Nonlinear characteristics of a battery energy storage system (BESS) may cause errors in the stored between operation plan and actual operation. These hinder reliability power especially environments such as microgrids with limited generation resources high uncertainty. This study proposes method to alleviate occurrence charging/discharging scheduling process BESS by piecewise linearizing its no...

This work proposes a hybrid genetic algorithm to address the Unit Commitment (UC) problem. In the UC problem, the goal is to schedule a subset of a given group of electrical power generating units and also to determine their production output in order to meet energy demands at minimum cost. In addition, the solution must satisfy a set of technological and operational constraints. The algorithm ...

This paper presents a novel method for unit commitment by synergistically combining Lagrangian relaxation for constraint handling with Hopfield-type recurrent neural networks for fast convergence to the minimum. The key idea is to set up a Hopfieldtype network using the negative dual as its energy function. This network is connected to “neuron-based dynamic programming modules” that make full u...

As an energy market transforms from a regulated market to a deregulated one, the demands for a power plant are highly uncertain. In this paper, we study a two-stage robust optimization formulation and provide a tractable solution approach for the problem. The computational experiments show the effectiveness of our approach.