Multi-Objective Optimization of Hybrid Solar-Wind-Battery Power Generation System

  • Ahmed Saif

Student thesis: Master's Thesis


Stimulated by concerns over the global warming and driven by technological advancements, renewable energy sources (RES) such as solar and wind are gaining interest as the energy sources of the future. To overcome the intermittency and uncontrollability issues of RES-powered generators, they can be combined together and/or with conventional generators and energy storage devices in Hybrid Power Systems (HPS). Proper design of a HPS is crucial for reliable, economic, and ecofriendly operation. In this thesis, three complementary optimization models are developed for the design of HPS, comprising a complete design strategy. The first is formulated as a Multi-objective Linear Programming (MOLP) optimization problem that assumes deterministic RES supply and disregards the network configurations. The second model is a rule-free Stochastic Multi-objective Non-Linear Programming (SMONLP) optimization problem for optimal sizing and siting of Distributed Generation and Storage (DGS), taking into account the stochastic nature of RES supply and grid availability and the network topology. The last model is a simulation/rule-based optimization framework combining a Dynamic Optimal Power Flow (DOPF) routine with Particle Swarm Optimization (PSO) algorithm.The proposed design strategy was applied on a grid-connected Micro-grid (MG), and the main findings were highlighted and explained. The trade-off between cost and emissions minimization is analyzed using the Pareto optimality concept and the cost of 'being green' is determined.
Date of AwardDec 2011
Original languageAmerican English


  • Energy Consumption
  • Renewable Energy Sources

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