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Prediction-Based Optimal Sizing of Battery Energy Storage Systems in PV Integrated Microgrids for Electricity Bill Minimization
https://orcid.org/http://orcid.org/0000-0002-1841-205X
Energy Storage Systems (ESSs) form an essential component of Microgrids and have a wide range of performance requirements. One of the challenges in designing microgrids is sizing of ESS to meet the load demand. Among various Energy storage systems, sizing of Battery Energy Storage System (BESS) helps not only in shaving the peak demand but also maximizes the benefits related to their use. This paper presents an algorithm to optimize the objectives of electricity and operating cost by allocating the size of BESS for delivering the maximum power, in a selected time interval based on C-rate and correspondingly obtained the energy management for PV-BESS and diesel generator-based microgrid system. Here, C-rate of BESS is considered to select the time interval of discharge from BESS as 0.5 and 1 which indicates 2 h and 1 h of discharge durations with respect to maximum load demand and determined the savings in electricity bill for corresponding discharge durations. Nonlinear Model Predictive Control with FMINCON solver-based technique has been adopted to perform the objectives and compared with heuristic-based methods for increasing durations of BESS size. The prediction horizon is divided into two different time intervals based on charging/discharging durations in 24 h to obtain optimal sizing of BESS. Simulation results obtained by Nonlinear Model Predictive Control with FMINCON prove the effective cost minimization of the electricity bill by proper coordination of charge/discharge times of BESS.
Prediction-Based Optimal Sizing of Battery Energy Storage Systems in PV Integrated Microgrids for Electricity Bill Minimization
https://orcid.org/http://orcid.org/0000-0002-1841-205X
Energy Storage Systems (ESSs) form an essential component of Microgrids and have a wide range of performance requirements. One of the challenges in designing microgrids is sizing of ESS to meet the load demand. Among various Energy storage systems, sizing of Battery Energy Storage System (BESS) helps not only in shaving the peak demand but also maximizes the benefits related to their use. This paper presents an algorithm to optimize the objectives of electricity and operating cost by allocating the size of BESS for delivering the maximum power, in a selected time interval based on C-rate and correspondingly obtained the energy management for PV-BESS and diesel generator-based microgrid system. Here, C-rate of BESS is considered to select the time interval of discharge from BESS as 0.5 and 1 which indicates 2 h and 1 h of discharge durations with respect to maximum load demand and determined the savings in electricity bill for corresponding discharge durations. Nonlinear Model Predictive Control with FMINCON solver-based technique has been adopted to perform the objectives and compared with heuristic-based methods for increasing durations of BESS size. The prediction horizon is divided into two different time intervals based on charging/discharging durations in 24 h to obtain optimal sizing of BESS. Simulation results obtained by Nonlinear Model Predictive Control with FMINCON prove the effective cost minimization of the electricity bill by proper coordination of charge/discharge times of BESS.
Prediction-Based Optimal Sizing of Battery Energy Storage Systems in PV Integrated Microgrids for Electricity Bill Minimization
https://orcid.org/http://orcid.org/0000-0002-1841-205X
Energy Storage Systems (ESSs) form an essential component of Microgrids and have a wide range of performance requirements. One of the challenges in designing microgrids is sizing of ESS to meet the load demand. Among various Energy storage systems, sizing of Battery Energy Storage System (BESS) helps not only in shaving the peak demand but also maximizes the benefits related to their use. This paper presents an algorithm to optimize the objectives of electricity and operating cost by allocating the size of BESS for delivering the maximum power, in a selected time interval based on C-rate and correspondingly obtained the energy management for PV-BESS and diesel generator-based microgrid system. Here, C-rate of BESS is considered to select the time interval of discharge from BESS as 0.5 and 1 which indicates 2 h and 1 h of discharge durations with respect to maximum load demand and determined the savings in electricity bill for corresponding discharge durations. Nonlinear Model Predictive Control with FMINCON solver-based technique has been adopted to perform the objectives and compared with heuristic-based methods for increasing durations of BESS size. The prediction horizon is divided into two different time intervals based on charging/discharging durations in 24 h to obtain optimal sizing of BESS. Simulation results obtained by Nonlinear Model Predictive Control with FMINCON prove the effective cost minimization of the electricity bill by proper coordination of charge/discharge times of BESS.
Prediction-Based Optimal Sizing of Battery Energy Storage Systems in PV Integrated Microgrids for Electricity Bill Minimization
J. Inst. Eng. India Ser. B
Vaka, Srinivas Sandeep Kumar Reddy (author) / Matam, Sailaja Kumari (author)
Journal of The Institution of Engineers (India): Series B ; 103 ; 1733-1745
2022-10-01
13 pages
Article (Journal)
Electronic Resource
English
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