An Optimal Multivariable Constrained Nonlinear (MVCNL) Stochastic Microgrid Planning and Operation Problem With Renewable Penetration

Abstract

Microgrids (MGs) are promising archetypes for the penetration of renewable energy sources (RES) into the system for reducing carbon footprints. This article presents a cost-based optimization model using a stochastic programming to obtain the optimal size of distributed energy resources including RES. Uncertainties in the solar output and the load demand data are considered using multiple scenarios with random variations, which are based on beta distribution. The objective function is formulated as a cost-based multivariable constrained nonlinear convex programming problem. Other than planning costs, the objective function also includes per day running or operational costs such as unit commitment costs as well as the switching costs associated with the dispatchable units. The overall problem is simulated under MATLAB environment. Quantitative results indicate the impact of operational paradigm along with the planning of an MG in the form of cost analysis with different reliability conditions. An assessment of results in tabular form is presented, which incorporates the optimal sizing of MG under the different system reliability conditions and constraints. Some additional cases pertain to the generation and the load demand scenarios have also been included in the article.