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Despite the ability of renewables to decarbonize energy use, their intermittent nature causes inconsistent energy generation, thus energy storage is required to tackle the supply-demand mismatch. While the use of hybrid battery-hydrogen energy storage for microgrids has been extensively studied, there is a lack of study on the integration of electricity and hydrogen supply systems. In other words, the concurrent targeting of hydrogen and electrical loads in a microgrid with hybrid battery-hydrogen storage is lacking. This study presents an optimization framework for the design and operation of a standalone microgrid with electrical and hydrogen loads. Two energy management strategies have been proposed and the optimization model is solved using particle swarm optimization algorithm. The proposed methodology was demonstrated through a case study and the levelized cost of energy ranges from 0.4551 USD/kWh to 0.4572 USD/kWh for the base case scenario. The optimal microgrid design in base case scenario is found to have a high value of potential energy waste possibility, indicating that the solar panel is oversized to reduce energy storage requirement. Sensitivity analysis results showed that a significant cost reduction can be achieved when only 95% of loads are targeted. [Display omitted] • Optimization of microgrid using particle swarm optimization method. • Design of microgrid considering fluctuations in energy profiles. • Integrated hydrogen and electricity supply systems. • Evaluation of the cost-effectiveness of solar tracking system. • Results proposed the most appropriate energy management strategy for microgrid. [ABSTRACT FROM AUTHOR]

Renewable energy is the key to decarbonize energy use despite the growing global energy demand. However, energy storage is required to tackle the supply-demand mismatch caused by the intermittent nature of renewable energy sources. As each type of energy storage has a distinct discharge duration, a hybrid energy storage system can be more cost-effective than a single energy storage system. While various process integration tools have been employed for the optimization of microgrid with hybrid energy storage, a graph theoretic algorithm known as P-graph allows the identification of optimal and near-optimal solutions for practical decision making. P-graph involves modelling by graphs and the embedded accelerated branch-and-bound algorithm enables efficient determination of optimal solution. This study proposes a multi-period P-graph optimization framework for the optimization of photovoltaic-based microgrid with battery-hydrogen energy storage and the proposed approach is demonstrated through two case studies. Results showed that the optimal cost of microgrid with hybrid battery-hydrogen storage is 704,990 USD/y, a carbon price of 1000 USD/t and above is required to make it more economical than conventional electricity use. Replacing the hydrogen storage system with grid support reduces the total cost and required carbon price to 262,334 USD /y and 300 USD /y respectively. [Display omitted] • A multi-period P-graph optimization framework for renewable energy system. • Targeting of battery and hydrogen storage in microgrid. • The proposed methodology is demonstrated using two case studies. • Economic feasibility of microgrid and suitable rates of carbon pricing are studied. • The method is useful for the targeting of microgrid with intermittent energy source. [ABSTRACT FROM AUTHOR]

Decentralized energy generation (DEG) system which characterizes local power generation and utilization are recently getting more attention in energy system planning and implementation because it produces cleaner energy from renewable resources and is capable to avoid significant energy losses during the power transfer from the centralized power plants. These DEGs are however scattered in locations and have intermittent power supply, making it difficult to self-sustain. In this study, a novel integrated energy system consisting of multiple DEGs connected to the existing CEG is proposed. New aspects that are included in the model include the distribution and transmission losses as well as impact of operating load on the heat rate of power plants. Energy storage system were also modelled to operate within the DEG and CEG network. Through a case study demonstration, the capacities of the integrated system were optimized using superstructure-based mixed integer non-linear programming (MINLP) mathematical modelling. The system was also optimized based on economic and energy efficiency to study the effects and trade-off between the two parameters. The results revealed that the optimal system can be obtained with levelized cost of electricity of MYR 0.44/kWh. The result also revealed that biomass and wind energy favours industrial users. Image 1 • Decentralized energy generation (DEG) system prioritizing intermittent sources. • Scheduling of the DEG and CEG is modelled separately considering changes in heat rate. • Combination of wind and biomass-based electricity for industrial use is recommended. • A single powered solar PV is recommended for residential users. • The model suggests to build a larger natural gas power plant with energy storage. [ABSTRACT FROM AUTHOR]