Optimal Placement of Data Centers to Support Power Distribution Networks Using Intelligent Algorithms with Economic Indicators
Amin Hajihasani, Mahmoud Modaresi

TL;DR
This paper presents an intelligent optimization framework for optimal data center placement that minimizes power losses, improves voltage quality, and considers economic factors using a mixed integer nonlinear model and genetic algorithms.
Contribution
It introduces a novel integrated techno-economic model for data center siting in distribution networks with renewable generation and adaptive genetic algorithms.
Findings
Reduced power losses by approximately 73 kW in case study
Improved minimum bus voltage to 0.933 pu
Demonstrated effectiveness on IEEE 33 bus system
Abstract
Data centers are among the fastest growing electricity consumers and can impose severe voltage drops and feeder losses when connected to weak distribution networks. This paper formulates a techno economic siting problem in which each candidate data center site is mapped to a bus of the distribution network and is assumed to deploy on site renewable generation and power electronic interfaces, resulting in a controllable net active power injection equivalent to distributed generation. A mixed integer nonlinear optimization model is developed to jointly select the connection bus and size the DG capacity while respecting network operating limits. The objective combines three normalized terms including active power losses, a voltage deviation index capturing profile quality, and investment cost derived from location dependent land price and unit DG cost. To address the discrete continuous…
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Taxonomy
TopicsOptimal Power Flow Distribution · Cloud Computing and Resource Management · Advanced Optical Network Technologies
