Integrated Global Optimization Model for Electrical Cables in Offshore Wind Farms

A state-of-the-art review of the optimization of electrical cables in offshore wind farms (OWFs) is presented in this paper. One of the main contributions of this paper is to propose a general classification of this problem, framed in the general context of the OWFs design and optimization (OWiFDO). The classification encompasses two complementary aspects. First, the optimum sizing of electrical cables, with the three main approaches used nowadays, static-rated sizing, dynamic load cycle profile, and dynamic full time series, is conceptually analyzed and compared. The latest techniques and advances are described, along with the presentation of potential research areas not thoroughly addressed today, such as dynamic cable rating, and cable’s lifetime estimation under time-varying conditions. Second, the network optimization of large OWFs is thoroughly presented, dividing the problem with a bottom–top approach: cable layout of the collection system, wind turbines (WTs) allocation to offshore substations (OSSs), number and location of OSSs, and interconnection between OSSs and onshore connection points (OCPs). A comparison among different methods is performed, taking into consideration the main engineering constraints. Global optimization, specifically, binary programming (BIP) or mixed-integer linear programming (MILP), is envisaged as the best way to tackle this topic. The full combinatorial problem is found to be better addressed following a top–bottom approach, combining exact formulations with high-level heuristics, or holistically with evolutionary algorithms.

Experimental and numerical research on the wet-towing of wide-shallow bucket jacket foundation for offshore substation

An optimization framework for global optimization of the cable layout topology for offshore wind farm (OWF) is presented. The framework designs and compares closed‐loop and radial layouts for the collection system of OWFs. For the former, a two‐stage stochastic optimization program based on a mixed integer linear programming (MILP) model is developed, while for the latter, a hop‐indexed full binary model is used. The purpose of the framework is to provide a common base for assessing both designs economically, using the same underlying contingency treatment. A discrete Markov model is implemented for calculating the cable failure probability, useful for estimating the time under contingency for multiple power generation scenarios. The objective function supports simultaneous optimization of (i) initial investment (network topology and cable sizing), (ii) total electrical power loss costs and (iii) operation costs due to energy curtailment from cable failures. Constraints are added accounting for common engineering aspects. The applicability of the full method is demonstrated by tackling three differently sized real‐world OWFs. Results show that (i) the profitability of either topology type depends strongly on the project size and wind turbine rating. Closed loop may be a competitive solution for large‐scale projects where large amounts of energy are potentially curtailed. (ii) The stochastic model presents low tractability to tackle large‐scale instances, increasing the required computing time and memory resources. (iii) Strategies must be adopted in order to apply stochastic optimization for modern OWFs, intending analytically or numerically simplification of mathematical models.

The investment of offshore wind farm is large while the cost on electrical system can take up to 15% of the total costs. In order to reduce the cost, it is desirable to optimize the electrical system layout in design phase. Since the location of offshore substation (OS) is highly related to the electrical system layout, the optimal layout design work should be done with the consideration of the impact of the location of offshore substation on the submarine cable connection layout to minimize the investment of cables. This paper addresses a new method to optimize the OS location together with the cable connection layout. The results show that the proposed method is an effective way for offshore wind farm cable connection layout design.

<strong class="journal-contentHeaderColor">Abstract.</strong> An optimization framework for simultaneous design of wind turbines (WTs) and cable layout for a collection system of offshore wind farms (OWFs) is presented in this paper. The typical approach used in both research and practical design is sequential, with an initial annual energy production (AEP) maximization, followed then by the collection system design. The sequential approach is robust and effective. However it fails to exploit the synergies between optimization blocks. Intuitively, one of the strongest trade-offs is between the WTs and cable layout, as they generally compete; i.e. spreading out WTs mitigates wake losses for larger AEP but also results in longer submarine cables in the collection system and higher costs. The proposed optimization framework implements a gradient-free optimization algorithm to smartly move the WTs within the project area subject to minimum distance constraint, while a fast heuristic algorithm is called in every function evaluation in order to calculate a cost estimation of the cable layout. In a final stage, a refined cable layout design is obtained by iteratively solving a mixed integer linear programme (MILP), modelling all typical engineering constraints of this particular problem. A comprehensive performance analysis of the cost estimation from the fast heuristic algorithm with respect to the exact model is carried out. The applicability of the method is illustrated through a large-scale real-world case study. Results shows that (i) the quality of the cable layout estimation is strongly dependent on the separation between WTs, where dense WT layouts present better performance parameters in terms of error, correlation, and computing time, and (ii) the proposed simultaneous design approach provides up to 6 % of improvement on the quality of fully feasible wind farm designs, and broadly, a statistically significant enhancement is ensured in spite of the stochasticity of the optimization algorithm.

An optimization framework for simultaneous design of wind turbines (WTs) and cable layout for collection systemof offshore wind farms (OWFs) is presented in this paper. The typical approach used in both research and practical design is sequential, with an initial annual energy production (AEP) maximization, followed then by the collection system design. The sequential approach is robust and effective, however it fails to exploit the synergies between optimization blocks. Intuitively,one of the strongest trade-offs is between the WTs and cable layout, as they generally compete, i.e. spreading out WTs mitigates wake losses for larger AEP, but also results in longer submarine cables in the collection system and higher costs. The proposedo ptimization framework implements a gradient-free optimization algorithm to smartly move the WTs within the project area subject to minimum distance constraint, while a fast heuristic algorithm is called in every function evaluation in order to calculate a cost estimation of the cable layout. In a final stage, a refined cable layout design is obtained by iteratively solving amixed integer linear program (MILP), modelling all typical engineering constraints of this particular problem. A comprehensive performance analysis of the cost estimation from the fast heuristic algorithm with respect to the exact model is carried out.The applicability of the method is illustrated through a large-scale real-world case study. Results shows that: (i) the quality of the cable layout estimation is strongly dependent on the separation between WTs, where dense WTs layouts present better performance parameters in terms of error, correlation and computing time, and (ii) the proposed simultaneous design approach provides up to 6% of improvement on the quality of fully feasible wind farm designs, and broadly, a statistically significant enhancement is ensured in spite of the stochasticity of the optimization algorithm.

An optimization framework for simultaneous design of wind turbines (WTs) and cable layout for collection systemof offshore wind farms (OWFs) is presented in this paper. The typical approach used in both research and practical design is sequential, with an initial annual energy production (AEP) maximization, followed then by the collection system design. The sequential approach is robust and effective, however it fails to exploit the synergies between optimization blocks. Intuitively,one of the strongest trade-offs is between the WTs and cable layout, as they generally compete, i.e. spreading out WTs mitigates wake losses for larger AEP, but also results in longer submarine cables in the collection system and higher costs. The proposedo ptimization framework implements a gradient-free optimization algorithm to smartly move the WTs within the project area subject to minimum distance constraint, while a fast heuristic algorithm is called in every function evaluation in order to calculate a cost estimation of the cable layout. In a final stage, a refined cable layout design is obtained by iteratively solving amixed integer linear program (MILP), modelling all typical engineering constraints of this particular problem. A comprehensive performance analysis of the cost estimation from the fast heuristic algorithm with respect to the exact model is carried out.The applicability of the method is illustrated through a large-scale real-world case study. Results shows that: (i) the quality of the cable layout estimation is strongly dependent on the separation between WTs, where dense WTs layouts present better performance parameters in terms of error, correlation and computing time, and (ii) the proposed simultaneous design approach provides up to 6% of improvement on the quality of fully feasible wind farm designs, and broadly, a statistically significant enhancement is ensured in spite of the stochasticity of the optimization algorithm.

Based on particle swarm optimization (PSO), an optimization platform for offshore wind farm electrical system (OWFES) is proposed in this paper, where the main components of an offshore wind farm and key technical constraints are considered as input parameters. The offshore wind farm electrical system is optimized in accordance with initial investment by considering three aspects: the number and siting of offshore substations (OS), the cable connection layout of both collection system (CS) and transmission system (TS) as well as the selection of electrical components in terms of voltage level and capacity. Because hundreds of optimization variables, continuous or discrete, are involved in the problem, a mix integer PSO (MIPSO) is required to obtain the solution. The fuzzy C‐means clustering (FCM) algorithm is used to partition the wind farm into several sub regions. The collection system layout in each sub region as well as the connection scheme between offshore substations are optimized by an adaptive PSO‐minimum spanning tree algorithm (APSO‐MST) which has been proposed in a previous work. The simulation results show that the proposed optimization platform can find an optimized layout that save 3.01% total cost compared with the industrial layout, and can be a useful tool for OWFES design and evaluation. Copyright © 2016 John Wiley &amp; Sons, Ltd.

The wind turbine (WT) layout and electrical system layout plays a vital role in offshore wind farm (OWF) design. The wake effect has a significant impact on the power production of the OWF. WTs in wake region will not experience healthy wind; hence it affects the power production. The proper placement of WTs can reduce the wake effect in OWF. The optimal design of large OWF is based on combined approach of Ant colony optimization (ACO) with multiple travelling salesmen problem (MTSP) is presented. The objectives of the approach are to improve power production, minimize the length of cable and cable cost. By considering (a) placement of WT with consideration of wake effect, (b) placement of substation, (c) selection of submarine cables with higher reliability and minimal power loss, and (d) minimum length of WT cable routing with zero cross connection. ACO-MTSP approach is applied on large OWF connected with 280 WTs and results are compared with the outcome of reference OWF.

Recently, offshore wind farms have emerged as the most promising sector in the global renewable energy industry. The main reasons for the rapid development of offshore wind farms includes much better wind resources and smaller environmental impact (e.g., audible noise and visual effect). However, the current state of the offshore wind power presents economic challenges significantly greater than onshore. In this thesis, a novel interconnecting method for permanent magnet synchronous generator (PMSG)-based offshore wind farm is proposed, where cascaded pulse-width modulated (PWM) current-source converters (CSCs) are employed on both generator- and grid-side. With the converters in cascade to achieve high operating voltages, the proposed method eliminates the need for bulky and very costly offshore converter substation which is usually employed in voltage source converter (VSC) high voltage DC (HVDC)-based counterparts. Related research in terms of control schemes and grid integration are carried out to adapt the proposed cascaded CSC-based offshore wind farm configuration. The large distance between generator- and grid-side CSC in the proposed wind farm configuration addresses significant challenges for the system control. In order to overcome the problem, a novel decoupled control scheme is developed. The active and reactive power control on the grid-side converters are achieved without any exchange of information from the generator-side controller. Therefore, the long distance communication links between the generator- and grid-side converters are eliminated and both controllers are completely decoupled. At the same time, the maximum power tracking control is achieved for the generator-side converters that enable full utilization of the wind energy. Considering inconsistent wind speed at each turbine, a coordinated control scheme is proposed for the cascaded CSC-based offshore wind farm. In proposed control strategy, the wind farm supervisory control (WFSC) is developed to generate the optimized dc-link current control. This enables all the turbines to independently track their own MPPT even with inconsistent wind speed at each turbine. Grid integration issues, especially the fault ride-through (FRT) capability for the cascaded CSC-based offshore wind farm are addressed. Challenges in implementing existing FRT methods to the proposed offshore wind farm are identified. Based on this, a new FRT strategy using inherent short circuit operating capability of the CSC is developed. Moreover, the mitigation strategy is developed to ensure the continuous operation of the cascaded CSC-based offshore wind farm when one or more turbines fail to operate. Simulation and experimental verification for various objectives are provided throughout the thesis. The results validate the proposed solutions for the main challenges of the cascaded current source converter based offshore wind farm.

The development of offshore wind power has become a pressing energy issue, driven by the need to find new electrical power sources and to reduce the use of fossil fuels. Offshore wind farms can harness tremendous wind resources without annoying citizens and with a comparatively low environmental impact. They are thus becoming a central pillar of a carbon free energy system. However offshore turbines and wind farms are costly to install and maintain, making reliability and cost-effectiveness key issues. This work covers reliability of offshore wind farms as a whole, starting from weather and wind conditions, dealing with wind turbine technology, farm layout, monitoring, safety and maintenance. The thoroughly revised second edition additionally covers turbines of up to 10 MW, turbine design changes, turbine converters, HVDC converter stations and DC links, offshore sub-sea collector and export cables, and the structures supporting large offshore wind farms. Offshore Wind Power is essential reading for scientists, engineers, technicians and advanced students interested or engaged in the design of wind turbines, drivetrain technology and power mechatronics, in academia and industry.

Layout of offshore wind farm (OSWF) plays a major role in capital cost of its installation. The cost of OSWF depends on the cost of electrical collector system which includes, submarine cables, number of wind turbines, offshore platforms etc. The optimal design of OSWF will give better economical outcome. This paper explains the methodology for optimal design of OSWF electrical collector system and cost model of collector system. The methodology is based on the combination of Ant Colony optimization and Travelling Salesman problem. The objective is to minimize the length of submarine cable connected between wind turbines in wind farm. It will reduce the cost of cable and cable power loss. With the help of North Hoyle OSWF connected with 30 wind turbines, the optimization approach designs optimal OSWF based on minimum length of cable for radial and ring topologies.

China's wind energy resources are abundant. Its exploitable wind energy reserves are about 1 billion kW(Burrows 2020). Among them, the offshore wind energy reserves that can be developed and utilized are about 750 million kW(Burrows 2020). Historically, the price of offshore wind turbines has been significantly high. However, its cost decline is accelerated due to significant technological advancements. Recently, offshore wind power can compete with China's coal and nuclear power in terms of cost. This study aims to provide a detailed review of the current status, research trends, and challenges of offshore wind turbine development in China. Currently, the offshore wind turbine with the largest single-unit capacity released in China has reached 8 MW and will soon enter the 10 MW era. The most common offshore wind turbines in China are Gravity-based, Monopile, Jacket, and Tripods offshore wind turbines in shallow water, and SPAR buoy, Tension leg platforms, and semi-submersible in deep water. This paper first included an overview of these offshore wind turbines’ system functionalities, features, strengths, weaknesses, and case studies. We then focus on the critical technologies for developing offshore wind turbines in China. The current technology status of the major operators is also summarized, representing the most advanced technology on the market. At last, we briefly summarized the future research directions of offshore wind turbines. In this study, we first gave an overview of offshore wind turbines currently on the Chinese market with several case studies. From these case studies, we recognized the critical technologies needed for the further development of offshore wind turbines. These technologies include hydraulic pitch technology, optimization design of the supporting structure for large-scale offshore wind turbines, offshore wind farm layout optimization, offshore power transmission, and intelligent operation and maintenance technologies. This study presented and analyzed these key technologies’ technical value, significance, development trends, and application scenarios. This paper introduced offshore wind turbines and related case studies in various fields with different operational conditions in China. We extracted and summarized the critical knowledge and technologies from these case studies for current practices and future work, facilitating operators to understand and develop these technologies efficiently.

One of the most promising prospects being actively researched and implemented is the offshore wind turbine. The offshore wind turbine has proven to have great potential when looking to supply high amounts of clean and renewable energy. However, here in Malaysia, wind turbines productions are limited. In this study, the aim is to determine a potential installation of wind turbine. Wind data are determined, and a model of wind turbine are then subjected to the loading to analyze its movement and foundation in these different conditions. In this paper, a design study is presented which aims to encounter the problem involving the offshore wind turbine structure and analyze the structures load transferred to the surrounding soil. This paper also reviews previous research work and then presents a simple dynamic system of calculations along with free body diagrams to help define this problem. The model is developed and simulated with SIMULINK to obtain time domain force distribution. The results are then applied into the equations of motion to analyse the relationship between the turbine and soil foundation dynamics. The conclusion of this design analysis will help designers determine the best design for offshore wind turbine foundations and allow offshore wind turbines to be implemented in Malaysian region.KeywordsOffshore wind turbineFoundationsDynamics system modeling

In order to improve the simulation efficiency, a novel transformed linear Gaussian model has been first proposed in this paper for generating equivalent “nonlinear” irregular waves. It is demonstrated by calculation examples that for obtaining equivalent “nonlinear” waves with the same accuracy, the transformed linear Gaussian model is about 2.7 times faster than the traditional nonlinear simulation method and is about 2.14 times faster than the method proposed by Agarwal and Manuel (2011). The loads and dynamic responses calculation results regarding an offshore jacket wind turbine in this paper demonstrate that nonlinearly simulated irregular waves with bottom effects should be considered in order to design an un-conservative support structure for the offshore wind turbine. Furthermore, by studying the calculation results in this article we have found that the loads and dynamic responses of the offshore wind turbine when inputting transformed linearly simulated waves with bottom effects are almost identical to the corresponding values when inputting nonlinearly simulated waves with bottom effects. All these calculation results clearly demonstrate the superiority and effectiveness of using our novel transformed linear Gaussian model for predicting the wave loads and dynamic responses of an offshore wind turbine operating in a realistic nonlinear sea with bottom effects.