Browsing by Author "Calero, Fabian"

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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.
Aggregated BESS Dynamic Models for Active Distribution Network Studies
(Institute of Electrical and Electronics Engineers (IEEE), 2020-12-31) Calero, Fabian; Canizares, Claudio A.; Bhattacharya, Kankar
This article proposes a transmission-system-level aggregated model of Battery Energy Storage Systems (BESSs) distributed through Active Distribution Networks (ADNs), to study the dynamic performance and services provided by these systems to power grids. ADNs comprise intelligent loads, local generation, particularly solar PV, and BESSs, which can provide different services to transmission grids, including voltage control, oscillation damping, frequency regulation, and active and reactive power injections. Proper equivalent models of the ADN components allow to evaluate the impact and integration of these networks on power grids. In this article, ADN's measurements of the aggregated response of the BESSs at the boundary bus with the transmission system are used to develop an aggregated black-box model based on two Neural Networks (NNs), one for active power and another for reactive power, with their optimal topology obtained using a Genetic Algorithm (GA). Detailed simulations are performed, using a commercial-grade software for power system analysis, of multiple BESSs connected to a CIGRE benchmark ADN connected to a bus of the 9-bus WSCC benchmark transmission network; the test ADN is then replaced by the proposed black-box model, with aggregated models of the loads and PV generation, demonstrating that the proposed model can accurately reproduce the results obtained.
Dynamic Modeling of Battery Energy Storage and Applications in Transmission Systems
(Institute of Electrical and Electronics Engineers (IEEE), 2020-08-13) Calero, Fabian; Canizares, Claudio A.; Bhattacharya, Kankar
In this paper, a Battery Energy Storage System (BESS) dynamic model is presented, which considers average models of both Voltage Source Converter (VSC) and bidirectional buck-boost converter (dc-to-dc), for charging and discharging modes of operation. The dynamic BESS model comprises a simplified representation of the battery cells, which allows to simulate the effects of battery degradation, dc-to-dc converter, VSC, and the dynamics associated with the filter and transformer connecting the BESS to the grid. A decoupled dq-current control is used for the VSC, allowing the operation of the BESS in several modes, i.e., constant active and reactive power, constant power factor, voltage regulation, frequency regulation, oscillation damping, and a combination of the latter two. The proposed model is implemented in DSATools and tested for different contingencies on a benchmark system, and compared with a industry-grade BESS model used in power system dynamic studies. The importance of modeling the current control and dynamics of the dc-to-dc are demonstrated, especially when the battery cells are degraded due to, for instance, aging.