Optimisation of grid connected hybrid photovoltaic–wind–battery system using model predictive control design. Issue 14 (9th October 2017)

• Record Type: Journal Article
• Authors: Mbungu, Nsilulu T.; Naidoo, Raj; Bansal, Ramesh C.; Bipath, Minnesh
• Is Part Of: IET renewable power generation. Volume 11:Issue 14(2017)
• Page Start: 1760
• Page End: 1768
• Publication Date: 2017-10-09
• Subjects: power generation control -- power generation economics -- power markets -- pricing -- energy management systems -- predictive control -- control system synthesis -- photovoltaic power systems -- wind turbines -- wind power plants -- battery storage plants -- hybrid power systems -- smart power grids -- minimisation -- state‐space methods -- discrete systems -- demand side management; grid connected hybrid photovoltaic‐wind‐battery system optimization -- model predictive control design -- hybrid power system -- MPC design -- renewable energy -- smart grid framework -- wind turbine -- battery storage -- utility grid -- discrete state‐space model -- industry application -- real‐time electricity pricing environment -- energy management process -- energy demand delay cost minimization -- performance index -- demand side management; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2017.0381
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : This study explores optimisation of the hybrid power system in the smart grid framework, in conjunction with the model predictive control (MPC) design. This study also creates a strategy that can maximise the use of renewable energy, e.g. photovoltaic, the wind turbine with battery storage and minimise the utilisation of the utility grid for electricity usage in the industry. This is devised by modelling a discrete state‐space model of the hybrid power system for a given industry application. The system design is implemented within a real‐time electricity pricing environment that is integrated with renewable energy to optimally meet the demand according to a specific performance of the consumer. The emphasis of this approach is on its capacity to supply optimal power to the demand side by selecting the appropriate source; and its robustness against uncertainties. The results show that MPC design for hybrid power system not only optimises the energy flow but also improves the overall process of energy management. It was also observed that the optimal solution minimises the delay cost of energy demand from the utility grid according to a given reference from the consumer for the specified tuning parameter values of the performance index.