A Chance-Constrained Multistage Planning Method for Active Distribution Networks

Nikolaos Koutsoukis and Pavlos Georgilakis
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Nikolaos Koutsoukis: School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Zografou, Greece
Pavlos Georgilakis: School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Zografou, Greece

Energies, 2019, vol. 12, issue 21, 1-19

Abstract: This paper introduces a multistage planning method for active distribution networks (ADNs) considering multiple alternatives. The uncertainties of load, wind and solar generation are taken into account and a chance constrained programming (CCP) model is developed to handle these uncertainties in the planning procedure. A method based on a k-means clustering technique is employed for the modelling of renewable generation and load demand. The proposed solution methodology, which is based on a genetic algorithm, considers multiple planning alternatives, such as the reinforcement of substations and distribution lines, the addition of new lines, and the placement of capacitors and it aims at minimizing the net present value of the total operation cost plus the total investment cost of the reinforcement and expansion plan. The active network management is incorporated into planning method in order to exploit the control capabilities of the output power of the distributed generation units. To validate its effectiveness and performance, the proposed method is applied to a 24-bus distribution system.

Keywords: active distribution network; chance constrained programming; distribution network planning; metaheuristic optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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