Waterloo Research

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Proleptic Logics in Media Coverage of the IPCC Sixth Assessment Report
(Taylor & Francis, 2023) Mehlenbacher, Ashley Rose; Eckert, Carolyn; Doody, Sara; Forst, Sarah; Mehlenbacher, Brad
The rhetorical figure of speech called prolepsis, describing a presaging of time and events to come, commonly appears in environmental communication and importantly frames the possibilities for action. Prolepsis is a figure employed in communication about climate change that demands attention in its various deployments, configurations, and, importantly, rhetorical inducements. Such inducements may rely upon feelings of hope or fear, and this study investigates the rhetorical and ethical conditions prolepsis may generate. A considerable literature studying the concept of hope offers great insights into climate change perceptions and behavior concerning climate action. The present study examines prolepsis to discuss how the figure’s inducement of suasive effect through appeals to hope and fear shape the ethical horizons for action. We examine media coverage of the IPCC’s sixth report, Part I, warning of the enormous impacts of the ongoing climate emergency and necessary climate action to mitigate the worst of these effects.
Data-Driven Topology and Parameter Identification in Distribution Systems With Limited Measurements
(Institute of Electrical and Electronics Engineers (IEEE), 2024-11-05) de Jongh, Steven; Mueller, Felicitas; Osterberg, Fabian; Cañizares, Claudio A.; Leibfried, Thomas; Bhattacharya, Kankar
This manuscript presents novel techniques for identifying the switch states, phase identification, and estimation of equipment parameters in multi-phase low voltage electrical grids, which is a major challenge in long-standing German low voltage grids that lack observability and are heavily impacted by modelling errors. The proposed methods are tailored for systems with a limited number of spatially distributed measuring devices, which measure voltage magnitudes at specific nodes and some line current magnitudes. The overall approach employs a problem decomposition strategy to divide the problem into smaller subproblems, which are addressed independently. The techniques for identifying switch states and system phases are based on heuristics and a binary optimization problem using correlation analysis of the measured time series. The estimation of equipment parameters is achieved through a data-driven regression approach and by an optimization problem, and the identification of cable types is solved using a Mixed-Integer Quadratic Programming solver. To validate the presented methods, a realistic grid is used and the presented techniques are evaluated for their resilience to data quality and time resolution, discussing the limitations of the proposed methods.
Modeling and Application of Hybrid Power Flow Controller in Distribution Systems
(Institute of Electrical and Electronics Engineers (IEEE), 2018-08-01) Tamimi, Behnam; Canizares, Claudio A.
The smartening of distribution systems with distributed generation, storage devices, and intelligent loads have created challenges for the operation of distribution feeders, which can be addressed with power-electronics based controllers. However, the capital-intensive nature of these controllers is an obstacle for their wide use. The Hybrid Power Flow Controller (HPFC) is shown here to provide an adequate solution to the application of flexible ac transmission systems controllers to distribution systems and hence the merits and the added value of this controller are discussed here through detailed modeling and simulations, examining its impact on a distribution system under different conditions. Thus, in this paper, a detailed dynamic model of the HPFC is developed and implemented in PSCAD, describing and proposing control strategies to properly operate this controller in distribution-system applications, such as an effective and simple procedure for starting up the device. The developed model is used to demonstrate the effectiveness of the controller for solving problems in distribution systems, such as voltage sags associated with feeder faults and power flow fluctuations due to intermittent renewable generation using a benchmark network as an illustrative example.
Electric Thermal Storage System Impact on Northern Communities’ Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2017-09-18) Sauter, Patrick S.; V. Solanki, Bharatkumar; Canizares, Claudio A.; Bhattacharya, Kankar; Hohmann, Soren
In this paper, the impact of electric thermal storage (ETS) systems on the operation of Northern Communities' microgrids is analyzed. A mathematical model of the ETS system is developed and integrated into an energy management system (EMS) for isolated microgrids, in which the problem is divided into unit commitment and optimal power flow subproblems, to dispatch fossil-fuel-based generators, energy storage systems, and ETS charging. To account for the deviations in the forecast of renewables, a model predictive control technique is used. The proposed ETS-EMS framework is tested and studied on a modified CIGRE medium voltage benchmark system, which comprises various kinds of distributed energy resources, and on the real Kasabonika Lake First Nation isolated microgrid system. It is shown that the ETS significantly reduces operating costs, and allows for better integration of intermittent wind and solar sources.
Smart Residential Load Simulator for Energy Management in Smart Grids
(Institute of Electrical and Electronics Engineers (IEEE), 2018-03-22) Gonzalez Lopez, Juan Miguel; Pouresmaeil, Edris; Canizares, Claudio A.; Bhattacharya, Kankar; Mosaddegh, Abolfazl; Solanki, Bharatkumar V.
This paper describes the development of a freeware smart residential load simulator to facilitate the study of residential energy management systems in smart grids. The proposed tool is based on MATLAB-Simulink-GUIDE toolboxes and provides a complete set of user-friendly graphical interfaces to properly model and study smart thermostats, air conditioners, furnaces, water heaters, stoves, dishwashers, cloth washers, dryers, lights, pool pumps, and refrigerators, whose models are validated with actual measurements. Wind and solar power generation as well as battery sources are also modeled, and the impact of different variables, such as ambient temperature and household activity levels, which considerably contribute to energy consumption, are considered. The proposed simulator allows modeling of appliances to obtain their power demand profiles, thus helping to determine their contribution to peak demand, and allowing the calculation of their individual and total energy consumption and costs. In addition, the value and impact of generated power by residential sources can be determined for a 24-h horizon. This freeware platform is a useful tool for researchers and educators to validate and demonstrate models for energy management and optimization, and can also be used by residential customers to model and understand energy consumption profiles in households. Some simulation results are presented to demonstrate the performance and application of the proposed simulator.
Robust Energy Management of Isolated Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2018-05-07) Lara, Jose Daniel; Olivares, Daniel E.; Canizares, Claudio A.
This paper presents the mathematical formulation and architecture of a robust energy management system for isolated microgrids featuring renewable energy, energy storage, and interruptible loads. The proposed strategy addresses the challenges of renewable energy variability and forecast uncertainty using a two-stage decision process combined with a receding horizon approach. The first-stage decision variables are determined using a cutting-plane algorithm to solve a robust unit commitment; the second stage solves the final dispatch commands using a three-phase optimal power flow. This novel approach is tested on a modified International Council on Large Electric Systems (CIGRE) test system under different conditions. The proposed algorithm is able to produce reliable dispatch commands without considering probabilistic information from the forecasting system. These results are compared with deterministic and stochastic formulations. The benefits of the proposed control are demonstrated by a reduction in load interruption events and by increasing available reserves without an increase in overall costs.
An Affine Arithmetic-Based Energy Management System for Isolated Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2018-03-15) Romero-Quete, David; Canizares, Claudio A.
This paper presents a mathematical formulation of an energy management system (EMS) for isolated microgrids, which addresses uncertainty using the affine arithmetic (AA) method. The proposed EMS algorithm is based on an AA unit commitment (AAUC) problem for day-ahead dispatch, using uncertainty intervals of both load and renewable energy (RE) to provide robust commitment and dispatch solutions in AA form, which are feasible for all the possible realizations within the predetermined uncertainty bounds. A real-time dispatch solution is then found by the proposed algorithm, which computes the noise symbols values of the affine forms obtained by the AAUC, based on the current and actual load and RE power levels and available reserves. If the actual forecast error is outside the uncertainly bounds considered in the AAUC solution process, leading to possible load and/or RE curtailment, the AAUC is recalculated with updated forecast information. The proposed AA-based EMS is tested on a modified CIGRE microgrid benchmark and is compared against day-ahead deterministic, model predictive control (MPC), stochastic optimization, and stochastic-MPC approaches. The simulation results show that the proposed EMS provides robust and adequate cost-effective solutions, without the need of frequent re-calculations as with MPC-based approaches, or assumptions regarding statistical characteristics of the uncertainties as in the case of stochastic optimization.
Smart Operation of Electric Vehicles With Four-Quadrant Chargers Considering Uncertainties
(Institute of Electrical and Electronics Engineers (IEEE), 2018-03-15) Mehboob, Nafeesa; Restrepo, Mauricio; Canizares, Claudio A.; Rosenberg, Catherine; Kazerani, Mehrdad
Given the expected impact of electric vehicle (EV) charging on power grids, this paper presents a novel two-step approach for the smart operation of EVs with four-quadrant chargers in a primary distribution feeder, accounting for the uncertainties associated with EVs, and considering the perspectives of both the utility and the EV owners. In the first step of the proposed approach, the mean daily feeder peak demand and corresponding hourly feeder control schedules, such as taps and switched capacitor setpoints, considering the bidirectional active and reactive power transactions between EVs and the grid, are determined. A nonparametric bootstrap technique is used, in conjunction with a genetic algorithm-based optimization model, to account for EV uncertainties and discrete variables. In the second step, the maximum possible power that can be given to connected EVs at each node, while providing active and/or reactive power to maintain the peak demand value and corresponding feeder dispatch schedules defined in the first step, is computed every few minutes in a way which is fair to the EVs. The proposed approach is validated using the distribution feeder model of a real primary feeder in Ontario, Canada, considering significant EV penetration levels. The results show that the proposed approach could be implemented in practice to properly operate EVs, satisfying feeder, and peak demand constraints, which would be better than the business-as-usual practice or a popular heuristic method in terms of number of tap operations, system peak demand, and voltage regulation.
Practical Energy Management Systems for Isolated Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2019-08-31) Solanki, Bharatkumar V.; Canizares, Claudio A.; Bhattacharya, Kankar
This paper presents practical energy management system (EMS) models which consider the operational constraints of distributed energy resources, active-reactive power balance, unbalanced system configuration and loading, and voltage dependent loads. A novel linearization approach is proposed and validated based on the fact that, for isolated microgrids, due to the characteristics of feeders, network losses, and voltage drops across feeders are relatively small. The proposed EMS models are mixed integer quadratic programming problems, requiring less computation time and thus suitable for online applications. The practical EMS models are compared with a typical decoupled unit commitment and optimal power flow-based EMS with and without consideration of system unbalancing. The models, along with “standard” EMS models, are tested, validated, and compared using a CIGRE medium voltage benchmark system and the real isolated microgrid of Kasabonika Lake First Nation in Northern Ontario, Canada. The presented results demonstrate the effectiveness and practicability of the proposed models.
Compressed Air Energy Storage System Modeling for Power System Studies
(Institute of Electrical and Electronics Engineers (IEEE), 2019-02-25) Calero, Ivan; Canizares, Claudio A.; Bhattacharya, Kankar
In this paper, a detailed mathematical model of the diabatic compressed air energy storage (CAES) system and a simplified version are proposed, considering independent generators/motors as interfaces with the grid. The models can be used for power system steady-state and dynamic analyses. The models include those of the compressor, synchronous motor, cavern, turbine, synchronous generator, and associated controls. The configuration and parameters of the proposed models are based on the existing bulk CAES facilities of Huntorf, Germany. The models and performance of the CAES system are first evaluated with step responses, and then examined when providing frequency regulation in a test power system with high penetration of wind generation, comparing them with existing models of CAES systems. The simulation results confirm that the dynamic responses of the detailed and simplified CAES models are similar, and demonstrate that the simultaneous charging and discharging can significantly contribute to reduce the frequency deviation of the system from the variability of the wind farm power.
Renewable Energy Integration in Diesel-Based Microgrids at the Canadian Arctic
(Institute of Electrical and Electronics Engineers (IEEE), 2019-08-14) Das, Indrajit; Canizares, Claudio A.
The effect of climate change is significant in the arctic regions of the world, with the carbon footprint from diesel-only based electricity generation in remote arctic communities adding to the environmental degradation through greenhouse gas (GHG) emission, oil spills, and black carbon. Moreover, the dependence on diesel and its associated costs are an economic problem for these communities, particularly in the Canadian Arctic, where governments subsidize this fuel. Thus, this article presents specific studies including new variable-speed generator (VSG) technologies that demonstrate the feasibility, impact, and benefits of introducing renewable energy (RE) together with VSGs in remote microgrids in the Canadian Arctic. More specifically, this article describes a two-step procedure to select remote communities for detailed feasibility studies of deployment of RE sources, including a generation expansion planning (GEP) framework and optimization model for RE and new VSG integration applied to the selected communities, to minimize diesel dependence of isolated microgrids and maximize the incorporation of environmentally friendly generation technologies. The proposed approach is applied to communities in Nunavut and the North West Territories in the Canadian Arctic, based on actual data, to study the technoeconomic feasibility of RE integration and develop business cases for diesel generation replacement with RE and VSG generation in these communities. The obtained optimal plans contain diesel-RE hybrid combinations that would yield substantial economic savings and reductions on GHG emissions, which are being used as the base for actual deployments in some of the studied communities.
Power Generation Planning of Galapagos’ Microgrid Considering Electric Vehicles and Induction Stoves
(Institute of Electrical and Electronics Engineers (IEEE), 2018-10-15) Clairand, Jean-Michel; Arriaga, Mariano; Canizares, Claudio A.; Alvarez-Bel, Carlos
Islands located far away from the mainland and remote communities depend on isolated microgrids based on diesel fuel, which results in significant environmental and cost issues. This is currently being addressed by integrating renewable energy sources (RESs). Thus, this paper discusses the generation planning problem in diesel-based island microgrids with RES, considering the electrification of transportation and cooking to reduce their environmental impact, and applied to the communities of Santa Cruz and Baltra in the Galapagos Islands in Ecuador. A baseline model is developed in HOMER for the existing system with diesel generation and RES, while the demand of electric vehicles and induction stoves is calculated from vehicle driving data and cooking habits in the islands, respectively. The integration of these new loads into the island microgrid is studied to determine its costs and environmental impacts, based on diesel cost sensitivity studies to account for its uncertainty. The results demonstrate the economic and environmental benefits of investing in RES for Galapagos' microgrid, to electrify the local transportation and cooking system.
The Canadian Renewable Energy Laboratory: A testbed for microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2020-03-04) Nasr-Azadani, Ehsan; Su, Peter; Zheng, Wenda; Rajda, Janos; Canizares, Claudio; Kazerani, Mehrdad; Veneman, Erik; Cress, Stephen; Wittemund, Michael; Manjunath, Manoj Rao; Wrathall, Nicolas; Carter, Mike
This article presents a test facility for design validation of microgrids with high penetration of renewable energy, developed as a joint effort with industry, government, and academia. The Canadian Renewable Energy Laboratory (CANREL) described here is a physical simulation tool for the design, development, and performance testing of islanded and grid-connected microgrid projects. CANREL is equipped with a diesel generator, different renewable energy sources, various renewable energy generation simulators and physical systems, a bidirectional power-flow grid simulator, a battery- based energy-storage system, and controllable resistive?inductive?capacitive and electronic test loads for the design and testing of a variety of microgrid solutions. The test facility provides project performance demonstration and validation services at each stage of a microgrid project development to help utilities and project developers reduce risks. It is also a physical simulation tool for benchmarking microgrid equipment and controllers for research and development purposes. Some facility test results are presented in this article to demonstrate the capabilities of CANREL for simulating a wide range of scenarios.
Modeling and Control of Variable Speed Wind Turbine Generators for Frequency Regulation
(Institute of Electrical and Electronics Engineers (IEEE), 2019-04-23) Ravanji, Mohammad Hasan; Canizares, Claudio A.; Parniani, Mostafa
Wind turbine generators (WTG) can participate in system frequency regulation via virtual inertial controllers (VIC). In the presence of frequency disturbances, VIC temporarily regulates the WTG power output forcing it to release/absorb kinetic energy into/from the grid. With increasing penetration of WTGs in power systems, grid operators require these generators to provide frequency regulation services; however, kinetic energy release/absorption can destabilize WTGs. Hence, to address these issues, a new large-perturbation nonlinear WTG model is proposed in this paper, based on the WTG internal response that is used to tune typical VICs. Novel worst case and optimal VIC tuning approaches are also proposed and discussed based on the developed WTG nonlinear model. Several simulations are presented to test and validate the proposed model and VIC tuning techniques, demonstrating their adequate performance and advantages.
Incentive Design for Voltage Optimization Programs for Industrial Loads
(Institute of Electrical and Electronics Engineers (IEEE), 2015-02-10) Le, Brian; Canizares, Claudio A.; Bhattacharya, Kankar
This paper presents a novel framework for planning and investment studies pertaining to the implementation of system-wide conservation voltage reduction (CVR). In the CVR paradigm, optimal voltage profiles at the load buses are determined so as to yield load reductions and hence energy conservation. The system modifications required to operate at such voltages is known to be capital intensive, which is not desirable by investors. Hence, the proposed model determines the system savings and the appropriate price incentives to offer industries such that a minimum acceptable rate of return is accrued. In this model, the industrial facilities are represented by a combination of constant impedance, constant current, and constant power loads. A detailed case study for Ontario, Canada, is carried out considering that industrial loads are investing in voltage optimization to reduce their energy costs. The optimal incentives that need to be offered by the system planner, over a long-term horizon, and across various zones of Ontario, are determined using the presented mathematical model. Furthermore, a comprehensive risk analysis comprising sensitivity studies and Monte Carlo simulations is carried out considering the variations in the most uncertain model parameters.
Stochastic-Predictive Energy Management System for Isolated Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2015-09-14) Olivares, Daniel E.; Lara, Jose D.; Canizares, Claudio A.; Kazerani, Mehrdad
This paper presents the mathematical formulation and control architecture of a stochastic-predictive energy management system for isolated microgrids. The proposed strategy addresses uncertainty using a two-stage decision process combined with a receding horizon approach. The first stage decision variables (unit commitment) are determined using a stochastic mixed-integer linear programming formulation, whereas the second stage variables (optimal power flow) are refined using a nonlinear programming formulation. This novel approach was tested on a modified CIGRE test system under different configurations comparing the results with respect to a deterministic approach. The results show the appropriateness of the method to account for uncertainty in the power forecast.
Long-Term Renewable Energy Planning Model for Remote Communities
(Institute of Electrical and Electronics Engineers (IEEE), 2015-10-27) Arriaga, Mariano; Canizares, Claudio A.; Kazerani, Mehrdad
This paper presents a novel long-term renewable energy (RE) planning model for remote communities (RCs), considering the characteristics of diesel-based RCs in Canada and other parts of the world such as Alaska and northern Chile. Over the past few years, there has been a significant increase in assessing and deploying RE projects in northern remote locations. The model proposed in this paper adds to such efforts by creating a multiple-year community planning tool that can be used to determine economic and technically feasible RE solutions, considering the current operating structures, electricity pricing systems, subsidy frameworks, and project funding alternatives under which RE can be deployed in RCs. The proposed model is implemented in a case study for the Kasabonika Lake First Nation community in northern Ontario. The case study shows that RE projects can be feasible under current operating conditions, for a set of funding alternatives that share the economic risks.
Hybrid Power Flow Controller Steady-state Modeling, Control, and Practical Application
(Institute of Electrical and Electronics Engineers (IEEE), 2016-07-07) Tamimi, Behnam; Canizares, Claudio; Battistelli, Claudia
Steady-state models of the hybrid power flow controller (HPFC) for power flow and optimal power flow (OPF) studies are presented in this paper, considering the multiple control modes of the device. A strategy for control mode switching and limit handling in power flow calculations is proposed. The OPF model of the HPFC represents all the device control and physical limits as constraints in the mathematical formulation, so that the HPFC can be optimally dispatched as a part of the transmission system control assets. The power flow model is demonstrated and validated through loadability studies on a two-area benchmark test system, where the OPF model is used to determine the optimal ratings of the device based on a cost-benefit analysis. A study is also presented of the HPFC application to Ontario-Canada's grid, to address particular congestion problems in this network; an HPFC cost analysis is also shown for this system. The presented studies demonstrate the application of the proposed models for planning and operation studies, illustrating the performance, effectiveness, and feasibility of the controller to solve congestion issues in a real grid.
Frequency Control in Isolated/Islanded Microgrids Through Voltage Regulation
(Institute of Electrical and Electronics Engineers (IEEE), 2015-10-06) Farrokhabadi, Mostafa; Canizares, Claudio A.; Bhattacharya, Kankar
This paper presents a frequency control mechanism for an isolated/islanded microgrid through voltage regulation. The proposed scheme makes use of the load voltage sensitivity to operating voltages and can be easily adopted for various types of isolated microgrids. The proposed controller offers various advantages, such as allowing the integration of significant levels of intermittent renewable resources in isolated/islanded microgrids without the need for large energy storage systems, providing fast and smooth frequency regulation with no steady-state error, regardless of the generator control mechanism. The controller requires no extra communication infrastructure, and only local voltage and frequency is used as feedback. The performance of the controller is evaluated and validated through various simulation studies in the PSCAD/EMTDC software environment based on a realistic microgrid test system, using small-perturbation stability analysis to demonstrate the positive effect of the proposed controller in system damping.
Including Smart Loads for Optimal Demand Response in Integrated Energy Management Systems for Isolated Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2015-12-23) Solanki, Bharatkumar V.; Raghurajan, Akash; Bhattacharya, Kankar; Canizares, Claudio A.
This paper presents a mathematical model of smart loads in demand response (DR) schemes, which is integrated into centralized unit commitment (UC) with optimal power flow coupled energy management systems for isolated microgrids for optimal generation and peak load dispatch. The smart loads are modeled with a neural network (NN) load estimator as a function of the ambient temperature, time of day, time of use price, and the peak demand imposed by the microgrid operator. To develop the NN-based smart load estimator, realistic data from an actual energy hub management system is used for supervised training. Based on these, a novel microgrid energy management system (MEMS) framework based on a model predictive control approach is proposed, which yields optimal dispatch decisions of dispatchable generators, energy storage system, and peak demand for controllable loads, considering power flow and UC constraints simultaneously. To study the impact of DR on the microgrid operation with the proposed MEMS framework, a CIGRE benchmark system is used that includes distributed energy resources and renewables based generation. The results show the feasibility and benefits of the proposed models and approach.

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