TACMA: total annual cost minimization algorithm for optimal sizing of hybrid energy systems

Abstract

In a stand-alone environment, a system comprising of non-renewable source, renewable energy sources (RESs), and energy storage systems like fuel cells (FCs) provide an effective and reliable solution to fulfill the user’s load. In this paper, a diesel generator (DG), photovoltaics (PVs), wind turbines (WTs) and FCs are modeled, optimally sized, and compared in three scenarios: PV–WT–FC–DG, PV–FC–DG, and WT–FC–DG in terms of environmental emission and total annual cost (TAC) for a home, located in Hawksbay, Pakistan. The optimal size of hybrid RESs and their components is achieved using a novel TAC minimization algorithm (TACMA). The TACMA achieves superior results in terms of TAC when it is compared to two algorithm-specific parameter-less schemes: Jaya and teaching learning-based optimization. Further, the PV–WT–FC–DG and PV–FC–DG hybrid systems are found as the most economical and nature-friendly scenarios, respectively.

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Correspondence to Nadeem Javaid.

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Khan, A., Javaid, N. TACMA: total annual cost minimization algorithm for optimal sizing of hybrid energy systems. J Ambient Intell Human Comput 11, 5785–5805 (2020). https://doi.org/10.1007/s12652-020-01964-6

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Keywords

  • Unit sizing
  • Stand-alone system
  • Renewable energy sources
  • Energy storage system
  • Meta-heuristic algorithms
  • Optimization