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Model Predictive Control of Integrated Gasification Combined Cycle Power Plants
The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.
Key Residential Building Equipment Technologies for Control and Grid Support PART I (Residential)
Electrical energy consumption of the residential sector is a crucial area of research that has in the past primarily focused on increasing the efficiency of household devices such as water heaters, dishwashers, air conditioners, and clothes washer and dryer units. However, the focus of this research is shifting as objectives such as developing the smart grid and ensuring that the power system remains reliable come to the fore, along with the increasing need to reduce energy use and costs. Load research has started to focus on mechanisms to support the power system through demand reduction and/or reliability services. The power system relies on matching generation and load, and day-ahead and real-time energy markets capture most of this need. However, a separate set of grid services exist to address the discrepancies in load and generation arising from contingencies and operational mismatches, and to ensure that the transmission system is available for delivery of power from generation to load. Currently, these grid services are mostly provided by generation resources. The addition of renewable resources with their inherent variability can complicate the issue of power system reliability and lead to the increased need for grid services. Using load as a resource, through demand response programs, can fill the additional need for flexible resources and even reduce costly energy peaks. Loads have been shown to have response that is equal to or better than generation in some cases. Furthermore, price-incentivized demand response programs have been shown to reduce the peak energy requirements, thereby affecting the wholesale market efficiency and overall energy prices. The residential sector is not only the largest consumer of electrical energy in the United States, but also has the highest potential to provide demand reduction and power system support, as technological advancements in load control, sensor technologies, and communication are made. The prevailing loads based on the largest electrical energy consumers in the residential sector are space heating and cooling, washer and dryer, water heating, lighting, computers and electronics, dishwasher and range, and refrigeration. As the largest loads, these loads provide the highest potential for delivering demand response and reliability services. Many residential loads have inherent flexibility that is related to the purpose of the load. Depending on the load type, electric power consumption levels can either be ramped, changed in a step-change fashion, or completely removed. Loads with only on-off capability (such as clothes washers and dryers) provide less flexibility than resources that can be ramped or step-changed. Add-on devices may be able to provide extra demand response capabilities. Still, operating residential loads effectively requires awareness of the delicate balance of occupants health and comfort and electrical energy consumption. This report is Phase I of a series of reports aimed at identifying gaps in automated home energy management systems for incorporation of building appliances, vehicles, and renewable adoption into a smart grid, specifically with the intent of examining demand response and load factor control for power system support. The objective is to capture existing gaps in load control, energy management systems, and sensor technology with consideration of PHEV and renewable technologies to establish areas of research for the Department of Energy. In this report, (1) data is collected and examined from state of the art homes to characterize the primary residential loads as well as PHEVs and photovoltaic for potential adoption into energy management control strategies; and (2) demand response rules and requirements across the various demand response programs are examined for potential participation of residential loads. This report will be followed by a Phase II report aimed at identifying the current state of technology of energy management systems, sensors, and communication technologies for demand response and load factor control applications for the residential sector. The purpose is to cover the gaps that exist in the information captured by the sensors for energy management system to be able to provide demand response and load factor control. The vision is the development of an energy management system or other controlling enterprise hardware and software that is not only able to control loads, PHEVs, and renewable generation for demand response and load factor control, but also to do so with consumer comforts in mind and in an optimal fashion.
New demands, new supplies : a national look at the water balance of carbon dioxide capture and sequestration.
Concerns over rising concentrations of greenhouse gases in the atmosphere have resulted in serious consideration of policies aimed at reduction of anthropogenic carbon dioxide (CO2) emissions. If large scale abatement efforts are undertaken, one critical tool will be geologic sequestration of CO2 captured from large point sources, specifically coal and natural gas fired power plants. Current CO2 capture technologies exact a substantial energy penalty on the source power plant, which must be offset with make-up power. Water demands increase at the source plant due to added cooling loads. In addition, new water demand is created by water requirements associated with generation of the make-up power. At the sequestration site however, saline water may be extracted to manage CO2 plum migration and pressure build up in the geologic formation. Thus, while CO2 capture creates new water demands, CO2 sequestration has the potential to create new supplies. Some or all of the added demand may be offset by treatment and use of the saline waters extracted from geologic formations during CO2 sequestration. Sandia National Laboratories, with guidance and support from the National Energy Technology Laboratory, is creating a model to evaluate the potential for a combined approach to saline formations, as a sink for CO2 and a source for saline waters that can be treated and beneficially reused to serve power plant water demands. This presentation will focus on the magnitude of added U.S. power plant water demand under different CO2 emissions reduction scenarios, and the portion of added demand that might be offset by saline waters extracted during the CO2 sequestration process.
System Study: Emergency Power System 1998–2013
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 fiscal year 1998 through 2013 for selected components were obtained from the Institute of Nuclear Power Operations (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 trends were identified in the EPS results.
Energy Conversion Loop: Process Heat Applications of Hybrid Energy Systems
Climate change due to greenhouse gas (GHG) emissions has prompted a shift from fossil fuel energy to other sources for electricity production such as nuclear, solar or wind. These alternatives since no GHG is produced, and no fossil fuels are burned. Both nuclear and other renewable energy sources are recognized as reliable technologies in the United States and around the world. However, they all have a unique set of challenges. Two of the most common renewable energy sources are solar and wind. A particular shortcoming of these two options is the variability of the energy produced; that is they are highly dependent on weather. Many times wind and/or solar power systems are not able to meet the electric demand during peak times. Replacing fossil fuels with nuclear energy is an option (non fossil fuel) for clean energy production. Two primary challenges with using nuclear energy are; wasted heat energy and the lack of load following capabilities. First, heat energy is wasted in the production stream from steam that is created while cooling the core of a nuclear reactor. This steam is initially used in turbines where the electricity is produced. However, once the steam passes through the turbines it is cooled, re-condensed to water, and reused. Large amounts of heat energy are released in the form of heat to the environment (either to the atmosphere or as waste water) and go unused. Secondly, nuclear energy is primarily a baseload power producer - the power output does not fluctuate with power demands, or is not load following. A nuclear hybrid energy system (NHES) may be a solution to the two issues mentions above. Traditional hybrid energy systems (HES) are a combination of two or more energy producers working together to create different energy commodities such as fuel or electricity. To create a NHES, normal use of the reactor for electricity production is combined with renewable power sources to meet the peak power demand of the grid. When electricity demand is high the renewable source and NPP are used in conjunction to meet the demand. When the electricity demand is low the renewable power is used to produce electricity while the NPP operates at full capacity. Rather than sending the excess heat to the cooling towers the excess energy created by the NPP (heat) is diverted to another industrial process.There is no need to decrease the power coming out of the NPP. This research proposal addresses harvesting unused thermal energy from a NPP during normal operations and in times of low power demand.
Outlook on Industrial Requirements for Incorporating Nuclear Energy into Industrial Processes
There is an increasing interest globally and in the U.S. in decarbonizing heavy industrial processes which have large demands for heat and power. Currently these industries primarily use fossil fuels to meet these demands and they include: oil & gas, petroleum refining, chemicals and derivative products manufacturing, iron & steel production, polymers, ammonia and fertilizers, etc. The U.S. DOE Integrated Energy Systems (IES) program seeks to identify and analyze opportunities for integrating and substituting nuclear energy to fulfil these large heat and power demands in a cost competitive and sustainable manner while reducing carbon emissions of the processes by using clean nuclear power. Presently various representatives from a subset of these industrial companies have expressed interest in evaluating the options of integrating future advanced nuclear small modular reactors with their industries. This study is a scoping study to provide an outlook of industrial energy demands and the potential nuclear energy substitution potential. Future work will analyze in a more detailed manner the potential designs for coupling advanced nuclear reactors with various industries. The industrial processes of oil refining, methanol production, pulp and paper, ammonia and chlorine-alkali are described focusing on how heat and power is used within the facilities in the context of identifying nuclear substitution opportunities. The aim is to provide reliable, competitive, and sustainable energy that is clean while reducing carbon emissions and other environmental impacts such as water withdrawals, consumption, and contamination.
Decentralized control of units in smart grids for the support of renewable energy supply
Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced by a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10{sup 100} feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets. - Highlights: • Distributed load management for electrical vehicles supports local supply from PV. • Appliances can self-organize into so called virtual appliances for load control. • Dynamic VPPs can be controlled by extensively decentralized control centers. • Flexibilities of units can efficiently be represented by support-vector descriptions.
Optics Enabled Networks and Architectures for Data Center Cost and Power Efficiency
Bandwidth demand for datacenter networks continues as performance increases and is further fueled by the exploding demand for AI and new HPC workloads. Managing power and costs will require a range of solutions including new networking and workload specialized architectures, composable systems and optical circuit switching. In this study we focus primarily on two topics, examining the benefits of flatter networks (enabled mainly by means of co-packaged-optics-enabled switches) and the utilization improvement potential for composable (disaggregated) systems, while discussing specialized hardware and networks, and optical circuit switching more briefly.
Simulating Discharge Curves of an All-Aqueous TRAB to Identify Pathways for Improving System Performance
Thermally regenerative ammonia batteries (TRABs) are an emerging technology that use low temperature heat (T < 150 °C) to recharge a flow battery that produces electrical power on demand. The all-aqueous copper TRAB can provide high power densities and thermal energy efficiencies relative to other devices that harvest energy from waste heat, but its performance is adversely impacted by the crossover of undesired species through the membrane and lower cell voltages compared to conventional batteries. In this work, we developed a numerical model to simulate discharge curves while accounting for crossover inefficiencies without tracking all electrolyte species through the membrane. The model was able to successfully reproduce discharge curves across a diverse range of battery conditions using a single fitting parameter to account for decay of electrode standard potential due to species crossover with minimal error (< 5%). The model was then used to simulate different design scenarios to estimate changes in energy output from alterations to the aspects of the battery electrolyte chemistry. Results from this study are used to identify pathways for improving future TRAB designs with respect to energy capacity and cost-effectiveness of the technology.
Drivers for the Value of Demand Response under Increased Levels of Wind and Solar Power; NREL (National Renewable Energy Laboratory)
Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, like storage, can easily saturate ancillary service markets.
Deliverable Flexible Ramping Products Considering Spatiotemporal Correlation of Wind Generation and Demand Uncertainties
Flexible ramping products (FRPs) have been implemented by several independent system operators (ISOs) to procure adequate flexible resources. Currently, system operators estimate the system level ramping requirements ignoring the spatiotemporal correlations among various uncertainty sources. This leads to overestimates/underestimates of ramping requirements. In addition, the explicit FRPs model considers only the generation ramping limitation. Other security constraints, such as the transmission limits, are not considered, which leads to deliverability issues of FRPs. To deal with these shortcomings of current FRPs models, this paper proposes a deliverable FRPs based on a distributionally-robust chance constrained multi-interval optimal power flow (DRCC-MIOPF) considering the spatiotemporal correlation of wind power and demand uncertainties endogenously. Furthermore, an asymmetrical affine policy (AAP) is proposed to leverage generation flexibility and mitigate the uncertainty in different directions. The pricing mechanism of the FRPs is proposed using a novel uncertainty-contained locational marginal price (U_LMP) which is derived from the proposed AAP-DRCC-MIOPF model. New components representing the price of FRPs are added into the traditional LMP formulation. Finally, the PJM 5-bus, IEEE 39-bus and IEEE 118-bus systems case studies validate the proposed FRPs approach. The payment of uncertain demand and wind power on FRPs are analyzed.
Power Sources for Micro-Autonomous Vehicles- Challenges and Prospects
Micro-autonomous vehicle systems are expected to have expanded role in military missions by providing full spectrum intelligence, surveillance and reconnaissance support on the battlefield, suppression of enemy defenses, and enabling co-operative (swarm-like) configurations. Of the numerous demanding requirements of autonomy, sensing, navigation, mobility, etc., meeting the requirement of mission duration or endurance is a very challenging one. This requirement is demanding because of the constraints of mass and volume that limit the quantity of energy that can be stored on-board. Energy is required for mobility, payload operation, information processing, and communication. Mobility requirements typically place an extraordinary demand on the specific energy (Wh/kg) and specific power (W/kg) of the power source; the actual distribution of the energy between mobility and other system functions could vary substantially with the mission type. The power requirements for continuous mobility can vary from 100-1000 W/kg depending on the terrain, ground speed and flight speed. Even with the power source accounting for 30% of the mass of the vehicle, the best of rechargeable batteries can provide only up to 1-2 hours of run-time for a continuous power demand at 100W/kg. In the case of micro-aerial vehicles with flight speed requirements in the range of 5-15 m s-1, the mission times rarely exceed 20 minutes [2]. Further, the power required during take-off and hover can be twice or thrice that needed for steady level flight, and thus the number and sequence of such events is also limited by the mass and size of the power source. For operations such as "perch and stare" or "silent watch" the power demand is often only a tenth of that required during continuous flight. Thus, variation in power demand during various phases of the mission importantly affects the power source selection.
Coordinating Demand-Side Efficiency Evaluation, Measurement and Verification Among Western States: Options for Documenting Energy and Non-Energy Impacts for the Power Sector
Demand-side energy efficiency (efficiency) represents a low-cost opportunity to reduce electricity consumption and demand and provide a wide range of non-energy benefits, including avoiding air pollution. Efficiency-related energy and non-energy impacts are determined and documented by implementing evaluation, measurement and verification (EM&V) systems. This technical brief describes efficiency EM&V coordination strategies that Western states can consider taking on together, outlines EM&V-related products that might be appropriate for multistate coordination, and identifies some implications of coordination. Coordinating efficiency EM&V activities can save both time and costs for state agencies and stakeholders engaged in efficiency activities and can be particularly beneficial for multiple states served by the same utility. First, the brief summarizes basic information on efficiency, its myriad potential benefits and EM&V for assessing those benefits. Second, the brief introduces the concept of multistate EM&V coordination in the context of assessing such benefits, including achievement of state and federal goals to reduce air pollutants.1 Next, the brief presents three coordination strategy options for efficiency EM&V: information clearinghouse/exchange, EM&V product development, and a regional energy efficiency tracking system platform. The brief then describes five regional EM&V products that could be developed on a multistate basis: EM&V reporting formats, database of consistent deemed electricity savings values, glossary of definitions and concepts, efficiency EM&V methodologies, and EM&V professional standards or accreditation processes. Finally, the brief discusses options for next steps that Western states can take to consider multistate coordination on efficiency EM&V. Appendices provide background information on efficiency and EM&V, as well as definitions and suggested resources on the covered topics. This brief is intended to inform state public utility commissions, boards for public and consumer-owned utilities, state energy offices and air agencies, and other organizations involved in discussions about the use of efficiency EM&V.
Smart Grid and Smart Cities
We hope the proceedings will offer the readers a good opportunity to explore the state-of-the art developments and future directions of researches on smart grid and smart cities. These conferences covered the recent trends and progresses made in the field of smart grid and smart cities. For the past few years, smart grids have been one of the main topics in research and development at academic, industry, business and government level. The smart grid is envisaged to be the next generation electric grid for Smart Cities. It enables the smart integration of conventional power generation, renewable generation, distributed generation, energy storage, transmission, distribution and demand management. The benefits of smart grid include the enhanced reliability and resilience, higher intelligence and optimized control, decentralized operation, higher operational efficiency, more efficient demand management, and better power quality. However, all these prospected transformations also bring with them numerous challenges and opportunities. The conference program covers keynotes, invited, oral and poster presentations. The keynotes and invited talks are focused on the potential application of smart grid and smart cities in various fields of application. Among 105 full length articles submitted to the conference, 59 manuscripts were accepted after a thorough peer reviews and were recommended for presentations and publication in this proceedings.
An Automatic Learning Framework for Smart Residential Communities
Predictability has been foundational to matching supply and demand in the day-to-day operation of the electric power system. Demand predictability is eroding because of the increased use of renewable energy resources and more sophisticated loads, such as electric vehicles and smart appliances. In this paper, an automatic software framework is described which can be used for load forecasting in smart communities. A time-varying clustering-based Markov chain approach is used to predict the energy consumption of residential buildings in a smart community. The training data is based on 1-minute meter data of occupied homes over one month. The data points are first clustered based on the energy consumption and the time of the day. Then, the original data is converted using the Centroids of the clusters. A time-varying Markov chain is subsequently trained to model the energy consumption behavior of residents for each home using the transformed data. The trained model is shown to successfully predict load in 5-minute intervals over a 24 hours period.
Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration
Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.
Landmark Report Analyzes Current State of U.S. Offshore Wind Industry (Fact Sheet)
New report assesses offshore wind industry, offshore wind resource, technology challenges, economics, permitting procedures, and potential risks and benefits. The National Renewable Energy Laboratory (NREL) recently published a new report that analyzes the current state of the offshore wind energy industry, Large-Scale Offshore Wind Power in the United States. It provides a broad understanding of the offshore wind resource, and details the associated technology challenges, economics, permitting procedures, and potential risks and benefits of developing this clean, domestic, renewable resource. The United States possesses large and accessible offshore wind energy resources. The availability of these strong offshore winds close to major U.S. coastal cities significantly reduces power transmission issues. The report estimates that U.S. offshore winds have a gross potential generating capacity four times greater than the nation's present electric capacity. According to the report, developing the offshore wind resource along U.S. coastlines and in the Great Lakes would help the nation: (1) Achieve 20% of its electricity from wind by 2030 - Offshore wind could supply 54 gigawatts of wind capacity to the nation's electrical grid, increasing energy security, reducing air and water pollution, and stimulating the domestic economy. (2) Provide clean power to its coastal demand centers - Wind power emits no carbon dioxide (CO2) and there are plentiful winds off the coasts of 26 states. (3) Revitalize its manufacturing sector - Building 54 GW of offshore wind energy facilities would generate an estimated $200 billion in new economic activity, and create more than 43,000 permanent, well-paid technical jobs in manufacturing, construction, engineering, operations and maintenance. NREL's report concludes that the development of the nation's offshore wind resources can provide many potential benefits, and with effective research, policies, and commitment, offshore wind energy can play a vital role in future U.S. energy markets.