Multi‐variable constrained non‐linear optimal planning and operation problem for isolated microgrids with stochasticity in wind, solar, and load demand data. Issue 11 (15th April 2020)

• Record Type: Journal Article
• Authors: Kumar, Maneesh; Tyagi, Barjeev
• Is Part Of: IET generation, transmission & distribution. Volume 14:Issue 11(2020)
• Page Start: 2181
• Page End: 2190
• Publication Date: 2020-04-15
• Subjects: distributed power generation -- particle swarm optimisation -- power distribution planning -- power generation planning -- power distribution reliability -- power generation reliability -- stochastic programming; operational costs -- DERs -- test MG system -- isolated MG -- global optimal solution -- sequential programming approach -- hybrid particle swarm optimisation approach -- optimal sizing -- reliability conditions -- system constraints -- operation problem -- isolated microgrids -- stochasticity -- load demand data -- microgrid -- small‐scale sources -- microsources -- energy storage devices -- renewable energy penetration -- stochastic optimisation model -- optimal size -- distributed energy resources -- random variables -- wind output -- solar output -- Beta distribution -- cost‐based function -- nonlinear objective function -- multivariable constrained nonlinear optimal planning; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2019.0643
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : A microgrid (MG) is a cluster of small‐scale sources known as micro‐sources, the energy storage devices, and the loads. MGs are promising entities that allow a considerable amount of renewable energy penetration into the system. A stochastic optimisation model is presented in this study to find the optimal size of the distributed energy resources (DERs). The uncertainties are considered with the help of multiple scenarios of random variables viz. wind output, solar output, and load demand data. A particular case of Beta distribution is used to create these variations. A cost‐based, multi‐variable constrained non‐linear objective function is formulated. The considered test MG system is more generalized with solar and wind energy penetration. The results show the effect of operational as well as the planning aspects together under various reliability conditions for an isolated MG. The formulated problem is solved to obtain a global optimal solution using a sequential programming approach and a comparative assessment of results with a hybrid particle swarm optimisation (PSO) approach has also been presented. It is found that the results obtained from the sequential programming approach are better compared to the hybrid PSO approach.