Hybrid and Intelligent Energy Storage Systems in Standalone Photovoltaic Applications.

Remote systems such as communication relays or irrigation control installations cannot usually be powered by the electrical grid. One of the alternatives is to power these systems through solar panels, in what is known as standalone photovoltaic applications.Most of these systems need a continuous operation, but a standalone photovoltaic installation cannot be powered during the night. For this reason, they use batteries to store excess energy during the day. These storage systems have been traditionally based on Valve Regulated Lead Acid (VRLA) batteries, but some effects can alter their performance in terms of reliability, operation cost and maintenance. One of the key issues that alter the energy behavior of the photovoltaic off-grid systems is the Partial State of Charge (PSoC) effect: Batteries cannot be completely charged as manufacturers indicate due to the day-night cycle. This gets the battery into an intermediate state of charge that effectively reduces its capacity, even halving it in some cases. To mitigate the impact of these effects on the installation, batteries tend to be oversized with some security margins. These oversizing factors can be incredibly high and have a huge impact on the deployment and maintenance cost of the facility.The first part of this thesis highlights some of these key concepts, analyzing which of them are critical in specific design cases, modeling them into a simulation tool, and as an outcome, establishing optimal sizing regions for the installations. After the analysis, different ways of improving the performance of the installations are proposed. One idea to mitigate PSoC is to combine different storage technologies in a Hybrid Energy Storage Systems (HESS). HESSs have traditionally combined high energy density elements as batteries with high power density elements as ultracapacitors. An iteration of this idea is carried out throughout this thesis, where different types of batteries are combined. Each of them is best fitted to different power patterns in the application, such as daily cycles or emergency periods. It is possible to further increase the performance by using intelligent algorithms to improve the functionalities of the Battery Management Systems embedded in these applications. To this end, failure prediction and health estimation algorithms are proposed as contributions of this work. These new algorithms endow the HESS with tools to predict possible energy disruption events and to anticipate aging, and thus, act accordingly.<br /

Intelligent Storage Location Allocation with Multiple Objectives for Flood Control Materials

Intelligent storage is an important element of intelligent logistics and a key development trend in modern warehousing and logistics. Based on the characteristics of flood control materials and their intelligent storage, this study established a flood control material storage location allocation model reflecting the multiple objectives of retrieval efficiency and shelf stability and used a weighting method to transform a multi-objective optimization problem into a single-objective optimization problem. We then used the facilities and equipment planning and storage location allocation in the intelligent storage area for provincial flood control materials at the Zhenjiang warehouse of the Jiangsu water conservancy and flood control material reserve center as a case study. Empirical analysis was performed and used the genetic algorithm and Matrix Laboratory (MATLAB) software to optimize the storage location allocation of provincial flood prevention supplies at this warehouse, and it achieved effective results

Intelligent sampling for the measurement of structured surfaces

Uniform sampling in metrology has known drawbacks such as coherent spectral aliasing and a lack of efficiency in terms of measuring time and data storage. The requirement for intelligent sampling strategies has been outlined over recent years, particularly where the measurement of structured surfaces is concerned. Most of the present research on intelligent sampling has focused on dimensional metrology using coordinate-measuring machines with little reported on the area of surface metrology. In the research reported here, potential intelligent sampling strategies for surface topography measurement of structured surfaces are investigated by using numerical simulation and experimental verification. The methods include the jittered uniform method, low-discrepancy pattern sampling and several adaptive methods which originate from computer graphics, coordinate metrology and previous research by the authors. By combining the use of advanced reconstruction methods and feature-based characterization techniques, the measurement performance of the sampling methods is studied using case studies. The advantages, stability and feasibility of these techniques for practical measurements are discussed

An Intelligent Fuse-box for use with Renewable Energy Sources integrated within a Domestic Environment

This paper outlines a proposal for an intelligent fuse-box that can replace existing fuse-boxes in a domestic context such that a number of renewable energy sources can easily be integrated into the domestic power supply network, without the necessity for complex islanding and network protection. The approach allows intelligent control of both the generation of power and its supply to single or groups of electrical appliances. Energy storage can be implemented in such a scheme to even out the power supplied and simplify the control scheme required, and environmental monitoring and load analysis can help in automatically controlling the supply and demand profiles for optimum electrical and economic efficiency. Simulations of typical scenarios are carried out to illustrate the concept in operation

A review: intelligent controllers for tropical food storage system

Food security can be assured by improving on post harvest storage methods. Food stored under improper storage conditions are prone to increased respiration and transpiration processes which often result in depletion and weight loss of edible material. Storage temperature and relative humidity are major factors that ultimately determine product quality and quantity. This paper presents a survey on methods of post harvest storage systems. The indigenous methods of tropical food storage common to the West African region are discussed. The attendant problems associated with these methods are highlighted. Intelligent control methods are also discussed. A novel intelligent controller is proposed to sustain product quality and quantity by optimizing the storage process