Development of fuzzy logic for demand response and storage management in hybrid energy system

A Hybrid Energy System (HES) is a system that integrates multiple energy sources obtained by synchronizing energy output. Previous work has confirmed that HES in off-grid applications is economically viable, especially in remote areas. The energy management system (EMS) used in existing HESs are complicated, costly and less reliable this is because of over-or under unit sizing or mismatch between supply and demand, despite several improvements made over the last decade. The study was conducted to provide novel strategies for energy management of HESs by improving energy unit sizing and considering demand response program as well as storage management. The first objective of this thesis is to develop an existing computational model for optimising the sizing of micro-scale HES using Particle Swarm Optimisation (PSO). The second objective was to model and simulate an economic system in evaluating the performance and identifying the constraints in line with HES applications. Another objective of the study was to investigate the improvements that can be achieved in the storage management by minimising the mismatch between supply and demand during peak demand. The last objective was to design a real-time physical control system, by analysing the energy generation ability compared to load demand characteristics. The control unit should be able to be used in any weather condition. MATLAB Simulink software was used to model, simulate, and analyse the entire HES. The developed model was used to optimise the HES with an off-grid load. The constructed HES included a wind turbine, a hydro turbine, and a photovoltaic array, which were used as primary energy systems along with a compact battery as a backup energy system to supply continuous power to the load when the HES power was less than the load demand. Additionally, a Proton-exchange membrane fuel cells (PEMFC) was integrated into the system to harness excess energy from the hybrid system during the periods that the load demand was below the energy generation and the battery was fully charged. A Fuzzy Logic Controller (FLC) structure has been implemented in this system as the power management technique to control dispatch strategies and make optimum decisions. Due to the high cost of the energy storage system equipment, the combination of Energy Storage Management (DSM) and the Demand Side Management (DSM) was considered and subsequently, this could bring more reliability to the system. The experimental aspect of the research was conducted in the Nectar Lab in Serdang, Malaysia. A Programmable Logic Controller (PLC) was used for implementing, monitoring and controlling the HES, i.e. the Power Management Box. The design of the control panel unit was mainly aimed to control the dispatch between Generation, Demand and the backup system. The PLC controller, after receiving the data from all components via Remote IO, decided the best optimum operation mode for a specific location by considering the above objectives. The outcomes of this study, together with an economic analysis for a given system provide optimal costing and sizing for the planned system. The optimal cost of the system obtained in the economic analysis demonstrates that the system can be a good alternative for a grid isolated area and could be used as an off-grid system in areas of low demand.

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