Challenges to the Integration of Renewable Resources at High System Penetration

Successfully integrating renewable resources into the electric grid at penetration levels to meet a 33 percent Renewables Portfolio Standard for California presents diverse technical and organizational challenges. This report characterizes these challenges by coordinating problems in time and space, balancing electric power on a range of scales from microseconds to decades and from individual homes to hundreds of miles. Crucial research needs were identified related to grid operation, standards and procedures, system design and analysis, and incentives, and public engagement in each scale of analysis. Performing this coordination on more refined scales of time and space independent of any particular technology, is defined as a “smart grid.” “Smart” coordination of the grid should mitigate technical difficulties associated with intermittent and distributed generation, support grid stability and reliability, and maximize benefits to California ratepayers by using the most economic technologies, design and operating approaches

Day-Ahead Solar Resource Prediction Method Using Weather Forecasts for Peak Shaving

Due to recent concerns about energy sustainability, solar power is becoming more prevalent in distributed power generation. There are still obstacles which need to be addressed before solar power can be provided at the level of reliability that utilities require. Some of these issues can be mitigated with strategic use of energy storage. In the case of load shifting, energy storage can be used to supply solar energy during a time of day when utility customer\u27s demand is highest, thus providing partial peak load burden relief or peak shaving. Because solar resource availability is intermittent due to clouds and other atmospheric factors, charge/discharge planning must take weather into consideration. Many inter-day and intra-day solar resource prediction methods have been developed to aid in rm (high-reliability) resource establishment and peak-shaving through various methods and data sources with different levels of complexity. The purpose of this study was to investigate the use of readily-available, day-ahead National Weather Service (NWS) forecasts to develop a PV resource prediction. Using past day-ahead NWS weather forecasts and historical performance data from the Prosperity Energy Storage Project near Mesa del Sol in Albuquerque, New Mexico, several correlations were created based on regression analysis and optimized for minimal Root Mean Square (RMS) error for daily insolation prediction. Though some other methods such as the National Digital Forecast Database (NDFD) and Global Forecast System (GFS) exhibit greater accuracy, this method could prove to be a relatively simple means of planning the use of energy storage for peak-shaving or arbitrage. Additionally, given appropriate considerations for prediction uncertainty one could establish a rm resource to meet customer demand

Preliminary design of flight hardware for two-phase fluid research

This study defined the preliminary designs of flight software for the Space Shuttle Orbiter for three two-phase fluid research experiments: (1) liquid reorientation - to study the motion of liquid in tanks subjected to small accelerations; (2) pool boiling - to study low-gravity boiling from horizontal cylinders; and (3) flow boiling - to study low-gravity forced flow boiling heat transfer and flow phenomena in a heated horizontal tube. The study consisted of eight major tasks: reassessment of the existing experiment designs, assessment of the Spacelab facility approach, assessment of the individual carry-on approach, selection of the preferred approach, preliminary design of flight hardware, safety analysis, preparation of a development plan, estimates of detailed design, fabrication and ground testing costs. The most cost effective design approach for the experiments is individual carry-ons in the Orbiter middeck. The experiments were designed to fit into one or two middeck lockers. Development schedules for the detailed design, fabrication and ground testing ranged from 15 1/2 to 18 months. Minimum costs (in 1981 dollars) ranged from $463K for the liquid reorientation experiment to$998K for the pool boiling experiment

Individual risk in mean-field control models for decentralized control, with application to automated demand response

Flexibility of energy consumption can be harnessed for the purposes of ancillary services in a large power grid. In prior work by the authors a randomized control architecture is introduced for individual loads for this purpose. In examples it is shown that the control architecture can be designed so that control of the loads is easy at the grid level: Tracking of a balancing authority reference signal is possible, while ensuring that the quality of service (QoS) for each load is acceptable on average. The analysis was based on a mean field limit (as the number of loads approaches infinity), combined with an LTI-system approximation of the aggregate nonlinear model. This paper examines in depth the issue of individual risk in these systems. The main contributions of the paper are of two kinds: Risk is modeled and quantified: (i) The average performance is not an adequate measure of success. It is found empirically that a histogram of QoS is approximately Gaussian, and consequently each load will eventually receive poor service. (ii) The variance can be estimated from a refinement of the LTI model that includes a white-noise disturbance; variance is a function of the randomized policy, as well as the power spectral density of the reference signal. Additional local control can eliminate risk: (iii) The histogram of QoS is truncated through this local control, so that strict bounds on service quality are guaranteed. (iv) This has insignificant impact on the grid-level performance, beyond a modest reduction in capacity of ancillary service.Comment: Publication without appendix to appear in the 53rd IEEE Conf. on Decision and Control, December, 201

Proceedings of Small Power Systems Solar Electric Workshop. Volume 2: Invited papers

The focus of this work shop was to present the committment to the development of solar thermal power plants for a variety of applications including utility applications. Workshop activities included panel discussions, formal presentations, small group interactive discussions, question and answer periods, and informal gatherings. Discussion on topics include: (1) solar power technology options; (2) solar thermal power programs currently underway at the DOE, JPL, Electric Power Research Institute (EPRI), and Solar Energy Research Institute (SERI); (3) power options competing with solar; (4) institutional issues; (5) environmental and siting issues; (6) financial issues; (7) energy storage; (8) site requirements for experimental solar installations, and (9) utility planning

The Multi-Object, Fiber-Fed Spectrographs for SDSS and the Baryon Oscillation Spectroscopic Survey

We present the design and performance of the multi-object fiber spectrographs for the Sloan Digital Sky Survey (SDSS) and their upgrade for the Baryon Oscillation Spectroscopic Survey (BOSS). Originally commissioned in Fall 1999 on the 2.5-m aperture Sloan Telescope at Apache Point Observatory, the spectrographs produced more than 1.5 million spectra for the SDSS and SDSS-II surveys, enabling a wide variety of Galactic and extra-galactic science including the first observation of baryon acoustic oscillations in 2005. The spectrographs were upgraded in 2009 and are currently in use for BOSS, the flagship survey of the third-generation SDSS-III project. BOSS will measure redshifts of 1.35 million massive galaxies to redshift 0.7 and Lyman-alpha absorption of 160,000 high redshift quasars over 10,000 square degrees of sky, making percent level measurements of the absolute cosmic distance scale of the Universe and placing tight constraints on the equation of state of dark energy. The twin multi-object fiber spectrographs utilize a simple optical layout with reflective collimators, gratings, all-refractive cameras, and state-of-the-art CCD detectors to produce hundreds of spectra simultaneously in two channels over a bandpass covering the near ultraviolet to the near infrared, with a resolving power R = \lambda/FWHM ~ 2000. Building on proven heritage, the spectrographs were upgraded for BOSS with volume-phase holographic gratings and modern CCD detectors, improving the peak throughput by nearly a factor of two, extending the bandpass to cover 360 < \lambda < 1000 nm, and increasing the number of fibers from 640 to 1000 per exposure. In this paper we describe the original SDSS spectrograph design and the upgrades implemented for BOSS, and document the predicted and measured performances.Comment: 43 pages, 42 figures, revised according to referee report and accepted by AJ. Provides background for the instrument responsible for SDSS and BOSS spectra. 4th in a series of survey technical papers released in Summer 2012, including arXiv:1207.7137 (DR9), arXiv:1207.7326 (Spectral Classification), and arXiv:1208.0022 (BOSS Overview

Assessment of novel distributed control techniques to address network constraints with demand side management

The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid.The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid