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 voltage-led 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.
Highlights
To support net zero carbon emission by 2050, it is imperative a need to have significantly increasing integration of renewable energy resources (RESs), such as wind and photovoltaic generation, into both transmission and distribution networks [1]
While traditional generators are gradually replaced by renewable generation, fast reserve services supported by the declined traditional generation would become rarer and more expensive, load management (LM) would play an increasingly important role to make a short period load demand reductions [5], [6]
STIMULATION RESULTS AND COMPARISONS The Genetic Algorithm (GA)-based optimization for load demand reduction method was implemented on two practical UK high voltage (HV) distribution networks with 102-bus and 222-bus, correspondingly
Summary
To support net zero carbon emission by 2050, it is imperative a need to have significantly increasing integration of renewable energy resources (RESs), such as wind and photovoltaic generation, into both transmission and distribution networks [1]. This paper presents an improved optimal load demand reduction control strategy for the operation of primary transformer tap-changers in distribution networks, provided that the upstream transmission system requires active load demand reduction services during periods of low generation production or generation loss. Since frequent operation of OLTCs would impact the asset health of OLTC [31], the objective is to find an optimal dispatch solution of transformer OLTCs to achieve the required load demand reduction service by minimizing OLTC tap switching operations and the network power losses. Main contributions of this paper are as follows: i) Considering time series studies of “flexible control of distribution network transformer taps changers” with the permitted voltage limits to achieve voltage-led load demand reduction which would be required by the upstream transmission system to maintain frequency in case of generation loss. A faster optimal solution for a larger distribution network to ensure the method can meet the fast reserve service within 2 minutes requirement
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