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Reducing the fuel consumption within a power network is crucial to enhancethe overall system efficiency and minimize operating costs. Fuel consumptionminimization can be achieved through different optimization techniques wherethe output power of the generators is regulated based on their individualefficiency characteristics. Existing studies primarily focus either onmaximizing the efficiency function or minimizing the operating cost function ofthe generators to minimize fuel consumption. However, for practicalimplementation, it becomes imperative to incorporate a function within theoptimization framework to represent the fuel consumption rate directly. Thisstudy introduces a novel approach by formulating a minimization problem with asum-of-ratios objective function representing the fuel consumption rate.However, optimization problems with sum-of-ratios objective functions orconstraints are extremely challenging to solve because of their strongnonlinearity. To efficiently solve the formulated problem, a fractionalprogramming (FP) approach is adopted in this study. This reformulationtechnique significantly reduces the solution time of the optimization problemand provides a better solution than nonlinear programming (NLP). In addition,the reformulated problem can also be applied to large-scale systems where theNLP fails to converge. The proposed methodology of this study is tested on thenotional MVAC ship system, modified IEEE 30-bus and IEEE 118-bus systems. Theresults demonstrate that the model successfully minimizes fuel consumption byeffectively scheduling the generator and ESS dispatch.

An Advanced Fuel Efficiency Optimization Model with Fractional Programming