Browsing by Author "Cañizares, Claudio A."

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A Review of Modeling and Applications of Energy Storage Systems in Power Grids
(Institute of Electrical and Electronics Engineers (IEEE), 2022-03-25) Calero, Fabian; Cañizares, Claudio A.; Bhattacharya, Kankar; Anierobi, Chioma; Calero, Ivan; Zambroni de Souza, Matheus F.; Farrokhabadi, Mostafa; Guzman, Noela Sofia; Mendieta, William; Peralta, Dario; Solanki, Bharatkumar V.; Padmanabhan, Nitin; Violante, Walter
As the penetration of variable renewable generation increases in power systems, issues, such as grid stiffness, larger frequency deviations, and grid stability, are becoming more relevant, particularly in view of 100% renewable energy networks, which is the future of smart grids. In this context, energy storage systems (ESSs) are proving to be indispensable for facilitating the integration of renewable energy sources (RESs), are being widely deployed in both microgrids and bulk power systems, and thus will be the hallmark of the clean electrical grids of the future. Hence, this article reviews several energy storage technologies that are rapidly evolving to address the RES integration challenge, particularly compressed air energy storage (CAES), flywheels, batteries, and thermal ESSs, and their modeling and applications in power grids. An overview of these ESSs is provided, focusing on new models and applications in microgrids and distribution and transmission grids for grid operation, markets, stability, and control.
Affine Policies and Principal Components Analysis for Self-Scheduling in CAES Facilities
(Institute of Electrical and Electronics Engineers (IEEE), 2022-07-26) Zambroni de Souza, Matheus F.; Cañizares, Claudio A.; Bhattacharya, Kankar; Lorca, Alvaro
This paper presents a novel methodology based on Principal Components Analysis (PCA) and Affine Policies (AP) for self-scheduling of a price-taker Compressed Air Energy Storage (CAES) facility operating under uncertainties. The proposed PCA-AP model is developed from the facility owner's perspective, which partakes in energy, spinning, and idle reserve markets. A methodology is proposed to select the required price uncertainty intervals from actual data based on a Box Cox technique. For a more realistic representation, the detailed thermodynamic characteristics of the CAES facility are considered, taking into account as well modern CAES facilities that may charge and discharge concurrently. To validate the proposed PCA-AP model and approach, the results obtained are compared with an existing Affine Arithmetic (AA) model, which is also based on an affine approach, and Monte Carlo Simulations (MCS), which can be considered as the benchmark for comparison purposes. The input data, forecast prices and intervals of uncertainty, are taken from the Ontario-Canada electricity market for 2015-2019. From the studies presented, it can be observed that the new PCA-AP approach provides less conservative results as compared to the AA approach, and hence can be considered an adequate methodology for day-ahead operations in systems with significant sources of uncertainty.
Aggregate Modeling of Thermostatically Controlled Loads for Microgrid Energy Management Systems
(Institute of Electrical and Electronics Engineers (IEEE), 2023-03-09) Córdova, Samuel; Cañizares, Claudio A.; Lorca, Álvaro; Olivares, Daniel E.
Second-to-second renewable power fluctuations can severely hinder the frequency regulation performance of modern isolated microgrids, as these typically have a low inertia and significant renewable energy integration. In this context, the present paper studies the coordinated control of Thermostatically Controlled Loads (TCLs) for managing short-term power imbalances, and their integration in microgrid operations through the use of aggregate TCL models. In particular, two computationally efficient and accurate aggregate TCL models are developed: a virtual battery model representing the aggregate flexibility of TCLs considering solar irradiance heat gains and wall/floor heat transfers, and a frequency transient model representing the aggregate dynamics of a TCL collection considering communication delays and the presence of model uncertainty and time-variability. The proposed aggregate TCL models are then used to design a practical Energy Management System (EMS) integrating TCL flexibility, and study the impact of TCL integration on microgrid operation and frequency control. Computational experiments using detailed frequency transient and thermal dynamic models are presented, demonstrating the accuracy of the proposed aggregate TCL models, as well as the economic and reliability benefits resulting from using these aggregate models to integrate TCLs in microgrid operations.
Impact of 100‐MW‐scale PV plants with synchronous power controllers on power system stability in northern Chile
(Institution of Engineering and Technology (IET), 2017-08-11) Remon, Daniel; Cañizares, Claudio A.; Rodriguez, Pedro
The impact that renewable energy sources interfaced by power electronics have on power systems becomes more important as their share in the generation mix increases, thus requiring detailed analyses that take into account their dynamics and controllers. In this study, the impact of photovoltaic (PV) power plants on the power system of northern Chile is analysed. The studied plants employ a controller that allows power converters to interact with the grid like virtual synchronous generators, and their model includes the dynamics of the plant and converter controllers, as well as the dc and PV system. The presented analysis, which comprises modal analysis and time-domain simulations of large disturbances, evaluates the impact of these plants with respect to PV plants based on a conventional converter controller. Tests and validations of the proposed models and controllers are carried out for an actual PV plant connected to the power system of northern Chile, and for a higher PV penetration case. The results show the ability of PV plants formed by virtually synchronous power converters to limit frequency excursions induced by large power imbalances, and to mitigate power oscillations of the synchronous machines in the system.
Marginal Rate of Technical Substitution curves for frequency regulation services
(Elsevier, 2022-07-22) Guzman, Noela Sofia; Cañizares, Claudio A.; Bhattacharya, Kankar; Sohm, Daniel
This paper presents a detailed methodology to develop Marginal Rate of Technical Substitution (MRTS) curves, which can be used to optimally determine the appropriate substitution of traditional regulation signals with fast regulation signals, considering different Energy Storage System (ESS) technologies and discharging times, scenarios, and seasons. The presented work is based on the Ontario Power System (OPS) managed by the Independent Electricity System Operator (IESO) of Ontario, Canada. Different comparisons of the MRTS curves are carried out and the criteria used to obtain 16 average optimized MRTS curves, four per season, are presented. Finally, the 16 MRTS curves obtained for the IESO and their parameters are presented, and the use of these curves is explained through an example.
Optimization- and Rule-based Energy Management Systems at the Canadian Renewable Energy Laboratory microgrid facility
(Elsevier, 2021-03-05) Restrepo, Mauricio; Cañizares, Claudio A.; Simpson-Porco, John W.; Su, Peter; Taruc, John
This paper presents the development, implementation, and commissioning of two different Energy Management Systems (EMSs) for the Canadian Renewable Energy Laboratory (CANREL), a microgrid testbed located in Guelph, ON, Canada, for the existing hardware, software, and communication infrastructure, which constrained the implementation options. A Rule-based EMS (RBEMS), which is typically found in microgrid controllers nowadays, and an implementation of an Optimization-based EMS (OBEMS), which is not usual in today’s controllers, are proposed, tested, and demonstrated in the microgrid testbed. The RBEMS consists of a state machine that represents the commitment of different genset units in the system and the curtailment of load and renewable generation. The OBEMS is based on a unit commitment model for microgrids that minimizes the generation and curtailment costs, while operating the microgrid equipment according to technical limits. Both EMS systems are integrated into a Python application which integrates various open-source packages and solvers, making it affordable, flexible and easy to replicate and upgrade. The successful implementation and performance of the EMS is discussed, showing that the components of the microgrid follow the dispatch commands, with the OBEMS yielding better overall results than the RBEMS, as expected, using the existing communications links and maintaining the stability of the microgrid.
Regulation Signal Design and Fast Frequency Control With Energy Storage Systems
(Institute of Electrical and Electronics Engineers (IEEE), 2021-06-02) Guzman E., Noela Sofia; Arriaga, Mariano; Cañizares, Claudio A.; Simpson-Porco, John W.; Sohm, Daniel; Bhattacharya, Kankar
This paper presents a novel H2 filter design procedure to optimally split the Frequency Regulation (FR) signal between conventional and fast regulating Energy Storage System (ESS) assets, considering typical Communication Delays (CDs). The filter is then integrated into a previously validated FR model of the Ontario Power System (OPS) including Battery and Flywheel ESSs, which is used to analyze the impact of these ESSs, CDs, and limited regulation capacity in the FR process in a real system. The proposed methodology to split the FR signal is also compared with the existing FR process, with the results showing that the proposed H2 filter design and signal splitting strategy can improve the FR process performance significantly, in terms of reducing the Area Control Error (ACE) signal, and thus reduce the need for regulation capacity.
Two-Stage Stochastic Optimization Model for Multi-Microgrid Planning
(Institute of Electrical and Electronics Engineers (IEEE), 2022-10-03) Vera, Enrique Gabriel; Cañizares, Claudio A.; Pirnia, Mehrdad; Guedes, Tatiana Pontual; Trujillo, Joel David Melo
This paper presents a Two Stage stochastic Programming (TSSP) model for the planning of Multi-Microgrids (MMGs) in Active Distribution Networks (ADNs). The model aims to minimize the total costs while benefiting from interconnections of Microgrids (MGs), considering uncertainties associated with electricity demand and Renewable Energy Sources (RESs). The associated uncertainties are analyzed using Geometric Brownian Motion (GBM) and probability distribution functions (pdfs). The model includes long-term purchase decisions and short-term operational constraints, using Geographical information Systems (GIS) to realistically estimate rooftop solar limits. The planning model is used to study the feasibility of implementing an MMG system consisting of 4 individual Microgrids (MGs) at an ADN in a municipality in the state of São Paulo, Brazil. The results show that the TSSP model tends to be less conservative than the deterministic planning model, which is based on simple and pessimistic reserve constraints, while performing faster than a simple Stochastic Linear Programming (SLP) algorithm, with higher accuracy.