Optimization Model of Key Equipment Maintenance Scheduling for an AC/DC Hybrid Transmission Network Based on Mixed Integer Linear Programming

Abstract

The unbalanced distribution of resource and consuming centers in China has prompted the AC/DC hybrid transmission technology. The maintenance scheduling of an AC/DC hybrid transmission network is the key technology to ensure its safety and reliability. In this study, the mutual influence mechanism of an AC/DC system in a maintenance period was analyzed in detail. The overhead transmission line and transformer are key equipment within an AC/DC hybrid transmission network, and an optimization model of the key equipment maintenance scheduling was established. The objective of the model was to improve the system reliability during the maintenance scheduling. By considering the constraints of maintenance cost, maintenance resources, and maintenance workload, the maintenance scheduling of overhead transmission lines and transformer branches was obtained. The over-limit situation of power flow and the weakness of the system during the maintenance period was evaluated. The “double-layer substitution method” was adopted to convert the nonlinear constraints into its bilinear formulation such that it could then be solved. The random number sampling method was used to quantify the system reliability, and the commercial optimization software was used to solve the optimized scheduling. Based on the improved IEEE RTS-79 system and the Hubei Province electrical system, the simulation results showed the effectiveness of the proposed method.

Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling

“…Currently, there is a rich body of specialized literature related to the application of integer programming methods for generator maintenance scheduling [5][6][7][8]. There is certain disagreement over how adequate these types of methods are, since they were one of the first approaches used to solve the problem under consideration.…”

“…[6] and Ref. [7] propose to apply integer programming methods for generator maintenance scheduling, taking into account demand response strategies and AC/DC high voltage directed current (HVDC) link constraints, respectively. However, many researchers, as it was mentioned above, advocate the use of heuristic approaches to solve the problem-in particular, increasing attention today is being paid to ant colony algorithms [9][10][11], fuzzy and artificial neural network approaches [12][13][14], evolution [15,16] and genetic methods [17][18][19], simulated annealing methodologies [20][21][22][23], particle swarm techniques [24][25][26], taboo search procedures [27][28][29], etc.…”

“…Taking into account the diversity of the presented possible approaches, a question arises as to what method is the most appropriate for further application in a more complicated scheduling statement. Currently, it is an acceptable practice to consider only active power line loading constraints [6,7,21]. Nevertheless, in order to plan repairs or outages, for example, for either static reactive compensators or energy storage devices, it is necessary to consider more complex constraints, such as allowable voltage levels and small-signal stability limitations of a power system.…”

Effect of Deploying Routing and Facility Location Methods on Power Transmission to Increase the Reliability of the Power Network and Minimize the Total Logistics Cost

“…This is considered in terms of increasing reliability at some PPs to enhance power production by feeding to the less capacity PPs. The study also addresses the power generating cost by reducing the team visit to each PP as high power generating PPs cost is high and it affects the other PP module's expected regular service output in the long run (Cai et al, 2020). This problem is addressed by developing an algebraic framework for connecting different cities in the western region to a single loop having a minimum length between maintenance centers and setting up an appropriate number of teams for reliable and stable power supplies (Prukpanit et al 2021).…”

“…Data is loaded showing Longitude at X-axis and Latitude at Yaxis by using the following code: a. Building the Shortest Possible Network: The second step is to read data and manipulate it for building the shortest path network by using traditional Travelling Salesman Problem (TSP) algorithm construction (Cai et al, 2020). TSP was formulated in the 19 th century by William Rowan Hamilton and Thomas Kirkman and found a strong evidence-based method to solve distance-related problems using graph algorithms (Al-Furhud and Ahmed, 2020).…”