Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Anti-Corrosion performance of a new silane coating for corrosion protection of AZ31 Magnesium alloy in Hank’s solution

Mg alloys can be used as bioresorsable metallic implants. However, the high corrosion rate of magnesium alloys has limited their biomedical applications. Although Mg ions are essential to the human body, an excess may cause undesirable health effects. Therefore, surface treatments are required to enhance the corrosion resistance of magnesium parts, decreasing its rate to biocompatible levels and allowing its safe application as bioresorbable metallic implants. The application of biocompatible silane coatings is envisaged as a suitable strategy for retarding the corrosion process of magnesium alloys. In the current work, a new glycidoxypropyltrimethoxysilane (GPTMS) based coating was tested on AZ31 magnesium substrates subjected to different surface conditioning procedures before coating deposition. The surface conditioning included a short etching with hydrofluoric acid (HF) or a dc polarisation in alkaline electrolyte. The silane coated samples were immersed in Hank's solution and the protective performance of the coating was studied through electrochemical impedance spectroscopy (EIS). The EIS data was treated by new equivalent circuit models and the results revealed that the surface conditioning process plays a key role in the effectiveness of the silane coating. The HF treated samples led to the highest impedance values and delayed the coating degradation, compared to the mechanically polished samples or to those submitted to dc polarisation.

"In-vitro" corrosion behaviour of the magnesium alloy with Al and Zn (AZ31) protected with a biodegradable polycaprolactone coating loaded with hydroxyapatite and cephalexin

Mg alloys are very susceptible to corrosion in physiological media. This behaviour limits its widespread use in biomedical applications as bioresorbable implants, but it can be controlled by applying protective coatings. On one hand, coatings must delay and control the degradation process of the bare alloy and, on the other hand, they must be functional and biocompatible. In this study a biocompatible polycaprolactone (PCL) coating was functionalised with nano hydroxyapatite (HA) particles for enhanced biocompatibility and with an antibiotic, cephalexin, for anti-bacterial purposes and applied on the AZ31 alloy. The chemical composition and the surface morphology of the coated samples, before and after the corrosion tests, were studied by scanning electron microscopy (SEM) coupled with energy dispersive x-ray analysis (EDX) and Raman. The results showed that the presence of additives induced the formation of agglomerates and defects in the coating that resulted in the formation of pores during immersion in Hanks' solution. The corrosion resistance of the coated samples was studied in Hank's solution by electrochemical impedance spectroscopy (EIS). The results evidenced that all the coatings can provide corrosion protection of the bare alloy. However, in the presence of the additives, corrosion protection decreased. The wetting behaviour of the coating was evaluated by the static contact angle method and it was found that the presence of both hydroxyapatite and cephalexin increased the hydrophilic behaviour of the surface. The results showed that it is possible to tailor a composite coating that can store an antibiotic and nano hydroxyapatite particles, while allowing to control the in-vitro corrosion degradation of the bioresorbable Mg alloy AZ31. (C) 2015 Elsevier Ltd. All rights reserved.

Biofunctional composite coating architectures based on polycaprolactone and nanohydroxyapatite for controlled corrosion activity and enhanced biocompatibility of magnesium AZ31 alloy

In this work a biofunctional composite coating architecture for controlled corrosion activity and enhanced cellular adhesion of AZ31 Mg alloys is proposed. The composite coating consists of a polycaprolactone (PCL) matrix modified with nanohydroxyapatite (HA) applied over a nanometric layer of polyetherimide (PEI). The protective properties of the coating were studied by electrochemical impedance spectroscopy (EIS), a non-disturbing technique, and the coating morphology was investigated by field emission scanning electron microscopy (FE-SEM). The results show that the composite coating protects the AZ31 substrate. The barrier properties of the coating can be optimized by changing the PCL concentration. The presence of nanohydroxyapatite particles influences the coating morphology and decreases the corrosion resistance. The biocompatibility was assessed by studying the response of osteoblastic cells on coated samples through resazurin assay, confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). The results show that the polycaprolactone to hydroxyapatite ratio affects the cell behavior and that the presence of hydroxyapatite induces high osteoblastic differentiation. (C) 2014 Elsevier B.V. All rights reserved.