Novel heuristic and SVM based optimization algorithm for improving distribution feeder performance

Abstract: Secondary distribution networks generally perform as well as its LV feeders are performing. The main problem that a feeder is experiencing would be the load unbalancing due to the stochastic nature of its individual single-phase loads: larger losses in certain phases accompanied by bad voltage regulation and voltage unbalance. In order to address this problem, it may be economical to install apparatus to automatically balance or partially balance the loads progressing from the end of the feeder towards the front using smart devices based on a three-ways switch selector and an artificial intelligence algorithm to minimize the neutral current. The main idea behind this paper is therefore to keep the three phases progressively balanced along the whole length of the line. A Support Vector Machines (SVM) implementation and a heuristic method are presented as the numerical algorithm

A Multi-Objective Optimization Approach for Multi-Head Beam-Type Placement Machines

This paper addresses a highly challenging scheduling problem in the field of printed circuit board (PCB) assembly systems using Surface Mounting Devices (SMD). After describing some challenging optimization sub-problems relating to the heads of multi-head surface mounting placement machines, we formulate an integrated multi-objective mathematical model considering of two main sub-problems simultaneously. The proposed model is a mixed integer nonlinear programming one which is very complex to be solved optimally. Therefore, it is first converted into a linearized model and then solved using an efficient multi-objective approach, i.e., the augmented epsilon constraint method. An illustrative example is also provided to show the usefulness and applicability of the proposed model and solution method.PCB assembly. Multi-head beam-type placement machine. Multi-objective mathematical programming. Augmented epsilon-constraint method

Comprehensive STATCOM Control For Distribution And Transmission System Applications

This thesis presents the development of a comprehensive STATCOM controller for load compensation, voltage regulation and voltage balancing in electric power distribution and transmission networks. The behavior of this controller is first validated with published results. Subsequently, the performance of this STATCOM controller is examined in a realistic Hydro One distribution feeder for accomplishing the compensation of both mildly and grossly unbalanced loads, and balancing of network voltages using PSCAD/EMTDC software. The STATCOM voltage control function is utilized for increasing the connectivity of wind plants in the same distribution feeder. The thesis further presents a frequency scanning technique for simple and rapid identification of the potential of subsynchronous resonance in induction generator based wind farms connected to series compensated lines, utilizing MATLAB software. This technique is validated by published eigenvalue analysis results. The voltage control performance of the developed comprehensive STATCOM controller is then demonstrated for different scenarios in the modified IEEE First SSR Benchmark transmission system for mitigating subsynchronous resonance in series compensated wind farms using industry grade PSCAD/EMTDC software

Achieving the Dispatchability of Distribution Feeders through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage

We propose and experimentally validate a control strategy to dispatch the operation of a distribution feeder interfacing heterogeneous prosumers by using a grid-connected battery energy storage system (BESS) as a controllable element coupled with a minimally invasive monitoring infrastructure. It consists in a two-stage procedure: day-ahead dispatch planning, where the feeder 5-minute average power consumption trajectory for the next day of operation (called \emph{dispatch plan}) is determined, and intra-day/real-time operation, where the mismatch with respect to the \emph{dispatch plan} is corrected by applying receding horizon model predictive control (MPC) to decide the BESS charging/discharging profile while accounting for operational constraints. The consumption forecast necessary to compute the \emph{dispatch plan} and the battery model for the MPC algorithm are built by applying adaptive data driven methodologies. The discussed control framework currently operates on a daily basis to dispatch the operation of a 20~kV feeder of the EPFL university campus using a 750~kW/500~kWh lithium titanate BESS.Comment: Submitted for publication, 201

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

Load Impact Analysis Towards Power Loss in Distribution Substation in Wlingi District

This research aimed to find: (1) the distribution substations configuration in Kesamben Feeder, Wlingi District, (2) how much was the loading in those distribution substations, (3) how much load imbalance in the distribution substation’s load, and (4) how much was the power loss towards the imbalance load. This research used descriptive analysis by analyzing the loading imbalance towards the power loss of distribution substation in one feeder. The results showed that the higher percentage of loading imbalance meant higher power loss. However, although an imbalance percentage was more significant than a smaller percentage, the power loss that occurred might be more substantial due to the probable higher loading percentage so that the power loss in the substation was also influenced by the loading value, apart from the load imbalance

Robust Look-ahead Three-phase Balancing of Uncertain Distribution Loads

Increasing penetration of highly variable components such as solar generation and electric vehicle charging loads pose significant challenges to keeping three-phase loads balanced in modern distribution systems. Failure to maintain balance across three phases would lead to asset deterioration and increasing delivery losses. Motivated by the real-world needs to automate and optimize the three-phase balancing decision making, this paper introduces a robust look-ahead optimization framework that pursues balanced phases in the presence of demand-side uncertainties. We show that look-ahead moving window optimization can reduce imbalances among phases at the cost of a limited number of phase swapping operations. Case studies quantify the improvements of the proposed methods compared with conventional deterministic phase balancing. Discussions on possible benefits of the proposed methods and extensions are presented

Non-Gaussian residual based short term load forecast adjustment for distribution feeders

The evolving role for electricity network operators means that load forecasting at the distribution level has become increasingly important, presenting the need for anticipation of the behavior of highly dynamic and diversely distributed loads. The commonly held assumption of Gaussian residuals in forecasting does not always hold for distribution network loads, increasing the uncertainty in balancing a system at this network level. To reduce the operational impact of forecast errors, this paper utilizes different multivariate joint probability distributions to capture the intra-day dependency structure of forecast residuals. Transforming these to the conditional form enables forecast corrections to be made at variable horizons even in the absence of the forecast model. Improvements in accuracy are demonstrated on benchmark load forecast models at distribution level low voltage substations. A practical distribution system application on scheduling embedded energy storage shows substantial reductions in grid imports and hence costs to distribution level customers from utilizing the proposed intraday correction approach