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A simulator which generates and transmits a beam of audible sound energy mathematically similar to the SPS power beam is described. The simulator provides a laboratory means for analysis of ground based closed loop SPS phase control and of ionospheric effects on the SPS microwave power beam.
Detailed information on the environmental conditions on Mars are very desirable for the design of photovoltaic systems for establishing outposts on the Martian surface. The variation of solar insolation (global, direct, and diffuse) at the Viking lander's locations is addressed. It can be used, to a first approximation, for other latitudes. The radiation data is based on measured optical depth of the Martian atmosphere derived from images taken of the sun with a special diode on the Viking cameras; and computation based on multiple wavelength and multiple scattering of the solar radiation. The data are used to make estimates of photovoltaic system power, area and mass for a surface power system using regenerative fuel cells for storage and nighttime operation.
The launch of the Space Station Freedom solar power module requires a weight efficient structure that will include large components within the limited load capacity of the Space Shuttle cargo bay. The design iterations to meet these requirements have evolved from a proposal concept featuring a separate cradle and integrated equipment assembly (IEA), to a package that interfaces directly with the Shuttle. Size, weight, and cost have been reduced as a result.
Detailed information on the environmental conditions on Mars are very desirable for the design of photovoltaic systems for establishing outposts on the Martian surface. The variation of solar insolation (global, direct, and diffuse) at the Viking lander's locations is addressed. It can be used, to a first approximation, for other latitudes. The radiation data is based on measured optical depth of the Martian atmosphere derived from images taken of the sun with a special diode on the Viking cameras; and computation based on multiple wavelength and multiple scattering of the solar radiation. The data are used to make estimates of photovoltaic system power, area and mass for a surface power system using regenerative fuel cells for storage and nighttime operation.
System Power Analysis for Capability Evaluation (SPACE) is a computer model of the International Space Station's (ISS) Electric Power System (EPS) developed at the NASA Glenn Research Center. This uniquely integrated, detailed model can predict EPS capability, assess EPS performance during a given mission with a specified load demand, conduct what-if studies, and support on-orbit anomaly resolution.
UNKNOWN
Abstract not provided.
In the development of smart grid at distribution level, the realization of real-time nodal pricing is one of the key challenges. The research work in this paper implements and studies the methodology of locational marginal pricing at distribution level based on a real-world distribution power system. The pricing mechanism utilizes optimal power flow to calculate the corresponding distributional nodal prices. Both Direct Current Optimal Power Flow and Alternate Current Optimal Power Flow are utilized to calculate and analyze the nodal prices. The University of Denver campus power grid is used as the power distribution system test bed to demonstrate the pricing methodology.
Hydro power is one of the most flexible sources of electricity production. Power systems with considerable amounts of flexible hydro power potentially offer easier integration of variable generation, e.g., wind and solar. However, there exist operational constraints to ensure mid-/long-term security of supply while keeping river flows and reservoirs levels within permitted limits. In order to properly assess the effective available hydro power flexibility and its value for storage, a detailed assessment of hydro power is essential. Due to the inherent uncertainty of the weather-dependent hydrological cycle, regulation constraints on the hydro system, and uncertainty of internal load as well as variable generation (wind and solar), this assessment is complex. Hence, it requires proper modeling of all the underlying interactions between hydro power and the power system, with a large share of other variable renewables. A summary of existing experience of wind integration in hydro-dominated power systems clearly points to strict simulation methodologies. Recommendations include requirements for techno-economic models to correctly assess strategies for hydro power and pumped storage dispatch. These models are based not only on seasonal water inflow variations but also on variable generation, and all these are in time horizons from very short term up to multiple years, depending on the studied system. Another important recommendation is to include a geographically detailed description of hydro power systems, rivers' flows, and reservoirs as well as grid topology and congestion.
The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.
Increasingly frequent severe weather events in recent years threaten the security of power systems and result in major power outages throughout the world. The development of reasonable power system restoration (PSR) solutions is therefore urgently needed to speed up the recovery of the power supply while at the same time steering clear of vulnerable and risky equipment. This paper aims to develop a case-sensitive PSR model for power transmission systems that can adjust restoration solutions according to the evaluated availability of outage equipment in specific blackout scenarios and weather conditions. A novel PSR model that integrates the startup of generating units, formulation of the restoration network, renewable energy sources, and availability assessment of devices is proposed. A reformulated model is also proposed to relieve the computational burden of complex PSR problems. The availability of outage equipment is comprehensively assessed based on historical operating records, fault diagnosis results, and weather conditions. The assessed availability results are sensitive to the characteristics of real blackout cases and will support system operators generate case-sensitive PSR solutions while mitigating the vulnerable equipment. The feasibility and effectiveness of the proposed PSR model and its reformulations are verified through case studies.
The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.
Power system dynamics are generally modeled by high dimensional nonlinear differential-algebraic equations due to a large number of generators, loads, and transmission lines. Thus, its computational complexity grows exponentially with the system size. This paper demonstrates the potential use of quantum computing algorithms to model the power system dynamics. Leveraging a symbolic programming framework, we equivalently convert the power system dynamics’ differential algebraic equations (DAEs) into ordinary differential equations (ODEs), where the data of the state vector can be encoded into quantum computers via amplitude encoding. The system's nonlinearity is captured by Taylor polynomial expansion, the quantum state tensor, and Hamiltonian simulation, whereas state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can simulate the dynamics of the power system with high accuracy, whereas its complexity is polynomial in the logarithm of the system dimension. Our work also illustrates the use of scientific machine learning tools for implementing scientific computing concepts, e.g., Taylor expansion, DAEs/ODEs transform, and quantum computing solver, in the field of power engineering.
This report presents an unreliability evaluation of the emergency power system (EPS) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from 1998 through 2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. Statistically significant decreasing trends were identified in the industry-wide estimates of EPS system start-only mission as well as EPS system unreliability (8-hour mission).
This report presents an unreliability evaluation of the emergency power system (EPS) at 104 U.S. commercial nuclear power plants. Demand, run hours, and failure data from 1998 through 2018 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the EPS results.
This paper presents a test bed that utilities, vendors, and researchers can use to evaluate the performance of existing and emerging advanced distribution management systems (ADMS) or specific applications of such systems. The test bed provides a realistic laboratory test setting, including detailed modeling of the power system, controller and/or power hardware, and industry-standard communication protocols. The test bed can further represent the current state of a specific utility's distribution system or the anticipated state with increased penetrations of distributed energy resources, such as rooftop photovoltaic systems, residential battery energy storage systems, electric vehicles, and loads with smart controls. The paper describes the design and implementation of the test bed. We present two use cases of the test bed and preliminary results for these two use cases. We also discuss upcoming and potential future use cases. Results from test bed experiments are intended to accelerate industry deployment of ADMS technologies and advance development of ADMS capabilities.
This paper presents a test bed that utilities, vendors, and researchers can use to evaluate the performance of existing and emerging advanced distribution management systems (ADMS) or specific applications of such systems. The test bed provides a realistic laboratory test setting, including detailed modeling of the power system, controller and/or power hardware, and industry-standard communication protocols. The test bed can further represent the current state of a specific utility's distribution system or the anticipated state with increased penetrations of distributed energy resources, such as rooftop photovoltaic systems, residential battery energy storage systems, electric vehicles, and loads with smart controls. The paper describes the design and implementation of the test bed. We present two use cases of the test bed and preliminary results for these two use cases. We also discuss upcoming and potential future use cases. Results from test bed experiments can be used to accelerate industry deployment of ADMS technologies and advance development of ADMS capabilities.
The electric power system is intrinsically a cyber‐physical system (CPS) with power flowing inthe physical system and information flowing in the cyber‐network. Testbeds arecrucial for understanding the cyber‐physical interactions and provideenvironments for prototyping novel applications. This study proposes afour‐layer architecture for CPS testbeds with emphases on communication networkemulation and networked physical components. A configurable software‐definednetwork is employed to bridge physical components with wide‐area applicationsfor closed‐loop control. In order to distribute physically coupled devices intomultiple software simulations, this study proposes a data broker setup based ona distributed messaging environment to achieve low‐latency data streaming. Thedecoupled design with data streaming allows for building testbed components asmodules and running them in a distributed manner. Case studies verify the databroker setup for low‐latency sensing and actuation, as well as the communicationemulation setup for the desired network latency. Also illustrated is a replayattack scenario using synchrophasors in the Western Electricity CoordinatingCouncil (WECC) 181‐bus system for demonstrating the closed‐loop cyber‐physicalsimulation capability of the testbed.