Browsing by Author "Solanki, Bharatkumar V."

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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.
A Sustainable Energy Management System for Isolated Microgrids
(Institute of Electrical and Electronics Engineers (IEEE), 2017-04-12) Solanki, Bharatkumar V.; Bhattacharya, Kankar; Canizares, Claudio A.
In this paper, the equivalent CO2 emission models for fossil-fuel-based distributed generator units are developed considering their individual emission characteristic and fuel consumption. These models are then integrated within a microgrid energy management system (EMS) model. Constant energy, demand shifting load models are further integrated in the EMS to examine the possible impact of demand response (DR) on the total system emissions and economics of a microgrid. Thus, the impacts of including the developed emission models on the operation of an isolated microgrid, equivalent CO2 emissions, and costs are examined considering five different operating strategies. The proposed operating strategies are validated on a modified CIGRE medium voltage benchmark system. The results obtained highlight the effectiveness of the proposed EMS and also demonstrate the impact of DR on emissions and costs.
Energy Storage in Microgrids: Compensating for Generation and Demand Fluctuations While Providing Ancillary Services
(Institute of Electrical and Electronics Engineers (IEEE), 2017-08-16) Farrokhabadi, Mostafa; Solanki, Bharatkumar V.; Canizares, Claudio A.; Bhattacharya, Kankar; Koenig, Sebastian; Sauter, Patrick S.; Leibfried, Thomas; Hohmann, Soren
Driven by global environmental emission issues, energy access in remote communities, and tighter requirements for system resilience and reliability, electricity production is shifting from a centralized paradigm to a decentralized one. In this context, renewable energy sources (RESs) have proliferated over the past decade, exhibiting a steadily increasing trend. Thus, today, a large number of wind turbines and photovoltaic (PV) panels are connected to medium- (1-69 kV) and low-voltage (=1 kV) grids, with traditional integrated bulk power systems becoming decentralized in the presence of active distribution networks, where the flow of power is bidirectional between generators and "prosumers." In particular, with decreasing RES s costs, these technologies are becoming attractive solutions to bring energy to remote communities and/or replace expensive fossil-fuel-based generators. However, RES s such as wind and solar are intermittent sources of energy, difficult to predict, and prone to large output fluctuations-therefore, significantly affecting system voltage and frequency.
Energy Storage in Microgrids: Compensating for Generation and Demand Fluctuations While Providing Ancillary Services
(Institute of Electrical and Electronics Engineers (IEEE), 2020-11-05) Farrokhabadi, Mostafa; Solanki, Bharatkumar V.; Canizares, Claudio A.; Bhattacharya, Kankar; Koenig, Sebastian; Sauter, Patrick S.; Leibfried, Thomas; Hohmann, Soren
Driven by global environmental emission issues, energy access in remote communities, and tighter requirements for system resilience and reliability, electricity production is shifting from a centralized paradigm to a decentralized one. In this context, renewable energy sources (RESs) have proliferated over the past decade, exhibiting a steadily increasing trend. Thus, today, a large number of wind turbines and photovoltaic (PV) panels are connected to medium- (1-69 kV) and low-voltage (=1 kV) grids, with traditional integrated bulk power systems becoming decentralized in the presence of active distribution networks, where the flow of power is bidirectional between generators and "prosumers." In particular, with decreasing RES s costs, these technologies are becoming attractive solutions to bring energy to remote communities and/or replace expensive fossil-fuel-based generators. However, RES s such as wind and solar are intermittent sources of energy, difficult to predict, and prone to large output fluctuations-therefore, significantly affecting system voltage and frequency.
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.
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.
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.