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In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES for maximizing the life-cycle cost saving including capital cost associated with storage capacity as well as incentives from both fast DR and PLM.
Optimum resource allocation has been proposed in [9, 10] to optimize the capacity of AF networks.
This paper describes an approach to optimize the capacity of battery used in a grid-connected photovoltaic system (PV/storage system).
In this work we propose a mechanism to optimize the capacity of the main corridor within a railway network with a radial-backbone or X-tree structure.
The authors [18] propose a mixed-integer linear programming framework for DSM to optimize the capacity of PV and an energy storage system when considering the variability of loads during weekday-weekend and different seasons.
To maximize the benefits (energy-saving and emission-reducing) achieved by the BCHP system in comparison to the SP system, genetic algorithm (GA) is employed to optimize the capacity of BCHP system in consideration of its operation mode.
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Therefore, a mathematical model is proposed to optimize the capacities of micro-resources, which can harvest green energy from renewable energy resources (RERs) as much as possible.
This paper recommends an optimal sizing model, to optimize the capacity sizes of different components of photovoltaic water pumping system (PWPS) using water tank storage.
This paper recommends an optimal sizing model based on iterative technique, to optimize the capacity sizes of different components of hybrid photovoltaic/wind power generation system using a battery bank.
Mathematical Programming approaches have also been successfully applied to health care related problems: Zhang et al. used a Mixed Integer Program (MIP) to optimize the capacity allocation of operating rooms to specialties [ 25].
Tong and Haenggi [17] focus on an ALOHA system to provide analytical expression to optimize the capacity given the density of FD and HD nodes.
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