Abstract
A two-stage stochastic optimization model for the design of the closed-loop cable layout of an Offshore Wind Farm (OWF) is presented. The model consists on a Mixed Integer Linear Program (MILP) with scenario numeration incorporation to account for both wind power and cable failure stochasticity. The objective function supports simultaneous optimization of: (i) Initial investment (network topology and cable sizing), (ii) Total electrical power losses costs, and (iii) Reliability costs due to energy curtailment from cables failures. The mathematical optimization program is embedded in an iterative framework called PCI (Progressive Contingency Incorporation), in order to simplify the full problem while still including its global optimum. The applicability of the method is demonstrated by application to a real-world instance. The results show the functionality of the model in quantifying the economic profitability when applying stochastic optimization compared to a deterministic approach, given certain values of cables failure parameters.
Highlights
Offshore Wind Farms (OWFs) are shaping up as one of the main drivers towards the transition to carbon-neutral power systems
The model consists on a Mixed Integer Linear Program (MILP) with scenario numeration incorporation to account for both wind power and cable failure stochasticity
The mathematical optimization program is embedded in an iterative framework called PCI (Progressive Contingency Incorporation), in order to simplify the full problem while still including its global optimum
Summary
Offshore Wind Farms (OWFs) are shaping up as one of the main drivers towards the transition to carbon-neutral power systems. Model reduction implementing a Mixed Integer Linear Program along with Progressive Contingency Incorporation (PCI), and decomposition strategies is performed in [14] and [15], proving the ability to decrease computational resources while solving to optimality smallscale OWFs (less than or equal to 30 WTs) The latter papers provide relevant advances in stochastic optimization supporting several wind power and cable failure scenarios. The inclusion of practical engineering constraints such as non-crossing of cables, closed-loop topology, and losses inclusion in the objective function are missing in these papers This gap is covered in this manuscript, where a MILP optimization program based computational tool is presented, supporting decision makers during the design stage of OWFs. An algorithmic framework is developed targeting further computational simplification, supporting an objective function combining simultaneously initial investment, total electrical power losses, and energy curtailment due to cables failures.
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