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Load Estimation for Electric Power Distribution Networks
Title
Load Estimation for Electric Power Distribution Networks.
Creator
Eyisi, Chiebuka, Lotfifard, Saeed, Yuan, Jiann-Shiun, Wu, Xinzhang, University of Central Florida
Abstract / Description
In electric power distribution systems, the major determinant in electricity supply strategy is the quantity of demand. Customers need to be accurately represented using updated nodal load information as a requirement for efficient control and operation of the distribution network. In Distribution Load Estimation (DLE), two major categories of data are utilized: historical data and direct real-time measured data. In this thesis, a comprehensive survey on the state-of-the-art methods for...
Show moreIn electric power distribution systems, the major determinant in electricity supply strategy is the quantity of demand. Customers need to be accurately represented using updated nodal load information as a requirement for efficient control and operation of the distribution network. In Distribution Load Estimation (DLE), two major categories of data are utilized: historical data and direct real-time measured data. In this thesis, a comprehensive survey on the state-of-the-art methods for estimating loads in distribution networks is presented. Then, a novel method for representing historical data in the form of Representative Load Curves (RLCs) for use in real-time DLE is also described. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is used in this regard to determine RLCs. An RLC is a curve that represents the behavior of the load during a specified time span; typically daily, weekly or monthly based on historical data. Although RLCs provide insight about the variation of load, it is not accurate enough for estimating real-time load. This therefore, should be used along with real-time measurements to estimate the load more accurately. It is notable that more accurate RLCs lead to better real-time load estimation in distribution networks.This thesis addresses the need to obtain accurate RLCs to assist in the decision-making process pertaining to Radial Distribution Networks (RDNs).This thesis proposes a method based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) architecture to estimate the RLCs for Distribution Networks. The performance of the method is demonstrated and simulated, on a test 11kV Radial Distribution Network using the MATLAB software. The Mean Absolute Percent Error (MAPE) criterion is used to justify the accuracy of the RLCs.
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Date Issued
2013
Identifier
CFE0004995, ucf:49555
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004995
Modeling and fault detection in DC side of Photovoltaic Arrays
Title
Modeling and fault detection in DC side of Photovoltaic Arrays.
Creator
Akram, Mohd, Lotfifard, Saeed, Mikhael, Wasfy, Wu, Thomas, University of Central Florida
Abstract / Description
Fault detection in PV systems is a key factor in maintaining the integrity of any PV system. Faults in photovoltaic systems can cause irrevocable damages to the stability of the PV system and substantially decrease the power output generated from the array of PV modules. Among'st the various AC and DC faults in a PV system, the clearance of the AC side faults is achieved by conventional AC protection schemes,the DC side, however , there still exists certain faults which are difficult to...
Show moreFault detection in PV systems is a key factor in maintaining the integrity of any PV system. Faults in photovoltaic systems can cause irrevocable damages to the stability of the PV system and substantially decrease the power output generated from the array of PV modules. Among'st the various AC and DC faults in a PV system, the clearance of the AC side faults is achieved by conventional AC protection schemes,the DC side, however , there still exists certain faults which are difficult to detect and clear. This paper deals with the modeling, detection and classification of these types of DC faults. It is essential to be able to simulate the PV characteristics and faults through software. In this thesis a comprehensive literature survey of fault detection methods for DC side of a PV system is presented. The disparities in the techniques employed for fault detection are studied . A new method for modeling the PV systems information only from manufacturers datasheet using both the Normal Operating Cell temperature conditions (NOCT) and Standard Operating Test Conditions (STC) conditions is then proposed.The input parameters for modeling the system are Isc,Voc,Impp,Vmpp and the temperature coefficients of Isc and Voc for both STC and NOCT conditions. The model is able to analyze the variations of PV parameters such as ideality factor, Series resistance, thermal voltage and Band gap energy of the PV module with temperature. Finally a novel intelligent method based on Probabilistic Neural Network for fault detection and classification for PV farm with string inverter technology is proposed.
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Date Issued
2014
Identifier
CFE0005293, ucf:50571
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005293
Control Based Soft Switching Three-phase Micro-inverter: Efficiency and Power Density Optimization
Title
Control Based Soft Switching Three-phase Micro-inverter: Efficiency and Power Density Optimization.
Creator
Amirahmadi, Ahmadreza, Batarseh, Issa, Lotfifard, Saeed, Mikhael, Wasfy, Wu, Xinzhang, Kutkut, Nasser, University of Central Florida
Abstract / Description
In the field of renewable energy, solar photovoltaic is growing exponentially. Grid-tied PV micro-inverters have become the trend for future PV system development because of their remarkable advantages such as enhanced energy production due to MPPT implementation for each PV panel, high reliability due to redundant and distributed system architecture, and simple design, installation, and management due to its plug-and-play feature. Conventional approaches for the PV micro-inverters are mainly...
Show moreIn the field of renewable energy, solar photovoltaic is growing exponentially. Grid-tied PV micro-inverters have become the trend for future PV system development because of their remarkable advantages such as enhanced energy production due to MPPT implementation for each PV panel, high reliability due to redundant and distributed system architecture, and simple design, installation, and management due to its plug-and-play feature. Conventional approaches for the PV micro-inverters are mainly in the form of single-phase grid connected and they aim at the residential and commercial rooftop applications. It would be advantageous to extend the micro-inverter concept to large size PV installations such as MW-class solar farms where three-phase AC connections are used.The relatively high cost of the three-phase micro-inverter is the biggest barrier to its large scale deployment. Increasing the switching frequency may be the best way to reduce cost by shrinking the size of reactive components and heat-sink. However, this approach could cause conversion efficiency to drop dramatically without employing soft switching techniques or using costly new devices.This dissertation presents a new zero voltage switching control method that is suitable for low power applications such as three-phase micro-inverters. The proposed hybrid boundary conduction mode (BCM) current control method increases the efficiency and power density of the micro-inverters and features both reduced number of components and easy digital implementation. Zero voltage switching is achieved by controlling the inductor current bi-directional in every switching cycle and results in lower switching losses, higher operating frequency, and reduced size and cost of passive components, especially magnetic cores. Some practical aspects of hybrid control implementation such as dead-time insertion can degrade the performance of the micro-inverter. A dead-time compensation method that improves the performance of hybrid BCM current control by decreasing the output current THD and reducing the zero crossing distortion is presented.Different BCM ZVS current control modulation schemes are compared based on power losses breakdown, switching frequency range, and current quality. Compared to continuous conduction mode (CCM) current control, BCM ZVS control decreases MOSFET switching losses and filter inductor conduction losses but increases MOSFET conduction losses and inductor core losses. Based on the loss analysis, a dual-mode current modulation method combining ZVS and zero current switching (ZCS) schemes is proposed to improve the efficiency of the micro-inverter.Finally, a method of maintaining high power conversion efficiency across the entire load range of the three-phase micro-inverter is proposed. The proposed control method substantially increases the conversion efficiency at light loads by minimizing switching losses of semiconductor devices as well as core losses of magnetic components. This is accomplished by entering a phase skipping operating mode wherein two phases of an inverter are disabled and three inverters are combined to form a new three-phase system with minimal grid imbalance. A 400W prototype of a three-phase micro-inverter and its hybrid control system have been designed and tested under different conditions to verify the effectiveness of the proposed controller, current modulation scheme, and light load efficiency enhancement method.
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Date Issued
2014
Identifier
CFE0005125, ucf:50703
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005125
Optimal distribution network reconfiguration using meta-heuristic algorithms
Title
Optimal distribution network reconfiguration using meta-heuristic algorithms.
Creator
Asrari, Arash, Wu, Thomas, Lotfifard, Saeed, Haralambous, Michael, Atia, George, Pazour, Jennifer, University of Central Florida
Abstract / Description
Finding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the...
Show moreFinding optimal configuration of power distribution systems topology is an NP-hard combinatorial optimization problem. It becomes more complex when time varying nature of loads in large-scale distribution systems is taken into account. In the second chapter of this dissertation, a systematic approach is proposed to tackle the computational burden of the procedure. To solve the optimization problem, a novel adaptive fuzzy based parallel genetic algorithm (GA) is proposed that employs the concept of parallel computing in identifying the optimal configuration of the network. The integration of fuzzy logic into GA enhances the efficiency of the parallel GA by adaptively modifying the migration rates between different processors during the optimization process. A computationally efficient graph encoding method based on Dandelion coding strategy is developed which automatically generates radial topologies and prevents the construction of infeasible radial networks during the optimization process. The main shortcoming of the proposed algorithm in Chapter 2 is that it identifies only one single solution. It means that the system operator will not have any option but relying on the found solution. That is why a novel hybrid optimization algorithm is proposed in the third chapter of this dissertation that determines Pareto frontiers, as candidate solutions, for multi-objective distribution network reconfiguration problem. Implementing this model, the system operator will have more flexibility in choosing the best configuration among the alternative solutions. The proposed hybrid optimization algorithm combines the concept of fuzzy Pareto dominance (FPD) with shuffled frog leaping algorithm (SFLA) to recognize non-dominated suboptimal solutions identified by SFLA. The local search step of SFLA is also customized for power systems applications so that it automatically creates and analyzes only the feasible and radial configurations in its optimization procedure which significantly increases the convergence speed of the algorithm. In the fourth chapter, the problem of optimal network reconfiguration is solved for the case in which the system operator is going to employ an optimization algorithm that is automatically modifying its parameters during the optimization process. Defining three fuzzy functions, the probability of crossover and mutation will be adaptively tuned as the algorithm proceeds and the premature convergence will be avoided while the convergence speed of identifying the optimal configuration will not decrease. This modified genetic algorithm is considered a step towards making the parallel GA, presented in the second chapter of this dissertation, more robust in avoiding from getting stuck in local optimums. In the fifth chapter, the concentration will be on finding a potential smart grid solution to more high-quality suboptimal configurations of distribution networks. This chapter is considered an improvement for the third chapter of this dissertation for two reasons: (1) A fuzzy logic is used in the partitioning step of SFLA to improve the proposed optimization algorithm and to yield more accurate classification of frogs. (2) The problem of system reconfiguration is solved considering the presence of distributed generation (DG) units in the network. In order to study the new paradigm of integrating smart grids into power systems, it will be analyzed how the quality of suboptimal solutions can be affected when DG units are continuously added to the distribution network.The heuristic optimization algorithm which is proposed in Chapter 3 and is improved in Chapter 5 is implemented on a smaller case study in Chapter 6 to demonstrate that the identified solution through the optimization process is the same with the optimal solution found by an exhaustive search.
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Date Issued
2015
Identifier
CFE0005575, ucf:50238
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005575
Optimization and design of photovoltaic micro-inverter
Title
Optimization and design of photovoltaic micro-inverter.
Creator
Zhang, Qian, Batarseh, Issa, Shen, Zheng, Wu, Xinzhang, Lotfifard, Saeed, Kutkut, Nasser, University of Central Florida
Abstract / Description
To relieve energy shortage and environmental pollution issues, renewable energy, especially PV energy has developed rapidly in the last decade. The micro-inverter systems, with advantages in dedicated PV power harvest, flexible system size, simple installation, and enhanced safety characteristics are the future development trend of the PV power generation systems. The double-stage structure which can realize high efficiency with nice regulated sinusoidal waveforms is the mainstream for the...
Show moreTo relieve energy shortage and environmental pollution issues, renewable energy, especially PV energy has developed rapidly in the last decade. The micro-inverter systems, with advantages in dedicated PV power harvest, flexible system size, simple installation, and enhanced safety characteristics are the future development trend of the PV power generation systems. The double-stage structure which can realize high efficiency with nice regulated sinusoidal waveforms is the mainstream for the micro-inverter.This thesis studied a double stage micro-inverter system. Considering the intermittent nature of PV power, a PFC was analyzed to provide additional electrical power to the system. When the solar power is less than the load required, PFC can drag power from the utility grid.In the double stage micro-inverter, the DC/DC stage was realized by a LLC converter, which could realize soft switching automatically under frequency modulation. However it has a complicated relationship between voltage gain and load. Thus conventional variable step P(&)O MPPT techniques for PWM converter were no longer suitable for the LLC converter. To solve this problem, a novel MPPT was proposed to track MPP efficiently. Simulation and experimental results verified the effectiveness of the proposed MPPT.The DC/AC stage of the micro-inverter was realized by a BCM inverter. With duty cycle and frequency modulation, ZVS was achieved through controlling the inductor current bi-directional in every switching cycle. This technique required no additional resonant components and could be employed for low power applications on conventional full-bridge and half-bridge inverter topologies. Three different current mode control schemes were derived from the basic theory of the proposed technique. They were referred to as Boundary Current Mode (BCM), Variable Hysteresis Current Mode (VHCM), and Constant Hysteresis Current Mode (CHCM) individually in this paper with their advantages and disadvantages analyzed in detail. Simulation and experimental results demonstrated the feasibilities of the proposed soft-switching technique with the digital control schemes.The PFC converter was applied by a single stage biflyback topology, which combined the advantages of single stage PFC and flyback topology together, with further advantages in low intermediate bus voltage and current stresses. A digital controller without current sampling requirement was proposed based on the specific topology. To reduce the voltage spike caused by the leakage inductor, a novel snubber cell combining soft switching technique with snubber technique together was proposed. Simulation and experimental waveforms illustrated the same as characteristics as the theoretical analysis.In summary, the dissertation analyzed each power stage of photovoltaic micro-inverter system from efficiency and effectiveness optimization perspectives. Moreover their advantages were compared carefully with existed topologies and control techniques. Simulation and experiment results were provided to support the theoretical analysis.
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Date Issued
2013
Identifier
CFE0005286, ucf:50540
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005286
cooperative control and advanced management of distributed generators in a smart grid
Title
cooperative control and advanced management of distributed generators in a smart grid.
Creator
Maknouninejad, Ali, Qu, Zhihua, Lotfifard, Saeed, Haralambous, Michael, Wu, Xinzhang, Kutkut, Nasser, University of Central Florida
Abstract / Description
Smart grid is more than just the smart meters. The future smart grids are expected to include ahigh penetration of distributed generations (DGs), most of which will consist of renewable energysources, such as solar or wind energy. It is believed that the high penetration of DGs will resultin the reduction of power losses, voltage profile improvement, meeting future load demand, andoptimizingthe use of non-conventionalenergy sources. However, more serious problems will ariseif a decent control...
Show moreSmart grid is more than just the smart meters. The future smart grids are expected to include ahigh penetration of distributed generations (DGs), most of which will consist of renewable energysources, such as solar or wind energy. It is believed that the high penetration of DGs will resultin the reduction of power losses, voltage profile improvement, meeting future load demand, andoptimizingthe use of non-conventionalenergy sources. However, more serious problems will ariseif a decent control mechanism is not exploited. An improperly managed high PV penetration maycause voltage profile disturbance, conflict with conventional network protection devices, interferewith transformer tap changers, and as a result, cause network instability.Indeed, it is feasible to organize DGs in a microgrid structure which will be connected to the maingrid through a point of common coupling (PCC). Microgrids are natural innovation zones for thesmart grid because of their scalability and flexibility. A proper organization and control of theinteraction between the microgrid and the smartgrid is a challenge.Cooperative control makes it possible to organize different agents in a networked system to actas a group and realize the designated objectives. Cooperative control has been already appliedto the autonomous vehicles and this work investigates its application in controlling the DGs in amicro grid. The microgrid power objectives are set by a higher level control and the application ofthe cooperative control makes it possible for the DGs to utilize a low bandwidth communicationnetwork and realize the objectives.Initially, the basics of the application of the DGs cooperative control are formulated. This includesorganizing all the DGs of a microgrid to satisfy an active and a reactive power objective. Then, thecooperative control is further developed by the introduction of clustering DGs into several groupsto satisfy multiple power objectives. Then, the cooperative distribution optimization is introducedto optimally dispatch the reactive power of the DGs to realize a unified microgrid voltage profileand minimizethelosses. Thisdistributedoptimizationis agradient based techniqueand itis shownthat when the communication is down, it reduces to a form of droop. However, this gradient baseddroop exhibits a superior performance in the transient response, by eliminating the overshootscaused by the conventional droop.Meanwhile, the interaction between each microgrid and the main grid can be formulated as aStackelberg game. The main grid as the leader, by offering proper energy price to the micro grid,minimizes its cost and secures the power. This not only optimizes the economical interests ofboth sides, the microgrids and the main grid, but also yields an improved power flow and shavesthe peak power. As such, a smartgrid may treat microgrids as individually dispatchable loads orgenerators.
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Date Issued
2013
Identifier
CFE0004712, ucf:49817
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004712