Probabilistic analysis of the distributed power generation in weakly meshed distribution systems

This paper presents an approach for probabilistic analysis of unbalanced three-phase weakly meshed distribution systems considering uncertainty in load demand. In order to achieve high computational efficiency this approach uses both an efficient method for probabilistic analysis and a radial power flow. The probabilistic approach used is the well-known Two-Point Estimate Method. Meanwhile, the compensation-based radial power flow is used in order to extract benefits from the topological characteristics of the distribution systems. The generation model proposed allows modeling either PQ or PV bus on the connection point between the network and the distributed generator. In addition allows control of the generator operating conditions, such as the field current and the power delivery at terminals. Results on test with IEEE 37 bus system is given to illustrate the operation and effectiveness of the proposed approach. A Monte Carlo Simulations method is used to validate the results. © 2011 IEEE.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 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.

Market-driven security-constrained transmission network expansion planning

This paper presents a Bi-level Programming (BP) approach to solve the Transmission Network Expansion Planning (TNEP) problem. The proposed model is envisaged under a market environment and considers security constraints. The upper-level of the BP problem corresponds to the transmission planner which procures the minimization of the total investment and load shedding cost. This upper-level problem is constrained by a single lower-level optimization problem which models a market clearing mechanism that includes security constraints. Results on the Garver's 6-bus and IEEE 24-bus RTS test systems are presented and discussed. Finally, some conclusions are drawn. © 2011 IEEE.

Optimal allocation of distributed generators providing reactive power support ancillary service

Problems as voltage increase at the end of a feeder, demand supply unbalance in a fault condition, power quality decline, increase of power losses, and reduction of reliability levels may occur if Distributed Generators (DGs) are not properly allocated. For this reason, researchers have been employed several solution techniques to solve the problem of optimal allocation of DGs. This work is focused on the ancillary service of reactive power support provided by DGs. The main objective is to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). The LOC will be determined for different allocation alternatives of DGs as a result of a multi-objective optimization process, aiming the minimization of losses in the lines of the system and costs of active power generation from DGs, and the maximization of the static voltage stability margin of the system. The effectiveness of the proposed methodology in improving the goals outlined was demonstrated using the IEEE 34 bus distribution test feeder with two DGs cosidered to be allocated. © 2011 IEEE.

An application of a modified constructive heuristic algorithm to transmission expansion planning

Transmission expansion planning (TEP) is a non-convex optimization problem that can be solved via different heuristic algorithms. A variety of classical as well as heuristic algorithms in literature are addressed to solve TEP problem. In this paper a modified constructive heuristic algorithm (CHA) is proposed for solving such a crucial problem. Most of research papers handle TEP problem by linearization of the non-linear mathematical model while in this research TEP problem is solved via CHA using non-linear model. The proposed methodology is based upon Garver's algorithm capable of applying to a DC model. Simulation studies and tests results on the well known transmission network such as: Garver and IEEE 24-bus systems are carried out to show the significant performance as well as the effectiveness of the proposed algorithm. © 2011 IEEE.

Pricing of reactive power support provided by distributed generators in transmission systems

Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

GRASP with evolutionary path-relinking for the capacitated arc routing problem

The Capacitated Arc Routing Problem (CARP) is a well-known NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours servicing a subset of required edges under vehicle capacity constraints. There are numerous applications for the CARP, such as street sweeping, garbage collection, mail delivery, school bus routing, and meter reading. A Greedy Randomized Adaptive Search Procedure (GRASP) with Path-Relinking (PR) is proposed and compared with other successful CARP metaheuristics. Some features of this GRASP with PR are (i) reactive parameter tuning, where the parameter value is stochastically selected biased in favor of those values which historically produced the best solutions in average; (ii) a statistical filter, which discard initial solutions if they are unlikely to improve the incumbent best solution; (iii) infeasible local search, where high-quality solutions, though infeasible, are used to explore the feasible/infeasible boundaries of the solution space; (iv) evolutionary PR, a recent trend where the pool of elite solutions is progressively improved by successive relinking of pairs of elite solutions. Computational tests were conducted using a set of 81 instances, and results reveal that the GRASP is very competitive, achieving the best overall deviation from lower bounds and the highest number of best solutions found. © 2011 Elsevier Ltd. All rights reserved.

AC-DC three-phase multipulse converter with boost DC-DC stage and constant hysteresis control

This work proposes a new three-phase multipulse rectifier based on the delta autotransformer connection with DC-DC Boost stages and constant hysteresis control which has the objective of providing a reliable DC bus for on-board applications, electric motor drives and similars, always considering power quality issues. Thus, the proposal presents 0.99 power factor, 6% harmonic distortions in the currents from the mains and enhanced magnetic core utilization, which results in low weight and volume for the overall converter. The proposed control technique uses the simple constant hysteresis concept, thus leading to a low-cost but effective and reliable strategy. © 2011 IEEE.

Fluxo de potência trifásico probabilístico para redes de distribuição usando o método de estimação por pontos

In this paper the point estimation method is applied to solve the probabilistic power flow problem for unbalanced three-phase distribution systems. Through the implementation of this method the probability distribution functions of voltages (magnitude and angle) as well as the active and reactive power flows in the branches of the distribution system are determined. Two different approaches of the point estimation method are presented (2m and 2m+1 point schemes). In order to test the proposed methodology, the IEEE 34 and 123 bus test systems are used. The results obtained with both schemes are compared with the ones obtained by a Monte Carlo Simulation (MCS).

Transmission network expansion planning considering phase-shifter transformers

This paper presents a novel mathematical model for the transmission network expansion planning problem. Main idea is to consider phase-shifter (PS) transformers as a new element of the transmission system expansion together with other traditional components such as transmission lines and conventional transformers. In this way, PS are added in order to redistribute active power flows in the system and, consequently, to diminish the total investment costs due to new transmission lines. Proposed mathematical model presents the structure of a mixed-integer nonlinear programming (MINLP) problem and is based on the standard DC model. In this paper, there is also applied a specialized genetic algorithm aimed at optimizing the allocation of candidate components in the network. Results obtained from computational simulations carried out with IEEE-24 bus system show an outstanding performance of the proposed methodology and model, indicating the technical viability of using these nonconventional devices during the planning process. Copyright © 2012 Celso T. Miasaki et al.

Parameterization technique for the continuation power flow using the trivial and tangent predictor

This paper presents efficient geometric parameterization techniques using the tangent and the trivial predictors for the continuation power flow, developed from observation of the trajectories of the load flow solution. The parameterization technique eliminates the Jacobian matrix singularity of load flow, and therefore all the consequent problems of ill-conditioning, by the addition of the line equations which pass through the points in the plane determined by the variables loading factor and the real power generated by the slack bus, two parameters with clear physical meaning. This paper also provides an automatic step size control around the maximum loading point. Thus, the resulting method enables not only the calculation of the maximum loading point, but also the complete tracing of P-V curves of electric power systems. The technique combines robustness with ease of understanding. The results to the IEEE 300-bus system and of large real systems show the effectiveness of the proposed method. © 2012 IEEE.

Optimal reactive power dispatch using stochastic chance-constrained programming

Deterministic Optimal Reactive Power Dispatch problem has been extensively studied, such that the demand power and the availability of shunt reactive power compensators are known and fixed. Give this background, a two-stage stochastic optimization model is first formulated under the presumption that the load demand can be modeled as specified random parameters. A second stochastic chance-constrained model is presented considering uncertainty on the demand and the equivalent availability of shunt reactive power compensators. Simulations on six-bus and 30-bus test systems are used to illustrate the validity and essential features of the proposed models. This simulations shows that the proposed models can prevent to the power system operator about of the deficit of reactive power in the power system and suggest that shunt reactive sourses must be dispatched against the unavailability of any reactive source. © 2012 IEEE.

Unveiling fieldbus network technology through project-based learning

Fieldbus communications networks are a fundamental part of modern industrial automation technique. This paperwork presents an application of project-based learning (PBL) paradigm to help electrical engineering students grasp the major concepts of fieldbus networks, while attending a one-term long, elective microcontroller course. © 2012 IEEE.