New Multistage and Stochastic Mathematical Model for Maximizing RES Hosting Capacity—Part I: Problem Formulation

This two-part work presents a new multistage and stochastic mathematical model, developed to support the decision-making process of planning distribution network systems (DNS) for integrating large-scale "clean" energy sources. Part I is devoted to the theoretical aspects and mathematical...

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Bibliographic Details
Published in:IEEE transactions on sustainable energy 2017-01, Vol.8 (1), p.304-319
Main Authors: Santos, Sergio F., Fitiwi, Desta Z., Shafie-Khah, Miadreza, Bizuayehu, Abebe W., Cabrita, Carlos M. P., Catalao, Joao P. S.
Format: Article
Language:English
Subjects:
Capacitors
Clean energy
Computer applications
Decision making
Distributed generation
distribution network systems
Domain names
Electrical networks
Energy sources
Energy storage
energy storage systems
Energy technology
Exact solutions
Integer programming
integrated planning
Investment
Linear programming
Mathematical analysis
Mathematical models
Microbalances
Mixed integer
Optimization
Planning
Power sources
Power system stability
Reactive power
Renewable energy
Smart grids
stochastic programming
Stochasticity
Storage systems
Systems stability
variability and uncertainty
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Summary:This two-part work presents a new multistage and stochastic mathematical model, developed to support the decision-making process of planning distribution network systems (DNS) for integrating large-scale "clean" energy sources. Part I is devoted to the theoretical aspects and mathematical formulations in a comprehensive manner. The proposed model, formulated from the system operator's viewpoint, determines the optimal sizing, timing, and placement of distributed energy technologies (particularly, renewables) in coordination with energy storage systems and reactive power sources. The ultimate goal of this optimization work is to maximize the size of renewable power absorbed by the system, while maintaining the required/standard levels of power quality and system stability at a minimum possible cost. From the methodological perspective, the entire problem is formulated as a mixed integer linear programming optimization, allowing one to obtain an exact solution within a finite simulation time. Moreover, it employs a linearized ac network model which captures the inherent characteristics of electric networks and balances well accuracy with computational burden. The IEEE 41-bus radial DNS is used to test validity and efficiency of the proposed model, and carry out the required analysis from the standpoint of the objectives set. Numerical results are presented and discussed in Part II of this paper to unequivocally demonstrate the merits of the model.
ISSN:1949-3029
1949-3037
DOI:10.1109/TSTE.2016.2598400