PARAMETERIZED SAVINGS HEURISTIC FOR OPTIMIZING INFIELD CABLE ROUTING OF OFFSHORE WIND FARMS

The article discusses an approach to solving the problem of optimizing the routing of infield power cables layout to improve the efficiency and cost-effectiveness of offshore wind farms. Optimization seeks to reduce the total cost of the infield collection system while bearing in mind the constraints including use of sufficiently sized cables and the required absence of cable crossings in the circuit diagram. The problem is a degree-constrained capacitated minimum spanning tree (DCMST) problem with dependent node costs. Search for solu-tion is based on an integrated approach that uses a hybrid optimization algorithm, which combines a parameterized savings heuristic and particle swarm optimization to optimize the parameters of the primary algorithm, ultimately enabling better solutions. Several tests have been performed to compare the constructed circuit diagrams against solutions yielded by other algorithms; tests showed the proposed approach to significantly improve the efficiency of the constructed circuits as demonstrated in a series of tests and evaluated by comparison with other methods, as well as by comparing the efficiency and cost-effectiveness of the optimized routing against the actual layout of the Walney 1 offshore wind farm.

Capacitated Graph Theoretical Algorithms for Wireless Sensor Networks Towards Internet of Things

Main components of internet of things such as wireless sensor networks (WSNs) are generally modeled as graphs. Matching, dominating set, spanning tree, and vertex cover are fundamental graph theoretical structures which are widely used to solve backup assignment, clustering, backbone formation, routing, link monitoring, and other important problems in WSNs. Capacitated versions of these graph theoretical problems restrict at least one feature of the original problem such as a capacity value assignment to restrict the number of cluster member that a cluster head can serve in capacitated dominating set problem, limiting the number of nodes in each subtree connected to the root in capacitated minimum spanning tree problem, etc. The general aim of these operations is to provide energy efficiency by balancing the load evenly across the nodes. In this chapter, the authors introduce important capacitated graph theoretical problems and explain both central (sequential) and distributed algorithms for constructing these structures. The operations of the algorithms are demonstrated by sample topologies.