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Abstract
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The penetration of distributed generators (DGs) is continually increasing in the power sector due to its
ability in enhancing technical specifications as well as providing a promising future for power generation
in electric networks. The aforementioned objectives will be realized if DG units are allocated optimally
and coordinately simultaneous with distribution network expansion planning. On the other hand, given
the stochastic nature of renewable generation and severe fluctuations of load consumption and electricity
price, the DGs planning problem should be accomplished under uncertainties. To address these issues,
this paper proposes a novel joint chance constrained programming (JCCP) method to fulfill an acceptable
level of constraint feasibility for optimal simultaneous expansion planning of HV/MV substations and
multiple-DG units along with robust MV feeder routing problem. Our design objective is to determine
the optimal site and size of sub-transmission substations and various DG units associated with optimally
construction of network by implementing the feeder routing problem with aim to minimize the
investment costs, energy not supplied (ENS) cost and energy purchasing cost from upstream network.
The diverse objectives are mathematically formulated as an MINLP model and converted into a singleobjective
function through weighted sum method and subsequently has been minimized by adaptive
genetic algorithm. Furthermore, the Taguchi method is utilized in order to furnish an efficient algorithm
that can find a satisfactory solution. Finally, the effectiveness of the proposed method is investigated by
applying it on the 54-bus distribution network and the obtained results are duly drawn and discussed.
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