Voltage regulator modeling for the three-phase power flow in distribution networks

In this paper a three-phase power flow for electrical distribution systems considering different models of voltage regulators is presented. A voltage regulator (VR) is an equipment that maintains the voltage level in a predefined value in a distribution line in spite of the load variations within its nominal power. Three different types of connections are analyzed: 1) wye-connected regulators, 2) open delta-connected regulators and 3) closed delta-connected regulators. To calculate the power flow, the three-phase backward/forward sweep algorithm is used. The methodology is tested on the IEEE 34 bus distribution system. ©2008 IEEE.

HPF boost interleaved operating in discontinuous conduction mode for trolleybus application

This paper deals with results of a research and development (R&D) project in cooperation with Electric Power Distribution Company in São Paulo (Brazil) regarding the development and experimental analysis of a new concept of power drive system suitable for application in traction systems of electrical vehicles pulled by electrical motors, which can be powered by urban DC or AC distribution networks. The proposed front-end structure is composed by five boost power cells in interleaving connection, operating in discontinuous conduction mode as AC-DC converter, or as DC-DC converter, in order to provide the proper DC output voltage range required by DC or AC adjustable speed drivers. Therefore, when supplied by single-phase AC distribution networks, and operating as AC-DC converter, it is capable to provide high power factor, reduced harmonic distortion in the input current, complying with the restrictions imposed by the IEC 61000-3-4 standards resulting in significant improvements for the trolleybuses systems efficiency and for the urban distribution network costs. Considering the compliance with input current restrictions imposed by IEC 61000-3-4 standards, two digital control strategies were evaluated. The digital controller has been implemented using a low cost FPGA (XC3S200) and developed totally using a hardware description language VHDL and fixed point arithmetic. Experimental results from a 15 kW low power scale prototype operating in DC and AC conditions are presented, in order to verify the feasibility and performance of the proposed system. © 2009 IEEE.

Network reconfiguration of distribution systems using metaheuristics and reliability measures

In an evermore competitive environment, power distribution companies need to continuously monitor and improve the reliability indices of their systems. The network reconfiguration (NR) of a distribution system is a technique that well adapts to this new deregulated environment for it allows improvement of system reliability indices without the onus involved in procuring new equipment. This paper presents a reliability-based NR methodology that uses metaheuristic techniques to search for the optimal network configuration. Three metaheuristics, i.e. Tabu Search, Evolution Strategy, and Differential Evolution, are tested using a Brazilian distribution network and the results are discussed. © 2009 IEEE.

Distributed generation impact evaluation using a multi-objective tabu search

Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for the optimal DG allocation problem successfully used multi-objective optimization techniques. So this paper contributes to the fundamental stage of multi-objective optimization of finding the Pareto optimal solutions set. It is proposed the application of a Multi-objective Tabu Search and it was verified a better performance comparing to the NSGA-II method. © 2009 IEEE.

Distributed generation modelling for unbalanced three-phase power flow calculations in smart grids

Distributed Generators (DG) are generally modeled as PQ or PV buses in power flow studies. But in order to integrate DG units into the distribution systems and control the reactive power injection it is necessary to know the operation mode and the type of connection to the system. This paper presents a single-phase and a three-phase mathematical model to integrate DG in power flow calculations in distribution systems, especially suited for Smart Grid calculations. If the DG is in PV mode, each step of the power flow algorithm calculates the reactive power injection from the DG to the system to keep the voltage in the bus in a predefined level, if the DG is in PQ mode, the power injection is considered as a negative load. The method is tested on two well known test system, presenting single-phase results on 85 bus system, and three-phase results in the IEEE 34 bus test system. © 2011 IEEE.

Implementation of a DC-DC converter with variable structure control of switched systems

This paper presents a control method for a class of continuous-time switched systems, using state feedback variable structure controllers. The method is applied to the control of a two-cell dc-dc buck converter and a control circuit design using the software PSpice is proposed. The design is based on Lyapunov-Metzler-SPR systems and the performance of the resulting control system is superior to that afforded by a recently-proposed alternative sliding-mode control technique. The dc-dc power converters are very used in industrial applications, for instance, in power systems of hybrid electric vehicles and aircrafts. Good results were obtained and the proposed design is also inexpensive because it uses electric components that can be easily found for the hardware implementation. Future researches on the subject include the hardware validation of the dc-dc converter controller and the robust control design of switched systems, with structural failures. © 2011 IEEE.

Networked control system for the guidance of a four-wheel steering agricultural robotic platform

A current trend in the agricultural area is the development of mobile robots and autonomous vehicles for precision agriculture (PA). One of the major challenges in the design of these robots is the development of the electronic architecture for the control of the devices. In a joint project among research institutions and a private company in Brazil a multifunctional robotic platform for information acquisition in PA is being designed. This platform has as main characteristics four-wheel propulsion and independent steering, adjustable width, span of 1,80m in height, diesel engine, hydraulic system, and a CAN-based networked control system (NCS). This paper presents a NCS solution for the platform guidance by the four-wheel hydraulic steering distributed control. The control strategy, centered on the robot manipulators control theory, is based on the difference between the desired and actual position and considering the angular speed of the wheels. The results demonstrate that the NCS was simple and efficient, providing suitable steering performance for the platform guidance. Even though the simplicity of the NCS solution developed, it also overcame some verified control challenges in the robot guidance system design such as the hydraulic system delay, nonlinearities in the steering actuators, and inertia in the steering system due the friction of different terrains. Copyright © 2012 Eduardo Pacincia Godoy et al.

On switched control design of linear time-invariant systems with polytopic uncertainties

This paper proposes a new switched control design method for some classes of linear time-invariant systems with polytopic uncertainties. This method uses a quadratic Lyapunov function to design the feedback controller gains based on linear matrix inequalities (LMIs). The controller gain is chosen by a switching law that returns the smallest value of the time derivative of the Lyapunov function. The proposed methodology offers less conservative alternative than the well-known controller for uncertain systems with only one state feedback gain. The control design of a magnetic levitator illustrates the procedure. © 2013 Wallysonn A. de Souza et al.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

SINGULARLY PERTURBED DISCOUNTED MARKOV CONTROL PROCESSES IN A GENERAL STATE SPACE

This paper studies the asymptotic optimality of discrete-time Markov decision processes (MDPs) with general state space and action space and having weak and strong interactions. By using a similar approach as developed by Liu, Zhang, and Yin [Appl. Math. Optim., 44 (2001), pp. 105-129], the idea in this paper is to consider an MDP with general state and action spaces and to reduce the dimension of the state space by considering an averaged model. This formulation is often described by introducing a small parameter epsilon > 0 in the definition of the transition kernel, leading to a singularly perturbed Markov model with two time scales. Our objective is twofold. First it is shown that the value function of the control problem for the perturbed system converges to the value function of a limit averaged control problem as epsilon goes to zero. In the second part of the paper, it is proved that a feedback control policy for the original control problem defined by using an optimal feedback policy for the limit problem is asymptotically optimal. Our work extends existing results of the literature in the following two directions: the underlying MDP is defined on general state and action spaces and we do not impose strong conditions on the recurrence structure of the MDP such as Doeblin's condition.

Optimal mean-variance control for discrete-time linear systems with Markovian jumps and multiplicative noises

In this paper, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises under two criteria. The first one is an unconstrained mean-variance trade-off performance criterion along the time, and the second one is a minimum variance criterion along the time with constraints on the expected output. We present explicit conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. We conclude the paper by presenting a numerical example of a multi-period portfolio selection problem with regime switching in which it is desired to minimize the sum of the variances of the portfolio along the time under the restriction of keeping the expected value of the portfolio greater than some minimum values specified by the investor. (C) 2011 Elsevier Ltd. All rights reserved.

The port-Hamiltonian framework as a comprehensive approach to model and simulate complex systems

This thesis describes modelling tools and methods suited for complex systems (systems that typically are represented by a plurality of models). The basic idea is that all models representing the system should be linked by well-defined model operations in order to build a structured repository of information, a hierarchy of models. The port-Hamiltonian framework is a good candidate to solve this kind of problems as it supports the most important model operations natively. The thesis in particular addresses the problem of integrating distributed parameter systems in a model hierarchy, and shows two possible mechanisms to do that: a finite-element discretization in port-Hamiltonian form, and a structure-preserving model order reduction for discretized models obtainable from commercial finite-element packages.

MODELING AND PROTOCOL DESIGN FOR EMERGING WIRELESS SYSTEMS

Mobile Mesh Network based In-Transit Visibility (MMN-ITV) system facilitates global real-time tracking capability for the logistics system. In-transit containers form a multi-hop mesh network to forward the tracking information to the nearby sinks, which further deliver the information to the remote control center via satellite. The fundamental challenge to the MMN-ITV system is the energy constraint of the battery-operated containers. Coupled with the unique mobility pattern, cross-MMN behavior, and the large-spanned area, it is necessary to investigate the energy-efficient communication of the MMN-ITV system thoroughly. First of all, this dissertation models the energy-efficient routing under the unique pattern of the cross-MMN behavior. A new modeling approach, pseudo-dynamic modeling approach, is proposed to measure the energy-efficiency of the routing methods in the presence of the cross-MMN behavior. With this approach, it could be identified that the shortest-path routing and the load-balanced routing is energy-efficient in mobile networks and static networks respectively. For the MMN-ITV system with both mobile and static MMNs, an energy-efficient routing method, energy-threshold routing, is proposed to achieve the best tradeoff between them. Secondly, due to the cross-MMN behavior, neighbor discovery is executed frequently to help the new containers join the MMN, hence, consumes similar amount of energy as that of the data communication. By exploiting the unique pattern of the cross-MMN behavior, this dissertation proposes energy-efficient neighbor discovery wakeup schedules to save up to 60% of the energy for neighbor discovery. Vehicular Ad Hoc Networks (VANETs)-based inter-vehicle communications is by now growingly believed to enhance traffic safety and transportation management with low cost. The end-to-end delay is critical for the time-sensitive safety applications in VANETs, and can be a decisive performance metric for VANETs. This dissertation presents a complete analytical model to evaluate the end-to-end delay against the transmission range and the packet arrival rate. This model illustrates a significant end-to-end delay increase from non-saturated networks to saturated networks. It hence suggests that the distributed power control and admission control protocols for VANETs should aim at improving the real-time capacity (the maximum packet generation rate without causing saturation), instead of the delay itself. Based on the above model, it could be determined that adopting uniform transmission range for every vehicle may hinder the delay performance improvement, since it does not allow the coexistence of the short path length and the low interference. Clusters are proposed to configure non-uniform transmission range for the vehicles. Analysis and simulation confirm that such configuration can enhance the real-time capacity. In addition, it provides an improved trade off between the end-to-end delay and the network capacity. A distributed clustering protocol with minimum message overhead is proposed, which achieves low convergence time.

DC MICROGRID STABILIZATION THROUGH FUZZY CONTROL OF INTERLEAVED, HETEROGENEOUS STORAGE ELEMENTS

As microgrid power systems gain prevalence and renewable energy comprises greater and greater portions of distributed generation, energy storage becomes important to offset the higher variance of renewable energy sources and maximize their usefulness. One of the emerging techniques is to utilize a combination of lead-acid batteries and ultracapacitors to provide both short and long-term stabilization to microgrid systems. The different energy and power characteristics of batteries and ultracapacitors imply that they ought to be utilized in different ways. Traditional linear controls can use these energy storage systems to stabilize a power grid, but cannot effect more complex interactions. This research explores a fuzzy logic approach to microgrid stabilization. The ability of a fuzzy logic controller to regulate a dc bus in the presence of source and load fluctuations, in a manner comparable to traditional linear control systems, is explored and demonstrated. Furthermore, the expanded capabilities (such as storage balancing, self-protection, and battery optimization) of a fuzzy logic system over a traditional linear control system are shown. System simulation results are presented and validated through hardware-based experiments. These experiments confirm the capabilities of the fuzzy logic control system to regulate bus voltage, balance storage elements, optimize battery usage, and effect self-protection.