| 1. |
- Ariza Rocha, Oscar David, et al.
(författare)
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Dynamic rating assists cost-effective expansion of wind farms by utilizing the hidden capacity of transformers
- 2020
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Ingår i: International Journal of Electrical Power & Energy Systems. - : Elsevier. - 0142-0615 .- 1879-3517. ; 123
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Tidskriftsartikel (refereegranskat)abstract
- Dynamic rating of power transmission devices is a technology that allows better equipment utilization through real-time monitoring of the weather conditions and the load. Dynamic rating of transformers is a fairly new technology if compared to the dynamic rating of power lines, and has a high potential for significantly improving component utilization while lowering investment costs on installing new transformers.The following work investigates how to utilize already operational transformers, which are used for wind farm connection, for expanding wind generation capacity. Also, this paper shows improvements that dynamic transformer rating can bring to both power grid operators and wind farm owners by exploring the economic benefits of expanding wind parks without investing in new power transformers. Connecting additional wind turbines at sites with high wind potential after the wind park is already in exploitation can assist in lowering electricity price and provide a possibility of less risky investment in the wind energy sector. This paper uses transformer thermal modelling and wind farm expansion techniques such as convolution method and product method to investigate to which extent existing wind farms can be expanded using already installed transformer units.Five transformer locations and nine units are studied for finding the potential of dynamic transformer rating for network expansion applications. The analysis shows that the optimal expansion of wind power from a generator perspective is around 30%" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative;">% to 50%" role="presentation" style="box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative;">%, although, it can be limited further by network restrictions. A possibility to use a large component, such as power transformer, closer to its full potential can provide material and cost savings for building new devices and decrease investment costs on manufacturing, transportation and installation of new units. Dynamic rating of power transformers can also increase the socio-economic benefits of renewable energy by lowering electricity price from renewables and incentivize an increased share of green power in electricity markets.
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| 2. |
- Bragone, Federica, et al.
(författare)
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Physics-informed neural networks for modelling power transformer’s dynamic thermal behaviour
- 2022
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Ingår i: Electric power systems research. - : Elsevier. - 0378-7796 .- 1873-2046. ; 211, s. 108447-108447
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Tidskriftsartikel (refereegranskat)abstract
- This paper focuses on the thermal modelling of power transformers using physics-informed neural networks (PINNs). PINNs are neural networks trained to consider the physical laws provided by the general nonlinear partial differential equations (PDEs). The PDE considered for the study of power transformer’s thermal behaviour is the heat diffusion equation provided with boundary conditions given by the ambient temperature at the bottom and the top-oil temperature at the top. The model is one dimensional along the transformer height. The top-oil temperature and the transformer’s temperature distribution are estimated using field measurements of ambient temperature, top-oil temperature and the load factor. The measurements from a real transformer provide more realistic solution, but also an additional challenge. The Finite Volume Method (FVM) is used to calculate the solution of the equation and further to benchmark the predictions obtained by PINNs. The results obtained by PINNs for estimating the top-oil temperature and the transformer’s thermal distribution show high accuracy and almost exactly mimic FVM solution.
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| 3. |
- Chakrapani Manakari, Vageesh, et al.
(författare)
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Minimization of Wind Power Curtailment using Dynamic Line Rating
- 2020
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Ingår i: 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe).
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Konferensbidrag (refereegranskat)abstract
- Large scale penetration of wind power to the grid and unevenly spread power demand can result in the transmission system not being able to dispatch all the produced wind power, causing in wind power curtailment.Dynamic line rating (DLR) is a technology which uses thermal properties of overhead conductors and weather data to determine the real-time ampacity limits of transmission lines. In general, dynamic rating allows extending capacity limits of power lines and helps to remove congestion in the grid.(/p)(p This study looks into the possibility of using dynamic line rating for removing congestion in the power system to allow dispatching more wind power and minimize the need for curtailment. The results of case-studies have shown that DLR allows to significantly reduce the curtailment of generation, especially during winter, when wind production is highest and day time, when the power demand is the highest.
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| 4. |
- Cheng, Jialu, et al.
(författare)
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Impact of Advanced Bushing Diagnostic Techniques on Operation Reliability and Maintenance Strategy
- 2022
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Ingår i: Proceedings 2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- The reliability of power transformers is crucial for the safety operation of the power system. Detection of incipient faults, as well as natural aging, is the key to reduce the failure risk, which gives the operators adequate margin to perform maintenance before reaching a critical failure. Routine maintenance consists of a few testing techniques to check whether mechanical and electrical components fulfill the minimum threshold requirement. In addition, there are various advanced diagnostic testings that are capable of giving more precise condition indications of a transformer in thermal, electrical, and mechanical aspects. The reliability of transformers can thus be enhanced with the help of advanced diagnostic testings. However, in practice, it is often costly to perform the advanced testings and the effectiveness is hard to verify due to the lack of relevant cases and case studies. According to the published statistics, the failure rate is only around 0.1% - 0.2% per year. In this project, a widely accepted insulation condition diagnostic method, Dielectric Frequency Response, DFR was investigated in aspects of cost and return. Testing objects were a group of transformer bushings in three HVDC substations. Reliability is enhanced by identifying incipient bushing defects that cannot be detected by other routine testing techniques. By analyzing the cost and return of the DFR testing, the transition of the current maintenance strategy towards reliability-centered is in position.
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| 5. |
- Duvnjak Zarkovic, Sanja, 1989-, et al.
(författare)
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Addressing Data Deficiencies in Outage Reports : A Qualitative and Machine Learning Approach
- 2024
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This study investigates outage statistics in the Swedish power system. More specifically, this paper delves into the critical analysis and enhancement of data quality, focusing on inconsistencies and missing values, i.e. unknown outage causes and unidentified faulty equipment. By carefully examining the data, noticeable gaps and deficiencies are revealed. Thus, a format for improving outage reporting using a database with 3 relations (outage summary, outage breakdown and customer breakdown) is proposed. In addition to a qualitative analysis of the data, various machine learning algorithms are explored and tested for their capability to predict the unknown values within the dataset, thereby offering a twofold solution: enhancing the accuracy of outage data and facilitating deeper, more accurate analytical capabilities. The findings and proposals within this work not only illuminate the current challenges within outage data management but also pave the way for more robust, data-driven decision-making in outage management and policy formation.
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| 6. |
- Duvnjak Zarkovic, Sanja, 1989-, et al.
(författare)
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Integrated reliability centered distribution system planning — Cable routing and switch placement
- 2021
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Ingår i: Energy Reports. - : Elsevier BV. - 2352-4847. ; 7, s. 3099-3115
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Tidskriftsartikel (refereegranskat)abstract
- Distribution utilities aim to operate and plan their network in a secure and economical way. The prime focus of this work is to assist utilities by developing a new integrated approach which considers the impacts of system reliability in distribution system planning (DSP). This approach merges different problems together and solves them in a two-stage process, as follows: 1. cable routing and optimal location and number of switching devices (circuit breakers and reclosers); 2. optimal location and number of tie switches. Moreover, the possibility of installing different cable options, with different prices and capacities, is included. The optimization algorithm is designed using mixed-integer programming (MIP). The developed algorithm analytically evaluates relationships between different components in the system and dynamically updates reliability indices, failure rate and restoration time, of every node in the system. This approach has been tested on two distribution systems. Despite the complexity and the exhaustiveness of the problem, MIP converges and provides the optimal solution for every studied scenario. The results show that an integrated approach enables utilities to obtain more comprehensive solutions. Moreover, by understanding the impact of parameter variation enables utilities to categorize their priorities in the decision making process and optimally invest in distribution network with respect to reliability.
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| 7. |
- Duvnjak Zarkovic, Sanja, 1989-, et al.
(författare)
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Onshore wind farm - Reliability centered cable routing
- 2021
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Ingår i: Electric power systems research. - : Elsevier BV. - 0378-7796 .- 1873-2046. ; 196, s. 107201-
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Tidskriftsartikel (refereegranskat)abstract
- Designing an onshore wind farm is a complex planning process that requires various stages to be completed. The prime focus of this work is to assist planners and experts in finding the optimal cable layout of the onshore wind farm. The optimization algorithm is designed using mixed integer linear programming (MILP). The MILP algorithm takes into account system reliability, power transfer capacities and power quality issue. The novelty in this optimization algorithm is to simultaneously minimize cable installation cost and the cost of lost energy production and therefore maximize the reliability of the system. Additionally, the algorithm supports the optimal selection among different cable options, with different features, prices and capacities. By calculating voltage increase at the point of connection (POC), power quality issue is considered as well. The designed algorithm provides optimal results for four different wind farm layouts. Every layout is tested for three different case scenarios, where different number and type of cables are considered. The results show that more cable options contribute in lowering the total costs. Moreover, cables with higher capacity can help in improving the power quality issue.
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| 8. |
- Duvnjak Zarkovic, Sanja, 1989-, et al.
(författare)
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Outage Statistics and Trends in Sweden – What does data tell us?
- 2023
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Ingår i: Energy Proceedings.
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Konferensbidrag (refereegranskat)abstract
- Data analysis plays a pivotal role in identifying patterns and relationships within data sets. By examining historical outage statistics in power systems, trends in system performance can be revealed, contributing to a better understanding of its behavior. Furthermore, by understanding the past performance of the power system, utility companies can make better decisions to enhance system reliability and resilience. This study investigates outage statistics in the Swedish power system from 2009 to 2019 and examines in depth the reporting mechanism. The data is clustered and analyzed according to three different criteria: voltage level of the breaking device, cause of the failure, and faulty equipment. Although the presented overview highlights key trends in system performance, the analysis has uncovered issues related to data quality and availability, such as missing values and inconsistencies that require further attention.
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| 9. |
- Duvnjak Zarkovic, Sanja, 1989-
(författare)
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Security of Electricity Supply in Power Distribution System : Optimization Algorithms for Reliability Centered Distribution System Planning
- 2020
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The importance of electricity in everyday life and demands to improve the reliability of distribution systems force utilities to operate and plan their networks in a more secure and economical manner. With higher demands on reliability from both customers and regulators, a big pressure has been put on the security of electricity supply which is considered as a fundamental requirement for modern societies. Thus, efficient solutions for reliability and security of supply improvements are not just of increasing interest, but also have significant socio-economic relevance. Distribution system planning (DSP) is one of the major activities of distribution utilities to deal with reliability enhancement.This thesis deals with developing optimization algorithms, which aim is to min- imize customer interruption costs, and thus maximize the reliability of the system. This is implemented either by decreasing customer interruption duration, frequency of customer interruptions or both. The algorithms are applied on a single or multi- ple DSP problems. Mixed-integer programming has been used as an optimization approach.It has been shown that solving and optimizing each one of the DSP problems contributes greatly to the reliability improvement, but brings certain challenges. Moreover, applying algorithms on multiple and integrated DSP problems together leads to even bigger complexity and burdensome. However, going toward this inte- grated approach results in a more appropriate and realistic DSP model.The idea behind the optimization is to achieve balance between reliability and the means to achieve this reliability. It is a decision making process, i.e. a trade-off between physical and pricing dimension of security of supply.
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| 10. |
- Duvnjak Zarkovic, Sanja, 1989-
(författare)
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Security of Electricity Supply in Power Systems : Establishing a Global Framework for Assessing Power System Health and Analyzing Outage Statistics in Sweden
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The primary objective of this thesis is to enhance the security of electricity supply by providing a holistic perspective and introducing a comprehensive framework for assessing power system health. This novel approach aims for a thorough evaluation of the system’s overall performance and well-being, using the physical dimensions of the security of supply as the foundation for a power system health index. After establishing the theoretical framework, relevant and available data is collected in order to analyze and understand the system’s performance. By analyzing outage statistics in Sweden, the research identifies specific trends and performance metrics that can be further investigated and segmented according to various criteria. The insights gained from this research can, in turn, be used to inform proactive maintenance strategies and capacity planning, ultimately mitigating the risks of outages and ensuring a more reliable electricity supply. Outage statistics are furthermore analyzed from the aspect of data quality, focusing on inconsistencies and missing values in the outage reports, i.e. unknown outage causes and unidentified faulty equipment. By carefully examining the data, noticeable gaps and deficiencies are revealed. Thus, a format for improving outage reporting using a database with 3 relations (outage summary, outage breakdown and customer breakdown) is proposed. In addition to a qualitative analysis of the data, various machine learning algorithms are explored and tested for their capability to predict the unknown values within the dataset, thereby offering a twofold solution: enhancing the accuracy of outage data and facilitating deeper, more accurate analytical capabilities. The findings and proposals within this work highlight the current challenges within outage data management and also lay the groundwork for a more comprehensive, data-driven approach in outage management and policy development.
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