Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

The integration of distributed generation (DG) units in power distribution networks has become increasingly important in recent years. The aim of the optimal DG placement (ODGP) is to provide the best locations and sizes of DGs to optimize electrical distribution network operation and planning taking into account DG capacity constraints. Several models and methods have been suggested for the solution of the ODGP problem. This paper presents an overview of the state of the art models and methods applied to the ODGP problem, analyzing and classifying current and future research trends in this field.

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Optimal Distributed Generation Placement in Power Distribution Networks: Models, Methods, and Future Research

This paper investigates the problem of multiple distributed generator (DG units) placement to achieve a high loss reduction in large-scale primary distribution networks. An improved analytical (IA) method is proposed in this paper. This method is based on IA expressions to calculate the optimal size of four different DG types and a methodology to identify the best location for DG allocation. A technique to get the optimal power factor is presented for DG capable of delivering real and reactive power. Moreover, loss sensitivity factor (LSF) and exhaustive load flow (ELF) methods are also introduced. IA method was tested and validated on three distribution test systems with varying sizes and complexity. Results show that IA method is effective as compared with LSF and ELF solutions. Some interesting results are also discussed in this paper.

Multiple Distributed Generator Placement in Primary Distribution Networks for Loss Reduction

This paper presents a multiobjective performance index-based size and location determination of distributed generation in distribution systems with different load models. Normally, a constant power (real and reactive) load model is assumed in most of the studies made in the literature. It is shown that load models can significantly affect the optimal location and sizing of distributed generation (DG) resources in distribution systems. The simulation technique based on genetic algorithms is studied. The studies have been carried out on 16-bus and 37-bus distribution systems.

Multiobjective Optimization for DG Planning With Load Models

The problem of minimizing losses in distribution networks has traditionally been investigated using a single, deterministic demand level. This has proved to be effective since most approaches are generally able to also result in minimum overall energy losses. However, the increasing penetration of (firm and variable) distributed generation (DG) raises concerns on the actual benefits of loss minimization studies that are limited to a single demand/generation scenario. Here, a multiperiod AC optimal power flow (OPF) is used to determine the optimal accommodation of (renewable) DG in a way that minimizes the system energy losses. In addition, control schemes expected to be part of the future Smart Grid, such as coordinated voltage control and dispatchable DG power factor, are embedded in the OPF formulation to explore the extra loss reduction benefits that can be harnessed with such technologies. The trade-off between energy losses and more generation capacity is also investigated. The methodology is applied to a generic U.K. distribution network and results demonstrate the significant impact that considering time-varying characteristics has on the energy loss minimization problem and highlight the gains that the flexibility provided by innovative control strategies can have on both loss minimization and generation capacity.

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Minimizing Energy Losses: Optimal Accommodation and Smart Operation of Renewable Distributed Generation

This paper presents a critical review on different application of Phasor Measurement Units (PMUs) in electric power system
networks incorporated with FACTS controllers for advanced power system monitoring, protection, and control. Also this paper
presents the current status of the research and developments in the field of the applications of PMUs in electric power system
networks incorporated with FACTS controllers. Authors strongly believe that this survey article will be very much useful to the
researchers for finding out the relevant references in the field of the applications of PMUs in electric power system networks
incorporated with FACTS controllers.

/pdf/applications-of-phasor-measurement-units-pmus-in-electric-o612nuurst.pdf

Applications of phasor measurement units (PMUs) in electric power system networks incorporated with FACTS controllers

Location of unified power flow controller for congestion management

Power quality (PQ) issue has attained considerable attention in the last decade due to large penetration of power electronics based loads and/or microprocessor based controlled loads. On one hand these devices introduce power quality problem and on other hand these mal-operate due to the induced power quality problems. PQ disturbances/events cover a broad frequency range
with significantly different magnitude variations and can be non-stationary, thus, accurate techniques are required to identify and classify these events/disturbances. This paper presents a comprehensive overview of different techniques used for PQ events’ classifications. Various artificial intelligent techniques which are used in PQ event classification are also discussed. Major Key issues and challenges in classifying PQ events are critically examined and outlined.

 Keywords: Power quality, PQ event classifiers, artificial intelligence techniques, PQ noise, PQ key issues.

/pdf/power-quality-event-classification-an-overview-and-key-2kpkn8zts5.pdf

Power quality event classification: an overview and key issues

In deregulated power systems, total transfer capability (TTC) analysis is presently a critical issue either in operating or planning because of increased area interchanges among utilities. FACTS devices can be an alternative to reduce the flows in heavily loaded lines, resulting in an increased transfer capability, low system loss, improved stability of the network, reduced cost of production and fulfilled contractual requirement by controlling the power flows in the network. It is important to ascertain the location for placement of these devices because of their considerable costs. A method to determine the suitable locations of thyristor controlled series compensators (TCSC) and thyristor controlled phase angle regulators (TCPAR) based on the real power flow performance index sensitivity has been suggested, in the paper, for enhancing the total transfer capability of the interconnected power system. A conceptually reasonable and computationally feasible approach has been developed and is illustrated by an example.

K.S. Verma

Papers

Multiobjective Optimization for DG Planning With Load Models

Applications of phasor measurement units (PMUs) in electric power system networks incorporated with FACTS controllers

Location of unified power flow controller for congestion management

Power quality event classification: an overview and key issues

FACTS devices location for enhancement of total transfer capability