Optimal design of hybrid DG systems for microgrid reliability enhancement
| Autor: | Mohammad Al-Muhaini, Abass Afolabi Yahaya, Gerald T. Heydt |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Optimal design
Wind power business.industry Computer science 020209 energy Reliability (computer networking) 020208 electrical & electronic engineering Energy Engineering and Power Technology Particle swarm optimization 02 engineering and technology Sizing Renewable energy Reliability engineering Control and Systems Engineering Distributed generation 0202 electrical engineering electronic engineering information engineering Microgrid Electrical and Electronic Engineering business |
| Zdroj: | IET Generation, Transmission & Distribution. 14:816-823 |
| ISSN: | 1751-8695 |
| Popis: | While the concept of microgrids and renewable energy systems is not entirely new, these integrated technologies have become a special topic of interest for researchers, utility providers and governments. Many challenges must be overcome to achieve better integration of renewable sources into the energy framework. This study presents some viable possibilities for the utilisation of a hybridised microgrid system. The hybridisation is achieved by an efficient design approach for the enhancement of both load and system reliability indices through the intelligent placement and sizing of hybrid distributed generation (DG) systems. Real-time models of solar photovoltaics, wind turbines, batteries and thermal DGs are presented and implemented. Also, network component failures are stochastically modelled via Monte Carlo simulations, and a general tie-set algorithm using an adapted breadth-first search is proposed. Moreover, mixed-integer multi-objective particle swarm optimisation is employed, giving a four-dimensional Pareto solution that is attained by optimising four reliability-related objectives, namely system average interruption frequency index, System Average Interruption Duration Index (SAIDI), Energy Not Supplied (ENS) and total cost. |
| Databáze: | OpenAIRE |
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