Explaining Sympathetic Actions of Rational Agents

Wind Energy, 2014

Electrical layout design is, for offshore wind farms (OWF), a complex problem that has a far-reaching impact on both plant cost and reliability. A full optimization of the layout, as opposed to just selecting the most favorable pre-established configuration, is required in order to capture all the potential efficiencies. However, classical optimization methods such as mixed-integer programming (MIP) might not be applicable to large OWFs. This paper describes a novel combination of ordinal optimization (OO) and MIP that is able to deal with large problems in reduced computation times with a statistical optimality guarantee. The algorithm is applied to a real case study taken from Barrow Offshore Wind Farm in the East Irish Sea.

International Journal of Power Electronics and Drive Systems, 2023

Modern wind farms are considered one of the most important sources of energy today. The biggest cost of the farm is the cost of electrical connection to the farmers (constituting the largest part of the aesthetic cost of the farm) and finding the best method for electrical connection (the optimal method) for wind turbines (WTS), as well as the optimal size and measurement of electrical cables. Here, the (harmonious) search algorithm solves the optimization problem and the method of digging the soil in order to lay the cables in it. Two cases will be discussed in order to calculate the optimal size of the cables, namely partial calculation and optimal calculation for connection schemes in the best method for wind farms (OWFS). Also, the total cost, shipping methods, methods of digging extensions into the soil and the different classifications for turbines (wind turbines) will be addressed in order to obtain the best investment for them, so that we reach the optimal delivery and the lowest possible cost in a coordinated and thoughtful manner.

Marine Technology Society Journal, 2008

Offshore wind energy technology is a reality in Europe and is poised to make a significant contribution to the U.S. energy supply in the near future as well. The layout of an offshore wind farm is a complex problem involving many trade-offs. For example, energy production increases with turbine spacing, as do electrical costs and losses. Energy production also increases with distance from shore, but so do O&M (operations and maintenance), foundation, transmission, and installation costs. Determining which of these factors dominates requires a thorough understanding of the physics behind these trade-offs, can lead to the optimal layout, and helps lower the cost of energy from these farms. This paper presents the results of a study carried out to investigate these trade-offs and to develop a method for optimizing the wind farm layout during the micrositing phase of an offshore wind energy system design. It presents a method for analyzing the cost of energy from offshore wind farms as ...

International Journal of Offshore and Polar Engineering

A modular framework for the optimisation of an offshore wind farm using a discrete genetic algorithm is presented. This approach uses a bespoke grid generation algorithm to define the discrete positions that turbines may occupy thereby implicitly satisfying navigational and search and rescue constraints through the wind farm. The presented methodology takes a holistic approach optimising both the turbine placement and intra-array cable network, while minimising the levelised cost of energy and satisfying real world constraints. This tool therefore integrates models for the assessment of the energy production including wake losses; the optimisation of the intra-array cables; and the estimation of costs of the project over the lifetime. This framework will allow alternate approaches to wake and cost modelling as well as optimisation to be benchmarked in the future.

Applied Energy, 2016

h i g h l i g h t s Simultaneous optimization of wind farm's network layout and cable cross-sections. Proposed method brings substantial cost savings compared with other methods. Usefulness and effectiveness of the MILP optimization was demonstrated. Electrical losses need to be taken into account in the design process. An absolute optimal solution (GAP = 0) is received in a reasonable computation time.

Journal of the Operational Research Society, 2017

In this article we consider a real-world problem submitted to us by the Hatch company. This problem consists of designing a collection network for a wind farm, assuming that the locations of the turbines and the potential cables are known, several cable types are available, and the cost of the energy that dissipates through the cables is known. We propose a mixed integer quadratic programme to model the network design problem and then linearize the quadratic programme because the latter is too difficult to solve using a standard mathematical programming software. We describe several classes of inequalities that strengthen the resulting mixed integer linear programme. Finally we use real-world data supplied by Hatch to carry out computational experiments with several versions of our model.

In recent years the trend has been to collect wind generators into larger and larger wind farms. As the investments are substantial, the optimization of the wind farm layout plays a major role today. The scope of the present work is to define the state of the art in wind farm optimization. To do so the literature of the last two decades has been analyzed, and the structure of the problem has been defined. The most effective techniques and models used in the past are described. The common pitfalls are listed as well, with the aim to create a blueprint for future development of wind farm optimization tools/softwares. The main findings concern the high dependency of the resulting layout on the objective function chosen, which objective should be as detailed as possible; the energy yield alone has been proven not to be the best function for practical purposes. The need for all-encompassing functions requires the costs to be computed besides the production yield. New strategies have been developed to handle comprehensive objective functions and to reduce long computational times, namely the "two-steps" optimization, which consist of a combination of two algorithms, usually a meta-heuristic and a local search approach. The last point touched by this work highlights the areas where a better understanding is needed and more research should be addressed, like the models for degradation and the solving algorithms used.

IEEE Systems Journal, 2015

In this paper, an approach based on a genetic algorithm is presented in order to optimize the connection topology of an offshore wind farm network. The main objective is to introduce a technique of coding a network topology to a binary string. The first advantage is that the optimal connections of both middleand high-voltage alternating-current grids are considered, i.e., the radial clustering of wind turbines, the number and locations of the offshore electrical substations, and the number of high-voltage cables. The second improvement consists of removing infeasible network configurations as designs with crossing cables and thereby reduces the search space of solutions.

Sustainability

Wind energy is currently one of the fastest-growing renewable energy sources in the world. For this reason, research on methods to render wind farms more energy efficient is reasonable. The optimization of wind turbine positions within wind farms makes the exploitation of wind energy more efficient and the wind farms more competitive with other energy resources. The investment costs alone for substation and electrical infrastructure for offshore wind farms run around 15–30% of the total investment costs of the project, which are considered high. Optimizing the substation location can reduce these costs, which also minimizes the overall cable length within the wind farm. In parallel, optimizing the cable routing can provide an additional benefit by finding the optimal grid network routing. In this article, the authors show the procedure on how to create an optimized wind farm already in the design phase using metaheuristic algorithms. Besides the optimization of wind turbine position...

2023

In several countries, energy planners have analyzed wind energy expansion in the sea to, e.g., diversify their electricity generation matrix. For example, in Brazil, 700 GW of offshore wind energy can be used to generate electricity. However, offshore wind projects have high costs related to capital expenditures and operating expenses. One way to reduce these costs is to evaluate the production of electrical energy and clean hydrogen. Thus, this work presents an optimization model to determine the optimal layout of offshore wind farms, minimizing capital expenditures and operating expenses. Such a model is formulated as a mixed-integer nonlinear optimization problem. This model is applied to determine the layout of 30 offshore wind turbines to be connected to a 220 kV substation at sea. The optimal configuration of the offshore wind farm is found using two metaheuristics and an optimization solver to ensure the best solution to the problem. The results of this model can help energy sector planners and agents in each country to use offshore potential energy better, meeting demands for electricity and clean hydrogen.