A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

Abstract

With a typical investment of in excess of £100 million for each project, the installation phase of offshore wind farms is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined tool, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities

Application of Last Planner System to Modular Offshore Wind Construction

“…The case organization requested a solution for planning and controlling the respective construction activities in modular offshore wind construction. A planner had arranged all the processes similar to that which Barlow et al (2018) modeled with a detailed work break down (WBS) structure. During construction the planner would serve the role of progress reporter in the CPM based commercial software program (Primavera from Oracle).…”

Performance improvement of supplier-side e-tender-driven marketing process

“…We find use of DESM in a wide variety of applications, contexts and sectors. DESM is used as a dominant methodology in supply chain management (SCM), healthcare, manufacturing systems and business process management projects (Barlow et al , 2018; Bosilj Vukšić et al , 2017; Diaz et al , 2017; Gunal and Pidd, 2010; Jahangirian et al , 2010; Lobo et al , 2018; Mielczarek, 2014; Robinson et al , 2012; Barber et al , 2003). It is also used in some unique applications in context of banking operations, airport security, free-way systems, entertainment theme parks, software development project, forest fire suppression, multi-stage production system (MSPS), dynamic Bayesian networks (DBNs), intermodal freight transportation systems, mining, speech language pathology service, queuing systems, maritime search operations, business process re-engineering, construction, telephone response system, small and medium enterprises (SMEs), maintenance operations, flexible manufacturing system (FMS) scheduling, defence and contract costing in outsourcing (Alabdulkarim et al , 2014; Chan and Chan, 2004; Choudhari and Gajjar, 2017; Camargo et al , 2018; Crainic et al , 2017; Duff et al , 2015; Jansen-Vullers and Netjes, 2006; Kelton et al , 2014; Kouskouras and Georgiou, 2007; Liston et al , 2007; Yang and Liu, 2012; Onggo and Karatas, 2016; Poropudas and Virtanen, 2011; Roy et al , 2018; Van Volsem et al , 2007; Willoughby et al , 2016).…”

An optimisation model for scheduling the decommissioning of an offshore wind farm

“…Sarker and Faiz (2017) developed a model for wind turbine installation and transportation in an oshore wind farm to minimise the total cost where the eects of wind farm and vessel parameters on cost are investigated. Recently, Barlow et al (2018) proposed a mixed-method framework to address current oshore wind farm installation projects. The framework benets the complementary strengths of two decision-support methods namely discrete-event simulation and robust optimisation.…”