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The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
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In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
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An improved transient search optimization algorithm for building energy optimization and hybrid energy sizing

Thira Jearsiripongkul1, Mohammad Ali Karbasforoushha2, Mohammad Khajehzadeh3,4

  • 1Research Unit in Advanced Mechanics of Solids and Vibration, Department of Mechanical Engineering, Thammasat School of Engineering, Faculty of Engineering, Thammasat University, Pathumthani, 12121, Thailand. jthira@engr.tu.ac.th.

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A new Improved Transient Search Optimization Algorithm (ITSOA) enhances energy optimization for buildings and hybrid systems. ITSOA outperforms other methods in benchmark tests and real-world applications, demonstrating superior efficiency.

Keywords:
Building energy optimizationEnergy consumptionEnergy production costMeta-heuristic algorithmsTransient search optimization

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms
  • Sustainable Energy Systems

Background:

  • Conventional Transient Search Optimization Algorithm (TSOA) is inspired by electrical circuit dynamics.
  • Existing optimization methods face challenges in balancing exploration and exploitation.
  • Efficient optimization is crucial for reducing building energy consumption and improving hybrid energy systems.

Purpose of the Study:

  • To introduce and evaluate the Improved Transient Search Optimization Algorithm (ITSOA).
  • To assess ITSOA's effectiveness in solving benchmark functions and optimizing building energy usage.
  • To verify ITSOA's capability in optimizing hybrid energy system production.

Main Methods:

  • Developed the Improved Transient Search Optimization Algorithm (ITSOA) by integrating Rosenbrock's direct rotation technique into TSOA.
  • Tested ITSOA on 23 classical benchmark functions against conventional TSOA and other metaheuristic algorithms (DMO, SHO, GA, MRFO, PSO).
  • Applied ITSOA to single and multi-objective building energy optimization (BEO) problems for minimizing energy consumption.

Main Results:

  • ITSOA demonstrated superior performance over conventional TSOA and other compared methods in solving benchmark functions.
  • ITSOA achieved lower cost function values for both single and multi-objective building energy optimization problems.
  • ITSOA effectively identified optimal solutions within the Pareto front for multi-objective BEO using a fuzzy decision-making approach.

Conclusions:

  • The Improved Transient Search Optimization Algorithm (ITSOA) offers enhanced capabilities for complex optimization tasks.
  • ITSOA provides a more efficient and superior approach to building energy optimization compared to existing methods.
  • ITSOA shows significant potential for optimizing hybrid energy systems and contributing to sustainable energy solutions.