www.smart-microgrid.ca Project 1.1 Study of Dynamic Characteristics of Autonomous Droop-controlled Microgrids ABOUTALEB HADDADI (McGill University) AMIRNASER YAZDANI (Ryerson University) BENOIT BOULET (McGill University) GEZA JOOS (McGill University)
Problem statement A challenging task is to regulate the voltage amplitude and frequency of an autonomous microgrid: – Multi-input multi-output (MIMO), – Time varying, – Non-linear, – Considerable transient and steady-state impacts imposed by loads.
Problem statement Most commonly, the goal is achieved by coordinated control of multiple Distributed Energy Resource (DER) units through droop- based control. Advantages: – Simple structure (use of SISO controllers), – Plug-and-play feature, – No need for communication between the DERs, – Enables power sharing. Challenges: – Sensitivity of control to droop gains, – Sensitivity of control to the steady-state power flow (real- and reactive- power outputs of DGs), – Dependence of stability on the network and loads, – No control over transient performance.
Challenges of droop control ̶ Example Example: Poor transient performance of droop-based control due to dynamic coupling between the DER units and loads in a droop-controlled autonomous microgrid ̶ connecting an induction machine load to a test microgrid Figure 1: The test microgrid. A 12.47-kV North american Distribution network, Autonomous mode of operation, Droop-based voltage and frequency control, Figure 2: Response of the DERs to connection of an induction machine to the test microgrid showing poor stability of droop-based control due to dynamic coupling between the DER units and loads.
Fahimeh Kazempour and Reza Iravani University of Toronto A Robust Hierarchical Control Structure for Virtual Power Plants Project 1.2. Distributed and Hybrid Control
Problem Statement Unlike the conventional grid-connected mode, a microgrid in the Virtual Power Plant (VPP) mode of operation is obliged to: Exchange a specified active and reactive power at the PCC, Maintain PCC's voltage and frequency within specified values Provide dynamic power balance within the microgrid. A three-level hierarchical control structure needs to be employed to realize the VPP mode of operation. A VPP is subject to: Operating point changes, Parametric and topological uncertainties, and unmodeled dynamics in both the local DERs and their interactions, Exogenous disturbances. – At the primary control level, a robust control strategy is used to synthesize DER’s local controllers.
The Proposed Solution The method of decentralized robust H ∞ control with integral quadratic constraint (IQC) uncertainty description is employed to develop dynamic reference-tracking controllers. Using this method, necessary and sufficient conditions are derived to: Guarantee the stability of the overall VPP system Minimize the H ∞ -norm bound on a map from the disturbance input to the controlled output Our method only requires solving a set of game type algebraic Riccati equations Algebraic Riccati equations are presented in terms of rank constrained LMIs A suitable test system is employed, to investigate the robust dynamic performance of the VPP system under the proposed control structure.
www.smart-microgrid.ca Project 1.3 Current State Estimation for Microgrid Ahda P. Grilo, Pengfei Gao and Wilsun Xu (University of Alberta)
Current State Estimation for Microgrid Smart grids will increase load management opportunities for customers. For microgrids the real-time power consumption of loads is a useful information for energy management systems. In commercial facilities it is difficult to measure currents. Idea: Voltages at the load terminals are often accessible and can be measured by distributed voltage sensors.
Current State Estimation for Microgrid Proposed method: 1)To measure voltages at the load terminals by distributed voltage sensors. 2)Use these voltages, combined with the network topologies and parameters, to estimate the load currents. Traditional: Microgrid: Main Panel: Available measurements of V, P and Q. Subpanel: No Available measurements. Loads terminals: Measurements of V and θ.
Current State Estimation for Microgrid The proposed technique represents a good solution for microgrid facilities where the load conductors are inaccessible for current sensing. The idea of using voltages to estimate currents as presented in this paper has some other applications. For example, it could be used to monitor home appliance behavior by using distributed voltage sensors installed at various locations of a home.
A Stochastic Simulation Tool for Studying the Electric Features of Micro-grid Qingxin Shi and Ricardo Torquato, Department of Electrical and Computer Engineering, University of Alberta The development of smart micro-grid requires a lot of planning and monitoring studies. Therefore we need to model the real-time performance of the micro-grid. The model should take into consideration all kinds of random factors, such as random behavior of home appliance and random power generation of photovoltaic (PV) panel. This poster presents a simulation platform to handle this work. The application of this platform is: to simulate the real-time network response of the random loads and random PV generation, helping the engineers to manage the micro-grid.
www.smart-microgrid.ca Project 1.3 Contribution of DGs to fault current and their impacts on overcurrent Protection H. Yazdanpanahi PDS Lab, Department of Electrical & Computer Engineering, University of Alberta
Problem In spite of their undoubted advantages, DG units impact on over-current protection by contributing to fault current. Nuisance (sympathetic) trippingFailure in fuse-saving scheme Miscoordination between main and back-up
Research Four types of DGs have been investigated. For each type, the magnitude and duration of the current is assessed by analysis and simulation from the perspective of relay coordination. Inverter-based Synchronous Machine PMSMInduction Machine
www.smart-microgrid.ca Project 1.4 Operational Strategies and Storage Technologies to Address Barriers for a Very High Penetration of DG Units in Intelligent Microgrids Michael Ross (McGill University) Dr. Chad Abbey (Hydro-Québec) Professor Géza Joós
Point of Common Coupling - Limit power fluctuations - Reduce the peak power flow through PCC Point of Common Coupling - Limit power fluctuations - Reduce the peak power flow through PCC Energy Storage System - Time-dependent resource - Limited by power and energy rating Energy Storage System - Time-dependent resource - Limited by power and energy rating Demand Response -Ability to curtail non-critical load. -Critical load must be supplied with energy (high reliability) Demand Response -Ability to curtail non-critical load. -Critical load must be supplied with energy (high reliability) Problem: Optimized Microgrid Dispatch with a Very High Penetration of Renewable Energy Renewable Energy Distributed Generation -Fluctuating and variable power output -Power balance is difficult to achieve Renewable Energy Distributed Generation -Fluctuating and variable power output -Power balance is difficult to achieve Diesel Generator - High greenhouse gas emissions - Expensive fuel cost Diesel Generator - High greenhouse gas emissions - Expensive fuel cost
Proposed Solution: Multi-Objective Optimization Dispatch for Microgrids A Microgrid controller must be developed to c oordinate the control of available Distributed Energy Resources (DER) to: Minimize cost of energy Reduce peak power through PCC Minimize power fluctuations through PCC Improve reliability Reduce GHG emissions The multiple benefits can be optimized while mitigating the adverse effects of renewable energy integration.
www.smart-microgrid.ca Project 2.1 Cost-Benefit Framework: Secondary Benefits and Ancillary Services MIKE QUASHIE AND GEZA JOOS (MCGILL UNIVERSITY)
A Methodology to Optimize Benefits of Microgrids
The Methodology is applied to real feeder in north America. The study shows significant reduction in cost of energy which seek to advance the business case of microgrids. It also provides potential investors and stakeholders a planning strategy to maximize the benefits accrued from microgrids. Figure 1. Cigre's North American medium Voltage Distribution Network Benchmark with DG connected to operate as Microgrid
A Novel Affine Arithmetic Method to Solve OPF Problems with Uncertainties in Microgrids Mehrdad Pirnia Claudio Cañizares Kankar Bhattacharya Alfredo Vaccaro Department of Electrical & Computer Engineering
Motivation Increased focus on renewable generation has brought forth many concerns in planning and operation of microgrids. Margins of operation for thermal generators are needed to provide system reliability and efficiency in view of the variability brought about by DR and DG technologies. Common methods to consider uncertainties from renewable sources integration (e.g., Monte Carlo Simulation) rely on pdfs of random variables and are not efficient. Self Validated Computation Methods (SVC) do not need pdfs and are efficient: – Interval Arithmetic (IA) – Affine Arithmetic (AA) 24
Methodology and Results Develop an accurate and efficient AA-based OPF model to incorporate uncertainties in microgrids. Validate the AA-based operation system models with the MCS based method. Use the resulting AA based intervals to estimate the spinning reserve requirements in the presence of DR and variable DG penetration in microgrids. Test and validate the model on a benchmark microgrid. 25
EFFECT OF PRICE-RESPONSIVE DEMAND ON DISPATCH AND COSTS IN MICROGRIDS Felipe Ramos-Gaete Claudio Cañizares Kankar Bhattacharya Department of Electrical & Computer Engineering
Motivation With smart microgrids, loads in the grid are required to react to stressful conditions of the system. Depending on load reaction, cost inefficiencies, line congestions and even energy shortage may occur. It is necessary to examine the effect of price-responsive demand on smart microgrid unit commitment of distributed generators and storage. In the long run, is also relevant to study the inter- relationship between demand elasticity and electricity prices. 27
Methodology and Results 28 Develop models to represent demand response in dispatch. Develop a microgrid unit commitment and dispatch model. Establish a link between prices and customers’ response. Some interesting findings: – More elastic demand can make the system less stable, increasing or decreasing the demand beyond feasible operating points. – Multi-period price-responsiveness presents a similar behaviour as energy storage systems, soothing system variability while minimizing total operation cost. – A corrected real-time pricing scheme can be derived from this work, which would allow more controllability over demand response.
www.smart-microgrid.ca Stability and Control of Unbalanced Synchronous Machine Based Distributed Generators Ehsan Nasr Azadani, Claudio Canizares, and Kankar Bhattacharya Dept. Electrical and Computer Engineering, University of Waterloo
Motivation Rapid development and increase in penetration of decentralized or distributed generation (DG). Transition from a passive grid containing only loads to an active grid, including loads and “small” generation. The dynamics of both transmission and distribution system are affected. Lack of knowledge of the dynamics of DGs under unbalanced conditions. A full characterization of the unbalanced system in stability analyses would allow a better understanding of dynamic behaviour of DGs. Most DGs nowadays are equipped with small synchronous generators (e.g., diesel generators, microturbines)
Objectives Develop both static and dynamic models of synchronous- machine DG under unbalanced conditions. Perform: – Voltage stability studies based on P-V and P-L curves. – Small perturbation stability studies using a model identification approach to compute the eigenvalues. – Transient stability studies based on time domain simulations to study contingencies. Propose a control strategy to improve the stability of distribution systems with synchronous-machine DG units.
www.smart-microgrid.ca Project 2.4 Stochastic evaluation of transient stability of Micro-grids Mayssam Amiri, Ani Gole, Tomás Yebra Vega (University of Manitoba)
Stochastic evaluation of the stability in a Micro-Grid is more realistic and less conservative. Model Results Wind turbine PV µ-turbine Small SM DG µ- Grid Generator Mathetical SM 0.0 SM 2.1 Statistical approach 100’s or 1000’s of variables Closer to reality Less conservative than traditional methods Monte Carlo Method Time consuming Parallel Computing Evaluation Probability of failure caused by unstability Model Prob. LLL & LLLG Prob. LL & LLG Prob. LG SM 0.00.03670.10470.1554 SM 2.10.02540.0250.0013 Discrimination type of Fault Influence of the mathematical model Influence of µ-Grid design. Influence of the degree of penetration of DG’s PDF’s
www.smart-microgrid.ca Project 3.1 Universal Communication Infrastructure Are Omnidirectional Terminal Station Antennas a Better Choice for Point to Multipoint Deployments in NLOS Environments? Prof. David G. Michelson (University Of British Columbia) Sina Mashayekhi (PhD student)
Problem: Directional Antennas Performance in NLOS Multipath Environment Minimum requirement for P2MP radio systems for management of the electricity supply in Canada: – Minimum 12 dBi gain, maximum beamwidth of 30 o – Appropriate for high capacity systems operating under LOS – What about for relatively low capacity systems in NLOS condition? Directional antennas do not have 100% of expected performance in NLOS – Broadening the pattern, Gain reduction – Reduction in Average Area Spectral – Increase of Co-channel Interference – Reduction in Coverage
Solution: Revising SRSP 301.7 to allow using Omni antennas for critical applications in SG Impacts of Using Omni for P2MP deployments: – Co-channel Interference, Coverage, ASE – Increased second best server redundancy – Cost effective deployments and Maintenances
www.smart-microgrid.ca T HEME 3, P ROJECT 3.2 Throughput analysis of Narrow-band Power Line Communications in Advanced Distribution Automation Chon Wang Chao (MEng Student) Quang-Dung Ho (Research Associate) Tho Le-Ngoc (McGill University)
Overview of the project NSMG-Net Project 3.2: Chon Wang Chao Fig. 1 – Studied communications architecture of PLC for ADA
Contribution of the project Data rate estimation – Packet structure specified by IEC 61850 client- server communications – Expected data requirements for advanced distribution automation Impact of communication channel competition – Throughput variation – Bandwidth requirement – Improvement from using Clear to Send/ Request to Send mechanism NSMG-Net Project 3.2: Chon Wang Chao
www.smart-microgrid.ca T HEME 3, P ROJECT 3.2 Frequency Regulation by Aggregator-based Electric Vehicles Charging Control via Wireless Communications Chon Chon Wang Chao (MEng Student) Quang-Dung Ho (Research Associate) Tho Le-Ngoc (McGill University)
Overview of the Project NSMG-Net Project 3.2: Chon Wang Chao Frequency regulation with the battery capacity of electric vehicles (EV) Intelligence resides at the aggregators which are used to coordinate the responses of the EVs Fig. 2 – the proposed control and communications architecture of FR with EV
Contribution of the project NSMG-Net Project 3.2: Chon Wang Chao Index system for selecting EV to participate in FR – Map the EV private information (e.g. SOC, departure time) to an index – Aim to reduce the privacy concerns Impact of communications on FR – Frequency regulation performance (e.g. stability) under non-ideal communications – Communication delay – Packet Loss
www.smart-microgrid.ca T HEME 3, P ROJECT 3.2 E FFICIENT C OMMUNICATION A RCHITECTURE FOR I NTELLIGENT M ICRO G RIDS Tho Le-Ngoc (McGill University) Quang-Dung Ho (Research Associate) Yue Gao (MEng Student) Gowdemy Rajalingham (MEng Student)
Proposed System Architecture Fig. 1 – Neighbor Area Network
Performance Evaluation NSMG-Net Project 3.2: Gowdemy Rajalingham Fig. 2 – Simulation Scenario, sweep of cluster size Objective Determine capabilities and limitations of NAN with GPSR Investigate NAN clusters performance with various system parameters T ABLE 1 – S IMULATION P ARAMETERS Channel Model MAC layerIEEE 802.11 Routing ProtocolGreedy Perimeter Stateless Routing (GPSR) Performance MetricsPacket Transmission Delay & Packet Delivery Ratio (PDR) Traffic Topology System Parameters
①What is the problem for substation communication systems: I.The ZigBee wireless platform is a cost-effective wireless sensor networking system that can be used to monitor substation components in electric substations. II.Impulsive noise with a short duration and strong energy content caused by partial discharge of a dielectric breakdown can degrade the communication quality of ZigBee nodes. ②What are we doing for the above problem: I.Modelling the sequence of PD impulsive noise. II.Analysis of the impact of impulsive noise on ZigBee systems operated at 915 MHz and 2.4 GHz bands. ③What is the contribution of our research: I.Assessment of ZigBee operational bands that are more resistant to impulsive noise in electricity substations. II.Possibility of a ZigBee sesnor network that can be utilized for the detection of partial discharge events.
www.smart-microgrid.ca Project 3.4 Integrated Data Management and Portals Student: Moein Manbachi (Simon Fraser University) Supervisors: Dr. Hassan Farhangi (British Columbia Institute of Technology) Dr. Ali Palizban (British Columbia Institute of Technology) Dr. Siamak Arzanpour (Simon Fraser University)
*Ref. International Energy Agency (http://www.iea.org) Canada Electric Power Generation, Consumption and T&D Losses In 2010, Canada T&D Loss value: 65.661 Billion-kWh. Average Transmission & Distribution Losses: % 8.5388 About %40 of T&D Losses occurs in Distribution Network Ref. http://www.electricenergyonline.com Importance of Energy Conservation & Distribution Network Optimization Volt/VAR Optimization (VVO)
Project 3.4: Real-time Smart Grid Adaptive Volt/VAR Optimization 1. How Smart Grid new features can help VVO? 2. What is our proposed solution? 3. What are the key benefits of our solution? 4. Centralized Control Vs. Decentralized Control 5. Where we are now? How far we can go? 6. What will be the next generation of VVO? 7. Case Study Results 8. Future Plans & Targets VVO Technique can be improved by new Smart Grid Technologies More efficient solution with better results
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