Optimized Voltage-Led Customer Load Active Service Using Genetic Algorithm in Distribution Networks

Abstract

To mitigate the low frequency problem in a transmission system in an event of a power station failure or during low renewable generation production, UK National Grid (NG) Electricity System Operator has balancing mechanism in place with generators to provide temporary extra power, or with large energy users to reduce load demand or so call fast reserve services. This paper presents an alternative method to aggregately control the existing distribution network primary on load transformer tap changers as a voltageled customer load active service. The main benefits of the proposed method are (i) to unlock the distribution network load demand flexibility without causing any negative impact on customers, and (ii) to provide the lowest cost of fast reserve service from a distribution network to transmission network. In this paper an optimal control strategy based on genetic algorithm is proposed and developed to achieve an optimized voltage-led customer load active service with the aim of finding the optimal dispatch of on load transformer tap changers by minimizing each transformer tap switching operation as well as network losses. Two practical 102 buses and 222 buses UK distribution networks have been modelled and used to demonstrate and compare the effectiveness of the proposed control methods under different operating conditions. The performances of the proposed method are also compared with both the rule-based and the branch-and-bound methods. The results show that the proposed optimal control strategy based on the genetic algorithm is more effective by achieving more accuracy and a faster solution for a large distribution network than other two methods. These are important findings as the fast reserve service by transmission network requires the accuracy of the load demand reduction delivery within 2 minutes.INDEX TERMS Fast reserve, customer active load service, load demand reduction management, aggregately control of transformer tap changers, genetic algorithm, and optimizations.

Tap Staggering Analysis and Effects on the Adaptive Protection System in Networks With Renewable Energy Sources

“…The main benefits of the CLASS is unlocking the distribution network load demand flexibility without causing any negative impact on customers and providing the lowest cost of fast reserve service from a distribution network to a transmission network. When the CLASS method is applied to all 60 primary substations for 600 hours per year, this method provides up to 129 MVAr of reactive power absorption and saves up to 3336 tons of CO 2 per year and it also defers huge reinforcement cost by eliminating the need to install new equipment [6], [7]. Rousis, Pipelzadeh, et al, demonstrate the effectiveness of tap staggering application on 132/33 kV parallel transformers in the distribution network to mitigate the overvoltage problem on the 400 kV transmission system in southeast England [8].…”