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Renewable Energy Analysis Lab - Reasearch
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When running a power system to supply electrical energy to homes and businesses, engineers strive to satisfy three objectives:

  • Providing a reliable service

  • Minimizing the cost of providing this energy

  • Reducing the environmental impact of the system, in particular facilitating the use of renewable energy sources

Unfortunately, these objectives conflict: improving reliability increases costs and renewable energy sources affect reliability unless costly security measures are put in place. The main objective of our research is to develop techniques that achieve the optimal balance between these three essential goals. In particular, using advanced optimization techniques, we explore how flexibility resources (such as demand-side participation, energy storage and agile generating units) should be deployed and operated. This is the essence of what has recently been called the "smart grid." In this respect, we are also working with colleagues who are specialists in communications, sensors and control to explore how these rapidly evolving technologies can be harnessed to help meet the objectives mentioned above.

While integrating these objectives is an important part of our work, we also do research on each of these topics taken separately. For example, we have developed probabilistic techniques to assess the operational security of power systems. As part of this strand of work, we are exploring the complex mechanisms that lead to blackouts in large power systems. We also study electricity markets. The next challenge in this area is to develop mechanisms which will ensure that competitive electricity markets deliver sufficient investments to meet the evolving needs of the electricity supply system.

Past Research Projects

Design and Integration of a Large-Scale Demand-Side Flexibility Framework

Sponsor: Breakthrough Energy

Researchers:

Abstract: The aim of this project is to incorporate detailed demand-side flexibility modeling into the production cost tool that has been developed by the Breakthrough Energy Grid Modeling team. The demand-side flexibility model will capture the effects of increased electrification in sectors such as transportation, residential and commercial buildings, and industrial hydrogen use. Increased flexibility that is inherently created from this electrification provides grid operators with a cheap, dynamic resource that can help manage the temporal profiles of renewable energy generation and the congestion of transmission networks. To truly determine the value that demand-side flexibility provides, it must be modeled alongside the traditional forms of supply-side generation and grid-scale energy storage. Additionally, it is crucial that demand-side resources be considered in generation and transmission planning processes. Large-scale electrification figures to change intra-day and seasonal load shapes, while demand-side flexibility can offer an alternative to contemporary generation and transmission expansion planning.

Economic mechanisms for grid resilience against extreme events and natural gas disruptions

Sponsor: National Science Foundation

Researchers:

Abstract: Natural disasters have profound and long-lasting consequences because of the damage that they inflict on critical infrastructure. The electrical grid is especially sensitive to these events and has suffered more than $1.5 trillion in damage since 1980. However, because of the low frequency and high severity of major disasters, standard practice for resilience to disasters is reactive: ignore disasters until they happen, then spend heavily to fix problems in the aftermath. This may not necessarily be the most effective way to enhance system resilience in the long term, because the next disaster is likely going to inflict different damages compared to the last one. Further, in light of the increasing contribution of natural gas fired generation, U.S. electric power and natural gas systems are becoming more interdependent. Yet, the contribution of gas turbines to the resilience of the electric system is not straightforward to evaluate, because their fuel supply depends on a separately operated pipeline infrastructure and a disconnected capacity/commodity market. Poorly understood interdependencies between these systems may significantly hamper recovery efforts. This proposal seeks to develop an evidence-based, economically sound and validated approach to enhancing the resilience of U.S. electricity grids, accounting for their interdependence with the natural gas supply system. We aim to rigorously quantify the need for resilience in an electrical system that heavily relies on natural gas as fuel, and develop economic mechanisms to incent efficient resilience investments.

This project will produce advances in two directions:

  • Developing a robust and comprehensive technique to quantify how different types of actions and measures improve the resilience of an electric grid. Based on a harm function that unifies existing resilience metrics, we will compare the effectiveness of changing the structure of the electric grid, hardening some components, expanding gas transmission and storage capacity, or boosting preparedness.
  • Identifying combinations of market mechanisms and regulation that encourage agents to supply the efficient mix of resilience investments, i.e. investments that would provide the greatest benefit to society at lowering the susceptibility of the power system to low-probability, high-impact events. Based on key inputs from the first thrust, we will examine the application of incentive regulation mechanisms to electric transmission and distribution utilities for enhancing resilience.

Policies and Planning for Low-Carbon Power Systems

Sponsor: Grainger Foundation and UW Clean Energy Institute

Researchers:

Abstract: In order to avoid the worst effects of anthropogenic climate change, humanity needs to drastically reduce its greenhouse gas (GHG) emissions. Electricity generation is responsible for a large share of these GHG emissions, and existing regulatory policies are not enough to reach a sustainable trajectory. Since new policies are needed, which policy mechanisms are the most efficient in incentivizing changes in the investment and operational decisions which ultimately determine grid carbon intensity? If the most efficient mechanisms are not available due to political or social constraints, how much more expensive are the suboptimal mechanisms? What side-effects do these policy mechanisms have, and what sort of side-payments are necessary in order to achieve outcomes where as many parties as possible are better off in the end?

Data Analytics for Arlington Microgrid

Sponsor: Washington State Clean Energy Fund and Snohomish County PUD

Researchers:

Abstract: Snohomish County PUD has been awarded a grant under the Washington Department of Commerce Clean Energy Fund (CEF) for the design, construction, systems integration and monitoring of a microgrid. An additional component of the award includes system testing and data analysis. The University of Washington will be responsible for providing analysis of data gathered from this microgrid systems.

The Arlington Microgrid project will demonstrate the multiple uses of energy storage by combining a 500 kW battery energy storage system, 500 kW solar array, approximately five vehicle-to-grid charging stations, emergency backup generation and building management systems with a microgrid controller and a clean energy technology center (CETC) building.

Real-Time Digital Simulation of Microgrid Control Strategies

Quantification of the Grid Benefits of a Solar Microgrid

Sponsor: Washington State Clean Energy Fund and Seattle City Light

Researchers:

Abstract: Seattle City Light is constructing a small resiliency microgrid at a City of Seattle Community Center. This microgrid will consist of a solar array, a battery, the existing Community Center loads, and new microgrid controller. The work performed by UW as part of this project will focus on assessing the benefits that the microgrid could provide when connected to the grid under both normal and emergency conditions. Where possible, these benefits will be quantified in monetary terms. These benefits stem from the optimization of the operation of the distributed energy resources connected to the microgrid on different time scales. They include:

  • Grid Support and Ancillary Services:
    • Demonstrate frequency regulation reserve capability at the microgrid site. The available frequency regulation reserves will be quantified and/or modeled continually during all use cases to understand overall availability of this service. Additionally, smart inverters will be four quadrants capable and will be selected to comply with the pending updates and revisions to IEEE 1547 and CPUC Rule 21.
  • Improving Distribution Systems Efficiency:
    • Renewable Integration: The Battery Energy Storage System (BESS) and Solar PV will operate together to integrate the variable generation. The battery will mitigate rapid output changes from PV generation caused by changing cloud cover.
    • Deferment of distribution system upgrade: Distribution Upgrade Deferral-Postponing the need to reinforce the feeder connecting the microgrid to the rest of the system through an optimal dispatch of the microgrid resources. This analysis will be based on measurements or models.
  • Grid-Connected and Islanded micro-grid operations:
    • Microgrid operation in island mode: The microgrid is normally connected to the utility grid. In the case of an outage, it islands by disconnecting from the utility grid, providing increased operational resiliency. The transfer is "break before make", meaning that there will be a short outage to transfer from the utility grid to the microgrid. The operational sequences for going islanded and returning to the utility grid will be defined during the design confirmation phase of the project. This includes whether the system will be automatic or semi-automatic.

Capturing these benefits requires the development of optimal operating strategies. The development of these strategies is complex because it must take into account a variety of factors, including:

  • The allocation of the State of Charge of the BESS, i.e. the need to balance the day-today use of the battery under normal conditions with its use for resiliency under extreme conditions.
  • The constraints on the operation of the BESS and the distribution network.
  • The stochastic nature of the local load, the PV generation and the conditions in the remainder of the system (e.g. prices, congestion, system demand, ...).
  • Incompatibilities between the charging and discharging schedules that would be optimal for each benefit taken separately.
  • The cost associated with battery degradation caused by cycling and the dependence of this degradation on the depth of discharge.

Maximizing the Financial Benefits of Aggregated Distributed Energy Resources

Sponsor: Centrica plc

Researchers:

Abstract: The aim of this project is to develop a software tool that can accurately quantify the financial benefits that distributed energy resources (DERs) would derive by optimizing their operation to:

  • Minimize the total cost that the owner of these assets has to pay for energy and demand under the tariffs to which it is subject
  • the revenues that this owner collects by providing flexibility services such as frequency regulation and various forms of reserve.
While the functionality of this tool is conceptually similar to what packages such as DER-CAM and HOMER provide, the market, tariff, asset and demand models used by these tools are not sufficiently realistic and detailed to support the accurate and flexible assessment of the potential benefits of these resources.

Enhancing the Reliability of Power Systems for Semiconductor Manufacturing Facilities

Sponsor: Samsung Electronics

Researchers:

  • Prof. Daniel Kirschen
  • Prof. Rodrigo Moreno (Universidad de Chile)
  • Prof. Marcos Orchard (Universidad de Chile)

Abstract: Unplanned interruptions in the supply of electric power to industrial facilities can cause major disruptions to industrial processes and result in significant financial losses. It is thus important to determine how such interruptions can be minimized by avoiding failures of critical equipment. The frequency of power outages can be reduced if vulnerable components are maintained or replaced before their probability of failure increases either through normal aging or exposure to adverse environmental conditions. On the other hand, maintaining and replacing components of a power system is expensive, not only because of the cost of labor and materials but also because it disrupts the production processes.

As the size and complexity of semiconductor manufacturing facilities increases, the probability of a failure in their power system and the consequences of such a failure also increases. At the same time, developing an optimal strategy for maintenance and replacement of the components of the electrical supply becomes very complex. The aim of this project is thus to investigate how modern approaches to reliability-centered maintenance (RCM), risk-based inspection (RBI) and condition-based maintenance (CBM) can be used to develop effective tactical and strategic asset management (AM) plans for Samsung's industrial power systems.

Certifiable, Scalable, and Attack-resilient Submodular Control Framework for Smart Grid Stability

Sponsor: National Science Foundation

Researchers:

  • Prof. Linda Bushnell
  • Prof. Radha Poovendran
  • Prof. Daniel Kirschen
  • Prof. Andrew Clark (WPI)
  • PhD student Philip Lee

Abstract: The smart grid is a large-scale, societal-level hybrid cyber-physical system with tight coupling between cyber (sensing, communication, and computation) and physical (actuation) components. Ensuring availability and reliability of power requires maintaining stability of the power grid even as increasing demand and uncertain renewable power sources push the power system close to its operation limit. In addition, the cyber-enabled grid has multiple entry points, leaving it highly susceptible to cyber attacks by malicious adversaries. Currently, however, developing scalable, certifiable, bound-achieving, and attack-resilient control methodologies for power system stability in the context of Science, Technology, and Engineering of CPS is an open and vital research area.

We propose to research and develop a submodular framework that will provide control methodologies that are scalable, certifiable, and attack-resilient for the following power system problems:

  • voltage stability,
  • small-signal stability, and
  • transient stability.
Submodularity is a diminishing returns property that enables development of efficient algorithms with provable optimality guarantees. Our main insight is that the grid stability problems have inherent physical invariants that exhibit submodularity in terms of control variables. When submodular structures are exhibited by the physical dynamics, scalable algorithms can be developed to select control actions with certifiable stability guarantees, thus eliminating the computationally inefficient current practice of computing control actions and verifying stability through simulation. Since the physical dynamics are invariant from attacks on cyber components, submodular structures remain intact even under cyber attacks. Hence, our proposed approach is a fundamental contribution towards attack-resilient control design. Our approach of identifying submodular structures through physical invariants is applicable not only to power systems, but to other CPS domains including coordinating robotics and unmanned vehicles. Thus the results of this project address a fundamental need in the science of CPS.

Quantifying the Resilience of Power Systems to Natural Disasters

Sponsors: National Science Foundation

Researchers:

Abstract: Power systems are not likely to remain unscathed by natural disasters such as hurricanes, earthquakes, ice storms or floods. Power outages lasting days or even weeks might ensue and will affect not only the well-being and the economy of the affected communities but could also threaten their very fabric. Recent events, such as Super-storm Sandy and hurricane Katrina, have highlighted the need to improve the resilience of the electricity grid. Some utility companies, such as Consolidated Edison, have embarked on massive investment programs aimed at hardening parts of their network. The design changes that these companies are implementing are based on observations of which components failed during past disasters. While such measures will undoubtedly be useful, they tend to focus on the resilience of individual components but do not necessarily represent the most effective way to enhance the resilience of the system. Large infrastructure investments may therefore not be targeted at the most effective solutions. To overcome this problem, electric utilities and government agencies in all areas that could be affected by a natural disaster need a rigorous method for assessing the relative value of various investments.

This proposal describes how the overall resilience of a power system could be quantified. It also outlines a technique to assess the relative value of measures aimed at hardening various components or facilitating the repair and restoration of the system.Quantifying the resilience of a power system turns out to require the solution of a very complex optimization problem. New optimization algorithms will be needed to solve this problem and hence to answer the pressing practical issue that this project addresses.

Power System Flexibility

Sponsor: University of Washington

Researchers:

Abstract: Recent years have witnessed the integration of large amounts of stochastic renewable energy sources, such as wind and solar photovoltaic. This is likely to continue and will probably be accompanied by the deployment of a significant amount of demand response. While these developments are desirable, they are also likely to increase the uncertainty on the load/generation balance. The standard answer to this problem is to say that the system needs more "flexibility" to handle this uncertainty. However, installing and deploying flexibility costs money. On the other hand, if the system is not sufficiently flexible, operators may have to resort to load shedding or the curtailment of renewable generation to maintain the stability of the system. We are therefore investigating the following questions: How do we quantify flexibility on various timescales? How much flexibility do we actually need? How much physical flexibility (i.e. from generation, storage, and demand response) is needed and how much can be accomplished using virtual flexibility (i.e. improved operating procedures and market design)? What is the optimal portfolio of flexibility resources?

Assessment and enhancement the smart building's flexibility and responsiveness

Researchers:

Abstract: Buildings represent a large share (about 40%) of the total energy consumed at national level. The majority of this energy consumption takes place when the building is being occupied during office hours. As expected, these are the periods in which the power system's generation fleet is being used most heavily, not only producing large amounts of power to meet the demand, but also greenhouse gaseous emissions. Therefore by harnessing the flexibility of the pliant appliances in the building as well as energy efficiency measures, the timing and amount of power consumption, and thus on pollution from the supply sector would be greatly reduced. This research proposes tools to optimally operate and retrofit buildings to minimize their power consumption and their carbon footprint. Go to this project's web page.

Transactive Campus Energy Systems: An R&D Testbed for Renewables Integration, Efficiency, and Grid Services

Sponsor: Washington Clean Energy Fund, US Department of Energy

Researchers:

Abstract: The project team consisting of Pacific Northwest National Laboratory (PNNL), the University of Washington (UW) and Washington State University (WSU), will connect the PNNL, UW, and WSU campuses to form a multi-campus test bed for transaction-based energy management. The test bed will support the integration of renewables and other regional needs, using the flexibility provided by loads, energy storage, and smart inverters for batteries and photovoltaic (PV) solar systems, at four physical scales: multi-campus, campus, microgrid, and building. The multi- campus test bed forms an R&D platform for how: i) Campus resources can be aggregated and operated to balance fluctuations in the region's renewable generation, both up and down, ii) Self-aware buildings, smart enough to transact with the grid to provide services, result in reduced energy consumption and increased energy efficiency opportunities, and iii) Campuses can support the grid by reducing their impact on local and regional peak loads and wholesale power costs.

Each campus test bed will further be specialized as a platform upon which R&D will be conducted to advance the state of knowledge in three key areas of critical interest to the project's DOE sponsors: i) PNNL -- transactive energy management systems for campuses and buildings, ii) UW -- smart campus and building information systems that provide energy efficiency benefits from transactive energy management systems, and iii) WSU -- operation of campus-scale microgrids to provide services to the bulk grid and their extension to planning and operation of resilient distribution systems and smart cities.

The technical aim of this joint activity is to streamline the interactions between clean energy supply, efficient buildings and the smart grid to enhance the impact of renewable generation, energy storage, and advanced energy efficiency -- while simultaneously improving the reliability and resilience of the electric grid. Moreover, through the proposed series of linked investments state-wide, and upfront collaboration with resident industry, it is the intention of the project team to create a test bed for advanced clean technology integration that differentiates Washington State as a leader in the growing global market for energy management products and services.

Distributed Energy Resources Management System

Sponsors: Department of Energy, Alstom Grid

Researchers:

Abstract: Until recently, it was possible to operate distribution networks in a "build and forget" mode because the load evolved slowly and in a predictable way and because these networks did not involve any active components. A number of factors are converging to make this operating paradigm unsustainable:

  • The integration of Distributed Energy Resources (DERs) such as wind generators, PV panels, and small scale Combined Heat and Power plants in the distribution network
  • The large scale deployment of electric cars, which will not only increase the overall demand for energy but also change the profile and characteristics of the loads in the distribution network
  • The implementation of Demand Response (DR) schemes that will link the load to price signals that may become increasingly local.

In this project we are exploring how we can leverage the various sources of data that are becoming available (e.g. smart meters, distribution automation) to make the operation of the distribution networks more efficient and more reliable and to facilitate the integration of distributed energy resources. Go to this project's web page.

Energy Positioning: Control and Economics

Sponsor: Department of Energy, ARPA-E GENI program

Collaborators: Prof. Ian Hiskens, University of Michigan

Researchers:

  • Prof. Daniel Kirschen
  • Dr. Hrvoje Pandzic
  • PhD student Ting Qiu
  • PhD student Yishen Wang

Abstract: The University of Washington and the University of Michigan are developing an integrated system to match well-positioned energy storage facilities with precise control technologies so the electric grid can more easily include energy from renewable power sources like wind and solar. Because renewable energy sources provide intermittent power, it is difficult for the grid to efficiently allocate those resources without developing solutions to store their energy for later use. The two universities are working with utilities, regulators, and the private sector to position renewable energy storage facilities in locations that optimize their ability to provide and transmit electricity where and when it is needed most. Expanding the network of transmission lines is prohibitively expensive, so combining well-placed storage facilities with robust control systems to efficiently route their power will save consumers money and enable the widespread use of safe, renewable sources of power. Go to this project's web page.

For a project description, click here.

For the project fact sheet, click here.

Using Distribution-Level Energy Assets to Help Optimize Regional Transmission

Sponsors: BPA/SnoPUD

Researchers:

  • Prof. Daniel Kirschen (PI)
  • Dr. Ricardo Fernandez-Blanco
  • M.Sc. student Kelly Kozdras

Abstract: In the proposed project, Snohomish County PUD (the "District") will give BPA incentive-based access to District-owned and operated energy storage (ES) and demand response (DR) assets. The technologies deployed will let BPA send specific requests to District control software to supply or absorb energy (e.g., absorb 2MW for 2 hours, starting at HE03). Resulting energy transfers can be used to support BPA operations by, for example, reducing network congestion, mitigating energy imbalance or improving wind integration. District assets made available in this project include 4 MW and 8 MWh of energy storage funded jointly by the District and Washington State Department of Commerce (DoC), under the Washington Clean Energy Fund. An initial project task, with BPA input, will define the communication protocol for processing energy transfer requests. The protocol will be standards-based and may, optionally, use transactive control signal technology from the PNW Smart Grid Demonstration Project. Software deployed for BPA will also include a transmission-oriented optimizer, based on Energy Positioning technology developed by the University of Washington (UW) and the University of Michigan (UM) under an ARPA-E grant. This technology will help BPA determine optimal requests for distributed energy services. Once fielded and tested in this project, the proposed technologies can be further deployed as standard mechanisms, enabling BPA requests for energy services from any distribution-connected ES and DR assets, throughout the BPA grid.

Development of Tools for Analyzing the Profitability of Energy Storage in Competitive Electricity Markets

Sponsor: Sandia National Laboratory

Researchers:

Abstract: The objective of this project is to investigate techniques to assess the profitability of deploying distributed energy storage systems in a power system operating in a competitive market environment. The project will start by reviewing the rules that have been implemented or proposed for the integration of such devices. It will then develop optimization models of increasing accuracy and complexity to determine the optimal location and size of these devices.

Development of aggregated dynamic models for active distribution systems using heuristic optimization techniques

Sponsor: EPRI

Researchers:

Abstract: The increasing connection of distributed energy resources (DERs) to distribution systems transforms the latter from a passive to an active part of the power system. In bulk power system stability studies, the dynamic behavior of these active distribution systems (ADSs) has to be accurately accounted for in order to properly reflect their influence on the overall dynamic performance of the system. However, limitations in computational performance as well as in the availability of distribution system data require a certain degree of simplification. The objective of this project is to refine an existing aggregation methodology that maintains the minimum level of detail necessary to accurately model ADSs in bulk system stability studies. The contribution of the work is expected to be the application of a selected heuristic optimization techniques in order to determine the "equivalent impedance" that represents the lines in the detailed North American network of a specific voltage level as well as the creation and extension of dynamic models. Model validation techniques will be used to determine how accurately the aggregated ADS model represents the response of the detailed ADS to an external network fault, e.g. transmission system fault.

Architectural and Algorithmic Solutions for Large-Scale PEV Integration into Power Grids

Sponsors: National Science Foundation

Researchers:

Abstract: Electric Vehicles (EVs) are now a reality; and it is expected that in the near future large volumes of these devices will be integrated to the existing power grid. If allowed to charge in an uncontrolled manner, these devices will charge their batteries when connected to the grid circuits, increasing the already high peak-demands that are served by expensive generation sources. Furthermore these additional demands could be translated into potential over-loadings and the need to invest into wires and power generation assets in order to be successfully accommodated. On the other hand, technical and economic benefit would be attained if the charging of these devices takes place when the system is lightly loaded, and being served by cheap generation.

The research conducted under this grant proposes algorithmic solutions to accommodate the EVs demand in an optimal manner, not only to minimize costs, but also to exploit their ability to charge and discharge on command, to provide services to the power system. At the same time, we also seek to exploit this inherent flexibility to minimize not only the electricity cost for the EV owners, but also the degradation of their batteries. Go to this project's web page.