it in onboard battery banks. The prototype system being developed is targeted at supporting development of self-powered autonomous mobile recharge stations for unmanned aerial vehicles in coastal zones. Once implemented on the vehicle, open water tests are planned for a range of environmental conditions, involving tidal and coastal currents, and system configurations. The status of the ongoing effort will be discussed.

16 TIDAL AND WAVE POWER↗

Distribution System Blackstart and Restoration Using DERs and Dynamically Formed Microgrids

Extreme weather events have led to long-duration outages in the distribution system (DS), necessitating novel approaches to blackstart and restore the system. Existing blackstart solutions utilize blackstart units to establish multiple microgrids (MGs), sequentially energize non-blackstart units, and restore loads. However, these approaches often result in isolated MGs. In DERs-aided blackstart, the continuous operation of these MGs is limited by the finite energy capacity of commonly used blackstart units like battery energy storage (BES)-based gridforming inverters (GFMIs). To address this issue, this article proposes a holistic blackstart and restoration framework that incorporates synchronization between dynamic MGs and the entire DS with the transmission grid (TG). To support synchronization, we leveraged virtual synchronous generator-based control for GFMIs to estimate their frequency response to load pick-up events using only initial/final quasi-steady-state points. Subsequently, a synchronization switching condition is developed to model synchronizing switches, aligning them seamlessly with a linearized branch flow problem. Finally, we designed a bottomup blackstart and restoration framework that considers the switching structure of the DS, energizing/synchronizing switches, DERs with grid-following inverters, and BES-based GFMIs with frequency security constraints. In conclusion, the proposed framework is validated in IEEE-123-bus system, considering cases with two and four GFMIs under various TG recovery instants.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Integral Battery Power Limiting Circuit for Intrinsically Safe Applications

A circuit topology has been designed to guarantee the output of intrinsically safe power for the operation of electrical devices in a hazardous environment. This design uses a MOSFET (metal oxide semiconductor field-effect transistor) as a switch to connect and disconnect power to a load. A test current is provided through a separate path to the load for monitoring by a comparator against a preset threshold level. The circuit is configured so that the test current will detect a fault in the load and open the switch before the main current can respond. The main current passes through the switch and then an inductor. When a fault occurs in the load, the current through the inductor cannot change immediately, but the voltage drops immediately to safe levels. The comparator detects this drop and opens the switch before the current in the inductor has a chance to respond. This circuit protects both the current and voltage from exceeding safe levels. Typically, this type of protection is accomplished by a fuse or a circuit breaker, but in order for a fuse or a circuit breaker to blow or trip, the current must exceed the safe levels momentarily, which may be just enough time to ignite anything in a hazardous environment. To prevent this from happening, a fuse is typically current-limited by the addition of the resistor to keep the current within safe levels while the fuse reacts. The use of a resistor is acceptable for non-battery applications where the wasted energy and voltage drop across the resistor can be tolerated. The use of the switch and inductor minimizes the wasted energy. For example, a circuit runs from a 3.6-V battery that must be current-limited to 200 mA. If the circuit normally draws 10 mA, then an 18-ohm resistor would drop 180 mV during normal operation, while a typical switch (0.02 ohm) and inductor (0.97 ohm) would only drop 9.9 mV. From a power standpoint, the current-limiting resistor protection circuit wastes about 18 times more power than the switch and the inductor configuration. In the fault condition, both the resistor and the inductor react immediately. The resistor reacts by allowing more current to flow and dropping the voltage. Initially, the inductor reacts by dropping the voltage, and then by not allowing the current to change. When the comparator detects the drop in voltage, it opens the switch, thus preventing any further current flow. The inductor alone is not sufficient protection, because after the voltage drop has settled, the inductor would then allow the current to change, in this example, the current would be 3.7 A. In the fault condition, the resistor is flowing 200 mA until the fuse blows (anywhere from 1 ms to 100 s), while the switch and inductor combination is flowing about 2 A test current while monitoring for the fault to be corrected. Finally, as an additional safety feature, the circuit can be configured to hold the switch opened until both the load and source are disconnected.

Burns, Bradley M.↗

Hybrid-RL-MPC4CLR (Hybird-Reinforcement-Learning-Model-Predictive-Control-for-Reserve-Policy-Assisted-Critical-Load-Restoration-in-Distribution-Grids)

Hybrid-RL-MPC4CLR was developed as a hybrid controller for active distribution grid critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. The RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while the MPC models grid operations incorporating the RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. The developers formulated the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The software is developed using various software packages in Python. The MPC's optimal power flow (OPF) model is implemented using the Pyomo package, the RL simulation environment is implemented using the MPC simulation with various scenarios of renewable energy and load demand profiles and power outage beginning times, based on the OpenAI Gym framework. The RL agent training is performed using the RLlib Ray package. The RL algorithm is trained offline using historical forecasts of renewable generation and load demand profiles. Simulation analysis and performance tests are conducted using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery.

Eseye, Abinet Tesfaye↗

Application of Hybrid Optimization-Expert System for Optimal Power Management on Board Space Power Station

The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.

Momoh, James↗