Comparative study of optimal offshore wind turbine support structure configurations

This study aims to compare the weight (as an indicator for cost) of different configurations of support structures with respect to their deployment in different water depths. It is mainly car-ried out by the ISSC committee member, Dr. Athanasios Kolios, and his group from Cranfield University in UK. Two types of support structures, i.e. monopile and jacket, are considered in this study and an optimisation algorithm has been applied in order to compare concepts on a fair basis.

The response of the structure (based on FE analysis) for each case study under given loads is obtained through validated parametric models that have been developed for each case. The monopile consists of two parts, i.e. 1) monopile substructure, which is submerged into the wa-ter; and 2) monopile foundation, which is embedded into the soil. The soil profile considered in this study consists of three layers of sandy soil with given properties. In this study, the monopile support structure is modelled using beam elements. The soil-structure interaction is taken into account by modelling the soil using distributed springs, of which stiffness is de-rived from the p-y method defined in API standard. The springs are applied with 1m intervals along the monopile foundation in order to achieve good accuracy. Additionally, the RNA (Rotor-Nacelle Assembly) is treated as a point mass on the tower top. In this study, the transi-tion piece is ignored for simplificatransi-tion. The parametric FEA model for OWT monopile sup-port structures is used to calculate the natural frequencies of the NREL 5MW OWT on the OC3 monopile (Passon, 2006). The modal frequency results from the FEA model are com-pared against the results reported in Jonkman & Bir (2010), showing good agreement, with a maximum relative difference (1.55%) observed at 1st SS model. Comparison of deflection al-so show good agreement with a maximum relative difference (5.31%) observed for deflection of monopile foundation on mudline. This confirms the validity of the present FEA model of OWT monopile support structures.

The jacket structure model consists of mud-braces as well as several levels of legs and X-braces. The number of levels depends on the water depth. The RNA (Rotor-Nacelle

Assem-bly) is treated as a point mass on the tower top, and the transition piece is taken into account as a point mass attaching to the tower bottom. For simplification, the soil is not considered, and the bottom of the jacket is assumed to be fixed at the mudline. The parametric FEA model for OWT jacket support structures is used to calculate the natural frequencies of the NREL 5MW OWT on the OC4 jacket. The results from the FEA model show good agreement with those from Damiani et al. (2013), with a maximum relative difference (3.04%) observed at 2nd SS and FA modes. Similarly to the monopile, a comparison of deflections show good agreement with the results reported, with a maximum relative difference (8.23%) observed for deflection at RNA under load case 2. This confirms the validity of the present FEA model of OWT jacket support structures.

According to DNV-OS-J101 (DNV, 2014), the loads on OWT support structures can be cate-gorized into eight groups, i.e. 1) wind loads; 2) wave loads; 3) current loads; 4) hydrostatic pressure loads; 5) inertia loads; 6) sea ice loads; 7) loads due to marine growth; 8) loads due to exceptional events (e.g. earthquake, ship impact etc.). The wind, waves, current, hydrostat-ic pressure and inertia loads are considered in this study. Other loads associated with sea hydrostat-ice, marine growth and exceptional events are ignored. These effects may play a significant role for more detailed investigation or certain offshore locations; however, for the purpose of this generic study they are deemed negligible. In this study, both ultimate and fatigue load cases are considered. For the ultimate load case, the extreme sea condition (i.e. 50-year extreme wind condition combined with extreme significant wave height and extreme current velocity) represents a severe load and therefore is taken as a critical ultimate load case. For the fatigue load case, both wind and wave fatigue loads for the normal operation of OWTs are consid-ered. Table 2.3 presents both extreme and normal sea condition considered in this study. The rotor aerodynamic loads are presented in Table 2.4 and are taken from LaNier (2005) for a typical 5MW wind turbine. The wave loads on monopile submerged in water are calculated using the Morison’s formula. The current loads are taken into account by adding the current velocity to the wave particle velocity in the drag term of the Morison’s formula.

Table 2.3 Sea conditions

Item Values

Extreme sea condition Normal sea condition

Wind speed [m/s] 59.5 10

Significant wave height [m] 8.40 1.00

Wave period [s] 10.50 5.55

Current speed [m/s] 1.42 -

Table 2.4 Rotor aerodynamic loads

Load case Thrust [kN] Bending moment [kN-m] Torsion [kN-m]

Ultimate 781 38.567 7,876

Fatigue 197 3,687 3,483

The optimisation algorithm that has been selected is based on Genetic Algorithms, which is a search procedure based on genetics and natural selection mechanisms, in order to search for optimum solutions, as shown in Figure 2.19. In the GA, a population of candidate solutions (also called individuals) to an optimisation problem is evolved toward better solutions. The evolution generally begins with a population of randomly generated individuals. It is an itera-tive process, and the population in each iteration is called a generation. In each generation, the fitness of each individual in the population is assessed, and the fitness is generally the value of the objective function in the optimisation problem. The individuals having good fitness are stochastically selected from the population, and the genome of each individual is modified through mutation and crossover operators to form a new generation. The new generation of

individuals is then used in the next iteration of the algorithm. Generally, the algorithm termi-nates when either a satisfactory fitness level has been reached for the population, or a maxi-mum number of generation has been produced. The objective function to be minimised for this problem is that of the total mass subject to a series of the criteria which include (i) a de-flection constraint, (ii) a stress constraint for ultimate strength, (iii) fatigue constraint based on the SN curve approach, and (iv) buckling constraint and (v) frequency constraint.

The structural optimization model of OWT monopiles is applied to NREL 5MW OWT (Jonkman et al., 2009) on monopile support structures in seven water depths, ranging from 20m to 50m. The diameter of the monopile is assumed to be increased from 5.5m to 8.5m as water depth increase from 20m to 50m. The length of the monopile substructure is assumed identical to the length of the monopile foundation. The monopile foundation is designed with a uniform thickness to facilitate its installation. The monoopile substructure consists of sever-al five-meter-length segments, and the number of segments depends on the water depth. The thickness of the monopile foundation and the thickness of each segment of the monopile sub-structure are taken as design variables, of which optimum values are determined using the de-sign optimization model, which has been developed by combining the parametric FEA model and GA (genetic algorithm). The results from the optimization algorithm for the seven water depths for the monopile structure are depicted in Figure 2.20 (left plot).

The structural optimization model of OWT jacket support structure is applied to NREL 5MW OWT on jacket support structures in three water depths, i.e. 40m, 55m and 75m. For all cases, the angle between the two adjacent braces of X-braces is 110 deg, and the angle between the legs and X-braces is 37 deg. The legs are oriented with an angle of 2 deg with respect to the vertical axis. The diameter of legs is assumed to be 1.2m, and the diameter of both X-braces and mud-braces is assumed to be 0.8m. In this study, the thickness of X-braces and the thick-nesses of legs at each level are taken as design variables, of which values are determined us-ing the design optimization model. The thickness of mud-braces is assumed to be identical to that of X-braces. The results from the optimization algorithm for the three water depths for the jacket structure are depicted in Figure 2.20 (right plot).

Figure 2.19: Genetic Algorithm for optimization of offshore wind turbine support structures

Figure 2.20: Mass of the support structures as function of water depth obtained from the optimization analysis (left: monopile; right: jacket)