Abstract
This paper presents a design method based on an expert system for the optimisation of hybrid power systems used in applications. Hybrid power systems for off-grid have been widely discussed and tested since they can offer a potentially attractive alternative to diesel-based power systems, but they have not yet proven to be more reliable and cost competitive than conventional solutions. The main issues in hybrid power systems are inadequate component reliability -leading to unpredicted costs and unforeseen harsh environmental conditions exceeding the domain of conventional design techniques. While components are undergoing considerable improvement, system design methods and life cycle cost calculation are not being addressed thoroughly. Several software programs are currently available for simulating the operation of hybrid electric power systems, using either simple algorithms or dynamic methods, but none includes all relevant information for applications: information on local cost, reliability, climatic conditions for sites of interest, remote monitoring, maintenance strategies and actual estimate of maintenance and reduced running costs. An expert system (ES) has been developed on the basis of extensive dynamic simulation, using a conventional simulation model, and all relevant information on cost, maintenance schemes, load profiles specifically tailored for actual telecom outdoor applications in Italy and other countries in the Mediterranean area. Technology include Photovoltaic and Wind generators, battery storage and backup diesel. The ES has also been used to asses the potential impact of innovative components (such as charge regulators, fuel cells and remote monitoring systems) on reliability and life cycle cost. The ES only requires information generally available at the initial stage of a project (e.g. site installation, network type, reliability requirements) to determine the best hybrid mix of diesel generation, battery storage, photovoltaic and wind generation, for optimal performance in the regions of interest. The method has been validated using data on existing installations and has been applied to the design of a new hybrid power system.
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