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Learning methods for spiking neural networks are not as well developed as the traditional rate based networks, which widely use the back-propagation learning algorithm. We propose and implement an efficient Hebbian learning method with homeostasis for a network of spiking neurons. Similar to STDP, timing between spikes is used for synaptic modification. Homeostasis ensures that the synaptic weights...
In order to evaluate the techno-economic performance of Hybrid Energy System for remote rural area electrification, a mixed integer linear mathematical programming model (time-series) has been developed to determine the optimal operation, optimal configuration including the assessment of the economic penetration levels of photovoltaic array area, and cost optimization for a hybrid energy generation...
Different economic models have been applied to the resource allocation problem in grids. Contract net is one such model in which a job is announced to the resources, the resources bid for the job, and then the broker chooses one bid from the received bids based on some policy. The job is awarded to the resource with the winning bid. In this paper, we first propose a contract net based resource allocation...
This paper presents the results of the application of model (developed in Part-I) and simulation algorithm (developed in Part-II) for determining the techno-economics of battery storage type hybrid energy system intended to supply the load demand of a rural remote area having a cluster of nine villages (grid isolated). The hour-by-hour simulation model is intended to simulate a typical one month period...
Computer simulation is an increasingly popular tool for determining the most suitable hybrid energy system type, design and control for an isolated community or a cluster of villages. This paper presents the development of the optimum control algorithm based on combined dispatch strategies, to achieve the optimal cost of battery incorporated hybrid energy system for electricity generation, during...
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