Hybrid Offshore Power Generation

2021 ◽  
Author(s):  
Izleena Md. Iqbar ◽  
Fauzy Omar Basheer Othman ◽  
Hasmi Taib ◽  
M. Faizal Hamdan ◽  
Frank Adam ◽  
...  

Abstract Amid 2020 challenging business environments due to COVID-19 pandemic and strong global push towards transition to cleaner energy, PETRONAS has declared its' aspiration to achieve net zero carbon emissions by 2050. PETRONAS sustainability journey has begun for more than two decades and with strong management support towards renewable and as part of PETRONAS's technology agenda, its' research arm, PETRONAS Research Sdn. Bhd. (PRSB) has been working on ways to use renewable energy sources for offshore oil and gas platforms in Malaysia. Oil and Gas industry has long relied on turbine generators for offshore power generation. These turbo-fired machineries are operating as microgrid with existing power management system (PMS) as microgrid controllers. They normally use either gas or diesel as fuel gas to ensure reliable power generation where high maintence cost is expected to operate these generators. Also, they have low energy efficiency and hence, usually oversized to ensure meeting the demand reliably. Typically, the power generation load is being taken by two units of turbine generators with another unit as spare. This has resulted in high operational expenditure (OPEX) and contributes to high levelized cost of energy (LCOE) for offshore power generation for such conventional system. LCOE is the yardstick for power generation technology, and it measures discounted lifecycle cost consisting of both capital expenditure (CAPEX) and OPEX, divided by discounted lifecycle of annual energy production [2], [4], [5]. Also, these turbine generators operating at platforms that have gas evacuation pipelines will use up precious fuel gas which can otherwise be sold. This will have impact on the total sales gas revenue. Not withstanding, the burning of the fuel gas will result in the emissions of carbon dioxide (CO2) and hence is exposed to carbon tax. To mitigate this issue, PRSB has developed an offshore hybrid power generation concept to leverage and optimize wind turbine system for offshore power generation in weak wind area such as Malaysia. In this concept, one gas turbine generator is replaced by an offshore wind turbine adapted to low wind speed region. This will lower the maintenance cost and carbon exposure. Also, the fuel gas will be diverted to sales gas. This in turn will improve the economics of the renewable solution thereby making offshore renewable power generation feasible for oil and gas platforms. Forward thinking efforts include pushing the limits of harnessing wind energy in weak wind area such as Malaysia. In here, considerations of a total solution include not only the type of wind turbine generator that can be adapted to weak wind area and having the lowest maintenance requirements as possible, but also looking into cutting edge foundation technologies. The LCOE is expected to be lower than conventional power generation. To ensure optimized hybrid concept, careful selection and adaptations of wind turbine system and its' substructure are required to achieve a cost-effective solution [3], [2]. Conceptual engineering and front-end engineering design were conducted which resulted in the development of the hybrid offshore power generation system. In this paper, the hybrid concept will be shown, the considerations for selection of a suitable wind turbine will be shared and the decisions leading the to the selection and optimization of the foundation type, either fixed bottom or floating are elaborated.

2019 ◽  
Vol 122 ◽  
pp. 04001
Author(s):  
Mouayad Sahib ◽  
Thaker Nayl

In this work, a new strategy to control the pitch angle of wind turbine generator is proposed. The strategy is based on designing an intelligent control system capable of maintaining a stable minimum fluctuating power generation. This can be achieved by providing the wind speed information to the controller in advance and hence allowing the controller to take the optimum action in controlling the blade pitch angle. A model based optimizer uses Model Predictive Control (MPC) technique to predict the wind turbine generator future behaviour and select the optimal control actions assisted by the wind speed information while satisfying the power generation constraints. The simulation results show that a significant improvement can be made using the proposed control method.


2013 ◽  
Vol 2 (2) ◽  
pp. 69-74 ◽  
Author(s):  
A.K. Rajeevan ◽  
P.V. Shouri ◽  
Usha Nair

A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.


2018 ◽  
Vol 58 (2) ◽  
pp. 719
Author(s):  
Lourens Jacobs ◽  
Nancy Nguyen ◽  
Ryan Beccarelli

Woodside is an Australian oil and gas company and a leading global operator of offshore gas platforms and onshore LNG processing facilities. It is a public company listed on the Australian Securities Exchange headquartered in Perth, Western Australia. Woodside operates the Goodwyn A gas platform on behalf of the North West Shelf (NWS) Project. Woodside assessed Li-ion battery technology and considered the technology mature and ready to be utilised on offshore and onshore operating assets. Woodside operates dedicated islanded gas turbine power generation at each of its onshore and offshore facilities. It was concluded that a large battery energy storage solution (BESS) can deliver several advantages if connected to such an islanded power generation system. The most significant benefit materialises by using a BESS as backup (or spinning reserve) for the gas turbine generators (GTGs). Woodside decided to pioneer the Li-ion BESS technology in a first of its kind application on the NWS Project offshore Goodwyn A gas platform. The Goodwyn A BESS is designed for a 1 MW power and 1 MWh energy capacity, which is considered sufficient to provide the spinning reserve for the Goodwyn A platform. Currently, Goodwyn A operates four 3.2 MW GTGs to provide a typical load of 7–8 MW, with one GTG providing the N+1 spinning reserve. When the BESS is connected to the power generation system, Goodwyn A will operate three GTGs, with the BESS proving the backup in case one of the GTGs trip. The BESS will provide the full 1 MW for a minimum of 1 h, which will give the operators enough time to start the standby GTG or adjust the facility loads (load shedding). The result will be a decrease in overall fuel gas consumption (due to better efficiencies on the remaining GTGs in operation) and a related reduction in CO2 emissions. The project supports the overall objective of the North West Shelf Project to improve the energy intensity of its facilities by 5% by 2020. Woodside believes that developing capability and experience on the installation of BESSs, using Goodwyn A as an early adopter, will facilitate similar and larger installations on other Woodside operated offshore and onshore assets. This is one of the technologies Woodside believes will play an important role to ensure a lower carbon future globally.


Author(s):  
Young-Man Kim

In this research, it is developed to design LQG controller for wind turbine systems which are identified with Predictor-Based System Identification (PBSID) technique. The PBSID technique works well under closed-loop condition, which is useful for a system requiring closed-loop operation due to safety reason. First, a wind turbine system is identified using PBSID technique in full range of wind speed. Afterwards, using the identified system matrices, 1-DOF LQG controller is designed. The controller enables power generation to track the optimal power trajectory of a system. Simulation is used to demonstrate its usefulness.


Micromachines ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 39
Author(s):  
Chao-Tsung Ma ◽  
Zong-Hann Shi

As the penetration of renewable energy power generation, such as wind power generation, increases low-voltage ride-through (LVRT), control is necessary during grid faults to support wind turbine generators (WTGs) in compensating reactive current to restore nominal grid voltages, and maintain a desired system stability. In contrast to the commonly used centralized LVRT controller, this study proposes a distributed control scheme using a LVRT compensator (LVRTC) capable of simultaneously performing reactive current compensation for doubly-fed induction generator (DFIG)-, or permanent magnet synchronous generator (PMSG)-based WTGs. The proposed LVRTC using silicon carbide (SiC)-based inverters can achieve better system efficiency, and increase system reliability. The proposed LVRTC adopts a digital control scheme and dq-axis current decoupling algorithm to realize simultaneous active/reactive power control features. Theoretical analysis, derivation of mathematical models, and design of the control scheme are initially conducted, and simulation is then performed in a computer software environment to validate the feasibility of the system. Finally, a 2 kVA small-scale hardware system with TI’s digital signal processor (DSP) as the control core is implemented for experimental verification. Results from simulation and implementation are in close agreement, and validate the feasibility and effectiveness of the proposed control scheme.


Author(s):  
Junnian Wang ◽  
Yao Dou ◽  
Zhenheng Wang ◽  
Dan Jiang

With the continuous expansion of the scale of wind turbine system, wind power production, operation and equipment control of wind turbine have become more and more significant. To improve the reliability of wind turbine systems fault diagnosis, combining with data-driven technology, this paper proposes a multi-fault diagnosis method for wind power system based on recurrent neural network. According to the actual wind speed data, the normal operation and fault data of the wind turbine system are obtained by system modeling, and the classification and prediction model based on the recurrent neural network algorithm is established, which takes 30 characteristic parameters such as wind speed, rotor speed, generator speed and power generation as input, and 10 different types faults labels of the wind turbine as output. Specific rules formed inside the sample data of the wind turbine system are learned intelligently by the model which is continuously trained, optimized and tested to verify the feasibility of the algorithm. The results of evaluation standards such as accuracy rate, missed detection rate and F1-measure that compared with other related algorithms such as deep belief network show that the proposed algorithm can solve the problem of multi-classification fault diagnosis for wind power generation system efficiently.


Author(s):  
Michael Kirschneck ◽  
Daniel J. Rixen ◽  
Henk Polinder ◽  
Ron A. J. van Ostayen

In large direct-drive off-shore wind turbine generators one challenge is to engineer the system to function securely with an air gap length of about a thousandth of the outer rotor diameter. Compared to the large diameter of the generator rotor, the rolling element bearings can only be constructed with a relatively limited size. This makes it challenging to design appropriate constructions able to transmit the large applied magnetic forces encountered in the air gap of direct drive wind turbine generators. Currently, this challenge is met by designing stiff heavy rotors that are able to withstand the forces in the air gap. Incorporating flexibility into the design of the rotor structure can lead to a lighter less expensive rotor. In order to be able to do this the magnetomechanical coupling in the air gap and its effect on the structural dynamics need to be taken into account when predicting the intended flexibility. This paper introduces an approach for a multiphysical modal analysis that makes it possible to predict the dynamics of the strongly coupled magnetomechanical system. The new method is validated using measurements of a simple lab setup. It is then applied to a single-bearing design direct-drive wind turbine generator rotor to calculate the changes of the structural dynamics caused by the electromagnetomechanical coupling.


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