4,273 research outputs found
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An Assessment of PIER Electric Grid Research 2003-2014 White Paper
This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014
Asset Management in Electricity Transmission Utilities: Investigation into Factors Affecting and their Impact on the Network
This thesis draws on techniques from Management Science and Artificial Intelligence to explore asset management in electricity transmission enterprises. In this research, factors that influence policies and practices of asset management within electricity transmission enterprises have been identified, in order to examine their interaction and how they impact the policies, practices and performance of transmission businesses. It has been found that, while there is extensive literature on the economics of transmission regulation and pricing, there is little published research linking the engineering and financial aspects of transmission asset management at a management policy level. To remedy this situation, this investigation has drawn on a wide range of literature, together with expert interviews and personal knowledge of the electricity industry, to construct a conceptual model of asset management with broad applicability across transmission enterprises in different parts of the world. A concise representation of the model has been formulated using a Causal Loop Diagram (CLD).
To investigate the interactions between factors of influence it is necessary to implement the model and validate it against known outcomes. However, because of the nature of the data (a mix of numeric and non-numeric data, imprecise, incomplete and often approximate) and complexity and imprecision in the definition of relationships between elements, this problem is intractable to modelling by traditional engineering methodologies. The solution has been to utilise techniques from other disciplines. Two implementations have been explored: a multi-level fuzzy rule-based model and a system dynamics model; they offer different but complementary insights into transmission asset management. Each model shows potential to be used by transmission businesses for strategic-level decision support.
The research demonstrates the key impact of routine maintenance effectiveness on the condition and performance of transmission system assets. However, performance of the transmission network, is not only related to equipment performance, but is a function of system design and operational aspects, such as loading and load factor. Type and supportiveness of regulation, together with the objectives and corporate culture of the transmission organisation also play roles in promoting various strategies for asset management. The cumulative effect of all these drivers is to produce differences in asset management policies and practices, discernable between individual companies and at a regional level, where similar conditions have applied historically and today
Distributed photovoltaic systems: Utility interface issues and their present status
Major technical issues involving the integration of distributed photovoltaics (PV) into electric utility systems are defined and their impacts are described quantitatively. An extensive literature search, interviews, and analysis yielded information about the work in progress and highlighted problem areas in which additional work and research are needed. The findings from the literature search were used to determine whether satisfactory solutions to the problems exist or whether satisfactory approaches to a solution are underway. It was discovered that very few standards, specifications, or guidelines currently exist that will aid industry in integrating PV into the utility system. Specific areas of concern identified are: (1) protection, (2) stability, (3) system unbalance, (4) voltage regulation and reactive power requirements, (5) harmonics, (6) utility operations, (7) safety, (8) metering, and (9) distribution system planning and design
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Open-Source, Open-Architecture SoftwarePlatform for Plug-InElectric Vehicle SmartCharging in California
This interdisciplinary eXtensible Building Operating System–Vehicles project focuses on controlling plug-in electric vehicle charging at residential and small commercial settings using a novel and flexible open-source, open-architecture charge communication and control platform. The platform provides smart charging functionalities and benefits to the utility, homes, and businesses.This project investigates four important areas of vehicle-grid integration research, integrating technical as well as social and behavioral dimensions: smart charging user needs assessment, advanced load control platform development and testing, smart charging impacts, benefits to the power grid, and smart charging ratepayer benefits
Methodologies for the assessment of industrial and energy assets, based on data analysis and BI
In July 2020, post pandemic onset, Europe launched the Next Generation EU (NGEU) program. The amount of resources deployed to revitalize Europe has reached 750 billion. The NGEU initiative directs significant resources to Italy. These funds can enable our country to boost investment and increase employment. The missions of Italian Recovery and Resilience Plan (PNRR) include digitization, innovation and sustainable mobility (rail network investments, etc.). In this context, this doctorate thesis discusses the importance of infrastructure for society with a special focus on energy, railway and motorway infrastructure. The central theme of sustainability, defined by the World Commission on Environment and Development (WCDE) as ''development that meets the needs of the present generation without compromising the ability of future generations to meet their needs’’, is also highlighted. Through their activities and relationships, organizations contribute positively or negatively to the goal of sustainable development. Sustainability becomes an integrated part of corporate culture. First research in this thesis describes how Artificial Intelligence techniques can play a supporting role for both maintenance operators in tunnel monitoring and those responsible for safety in operation. Relevant information can be extracted from large volumes of data from
sensor equipment in an efficient, fast, dynamic and adaptive manner and made immediately usable by those operating machinery and services to support rapid decisions. Performing sensor-based analysis in motorway tunnels represents a major technological breakthrough that would simplify tunnel management activities and thus the detection of possible deterioration, while keeping risk within tolerance limits. The idea involves the creation of an algorithm for detecting faults, acquiring real-time data from tunnel subsystem sensors and using it to help identify the tunnel's state of service. Artificial intelligence models were trained over a sixmonth period with a granularity of one-hour time series measured on a road tunnel forming part of the Italian motorway systems. The verification was carried out with 3 reference to a series of failures recorded by the sensors. The second research argument is relates to the transfer capacities of high-voltage overhead lines (HVOHL), which are often limited by the critical temperature of the power line, which depends on the magnitude of the current transferred and the environmental conditions, i.e. ambient temperature, wind, etc. In order to use existing power lines more effectively (with a view to progressive decarbonization) and more safely with respect to critical power line temperatures, this work proposes a Dynamic Thermal
Rating (DTR) approach using IoT sensors installed on a number of HV OHL located in different geographical locations in Italy. The objective is to estimate the temperature and ampacity of the OHL conductor, using a data-driven thermomechanical model with a bayesian probabilistic approach, in order to improve the confidence interval of the results. This work shows that it might be possible to estimate a spatio-temporal temperature distribution for each OHL and an increase in the threshold values of the effective current to optimize the OHL ampacity. The proposed model was validated using the Monte Carlo method. Finally, in this thesis is presented study on KPIs as indispensable allies of top management in the asset control phase. They are often overwhelmed by the availability of a huge amount of Key Performance Indicators (KPIs). Most managers struggle In understanding and identifying the few vital management metrics and instead collect and report a vast amount of everything that is easy to measure. As a result, they end up drowning in data, thirsty for information. This condition does not allow good systems management. The aim of this research is help the Asset Management System (AMS)
of a railway infrastructure manager using business intelligence (BI) to equip itself with a KPI management system in line with the AM presented by the normative ISO 55000 - 55001 - 55002 and UIC (International Union of Railways) guideline, for the specific case of a railway infrastructure. This work starts from the study of these regulations, continues with the exploration, definition and use of KPIs. Subsequently KPIs of a generic infrastructure are identified and analyzed, 4 especially for the specific case of a railway infrastructure manager. These KPIs are fitted in the internal elements of the AM frameworks (ISO-UIC) for systematization. Moreover, an analysis of the KPIs now used in the company is made, compared with the KPIs that an infrastructure manager should have. Starting from here a gap analysis is done for the optimization of AMS
ESTABLISHMENT OF THE SECOND LIST OF UNION PROJECTS OF COMMON INTEREST: EVALUATION OF CANDIDATE PROJECTS OF COMMON INTEREST IN THE FIELD OF SMART GRIDS
The document presents the outcome of the evaluation process of candidate Projects of Common Interest in the area of Smart Grids, under the trans-European energy infrastructure regulation. The evaluation follows the guidelines of the assessment framework for Smart Grid projects, developed by the JRC within the EC Smart Grid Task Force.JRC.F.3-Energy Security, Systems and Marke
Energy Management Control for Multimode Microgrid Renewable Integration
The need for storing energy has grown in correlation with the need for renewable and distributed energy resources. Designing a storage unit system which complements the distributed generation is required for increased efficiency and reducing the burden on the utility grid. The energy storage model used in this thesis is the Li-ion battery which is efficient, has high energy density and has applications in field of electronics, transportation and electric power industry. The wind turbine generator, photovoltaic (PV) and the energy storage unit modeled in this work share a symbiotic relationship even though they are completely separate entities which can be connected at separate locations. This study contributes better control as well as ease of connection to the system. To show the effect of storage unit on microgrid distribution system two test systems were considered, standalone system and standard IEEE 13 node feeder system with wind turbine generator and photovoltaic panel. The integration and control of energy storage system is achieved using a battery energy management control (BEMC) at the upper level and a real/reactive power controlled voltage source converter at the lower level. To enhance the control, optimization is performed where the proportional gain and the integral time constant of the PI controller are optimized using genetic algorithm which reduces the losses and increases the efficiency of the system. The results show that the battery energy management control system is effective in controlling the modes of operation of energy storage module based on the wind and solar conditions and is able to completely balance the power produced by the wind generator and PV modules. In this thesis all the test systems and the control were implemented in PSCAD as it is emerging as the new industry standard for transient power applications research
Real-time thermal state and component loading estimation in active distribution networks
Highly stochastic loading and distributed generation in the emerging active distribution networks means that electric utilities need to deploy intelligent network management tools in order to use their assets to the fullest. Real-Time Thermal Rating (RTTR) provides the possibility for short term and even real-time active distribution network management, enabling the network to run closer to an overload state without damage. In this dissertation, pertinent developments and proposals are presented in three stages on the path towards the development of a real-time monitoring and operation system for active distribution networks.
The first stage is the development of distribution network component thermal models for real time implementation. In this dissertation, a numerical model of the air-gap convective heat transfer for underground cable installations inside unfilled conduit is developed. In addition, a dynamic thermal model is developed for prefabricated secondary substation cabins. The most dominant but difficult to solve heat transfer mechanism, natural convection, is modelled by introducing the stack effect principle into the problem. Measurements from a scaled model of prefabricated substations, measurements from actual cabins and 3D Finite Element Method (FEM) simulations are used to validate the numerical model.
In the second stage, this dissertation explores the usability of customer level automatic meter reading (AMR) measurements for distribution network state estimation and for load forecasting applications. A method to forecast substation level loads with their respective confidence intervals using hourly AMR metered customer level consumptions is presented. The forecasting and monitoring of a distribution network in real-time can be met with the modeling of classified type load classes. However, it requires careful incorporation of the necessary factors, such as within-group and between-group correlations of customer classes.
Binding the aforementioned findings, in the third stage, a framework for day-ahead hour-by-hour thermal state forecasting and thermal ratings of distribution network components is proposed and studied. This work has demonstrated that up to three hours ahead thermal state forecasting of an active distribution network can be achieved with an acceptable level of accuracy. In this dissertation, the benefits and practical implications of the real-time thermal rating are investigated. The introduction of real-time thermal rating in an active distribution network management system enhances the loading capacity significantly compared to static rating. This has been revealed through an increased utilization of installed DGs and through better integration potential of additional DGs
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