Closed-Loop Two-Stage Stochastic Optimization of Offshore Wind Farm Collection System (original) (raw)
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Reliability‐based topology optimization for offshore wind farm collection system
Wind Energy, 2021
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 losses costs, and (iii) operation costs due to energy curtailment from cables 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. Nomenclature Acronyms OWF(s) Offshore Wind Farm(s). LCOE Levelised Cost Of Energy.
Optimization and Reliability Evaluation of an Offshore Wind Farm Architecture
IEEE Transactions on Sustainable Energy, 2017
This paper presents an original approach aiming to obtain the optimum configuration of an offshore wind farm (OWF). Thanks to cost models, we take into account the costs off all the parts of the electrical network. The optimization platform, based on a genetic algorithm, also allows us to evaluate the reliability of an offshore wind farm (OWF). This approach is used to compare the topologies obtained in different cases on a real OWF, the "Banc de Guerande". The selected design of the OWF is compared to results obtained using different methods: cost optimization, or both cost and reliability optimization. The optimization results show that the ring topologies give interesting results if the total cost including the expected energy not supplied (EEN S) during the lifetime of the offshore wind farm are taken into account. The number of offshore substations and their positions are also considered in the optimization: we show that the introduction of more substations in order to obtain better performances is possible at a reasonable cost. The presented optimization tool can help to design such farms taking into account several constraints.
Design of a wind farm collection network when several cable types are available
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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.
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.
Optimal Design of the Electrical Layout of an Offshore Wind Farm Applying Decomposition Strategies
IEEE Transactions on Power Systems, 2013
Electrical layout design is a key element in offshore wind farm planning, with a critical impact on both plant cost and reliability. OffshoreWindfarm Layout optimizer (OWL) has been developed to efficiently find optimal electrical layouts in affordable computation times. The tool includes the possibility of HVDC connection and incorporates an approximation of losses, as well as stochasticity in wind inputs and component failures. OWL has been applied to several case studies including Barrow Offshore Wind Farm. OWL produces a significant cost reduction over the actually implemented design, with total realizable savings of EUR 800 k. The optimal layout includes redundant elements and deviates from a symmetrical pattern, therefore showing that a full optimization of the layout, rather than the selection of a pre-defined configuration, is necessary in order to fully capture efficiencies. The model relies on MIP and exploits the structure of the problem via decomposition strategies. Two different approaches have been developed, both resulting in substantial time savings. Benders' decomposition has been further improved by the addition of partially relaxed cuts and the application of scenario aggregation techniques. In addition, the Progressive Contingency Incorporation algorithm proposed by the authors is applied. Computation time savings reach two orders of magnitude.
An Analytical And Probabilistic Approach For Reliability/ Cost Assessment Of A Wind Power System
Rapid technological progress, combined with falling costs, a better understanding of financial risk and a growing appreciation of wider benefits, means that renewable energy is increasingly seen as the best solution. Global Renewable energy policies, arising from increasing environmental concerns have set very ambitious targets for wind power penetration in electric power systems all over the world. Modern power system aims to provide reliable as well as cost effective power supply to its consumers. Reliability benefits, environmental benefits and operating cost savings from wind power integration should be compared with the associated investment costs in order to determine optimum transmission facility for wind power delivery. In this paper an analytical & probabilistic approach for reliability/cost analysis is presented for determining costeffective transmission line size for wind power delivery. It describes the reliability/cost techniques for determining appropriate transmission line capacity to connect a wind farm to a power grid. The effects of site-specific wind regime, system load, transmission line unavailability, and redundancy on system reliability were studied using a basic system model. The methodology and results shown in this paper should be subsidiary in transmission system planning for delivering wind power to a power system.
Journal of Modern Power Systems and Clean Energy
Offshore wind farm (OWF) is the largest renewable energy resource. The electrical interconnection cost of OWFs is a considerable fraction of the overall design cost of the farm. In order to minimize the investment and operational costs, this paper proposes an optimization formulation to find the optimal electrical interconnection configuration of wind turbines (WTs), and the optimal cable sizing simultaneously. This simultaneous minimization of total trenching length and cable dimensions creates a complex optimization problem that is solved by the harmony search (HS) algorithm. In this paper, two distinct methods of full and partial optimal cable sizing are considered to comprehensively assess the optimal interconnection layout of OWFs. Furthermore, various shipping and burying costs as well as various WTs power ratings are considered in order to investigate their impact on the optimal electrical interconnection system. The optimal electrical interconnection design obtained by the HS algorithm corresponds to a lower cost that together with the technological developments can help policy makers increase the use of offshore wind energy as a feasible unlimited renewable resource in their energy production portfolios.
Decision Models for Operation and Maintenance of Offshore Wind Farms Considering Uncertainties
2020
Wind energy is an important renewable resource to meet the continually increasing global energy demand. The high wind power potential in the sea has led to the development of wind farms in the sea, referred to as offshore wind farms (OWFs). OWFs are an array of wind turbines built in the sea to generate electricity from the abundant wind energy in the sea. In addition to high productivity, OWFs do not produce any noise pollution to human life and do not affect wildlife (especially birds). These advantages have made OWFs, a reliable renewable option to meet future energy demand through green energy. On the downside, the cost of energy produced by OWFs is high when compared to the cost of energy from wind farms in the land. Almost one-third of the cost of energy produced by OWFs is due to operation and maintenance (O&M) activities and is twice expensive as the wind farms in the land. The high O&M cost of OWFs is mainly due to its operating environment. The marine environment affects the reliability of offshore wind turbines (OWTs), creates uncertainty in turbine component lifetimes, and thereby increases the number of maintenance activities, effort, and costs. Also, the uncertain weather conditions and sea-state conditions limit accessibility to OWF for maintenance activities and increase downtime and production losses. The high O&M cost at OWFs creates a necessity to better analyze the situation in OWF maintenance and the associated uncertainties, identify maintenance problems, and come up with cost-effective solutions. This thesis aims to model the uncertainties in OWF vii Acknowledgments I would like to thank my supervisor, Dr. Ming J. Zuo, for his guidance, motivation, support, and mentorship during my MSc study. His supervision throughout my MSc program was invaluable, and without him, this thesis would not have been materialized. Under his guidance, I have gained excellent knowledge of how to plan and conduct research to solve real-world problems effectively. I would also like to thank him for allowing me to participate in international conferences, collaborative research internships, industry internships, and industry-academia collaborative projects. I am thankful to my research internship supervisor Dr. Yi Ding for his guidance and support during my visit to Zhejiang University, China. I am also grateful to my industry internship supervisor Mr. Stephen Seewald for the motivation and moral support during my time at EPCOR Utilities Inc., Canada. I thank all the group members of the Reliability Research Lab (RRL) at the University of Alberta for the exciting discussions and useful knowledge sharing through group meetings and all the help during my MSc study. Finally, I would like to thank my family and friends for all the support, encouragement, love, and prayers. viii Contents 2 Literature review 2.1 Terms and definitions 2.2 Fundamentals of operation and maintenance of offshore wind farms 2.