Dates: March 13 and 14, 2012
Location: Carnegie Mellon University
Baker Hall A51 – Giant Eagle Auditorium
Date: March 12, 1:00 p.m. - 6:00 p.m.
Location: Carnegie Mellon University
ECE, Hamerschlag Hall – HH 1107 Bombardier Smart Infrastructure Collaboration Center
RECEPTION, March 12 - Holiday Inn Select University Center, 7:00-8:30 p.m.
POSTER SESSION / DINNER, March 13 - Holiday Inn Select University Center, 6:00-9:00 p.m.
Title: A Proposed Approach to Distributed Power Flow and Equilibrium Calculation in Electric Energy Systems
Authors: Andrew Hsu, Marija Ilić
Abstract: As new and unconventional components are introduced to the electric energy grid, both as energy sources and control devices, the computation required to calculate operating points for the electric energy system must be adjusted accordingly. System operators currently do power flow calculations from the centralized approach, requiring knowledge of all parts of the system. However, in a system increasingly enabled by “smart” devices, it may be possible for individual components of the system to calculate their own operating point, by exchanging information with its neighbors and storing information about its own states. We have worked on an iterative method to calculate the power flow for electric energy systems, and want to extend it to finding the equilibrium solutions to the dynamic equations of an interconnected electric energy system. Decoupled power flow examples using this approach have been done on two bus, three bus, and the IEEE 14 bus system, which include resistive transmission line losses.
Title: Semidefinite Programming for Power System State Estimation
Authors: Yang Weng, Qiao Li, Rohit Negi, Marija D. Ilić
Abstract: State Estimation (SE) plays a key role in power system operation and management. For AC power system state estimation, SE is usually formalized mathematically as a Weighted Least Square or Weighted Least Absolute Value problem, and solved by Newton’s method. Although computationally tractable, Newton’s method is highly sensitive to the initial point, as it is essentially a local search algorithm. In this paper, we propose a Semidefinite Programming (SDP) approach to effectively obtain a good initial state to improve the performance of the existing Newton’s method. Our simulation results not only show that the SDP initial guess is much better than the currently used flat start on the IEEE standard bus systems, but also demonstrates approximately globally optimal results, with a lower bound provided in this paper.
Title: Zooming-in and Zooming-out Methods for Directing Power Flows and Simulating Loop Flows Author: Sanja Cvijic and Marija Ilić
Abstract: Due to increased congestion in transmission systems, the necessity to control power has grown tremendously in the last decade. Ability to direct power through a desired route is required due to technical limitations of the grid, contractual obligations and environmental pressures for incorporating renewables. There exists a high demand for accounting methods that could determine contributions of participants to line flows. This paper proposes a new method based on zooming-in and zooming-out of large power networks that explicitly models one seller-one buyer bilateral transactions and deviations from them, known as loop flows. It provides a clean tracing mechanism for determining contributions of bilateral transactions to line flows and loop flows applicable for accurate transmission pricing. Power flow control is achieved by cancelling loop flows with displacing power generation and/or devices capable of directing power flow.
Title: Convex Hull Stochastic Dynamic Programming applied to Electric Vehicle Charging and Frequency Regulation Bids
Authors: Jonathan Donadee and Marija Ilić
Abstract: Plug in electric drive vehicles (EVs) are expected to be adopted in large numbers in the coming decades. Meanwhile, electric grid operators are rolling out advanced metering infrastructure that will enable demand side participation in electrical energy and ancillary services markets. Many deterministic optimization models have been proposed for minimizing the cost of charging the batteries of individual EVs and aggregated fleets of EVs. These models also include revenues that EVs could earn by providing ancillary services to the grid, such as secondary frequency regulation. Providing frequency regulation would require altering the battery charge rate every 4 seconds to follow a control signal, causing the battery state of charge to take a biased random walk. Models in the literature do not accurately consider the risks of providing regulation. Hard constraints are imposed to avoid risky scenarios or the cost of such scenarios is ignored. We propose a stochastic dynamic programming approach to optimize EV charging while providing frequency regulation. Our model incorporates inconvenience costs to drivers and penalties for failing to meet regulation obligations. Starting at the final charge rate decision time before the vehicle unplugs, two stage stochastic MILP deterministic equivalent problems (DEP) are solved for many possible states of charge. Many hour-long samples of the regulation signal are used to create scenarios in the DEP. Binary variables indicate timesteps when a regulation contract has been broken, allowing for an accurate calculation of penalties. A convex hull of the resulting costs approximates a value function of the state of charge. Through backward recursion, a sub-optimal decision can be made and implemented at the current time. We present our problem formulation and simulation results for a single EV in an idealized energy market.
Title: Optimal Integration of Intermittent Energy Sources Using Distributed Multi-Step Optimization
Authors: Kyri Baker, Gabriela Hug, Xin Li
Abstract: The integration of renewable energy sources such as wind and solar into the electric power grid is a coveted yet challenging goal. The difficulties arise from the intermittency of the sources, the required increase in transmission capacity, and the lack of coordination between control entities. The problem of optimal coordination between storage and intermittent resources in multiple control areas is formulated as a decomposed multi-timestep optimization. Using the chosen decomposition method, the distributed optimization converges to the same solution as the centralized problem.
Title: A Multi-core High Performance Computing Framework for Probabilistic Solutions of Distribution Systems
Authors: Tao Cui, Franz Franchetti
Abstract: Multi-core CPUs with multiple levels of parallelism and deep memory hierarchies have become the mainstream computing platform. In this project we developed a generally applicable high performance computing framework for Monte Carlo simulation (MCS) type applications in distribution systems, taking advantage of performance-enhancing features of multi-core CPUs. The application in this project is to solve the probabilistic load flow (PLF) in real time, in order to cope with the uncertainties caused by the integration of renewable energy resources. By applying various performance optimizations an multi-level parallelization, the optimized MCS solver is able to achieve more than 50 % of a CPU's theoretical peak performance and the performance is scalable with the hardware parallelism. We tested the MCS solver on the IEEE 37-bus test feeder using a new Intel Sandy Bridge multi-core CPU. The optimized MCS solver is able to solve millions of load flow cases within a second, enabling the real-time Monte Carlo solution of the PLF.
Title: Energy Balancing-Based Transient Stabilization of Power Systems Using Power Electronically-Controlled Devices
Authors: Milos Cvetkovic, Marija Ilić
Abstract: Future electric energy grids are likely to have rich dynamic behavior due to the wide range of time scales the smart grid technologies operate at. Stability of the grid remains a high priority objective in such environment. Of a particular interest is the transient stability problem. Generally smaller inertia of distributed generators might affect the way transient stability problem manifests. Therefore, adequate transient stability control schemes are needed in order to guarantee stability under these conditions. In this work, we propose transient stability control logic for reactive compensation devices (Flexible AC Transmission Systems - FACTS) which will insure stability of the system affected by large disturbances. More precisely, FACTS devices are used as temporary energy storage. They inject or accumulate energy as needed in order to attenuate the disturbances. The controller is tested by running simulations on various test cases.
Title: Multi-temporal and multi-layered optimization of demand with risk management
Authors: Jhi-Young Joo and Marija Ilić
Abstract: Due to the nature of the power system and market, there always exist physical and financial risks both in the long run at the planning stage, and in the short run at the operation stage. Many attempts to minimize these risks from the demand side so far have failed because of the lack of information on the true value of demand resources to the system. We attempt to tackle these problems by proposing a framework where the system, load serving entities, and the end-users exchange the right information on the system condition (represented by the price) and the energy consumption with respect to it (represented by the demand function). This information should be exchanged through different layers of the market ranging from the end-users on the bottom to the system operator at the top. The information should also be presented in different time frames so that it captures the right signals for different purposes, such as long-term planning on energy efficiency and short-term energy balance of supply and demand. We present the mathematical formulation of this framework as a decision making of each entity.(same abstract with the General Meeting 2012 paper)
Title: Stable Levitation in Magnetic Bearings for Flywheel Energy Storage Systems
Author: Kevin Bachovchin and Marija D. Ilić
Abstract: A flywheel energy storage system stores mechanical energy by accelerating a rotor, called the flywheel, to a very high speed. It is advantageous to use magnetic bearings to support the rotor instead of conventional mechanical bearings in order to decrease frictional energy losses. Magnetic bearings are contactless and therefore can exhibit near-zero losses. A significant challenge with magnetic bearings results from Earnshaw’s Theorem, which states that it is not possible to stably levitate a rotor in all directions using only permanent magnets. However, by adding a Halbach array stabilizer, which induces currents in stabilization coils, to the levitation magnet system, this instability can be overcome. The levitation magnet system consists of a lower repelling magnet pair and an upper attracting magnet pair, which provide an upward magnetic levitation force to counteract the downward gravitational force of the rotor. The upper magnets are positioned slightly closer to each other than the lower magnets in order to make the levitation magnet system stable to lateral rotor displacements, but unstable to vertical displacements. The vertical instability of the levitation magnet system is stabilized by the Halbach array stabilizer. The stabilizer consists of two stabilization coils, both centered in the vertical direction between two rotating Halbach arrays. If the coils are exactly centered between the two arrays, the magnetic flux contributions through the coils from the upper and lower arrays cancel and no current is induced. If, however, the rotor is displaced in the vertical direction so that the coils are not exactly centered, the time-varying flux induces a current in each coil. Magnetic fields and forces in the magnetic bearing can be calculated by using electromagnetic theory. Magnetic fields from permanent magnets are calculated using superposition of fields due to patches of magnetization charge at the surfaces where the magnetization is discontinuous. Magnetic forces are calculated using a superposition of forces on each patch of magnetization charge. Resultant magnetic fields, forces, and stiffness of the entire magnetic bearing system, consisting of both the levitation magnets and the Halbach array stabilizer, are calculated, and the system is determined to be stable to both vertical and lateral displacements of the rotor.
Title: Advanced Primary Frequency Regulation: Coordination between energy storage and conventional generation in power systems with renewables
Authors: Dinghuan Zhu, Gabriela Hug
Abstract: Frequency deviations from the nominal value indicate the imbalance between active power supply and consumption in power systems. Large unattended frequency deviations could lead to severe consequences such as blackouts. With an increase in variable and intermittent renewable energy sources (RESs), frequency control becomes an increased challenge. This paper proposes a novel H∞-based primary frequency control approach named advanced primary frequency regulation (APFR) to coordinate conventional generators and energy storage devices and to address the increased frequency deviations introduced by RESs. Under the APFR design, the participating conventional generators are mainly responsible to balance the low frequency component of the system frequency deviation while the energy storage devices because of their fast response capability are employed to alleviate the relatively high frequency component. This frequency separation goal is fulfilled by assigning proper dynamic weighting functions to the control inputs. The ultimate goal of APFR is to significantly reduce the frequency deviations subject to the RES disturbances. In order to reduce the complexity in practical implementations, APFR controllers are synthesized through the static output feedback technique. Simulation results on the 9-bus WECC test system illustrate the performance of the proposed APFR approach.
Title: Timing Vulnerabilities in Phasor Measurement Units
Authors: Rohan Chabukswar, Bruno Sinopoli
Abstract: Phasor Measurement Units (PMUs) are deployed on electrical grids to capture synchronized real-time measurements of voltage and currents at multiple points on the grid. Also known as synchrophasors, these sensors are commonly deemed to be an important measuring device for future power grids. Utility companies and ISOs can use synchrophasors to improve conventional state estimation, to get deeper and more accurate knowledge about the health of the grid. Nonetheless, the presence of PMUs on the grid gives rise to several cyber-physical vulnerabilities. One such vulnerability can be exploited by spoofing GPS timing signals locally, using external hardware and low power antennae. The GPS signals are used by PMUs to synchronize across wide areas, and a malicious GPS signal can corrupt the phasor measurements enough to potentially disrupt the grid. In this work, we look at simplistic test systems provided by IEEE. A timing attack is simulated on such a system, and its effects on state estimation are studied. We conclude with an outlook towards future work, on more complex systems, as well as with more sophisticated attacks.
Title: Providing Differentiated Level of Reliability: Technology Options and Investment Decision
Authors: Chin Yen Tee and Marija D. Ilić
Abstract: Customers have different preferences for reliability, however; distribution utility generally provides the same minimal basic level of reliability to all customers. For customers who want high reliability, they may install distributed generations (DGs) as backup generation during power outages. Furthermore, in normal condition, customers can sell power from DGs back to distribution utility. However, in terms of operating, it would be more efficient if a distribution utility own DGs and deploy both DGs, sectionalizing switches (Normally Closed Switches: NCSs) and tie switches (Normally Open Switches: NOSs) to optimally reconfigure the system in order to provide reliability options to customers. The two scenarios, DGs owned by customers and DGs owned by distribution utility, are compared by determining the optimal investment decision and reliability performance of each scenario.
Title: Incentive-based Coordinated Charging Control of Plug-in Electric Vehicles at the Distribution-Transformer Level
Authors: Mads Almassalkhi, Ralph Hermans, and Ian Hiskens
Abstract: Distribution utilities are becoming increasingly aware that their networks may struggle to accommodate large amounts of plug-in electric vehicles (PEVs). In particular, uncoordinated overnight charging is expected to be problematic, as the corresponding power demand exceeds the capacity of most distribution substation transformers. In this paper, a dynamical model of PEVs served by a single temperature-constrained substation transformer is presented and a centralized scheduling scheme is formulated to coordinate charging of a heterogeneous PEV fleet. We employ the dual-ascent method to derive an iterative, incentive-based and non-centralized implementation of the PEV charging algorithm, which is optimal upon convergence. Then, an implementation is proposed, in which this distributed open-loop problem is embedded in a predictive control scheme to introduce robustness against exogenous disturbances. Simulations of a realistic charging scenario illustrate the effectiveness of the so-obtained incentive-based coordinated PEV control scheme in terms of performance and enforcing the transformer's thermal constraint.
Title:Secure Multi-party Computation Applications in Smart Grid Privacy Preserving
Authors: Cory Thoma, Tao Cui, Franz Franchetti
Abstract: Smart Grid controlling and monitoring system including smart meters and advanced metering infrastructure provides high resolution, near real-time end user energy consumption data for utility to better monitor and control the system, and for users to better manage their energy usages. However, the high resolution near real-time household data can be used to extract end user's detail activities, which poses great threat to end user's privacy. In this project, we proposed a secure multi-party computation based framework for privacy preserving in Smart Grid controlling and monitoring system. An interactive simulation using secure multi-party computation was built to demonstrate how a secure Smart Grid data collection environment would operate. A user of the simulation would experience the Smart Grid with different cryptosystems, and would also experience the environment without the security in place. Without privacy protocols in place, any collected data on power consumption would allow the utility or a third party to derive information on an individual household’s private activities. Such information can include what TV shows they watch, what time they wake up, and even when they leave the house. Using the Paillier cryptosystem as well as Yao’s solution to the millionaire money comparison problem, Smart Grid usage data is able to remain private, while still allowing power suppliers to monitor the grid and make necessary adjustments to the power supply. The simulation draws upon these two RSA based cryptosystems to demonstrate a daily, monthly, and yearly experience in a secure Smart Grid environment. The simulation also utilizes a monthly billing system that shows how the energy companies can monitor the grid and each household to ensure compliance with policies and usage levels without violating the user’s privacy.
Title: A Queueing Based Scheduling Approach for Load Management in Electrical Energy Systems: The Case of Electric Vehicle Charging
Authors: Qiao Li, Tao Cui, Rohit Negi, Franz Franchetti and Marija D. Ilić
Abstract: The power system is a vital national infrastructure that is currently undergoing radical transformations in both structure and functionalities. The concurrent integration of new and intermittent energy sources (wind and solar), new and large loads (electric vehicles), and advanced sensing (phasor measurement units) and communication capabilities greatly expands the size and complexity of the power system, and introduces many sources of uncertainties. Therefore, it is highly challenging, and yet crucial, to develop efficient operation schemes to guarantee that the whole system can operate in an efficient, reliable and sustainable manner. In this presentation, we will propose a queueing based scheduling framework to achieve efficient management of delay tolerant loads in power systems, in particular the coordinated charging of electric vehicles. Based on the queueing formulation, a myopic scheduling algorithm is proposed, which can achieve the same optimal performance asymptotically as compared to the conventional dynamic programming approach, while dramatically reducing the computation complexity. This research can not only achieve large-scale integration of electric vehicles in the power system, but also hold the premise of successful integration of renewable energy sources by absorbing their intermittencies.
Title: Using smart devices for system-level management and control in the smart grid
Authors: Emre Can Kara, Mario Bergés, Bruce Krogh, Soummya Kar
Abstract: Buildings are being rapidly populated with smart devices that can monitor and control individual end-use loads, opening the door for a wide variety of applications and a re-thinking of the traditional power distribution system. The typical use cases for these smart devices relate to the reduction of energy consumption through a number of mechanisms ranging from load shedding during peak demand hours (demand response), to occupancy-controlled heating, ventilation and air conditioning (HVAC) and lighting systems, to simply providing real-time energy consumption information to end-users in order to encourage more energy-efficient behavior. However, more dynamic mechanisms are possible through distributed fine-grained control of small loads, which is the focus of this research. The main problem we seek to address in this research is how to leverage end-use electrical loads to provide ancillary services (particularly balancing generation to load through frequency regulation) in the power grid. In particular we would like to shed light on the system-level properties that can be influenced through coordinated (centralized or otherwise) control of a large collection of smart loads, where we use the term smart to denote their ability to react to measurements or signals. A motivating case engaging thermostatically controlled loads to provide load following services based on literature review is demonstrated where the probability mass evolution in temperature state space is represented by a Markov Chain-based model and a predictive controller is employed to control the population of loads to track an aggregate power reference signal.
Title: A Feasibility Study on Using Residential Demand Response for Ancillary Services in PJM
Authors: Fallaw Sowell, Jay Apt, Pedro Carvalho, Shira Horowitz, Brandon Mauch
Abstract: We assess the feasibility of using residential air-conditioner loads for spinning reserves in the PJM market from a regulatory and economic perspective. The major regulatory barrier for such a program is a requirement that participating demand resources provide load measurements every minute to verify resource availability and bid compliance. Placing SCADA systems on all residential participants is prohibitively expensive, so we devise a way to estimate total response using data from only a sample of customers while meeting PJM’s accuracy and precision requirements. Our analysis is based on three-minute data collected over July - October 2010 from 480 residential air-conditioners in Maryland, Delaware and New Jersey. We create a model for each air-conditioner to forecast air-conditioner load and the expected load reduction from a direct load control (DLC) event. Model estimates are based on weather conditions and DLC strategies. Aggregated load estimates and expected load reductions are derived from the individual models. We will use the model results to determine the necessary sample size of air conditioner data to provide an acceptable confidence interval of the estimates.
Title: Game-Theoretic Methods for Distributed Management of Energy Resources in the Smart Grid
Authors: Quanyan Zhu and Tamer Basar
Abstract: The smart grid is an ever-growing complex dynamic system with multiple interleaved layers and a large number of interacting components. In this talk, we discuss how game-theoretic tools can be used as an analytical tool to understand strategic interactions at different layers of the system and between different decision-making entities for distributed management of energy resources. We first investigate the issue of integration of renewable energy resources into the power grid. We establish a game-theoretic framework for modeling the strategic behavior of buses that are connected to renewable energy resources, and study the Nash equilibrium solution of distributed power generation at each bus. Our framework uses a cross-layer approach, taking into account the economic factors as well as system stability issues at the physical layer. In the second part of the talk, we discuss the issue of integration of plug-in electric vehicles (PHEVs) for vehicle-to-grid (V2G) transactions on the smart grid. Electric vehicles will be capable of buying and selling energy from smart parking lots in the future. We propose a multi-resolution and multi-layer stochastic differential game framework to study the dynamic decision-making process among PHEVs. We analyze the stochastic game in a large-population regime and account for the multiple types of interactions in the grid. Using these two settings, we demonstrate that game theory is a versatile tool to address many fundamental and emerging issues in the smart grid.
Title: Power System Economic Dispatch with Spatial-Temporal Wind Generation Scheduling
Authors: Yingzhong (Gary) Gu, Le Xie, Xinxin Zhu, and Marc G. Genton
Abstract: In this poster, spatial-temporal wind forecast is incorporated in power system economic dispatch model. Compared to most existing power system dispatch models, the proposed formulation takes into account both spatial and temporal wind power correlation. This in turn leads to an overall more cost-effective scheduling of system-wide wind generation portfolio. The potential economic benefits are manifested in the system-wide generation cost savings, as well as the ancillary service cost savings. We illustrate in a modified IEEE 24 bus system that the overall generation cost can be reduced by 7% by using spatial-temporal wind forecast compared with using the popular persistent forecast model.
Title: Towards Unified Operational Value Index of Energy Storage Services in Power Systems
Authors: Anupam A. Thatte and Le Xie
Abstract: This poster proposes a unified operational value index of energy storage in the deregulated electricity market environment. Given the heterogeneity of many storage service providers enabled by smart grid technologies, this unified value index will allow for comparison across different technology choices. It is also argued that implicit forms of energy storage, such as demand response should be valued and utilized. A cross-market co-optimization is proposed to maximize the operational value of energy storage under the deregulated electricity market environment. For numerical illustration a case study is conducted in a modified IEEE Reliability Test System (RTS) 24-bus system, which includes flywheels, battery storage in the form of plug-in electric vehicles, and price responsive thermal load. A unified valuation of storage services would benefit both the service providers as well as the power system in terms of energy balancing and ancillary services. The proposed operational value index is a first step towards such unified valuation.
Title: Limitations in reduction of wind power intermittency with storage technologies
Authors: Christina Jaworsky, Konstantin Turitsyn
Abstract: Stochastic variations and unpredictability of wind energy are the major concerns of power industry and hinder the wide scale adoption of wind power. Compensation of short term variability is one of the major challenges that the industry will face in the coming years. Our study focuses on statistical analysis of fluctuations of wind power on the minute to hour time scales. Using the publicly available wind measurement data we show that the statistics of fluctuations is strongly non-Gaussian and highly correlated in this time frame. Specifically we show that traditional Gaussian can underestimate the probability of rare events by several orders of magnitude. In the second part of our work we analyze the potential impact of advanced control and storage technologies in reducing the intermittency of wind power. Using the convex optimization techniques we study the theoretical limits on the performance of storage technologies. Specifically we analyze the interplay between the statistics of electric power fluctuations and the characteristics of storage available in the system. We quantify the trade-off between the reduction in power intermittency, storage capacity, and charging rate. In the end we present a general approach to the intermittency mitigation problem that incorporates multiple objectives and system constraints.
Title: Optimal Usage of Transmission Capacity with FACTS Devices in the Presence of Wind Generation
Authors: Rui Yang, Gabriela Hug-Glanzmann
Abstract: The two major challenges with regard to the integration of wind energy resources are their variable power output and the fact that the areas with high availability of wind energy resources may not coincide with the load centers or where currently generation is located. The transmission system was not designed for this situation, resulting in insufficient transfer capacity. Solutions to this problem include to build new transmission lines or to better utilize the existing infrastructures by using power flow control devices. In this work, we investigate and design a control concept for power flow control with Flexible AC Transmission Systems (FACTS). In this study, a control approach is proposed to determine the optimal steady-state settings of FACTS devices. In the proposed approach, the local controller of each FACTS device determines the optimal settings with respect to certain objectives only using a limited amount of local information. The control scheme is a two-stage algorithm, including the offline simulation stage and online decision making stage. In the offline simulation stage, the controller of the device is trained by solving Optimal Power Flow (OPF) problems for various generation and loading scenarios of the system. Regression analysis is used to find a function describing the relationship between particular measurements and the optimal settings. In the online decision making stage, the controller uses this function and the information of local measurements to determine the optimal setting of the power flow control device. In the online operation, the controller only needs to evaluate the locally stored function; therefore it could quickly adjust the device settings and is able to deal with the rapid fluctuations of wind generation. The proposed method has been implemented and tested for the IEEE 14-bus system. Promising preliminary results have been obtained with one or two FACTS devices in the system.
Title: Dynamic Modeling and Stability Analysis of the Cyprus Power System
Authors: Stefanos Baros and Marija Ilić
Abstract: Cyprus is an island in the Meditteranean Sea that has an isolated power system. The whole load is covered by three large power stations in the island, Vasilikos, Moni and Dhekelia power station. In this study, we are trying to assess the small signal frequency stability of the existing power system in Cyprus and potential problems that might arise. Isolated systems such the one in Cyprus are more prone to frequency instabilities since every imbalance between generation and demand should be covered by the local generators. Although, the system might be stable regarding the stand-alone units, when it is interconnected the stability could be in a great risk as shown if careful measures are not taken. Sufficient damping in generators that present a very oscillatory behavior during primary response is crucial for the stability of the interconnected system. A specific scenario as expected for 2015 before the extended damages in the Vasilikos power system happened is analyzed thoroughly.
Title: Enhanced AGC and AVC to Ensure Frequency Quality during Normal Operations: The Case of Azores Islands
Authors: Qixing Liu
Abstract: In this poster we introduce a control and communications framework for ensuring that frequency remains within the pre-specified industry standards in systems with high penetration of wind power. It is assumed that wind power changes are persistent low-amplitude fast fluctuations around a given equilibrium. We derive a linearized dynamic model which relates small changes in wind power and frequency. We further assume that the effects of voltage changes on frequency dynamics are negligible, which results in a mathematical model representing decoupled electromechanical system dynamics. Based on this model, we propose a general control and communications framework for systematic frequency stabilization and regulation in future electric energy systems with highly variable disturbances. Potential of fast storage controllers, such as flywheels, is studied for avoiding excessive wear-and-tear of the existing primary controllers, governors in particular, and for increasing the stability margin of the interconnected system. The proposed framework is illustrated using the electrical systems of Flores and Sao Miguel islands.
Title: Towards Sustainable Intra-Dispatch Power Balancing
Authors: Nipun Popli and Marija Ilić
Abstract: Electric energy systems are composed of heterogeneous energy resources, broadly categorized as controllable conventional generators and intermittent renewable resources. Power output of the later consists of fluctuations and persistent variations over multiple time-scales. Consequently, it is critical to balance supply and demand in real-time once the system is dispatched, i.e. before the operator re-schedules additional conventional resources. A classificatory approach is needed for planning resources for namely two intra-dispatch control actions, stabilization for small but fast fluctuations and tracking/regulation for slow but sustained deviations. Our objective is to track sustained/persistent intra-dispatch real power variations. A two-pronged approach has been proposed for the same. Firstly, we aim to achieve higher degree of efficiency by aligning natural response characteristics of conventional balancing resources with the time-scales of power imbalances in the system. These may arise from load as well as renewable energy resources, particularly wind power. Slow generation resources respond to minute-by-minute real-power imbalances between consecutive dispatch actions. Secondly, we aim to harness the demand response characteristics of aggregate load, where the demand adjust its real-power consumption based on system imbalances. This is in addition to the demand participation in energy market or economic dispatch. For the same, we propose a model-based control framework for generating real power needed to follow the sustained wind power deviations within each dispatch interval. A quasi-stationary model is derived which explicitly states the inter-dependence between the real power generation as states and the non-zero mean wind variations as disturbances. The proposed control framework is an automated function to track sustained intra dispatch real-power imbalances in the system. The concept can be extended to map the demand side response to real-power imbalances.
Title: Hysteresis-Based Control of Electrical Loads
Authors: Soumya Kundu, Nikolai Sinitsyn, Scott Backhaus and Ian Hiskens
Abstract: With the growing proportion of intermittent energy sources within the power grid, loads will play an increasingly important role in compensating the fast time-scale fluctuations in the generated power. For example, a large number of thermostatically-controlled-loads (TCLs) or plug-in electric vehicles (PEVs) can collectively be used for generation-balancing. We seek a control strategy to regulate the electricity demanded by such loads. A model has been developed for the aggregate power response of a homogeneous group of TCLs to a disturbance where all TCL set-points are increased or decreased uniformly. We derived a linearized model of the response, and designed a linear-quadratic-regulator (LQR). Using TCL set-point as the control input, the regulator enables aggregate power to track reference signals that exhibit step, ramp and sinusoidal variations. A brief outline of how a hysteresis-based charging process can be implemented for PEVs is presented as well.
Title: Potential Cost Savings of Controlled Electric Vehicle Charging
Authors: Remco Verzijlbergh, M.O.W. Grond, Z. Lukszo, J.G. Slootweg, Marija Ilic
Abstract: This work deals with the distribution system impacts of electric vehicle (EV) charging. Future load profiles have been constructed by adding different EV charging profiles to household loads and solving the power flows to assess the network impacts on various network levels. The results indicate that controlled charging of EVs leads to significant reduction of overloaded network components that have to be replaced, but the impact varies per network level. Overall, in the uncontrolled charging scenarios roughly two times more replacements are needed compared to the controlled charging scenario. Furthermore, it was shown that for the controlled charging scenario the overall reduction in net present value due to energy losses and the replacement of overloaded network components is approximately 20 % in comparison with the uncontrolled charging scenario. The results suggest that the deployment of a flexible and intelligent distribution network is a cost-beneficial way to accommodate large penetrations of EVs.