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.

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

The statistical characteristics of wind and the selection of suitable wind turbines are essential to effectively evaluate wind energy potential and design wind farms. Using four sites in central China as examples, this research reviews and compares the popular parametric and non-parametric models for wind speed probability distribution and the estimation methods for these models’ parameters (the widely used methods and stochastic heuristic optimization algorithm). The simulations reveal that the non-parametric model outperforms all of the selected parametric models in terms of the fitting accuracy and the operational simplicity, and the stochastic heuristic optimization algorithm is superior to the widely used estimation methods. This study also reviews and discusses six power curves proposed by the literature and the power loss caused by the mutual wake effect between turbines in the wind energy potential assessment process. The evaluation results demonstrate that choice of power curves influences the selection of wind turbines and that consideration of the mutual wake effect may help to optimize wind farm design in wind energy assessment.

Wind speed probability distribution estimation and wind energy assessment

The application of wind energy in electric power systems is growing rapidly due to enhanced public concerns to adverse environmental impacts and escalation in energy costs associated with the use of conventional energy sources. Electric power from wind energy is quite different from that of conventional resources. The fundamental difference is that the wind power is intermittent and uncertain. Therefore, it affects the reliability of power system in a different manner from that of the conventional generators. This paper, from available literatures, presents the model of wind farms and the methods of wind speed parameters assessment. Two main categories of methods for evaluating the wind power reliability contribution, i.e., the analytical method and the Monte Carlo simulation method have been reviewed. This paper also summarizes factors affecting the reliability of wind power system, such as wake effect, correlation of output power for different windturbines, effect of windturbine parameters, penetration and environment. An example has been used to illustrate how these factors affect the reliability of wind power system. Finally, mainstream reliability indices for evaluating reliability are introduced. Among these reliability indices, some are recently developed, such as wind generation interrupted energy benefit (WGIEB), wind generation interruption cost benefit (WGICB), Equivalent Capacity Rate (ECR), load carrying capacity benefit ratio (LCCBR).

A review on reliability assessment for wind power

Wind energy has been considered as an important substitution of fossil-based energy for future society. However large-scale integration of wind power will introduce great risks to both power system planning and operation due to its stochastic nature. By adopting power system reliability theory, the risks can be quantitatively estimated so that numerous publications have been published to study reliability impacts caused by wind power. This paper thoroughly investigates the features of existing reliability models of wind power, reliability assessment algorithms and its applications in wind power related decision making problems. The paper also reveals significant differences existed in reliability models and algorithms between planning and operational phase of power systems, which are neglected in existing review articles.

Reliability based power systems planning and operation with wind power integration: A review to models, algorithms and applications

Both grid-tied and off-grid diesel power plants are operational throughout the country. Integration of wind power into traditional diesel-only power supply system reduces the green house gases and thereby global warming. Many researches are conducted in improving the performance of the system but unfortunately the actual design of a hybrid wind-diesel system is less worked upon. In this work, we have built and simulated a wind-diesel hybrid system using the Hybrid Optimization Model for Electric Renewable (HOMER) and compared the operational and economic parameters with traditional diesel system parameters, widely used in rural India. The economic perspective in the design is highlighted with suitable graphical plots.

Optimal hybrid power system design using HOMER

The utilization of wind energy sources in autonomous power systems can significantly reduce the system fuel costs but increase the investment costs and have adverse effect on the system safety and reliability, therefore there is a need to study rational capacity expansion planning. This paper proposes the model of the optimal expansion planning of wind-diesel energy system based on improved genetic algorithm (IGA) due to its application to the highly constrained nonlinear discrete dynamic optimization problem. The main advantage of IGA approach is that "the curse of dimensionality" in the mathematical method can be overcame. In this paper the planning objective costs take into account unserved energy costs besides investment costs and operation costs. The evaluation of probability cost and reliability in the model is performed by using Monte-Carlo method for representing the uncertainty for wind speed and loads, forced outage rate of the units, the correlation of wind speed and load series, wind generation operational constraints. The example indicates that the model and algorithm that puts forward in this paper is feasible and provides the important reference value for the planning and design of wind generation system.

Optimal Expansion Planning of Wind-Diesel Energy System

Wind power generation of wind farm has relation to wind energy resources, wind generation unit parameter and its crew, etc. The goal of optimizing the design for wind turbine generator in wind farm should be to utilize wind energy as efficiently as possible and to reduce production cost of wind power generation. Therefore, the paper investigates optimal choice of wind generation unit type matching wind farm site, which takes wind power generation capacity factor and generation cost as optimization target. Probabilistic method used to evaluate the economic indices of wind turbine generators, such as wind power generation and capacity factor, is more reasonable due to wind energy randomness and component failure uncertainty. Results obtained from several case studies are presented and discussed.

Optimal choice of wind turbine generator based on Monte-Carlo method

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Optimal Expansion Planning of Wind-Diesel Energy System

Optimal choice of wind turbine generator based on Monte-Carlo method