Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Assessment and optimization of wind energy integration into the power systems: application to the portuguese system

The increasing integration of wind energy in power systems can be responsible for the occurrence of over-generation, especially during the off-peak periods. This paper presents a dedicated methodology to identify and quantify the occurrence of this over-generation and to evaluate some of the solutions that can be adopted to mitigate this problem. The methodology is applied to the Portuguese power system, in which the wind energy is expected to represent more than 25% of the installed capacity in a near future. The results show that the pumped-hydro units will not provide enough energy storage capacity and, therefore, wind curtailments are expected to occur in the Portuguese system. Additional energy storage devices can be implemented to offset the wind energy curtailments. However, the investment analysis performed show that they are not economically viable, due to the present high capital costs involved.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Optimization of the valence energy variance of the CuH molecule

We developed the concept of split-'t to deal with the large molecules (in terms of the number of electrons and nuclear charge Z). This naturally leads to partitioning the local energy into components due to each electron shell. The minimization of the variation of the valence shell local energy is used to optimize a simple two parameter CuH wave function. Molecular properties (spectroscopic constants and the dipole moment) are calculated for the optimized and nearly optimized wave functions using the Variational Quantum Monte Carlo method. Our best results are comparable to those from the single and double configuration interaction (SDCI) method.

Energy Management in Wireless Sensor Networks: A Crosslayer,Channel Adaptive Approach Towards Performance Optimization

The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.

Energy balance optimization of sugarcane crop residual biomass

This work presents a mathematical model for helping mills choose sugarcane varieties for planting. It maximizes crop residual biomass energy balance by considering the difference between generated and consumed energy in the process of transferring this biomass from the field to the processing center; it takes into account enterprise demand restrictions and cane planting area. For this full zero-one linear programming techniques were proposed. The model is viable for choosing sugarcane varieties that would benefit sugarcane production and industrial systems, by reducing crop residue and increasing final energy production. (c) 2006 Published by Elsevier Ltd.

Use of high energy ball milling on the sintering optimization of alumina ceramics

In this work, the effect of the milling time on the densification of the alumina ceramics with or without 5wt.%Y 2O 3, is evaluated, using high-energy ball milling. The milling was performed with different times of 0, 2, 5 or 10 hours. All powders, milled at different times, were characterized by X-Ray Diffraction presenting a reduction of the crystalline degree and crystallite size as function of the milling time increasing. The powders were compacted by cold uniaxial pressing and sintered at 1550°C-60min. Green density of the compacts presented an increasing as function of the milling time and sintered samples presented evolution on the densification as function of the reduction of the crystallite size of the milled powders. © (2010) Trans Tech Publications.

Volt-VAR multiobjective optimization to peak-load relief and energy efficiency in distribution networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of pattern gradation on the design of piezocomposite energy harvesting devices using topology optimization

Piezoelectric materials can be used to convert oscillatory mechanical energy into electrical energy. Energy harvesting devices are designed to capture the ambient energy surrounding the electronics and convert it into usable electrical energy. The design of energy harvesting devices is not obvious, requiring optimization procedures. This paper investigates the influence of pattern gradation using topology optimization on the design of piezocomposite energy harvesting devices based on bending behavior. The objective function consists of maximizing the electric power generated in a load resistor. A projection scheme is employed to compute the element densities from design variables and control the length scale of the material density. Examples of two-dimensional piezocomposite energy harvesting devices are presented and discussed using the proposed method. The numerical results illustrate that pattern gradation constraints help to increase the electric power generated in a load resistor and guides the problem toward a more stable solution. (C) 2012 Elsevier Ltd. All rights reserved.

Design methodology of piezoelectric energy-harvesting skin using topology optimization

Abstract This paper describes a design methodology for piezoelectric energy harvester s that thinly encapsulate the mechanical devices and expl oit resonances from higher- order vibrational modes. The direction of polarization determines the sign of the pi ezoelectric tensor to avoid cancellations of electric fields from opposite polarizations in the same circuit. The resultant modified equations of state are solved by finite element method (FEM). Com- bining this method with the solid isotropic material with penalization (SIMP) method for piezoelectric material, we have developed an optimization methodology that optimizes the piezoelectric material layout and polarization direc- tion. Updating the density function of the SIMP method is performed based on sensitivity analysis, the sequen- tial linear programming on the early stage of the opti- mization, and the phase field method on the latter stage

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Application and optimization of a thermal energy storage on a cruise ship

The thesis, developed in collaboration between the team Systems and Equipment for Energy and Environment of Bologna University and Chalmers University of Technology in Goteborg, aims to study the benefits resulting from the adoption of a thermal storage system for marine application. To that purpose a chruis ship has been considered. To reach the purpose has been used the software EGO (Energy Greed Optimization) developed by University of Bologna.

Optimización de la composición del hueco de fachada en materia de eficiencia energética. Propuesta de indicador como herramienta para el análisis integral del elemento acristalado = Energy performance optimization of window systems. Proposal of an indicator as a tool for an integrated analysis of glazing

La hipótesis de esta tesis es: "La optimización de la ventana considerando simultáneamente aspectos energéticos y aspectos relativos a la calidad ambiental interior (confort higrotérmico, lumínico y acústico) es compatible, siempre que se conozcan y consideren las sinergias existentes entre ellos desde las primeras fases de diseño". En la actualidad se desconocen las implicaciones de muchas de las decisiones tomadas en torno a la ventana; para que su eficiencia en relación a todos los aspectos mencionados pueda hacerse efectiva es necesaria una herramienta que aporte más información de la actualmente disponible en el proceso de diseño, permitiendo así la optimización integral, en función de las circunstancias específicas de cada proyecto. En la fase inicial de esta investigación se realiza un primer acercamiento al tema, a través del estado del arte de la ventana; analizando la normativa existente, los componentes, las prestaciones, los elementos experimentales y la investigación. Se observa que, en ocasiones, altos requisitos de eficiencia energética pueden suponer una disminución de las prestaciones del sistema en relación con la calidad ambiental interior, por lo que surge el interés por integrar al análisis energético aspectos relativos a la calidad ambiental interior, como son las prestaciones lumínicas y acústicas y la renovación de aire. En este punto se detecta la necesidad de realizar un estudio integral que incorpore los distintos aspectos y evaluar las sinergias que se dan entre las distintas prestaciones que cumple la ventana. Además, del análisis de las soluciones innovadoras y experimentales se observa la dificultad de determinar en qué medida dichas soluciones son eficientes, ya que son soluciones complejas, no caracterizadas y que no están incorporadas en las metodologías de cálculo o en las bases de datos de los programas de simulación. Por lo tanto, se plantea una segunda necesidad, generar una metodología experimental para llevar a cabo la caracterización y el análisis de la eficiencia de sistemas innovadores. Para abordar esta doble necesidad se plantea la optimización mediante una evaluación del elemento acristalado que integre la eficiencia energética y la calidad ambiental interior, combinando la investigación teórica y la investigación experimental. En el ámbito teórico, se realizan simulaciones, cálculos y recopilación de información de distintas tipologías de hueco, en relación con cada prestación de forma independiente (acústica, iluminación, ventilación). A pesar de haber partido con un enfoque integrador, resulta difícil esa integración detectándose una carencia de herramientas disponible. En el ámbito experimental se desarrolla una metodología para la evaluación del rendimiento y de aspectos ambientales de aplicación a elementos innovadores de difícil valoración mediante la metodología teórica. Esta evaluación consiste en el análisis comparativo experimental entre el elemento innovador y un elemento estándar; para llevar a cabo este análisis se han diseñado dos espacios iguales, que denominamos módulos de experimentación, en los que se han incorporado los dos sistemas; estos espacios se han monitorizado, obteniéndose datos de consumo, temperatura, iluminancia y humedad relativa. Se ha realizado una medición durante un periodo de nueve meses y se han analizado y comparado los resultados, obteniendo así el comportamiento real del sistema. Tras el análisis teórico y el experimental, y como consecuencia de esa necesidad de integrar el conocimiento existente se propone una herramienta de evaluación integral del elemento acristalado. El desarrollo de esta herramienta se realiza en base al procedimiento de diagnóstico de calidad ambiental interior (CAI) de acuerdo con la norma UNE 171330 “Calidad ambiental en interiores”, incorporando el factor de eficiencia energética. De la primera parte del proceso, la parte teórica y el estado del arte, se obtendrán los parámetros que son determinantes y los valores de referencia de dichos parámetros. En base a los parámetros relevantes obtenidos se da forma a la herramienta, que consiste en un indicador de producto para ventanas que integra todos los factores analizados y que se desarrolla según la Norma UNE 21929 “Sostenibilidad en construcción de edificios. Indicadores de sostenibilidad”. ABSTRACT The hypothesis of this thesis is: "The optimization of windows considering energy and indoor environmental quality issues simultaneously (hydrothermal comfort, lighting comfort, and acoustic comfort) is compatible, provided that the synergies between these issues are known and considered from the early stages of design ". The implications of many of the decisions made on this item are currently unclear. So that savings can be made, an effective tool is needed to provide more information during the design process than the currently available, thus enabling optimization of the system according to the specific circumstances of each project. The initial phase deals with the study from an energy efficiency point of view, performing a qualitative and quantitative analysis of commercial, innovative and experimental windows. It is observed that sometimes, high-energy efficiency requirements may mean a reduction in the system's performance in relation to user comfort and health, that's why there is an interest in performing an integrated analysis of indoor environment aspects and energy efficiency. At this point a need for a comprehensive study incorporating the different aspects is detected, to evaluate the synergies that exist between the various benefits that meet the window. Moreover, from the analysis of experimental and innovative windows, a difficulty in establishing to what extent these solutions are efficient is observed; therefore, there is a need to generate a methodology for performing the analysis of the efficiency of the systems. Therefore, a second need arises, to generate an experimental methodology to perform characterization and analysis of the efficiency of innovative systems. To address this dual need, the optimization of windows by an integrated evaluation arises, considering energy efficiency and indoor environmental quality, combining theoretical and experimental research. In the theoretical field, simulations and calculations are performed; also information about the different aspects of indoor environment (acoustics, lighting, ventilation) is gathered independently. Despite having started with an integrative approach, this integration is difficult detecting lack available tools. In the experimental field, a methodology for evaluating energy efficiency and indoor environment quality is developed, to be implemented in innovative elements which are difficult to evaluate using a theoretical methodology This evaluation is an experimental comparative analysis between an innovative element and a standard element. To carry out this analysis, two equal spaces, called experimental cells, have been designed. These cells have been monitored, obtaining consumption, temperature, luminance and relative humidity data. Measurement has been performed during nine months and results have been analyzed and compared, obtaining results of actual system behavior. To advance this optimization, windows have been studied from the point of view of energy performance and performance in relation to user comfort and health: thermal comfort, acoustic comfort, lighting comfort and air quality; proposing the development of a methodology for an integrated analysis including energy efficiency and indoor environment quality. After theoretical and experimental analysis and as a result of the need to integrate existing knowledge, a comprehensive evaluation procedure for windows is proposed. This evaluation procedure is developed according to the UNE 171330 "Indoor Environmental Quality", also incorporating energy efficiency and cost as factors to evaluate. From the first part of the research process, outstanding parameters are chosen and reference values of these parameters are set. Finally, based on the parameters obtained, an indicator is proposed as windows product indicator. The indicator integrates all factors analyzed and is developed according to ISO 21929-1:2011"Sustainability in building construction. Sustainability indicators. Part 1: Framework for the development of indicators and a core set of indicators for buildings".