An integrated framework for optimal planning and operation schedule of microgrid under uncertainty. (September 2019)

• Record Type: Journal Article
• Authors: Prathapaneni, Dimple Raja; Detroja, Ketan P.
• Is Part Of: Sustainable energy, grids and networks. Volume 19(2019)
• Publication Date: 2019-09
• Subjects: Optimal sizing -- Demand side management -- Chance constraint programming -- Uncertainty handling -- Unit commitment; Renewable energy sources -- Periodicals; Smart power grids -- Periodicals; Electric power systems -- Periodicals; 333.794
• DOI: 10.1016/j.segan.2019.100232
• Languages: English
• ISSNs: 2352-4677

Abstract

Abstract: With the emergence of new technologies in power generation methods, microgrids have become a complex system with multiple generators of different types. Sizing of these generators for an economical microgrid has multi-fold challenges. The primary aspect of sizing formulation is incorporating the effects of short-term decision mechanisms, unit commitment and demand side management which significantly impacts the operational cost of the microgrid. Accounting the degradation of the microgridunits and lifetime based on performance are the other important issues that need to be contemplated in sizing methodology. Also, microgrids are associated with uncertainties in load and power generated by renewable sources. Hence, the microgrid sizing problem is a large-scale stochastic optimization problem. In this manuscript, a unified optimization framework for the sizing of an islanded microgrid with features that can simultaneously handle all the challenging issues mentioned above is proposed. Results obtained using the proposed method are compared with the state-of-the-art sizing algorithm. Highlights: Optimal planning framework that simultaneously addresses all key aspects relevant to microgrid. Incorporating the effects of short-term decision mechanism in microgrid sizing. An improved DSM methodology and CCP incorporated in UC problem. Component degradation and lifetime are evaluated based on usage. Dependability of the proposed algorithm is verified.