Short-Term Transmission Maintenance Scheduling Based on the Benders Decomposition

Abstract

This paper proposes the model of short-term transmission maintenance scheduling to minimize the maintenance cost. In this model, maintenance cost is composed of transmission maintenance cost and load loss expectation. Meanwhile, maintenance constraints and system operation constraints are considered in the model. Due to the complexity of the transmission maintenance scheduling, the Benders decomposition is difficult to use directly. This paper analyzes the main difficulties from generation system reliability to transmission system reliability evolution, and presents some measures to improve the Benders decomposition method. Furthermore, this paper introduces a new importance index to choose the critical branches to reduce computational complexity. The proposed method is applied to a test power system. Results of the example demonstrate that the modified Benders decomposition is high efficient in arranging the short-term transmission maintenance. NOMENCLATURE it C overhaul cost of the line i at period t it x condition of line i at period t t c cost of load loss at period t it r loss of load at period t i s start time of maintenance of line i i d duration of maintenance for line i i e the earliest available time for maintenance of line i i l the latest available time for maintenance of line i mi σ resources required for maintenance of line i mt z available maintenance crew at period t θ vector of bus voltage angles B matrix of bus susceptance g vector of power generation L vector of load demand r vector of unserved power t ε load loss expectation constraint at period t . f branch power flow vector term f maximum limitation of branch power flow im

Maintenance scheduling in the electricity industry: A literature review

“…Along with generator maintenance, transmission-line maintenance must be scheduled. This problem, usually called the transmission maintenance scheduling (TMS) problem, has received less attention than the GMS problem (Abirami et al, 2014;Fu et al, 2007;Geetha and Shanti Swarup, 2009;Langdon and Treleaven, 1997;Lv et al, 2012;Marwali and Shahidehpour, 1998, 1999b, 2000b. It is necessary to ensure that taking a line out for maintenance does not impact the network reliability and security.…”

“…These are also constraints on the line capacity and may include voltage considerations. The network can be modeled as either a transportation model (Abirami et al, 2014;Shahidehpour, 1998, 1999b) or a more complex but more realistic DC power flow model 3 (Fu et al, 2007;Geetha and Shanti Swarup, 2009;Langdon and Treleaven, 1997;Lv et al, 2012;Marwali and Shahidehpour, 2000b).…”

“…The TMS problem can be addressed independently from the GMS problem (Langdon and Treleaven, 1997;Lv et al, 2012;Marwali and Shahidehpour, 2000b). In this approach, the state of the network appears as a constraint during the resolution of the GMS problem.…”

“…One can also (artificially) reduce the capacity of the generators and solve a deterministic problem, but the not-supplied energy can be overestimated. However, the use of stochastic reliability indices such as the expected energy not served or EENS (Baskar et al, 2003;Chattopadhyay, 2004b;Geetha and Shanti Swarup, 2009;Lv et al, 2012;Marwali and Shahidehpour, 1999a,b;Silva and Morozowski, 1995;Yellen and Al-Khamis, 1992) and the loss of load probability (LOLP) (Billinton and Abdulwhab, 2003;Han et al, 2011;Mohanta et al, 2004Mohanta et al, , 2007Reihani et al, 2012;Suresh and Kumarappan, 2013;Volkanovski and Mavko, 2008) is better suited to tackle problems in this scenario. The EENS is minimized or a threshold for acceptability is defined.…”

“…In Geetha and Shanti Swarup (2009); Lv et al (2012); Shahidehpour (1999a,b, 2000a); Silva and Morozowski (1995), a probabilistic approach takes FOR into account in a problem with network constraints.…”