Electricity Distribution System Switch Optimization Under Incentive Reliability Scheme

Abstract

The judicious placement of disconnecting switches is an efficient means to enhance the reliability of distribution networks. Aiming at optimizing the investment in these switches, this paper presents a mathematical programming-based model considering the installation of remote-controlled and manual switches at various locations in the distribution network. The proposed model not only yields the optimal location and type of switches in the main feeders but also specifies the optimal type of tie switches, i.e., backup switches at the reserve connection points. Incentive reliability regulation in the form of a reward-penalty scheme is incorporated into the proposed model to take the distribution service reliability worth into account realistically. In addition to this cost, the revenue lost due to energy undelivered during the distribution network faults is considered to determine the unreliability costs more accurately. In order to estimate such reliability-related costs, a novel reliability assessment technique is developed and integrated into the proposed switch optimization model. Formulated as an instance of mixed-integer linear programming, the proposed model is applied to a test distribution network, and the outcomes are investigated in detail. INDEX TERMS Electricity distribution system, mixed-integer linear programming, reliability, reward-penalty scheme, switch optimization. NOMENCLATURE INDICES

Reliability-Oriented Electricity Distribution System Switch and Tie Line Optimization

“…Also, in [17], Li et al proposed an MILP model for simultaneous deployment of fault indicators, MSs, and RCSs in a distribution network with branch lines. Finally, authors in [18] developed an MILP formulation for the optimal switch placement problem, which determined the type of tie switches at the reserve connection points.…”

“…Also, the existence of tie lines and type of tie switches in the network are determined prior to the placement of other switches [4], [6]- [8], [10]- [17]. Lastly, although the MILP model in [18] determines the type of tie switches as a result of the optimization, it assumes that the existence of tie lines is specified prior to the optimization. In addition to these drawbacks, in the studies which considered the existence of tie lines in the distribution network [4], [6]- [8], [10]- [18], the potential failures in the tie line itself, where the tie switch is placed, is not taken into consideration.…”

“…Lastly, although the MILP model in [18] determines the type of tie switches as a result of the optimization, it assumes that the existence of tie lines is specified prior to the optimization. In addition to these drawbacks, in the studies which considered the existence of tie lines in the distribution network [4], [6]- [8], [10]- [18], the potential failures in the tie line itself, where the tie switch is placed, is not taken into consideration. However, in practice, in order to monitor the availability of the tie switch in case of faults, the tie line should be energized by keeping one end of it connected to a feeder and the other end open for the sake of network radiality.…”

“…In addition to the benefits of tie lines, the impact of their potential failures is also considered in the proposed model. Furthermore, unlike [7], [8], [10]- [17], which used the total customer interruption cost as the unreliability cost of the DISCO, we leverage other reliability indices, based on which the unreliability cost a DISCO may incur in practical applications is calculated [18]. To be more specific, although, according to its classical definition in [19], the total customers' interruption cost can appropriately reflect the network performance in terms of service reliability, this index cannot be accurately calculated in practice owing to its dependence on the customer damage functions of load nodes, the values of which are difficult to assess.…”

“…To be more specific, although, according to its classical definition in [19], the total customers' interruption cost can appropriately reflect the network performance in terms of service reliability, this index cannot be accurately calculated in practice owing to its dependence on the customer damage functions of load nodes, the values of which are difficult to assess. Also, it goes without saying that the DISCOs are not obliged to consider such unreliability costs in their optimization models in practice, whereas they are typically under reliability incentive schemes [18], [20], [21]. These schemes are typically applied to system-oriented reliability indices such as system average interruption duration index (SAIDI) [21].…”