Optimum design of a multi-form energy hub by applying particle swarm optimization

Abstract

In this work, optimal expansion planning is modeled mathematically as an optimization problem that considers the optimal combination of different generators, energy devices, and transmission lines. A wide range of research was conducted for several years to identify a solution for this problem. In this work, a single hub with various energy sources, i.e., gas, heaters, and power, is considered for resolving the optimum extension planning problem. A hub is generally composed of a varying numbers of combined heat and power units, kilns, and power transformers, which are in charge of satisfying heat and electricity demands throughout a specified time. Natural gas, power, and wood chips are the inputs to the hub. The target of the optimization problem is to reduce the release of polluting gases and improve the overall energy expense. Scentless transformation is used for simulating the indeterminacy and correlated electrical and heat demands. Initially, the problem is simulated as a limitation optimization problem; then, it is modified to a limit-less problem based on the Lagrange technique. The particle swarm optimization algorithm is used to determine a solution for the optimization problem, which resulted in the identification of the optimum quantities of the input powers along with the optimal number of devices. Obtained results of PWin, PGin, and PEin in two case studies, demonstrate the validity of proposed model while, the interrelationship among demands increases, and the standard deviation of Z increases and the expected value of y reduces. The proposed approach is applied on two engineering test cases; the solution for the optimal expansion problem is determined for time durations of two and five years. The obtained results demonstrate the validity of the proposed model.