Control in distribution networks with demand side management

The way in which electricity networks operate is going through a period of significant change. Renewable generation technologies are having a growing presence and increasing penetrations of generation that are being connected at distribution level. Unfortunately, a renewable energy source is most of the time intermittent and needs to be forecasted. Current trends in Smart grids foresee the accommodation of a variety of distributed generation sources including intermittent renewable sources. It is also expected that smart grids will include demand management resources, widespread communications and control technologies required to use demand response are needed to help the maintenance in supply-demand balance in electricity systems. Consequently, smart household appliances with controllable loads will be likely a common presence in our homes. Thus, new control techniques are requested to manage the loads and achieve all the potential energy present in intermittent energy sources. This thesis is focused on the development of a demand side management control method in a distributed network, aiming the creation of greater flexibility in demand and better ease the integration of renewable technologies. In particular, this work presents a novel multi-agent model-based predictive control method to manage distributed energy systems from the demand side, in presence of limited energy sources with fluctuating output and with energy storage in house-hold or car batteries. Specifically, here is presented a solution for thermal comfort which manages a limited shared energy resource via a demand side management perspective, using an integrated approach which also involves a power price auction and an appliance loads allocation scheme. The control is applied individually to a set of Thermal Control Areas, demand units, where the objective is to minimize the energy usage and not exceed the limited and shared energy resource, while simultaneously indoor temperatures are maintained within a comfort frame. Thermal Control Areas are overall thermodynamically connected in the distributed environment and also coupled by energy related constraints. The energy split is performed based on a fixed sequential order established from a previous completed auction wherein the bids are made by each Thermal Control Area, acting as demand side management agents, based on the daily energy price. The developed solutions are explained with algorithms and are applied to different scenarios, being the results explanatory of the benefits of the proposed approaches.

Assessment of a novel Cu (II) complex as a potential anticancer agent

Widely used in cancer treatment, chemotherapy still faces hindering challenges, ranging from severe induced toxicity to drug resistance acquisition. As means to overcome these setbacks, newly synthetized compounds have recently come into play with the basis of improved pharmacokinetic/pharmacodynamic properties. With this mind-set, this project aimed towards the antiproliferative potential characterization of a group of metallic compounds. Additionally the incorporation of the compounds within a nanoformulation and within new combination strategies with commercial chemotherapeutic drugs was also envisaged. Cell viability assays presented copper (II) compound (K4) as the most promising, presenting an IC50 of 6.10 μM and 19.09 μM for HCT116 and A549 cell line respectively. Exposure in fibroblasts revealed a 9.18 μM IC50. Hoechst staining assays further revealed the compound’s predisposition to induce chromatin condensation and nuclear fragmentation in HCT116 upon exposure to K4 which was later demonstrated by flow cytometry and annexin V-FITC/propidium iodide double staining analysis (under 50 % cell death induction). The compound further revealed the ability to interact with major macromolecules such as DNA (Kb = 2.17x105 M-1), inducing structural brakes and retardation, and further affecting cell cycle progression revealing delay in S-phase. Moreover BSA interactions were also visible however not conclusive. Proteome profiling revealed overexpression of proteins involved in metabolic activity and underexpression of proteins involved in apoptosis thus corroborating Hoechst and apoptosis flow cytometry data. K4 nanoformulation suffered from several hindrances and was ill succeeded in part due to K4’s poor solubility in aqueous buffers. Other approaches were considered in this regard. Combined chemotherapy assays revealed high cytotoxicity for afatinib and lapatinib strategies. Lapatinib and K4 proteome profiling further revealed high apoptosis rates, high metabolic activity and activation of redundant proteins as part of compensatory mechanisms.

Development of human central nervous system 3D in vitro models for preclinical research

Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.

Investigation of Novel Circuits Involved in Virgin Female Receptivity of Drosophila melanogaster

Courtship is a behavior that allows the display of fitness of one sex to the other and gates possible subsequent mating. This behavior is crucial for reproduction and has strong innate components in all animals. Courtship in Drosophila melanogaster consists of a series of highly stereotyped actions that the male performs towards the female. He sings with vibrations of the wings, touches and licks her abdomen, while she evaluates the information presented to her.(...)