Active congestion quantification and reliability improvement considering aging failure in modern distribution networks

The enormous concerns of climate change and traditional resource crises lead to the increased use of distributed generations (DGs) and electric vehicles (EVs) in distribution networks. This leads to significant challenges in maintaining safe and reliable network operations due to the complexity and uncertainties in active distribution networks, e.g., congestion and reliability problems. Effective congestion management (CM) policies require appropriate indices to quantify the seriousness and customer contributions to congested areas. Developing an accurate model to identify the residual life of aged equipment is also essential in long-term CM procedures. The assessment of network reliability and equipment end-of-life failure also plays a critical role in network planning and regulation. The main contributions of this thesis include a) outlining the specific characteristics of congestion events and introducing the typical metrics to assess the effectiveness of CM approaches; b) proposing spatial, temporal and aggregate indices for rapidly recognizing the seriousness of congestion in terms of thermal and voltage violations, and proposing indices for quantifying the customer contributions to congested areas; c) proposing an improved method to estimate the end-of-life failure probabilities of transformers and cables lines taking real-time relative aging speed and loss-of-life into consideration; d) quantifying the impact of different levels of EV penetration on the network reliability considering end-of-life failure on equipment and post-fault network reconfiguration; and e) proposing an EV smart charging optimization model to improve network reliability and reduce the cost of customers and power utilities. Simulation results illustrate the feasibility of the proposed indices in rapidly recognizing the congestion level, geographic location, and customer contributions in balanced and unbalanced systems. Voltage congestion can be significantly relieved by network reconfiguration and the utilization of the proposed indices by utility operators in CM procedures is also explained. The numerical studies also verify that the improved Arrhenius-Weibull can better indicate the aging process and demonstrate the superior accuracy of the proposed method in identifying residual lives and end-of-life failure probabilities of transformers and conductors. The integration of EV has a great impact on equipment aging failure probability and loss-of-life, thus resulting in lower network reliability and higher cost for managing aging failure. Finally, the proposed piecewise linear optimization model of the EV smart charging framework can significantly improve network reliability by 90% and reduce the total cost by 83.8% for customers and power utilities

Enhancement of deregulated and restructured power network performance with flexible alternating current transmission systems devices.

Doctoral degree. University of KwaZulu- Natal, Durban.The increase in power transactions, consequent open access created by deregulation and restructuring has resulted into network operation challenges including determination as well as enhancement of available transfer capability (ATC), and congestion management among others. In this study, repeated alternating current power flow (RACPF) approach was implemented for determination of ATC. ATCs for inter-area line outage and generator outage contingency conditions were obtained and analyzed. Analyses of most severe line outage contingencies resulting from evaluation of different performance index (PI) ranking methods were carried out for severe line outage contingency identification. A comprehensive review of FACTS controllers with their various background, topological structures, deployment techniques and cutting-edge applications was carried out for network performance enhancement. In addition, different placement methods were investigated for optimal performance evaluation of FACTS devices. Following this, comparative performance of static var compensator (SVC) and thyristor-controlled series compensator (TCSC) models for enhancement of ATC, bus voltage profile improvement and real power loss minimization was investigated. In addition, particle swarm optimization (PSO) and brain-storm optimization algorithms (BSOA) were engaged for optimum setting of FACTS devices through multi-objective problem formulation and allocation purposes. Thereafter, sensitivity-based technique involving incorporation of proposed FACTS device loss with the general loss equation for the determination of optimum location with same objectives was developed and TCSC location was established based on this sensitivity factors analyses, obtained from partial derivatives of the resultant loss equations with respect to control parameters. Subsequently, investigation and analyses of capability of an optimized VSC-HVDC transmission system in enhancing power network performance were conducted. Furthermore, this optimized VSC-HVDC transmission system was applied for mitigation of bus voltage and line thermal limit violation as a result of n-1-line outage contingency. All these investigations and analyses were implemented for bilateral, simultaneous and multilateral transactions as characterized by network liberalization and IEEE 5 and 30 bus networks were used for implementation in MATLAB environment. RACPF method found to be more accurate especially when compared with other methods with 11.574 MW above and 29.014 MW below recorded ATC values. Voltage and real power PI have also been proven to be distinctly dissimilar in severe contingency identification. In placement method comparison however, disparities in ATC enhancement ranges between 2% and 85% were achieved while real power loss minimization of up to 25% was obtained for different methods. Real power loss minimization of up to 0.06 MW and voltage improvement of bus 21 to 30 were achieved with SVC, while ATC enhancement of up to 14% were recorded for both devices. However, BSO behaved much like PSO throughout the achievements of other set objectives but performed better in ATC enhancement with 27.12 MW and 5.24 MW increase above enhanced ATC values achieved by the latter. The comparison of set objectives values relative to that obtained with PSO methods depict suitability and advantages of BSOA technique. Sensitivity based placement technique resulted into ATC enhancement of more than 60% well above the values obtained when TCSC was placed with thermal limit method. In addition, a substantial bus voltage improvement and active power loss reduction were recorded with this placement method. With incorporation of a VSC-HVDC based transmission system into ac network however, there was an improvement in power flow up to 15.66% corresponding to 46 MW for various transactions, transmission line power loss minimization up to 0.38 MW and bus voltage profile deviation minimization. Besides, automatic alleviation of violated thermal and voltage limits during contingency present VSC-HVDC system as a solution for network performance optimization especially during various transactions occasioned by unbundling power processes. Therefore, ATCs were properly enhanced, bus voltage profile improved, and system real power loss minimized. Likewise, HVDC system enhanced network performance and automatically alleviated violated thermal and voltage limits during contingency

Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems

The electrical power system is undergoing a revolution enabled by advances in telecommunications, computer hardware and software, measurement, metering systems, IoT, and power electronics. Furthermore, the increasing integration of intermittent renewable energy sources, energy storage devices, and electric vehicles and the drive for energy efficiency have pushed power systems to modernise and adopt new technologies. The resulting smart grid is characterised, in part, by a bi-directional flow of energy and information. The evolution of the power grid, as well as its interconnection with energy storage systems and renewable energy sources, has created new opportunities for optimising not only their techno-economic aspects at the planning stages but also their control and operation. However, new challenges emerge in the optimization of these systems due to their complexity and nonlinear dynamic behaviour as well as the uncertainties involved.This volume is a selection of 20 papers carefully made by the editors from the MDPI topic “Optimisation, Optimal Control and Nonlinear Dynamics in Electrical Power, Energy Storage and Renewable Energy Systems”, which was closed in April 2022. The selected papers address the above challenges and exemplify the significant benefits that optimisation and nonlinear control techniques can bring to modern power and energy systems

Power System Simulation, Control and Optimization

This Special Issue “Power System Simulation, Control and Optimization” offers valuable insights into the most recent research developments in these topics. The analysis, operation, and control of power systems are increasingly complex tasks that require advanced simulation models to analyze and control the effects of transformations concerning electricity grids today: Massive integration of renewable energies, progressive implementation of electric vehicles, development of intelligent networks, and progressive evolution of the applications of artificial intelligence

A World-Class University-Industry Consortium for Wind Energy Research, Education, and Workforce Development: Final Technical Report

During the two-year project period, the consortium members have developed control algorithms for enhancing the reliability of wind turbine components. The consortium members have developed advanced operation and planning tools for accommodating the high penetration of variable wind energy. The consortium members have developed extensive education and research programs for educating the stakeholders on critical issues related to the wind energy research and development. In summary, The Consortium procured one utility-grade wind unit and two small wind units. Specifically, the Consortium procured a 1.5MW GE wind unit by working with the world leading wind energy developer, Invenergy, which is headquartered in Chicago, in September 2010. The Consortium also installed advanced instrumentation on the turbine and performed relevant turbine reliability studies. The site for the wind unit is InvenergyÃÂÃÂÃÂâÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂs Grand Ridge wind farmin Illinois. The Consortium, by working with Viryd Technologies, installed an 8kW Viryd wind unit (the Lab Unit) at an engineering lab at IIT in September 2010 and an 8kW Viryd wind unit (the Field Unit) at the Stuart Field on IITÃÂÃÂÃÂâÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂs main campus in July 2011, and performed relevant turbine reliability studies. The operation of the Field Unit is also monitored by the Phasor Measurement Unit (PMU) in the nearby Stuart Building. The Consortium commemorated the installations at the July 20, 2011 ribbon-cutting ceremony. The ConsortiumÃÂÃÂÃÂâÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂs researches on turbine reliability included (1) Predictive Analytics to Improve Wind Turbine Reliability; (2) Improve Wind Turbine Power Output and Reduce Dynamic Stress Loading Through Advanced Wind Sensing Technology; (3) Use High Magnetic Density Turbine Generator as Non-rare Earth Power Dense Alternative; (4) Survivable Operation of Three Phase AC Drives in Wind Generator Systems; (5) Localization of Wind Turbine Noise Sources Using a Compact Microphone Array; (6) Wind Turbine Acoustics - Numerical Studies; and (7) Performance of Wind Turbines in Rainy Conditions. The ConsortiumÃÂÃÂÃÂâÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂs researches on wind integration included (1) Analysis of 2030 Large-Scale Wind Energy Integration in the Eastern Interconnection; (2) Large-scale Analysis of 2018 Wind Energy Integration in the Eastern U.S. Interconnection; (3) Integration of Non-dispatchable Resources in Electricity Markets; (4) Integration of Wind Unit with Microgrid. The ConsortiumÃÂÃÂÃÂâÃÂÃÂÃÂÃÂÃÂÃÂÃÂÃÂs education and outreach activities on wind energy included (1) Wind Energy Training Facility Development; (2) Wind Energy Course Development; (3) Wind Energy Outreach

Self-organizing Coordination of Multi-Agent Microgrid Networks

abstract: This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.Dissertation/ThesisDoctoral Dissertation Systems Engineering 201

Shortest Route at Dynamic Location with Node Combination-Dijkstra Algorithm

Abstract— Online transportation has become a basic requirement of the general public in support of all activities to go to work, school or vacation to the sights. Public transportation services compete to provide the best service so that consumers feel comfortable using the services offered, so that all activities are noticed, one of them is the search for the shortest route in picking the buyer or delivering to the destination. Node Combination method can minimize memory usage and this methode is more optimal when compared to A* and Ant Colony in the shortest route search like Dijkstra algorithm, but can’t store the history node that has been passed. Therefore, using node combination algorithm is very good in searching the shortest distance is not the shortest route. This paper is structured to modify the node combination algorithm to solve the problem of finding the shortest route at the dynamic location obtained from the transport fleet by displaying the nodes that have the shortest distance and will be implemented in the geographic information system in the form of map to facilitate the use of the system. Keywords— Shortest Path, Algorithm Dijkstra, Node Combination, Dynamic Location (key words