Mathematical Optimization and Algorithms for Offshore Wind Farm Design: An Overview

Wind energy is a fast evolving field that has attracted a lot of attention and investments in the last dec- ades. Being an increasingly competitive market, it is very important to minimize establishment costs and increase production profits already at the design phase of new wind parks. This paper is based on many years of collaboration with Vattenfall, a leading wind energy developer and wind power operator, and aims at giving an overview of the experience of using Mathematical Optimization in the field. The paper illustrates some of the practical needs defined by energy companies, showing how optimization can help the designers to increase production and reduce costs in the design of offshore parks. In particular, the study gives an overview of the individual phases of designing an offshore windfarm,andsomeoftheoptimizationproblemsinvolved. Finally it goes in depth with three of the most important optimization tasks: turbine location, electrical cable routing and foundation optimization. The paper is concluded with a discussion of future challenges

Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

A Review of Methodological Approaches for the Design and Optimization of Wind Farms

This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research

Optimisation of scheduling and routing for offshore wind farm maintenance

The growing increase in the size and scope of offshore wind farms motivates the need for industry to have access to mathematical tools that reduce costs by efficiently performing daily operations and maintenance activities. Key offshore activities require the transportation of technicians to and within offshore wind farms to complete corrective and preventive maintenance tasks to keep turbines operating efficiently. We provide a new deterministic mixed integer linear programming formulation for deciding the optimal vessel routes for transporting technicians around a wind farm and the scheduling of crew transfers, by minimising downtime, travel and technician costs. The model contains sufficient flexibility to account for multiple vessels, shifts and task profiles, whilst being able to prioritise and omit tasks in environments containing limited resources. Computational experiments are performed which quantify and confirm the impact of key instance characteristics such as technician availability, task profiles and weather conditions. We implement and evaluate the impact of a novel industry safety constraint. The complexity of larger instances motivates a second continuous time formulation, in which preventive maintenance again requires no minimum duration of work before it can provide benefit. We employ a specific decomposition structure to take advantage of variable preventive maintenance and utilise an adaptive large neighbourhood search procedure to solve instances. We evaluate several distinct acceptance criteria in conjunction with random and adaptive operator selection to determine the best option for our model. We produce a statistical model of offshore weather conditions to help quantify the likelihood of limited vessel accessibility to offshore wind farms. We model the joint distribution of key meteorological and oceanographic variables over time whilst accounting for seasonal trends using multivariate kernel density estimation. Our method generates alternative metocean realisations from historical data and reproduces the important long term persistence statistics of good and adverse offshore conditions