Data Mining Practical Machine Learning Tools and Techniques

2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

DC and AC Microgrids are key elements to integrate renewable and distributed energy resources as well as distributed energy storage systems. In the last years, efforts toward the standardization of these Microgrids have been made. In this sense, this paper present the hierarchical control derived from ISA-95 and electrical dispatching standards to endow smartness and flexibility to microgrids. The hierarchical control proposed consist of three levels: i) the primary control is based on the droop method, including an output impedance virtual loop; ii) the secondary control allows restoring the deviations produced by the primary control; and iii) the tertiary control manage the power flow between the microgrid and the external electrical distribution system. Results from a hierarchical-controlled microgrid are provided to show the feasibility of the proposed approach.

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Hierarchical control of droop-controlled DC and AC microgrids — a general approach towards standardization

An Introduction to MultiAgent Systems.

The enabling of ac microgrids in distribution networks allows delivering distributed power and providing grid support services during regular operation of the grid, as well as powering isolated islands in case of faults and contingencies, thus increasing the performance and reliability of the electrical system. The high penetration of distributed generators, linked to the grid through highly controllable power processors based on power electronics, together with the incorporation of electrical energy storage systems, communication technologies, and controllable loads, opens new horizons to the effective expansion of microgrid applications integrated into electrical power systems. This paper carries out an overview about microgrid structures and control techniques at different hierarchical levels. At the power converter level, a detailed analysis of the main operation modes and control structures for power converters belonging to microgrids is carried out, focusing mainly on grid-forming, grid-feeding, and grid-supporting configurations. This analysis is extended as well toward the hierarchical control scheme of microgrids, which, based on the primary, secondary, and tertiary control layer division, is devoted to minimize the operation cost, coordinating support services, meanwhile maximizing the reliability and the controllability of microgrids. Finally, the main grid services that microgrids can offer to the main network, as well as the future trends in the development of their operation and control for the next future, are presented and discussed.

Control of Power Converters in AC Microgrids

The transition towards a decarbonized power system requires the integration of large shares of variable renewable energy sources. Their intermittent nature challenges the short-term ability of the power system to maintain the system balance, and its long-term ability to meet the peak demand. This results in an increased need for operational flexibility. Simultaneously, the availability of conventional dispatchable generation to provide such flexibility becomes less evident. Energy storage systems present an alternative source of flexibility. This paper focuses on the role of long-term storage, such as power-to-gas, which is able to also deal with seasonal variations in the output of renewables. It studies the impact of long-term storage on the investment planning of a conceptual power system following the integration of large shares of variable renewable generation. Simulations show that long-term storage reduces the need for installed renewable generation capacity to meet renewable objectives, and that it has a pivotal role in realising a fully renewable supply at a realistic cost. Results further show that the deployment of long-term storage depends greatly on the availability of biomass. If biomass is available, long-term storage investment only occurs at extremely high renewable penetrations.

The role of long-term energy storage in investment planning of renewable power systems

Voltage control, grid reconfiguration and adaptive protection are three representative intra-grid control applications that are relevant in the context of smart grids which is characterized by the presence of bi-directional power flow due to the presence of distributed generation. These applications will lead to an efficient electric power grid. The implementation of the three control applications requires ICT. This paper identifies the technical and non-technical barriers, which are present in today's ICT, that impede the implementation of the three control applications. The technical barriers are ranked based on their severity in impeding implementation of the three control applications. The paper also provides the recommendations that will help in overcoming those barriers.

Barriers and recommendations for enabling ICT based intra-grid control applications in smart grids

A hybrid electric Kart is built as a didactical project for the students of the Master of Engineering: Energy of the KULeuven In order to cope with the growing number of students, a modular hybrid electric kart is conceived The hybrid configuration allows to diversify between several tasks that have to be addressed by the students The tasks include a control scheme for an induction motor, a control scheme and design of a power-factor-correction converter which enables power flow between the DC-link and a gasoline generator and finally the control scheme and design of a DC/DC converter allowing bidirectional power flow between a low voltage battery and the DC-link All control schemes are supervised by a top level control scheme which maximises efficiency The control schemes are programmed in Matlab/Simulink A rapid-prototyping control board runs the model made in Matlab/Simulink The control board interfaces between the different sensors and power electronics present on the kart

A hybrid electric kart with energy flow management as a student project

QoS monitoring at middleware level for depandable distributed automation systems

Increasing the share of renewable energy sources in the electrical grid requires new balancing means. Therefore, activating flexibility at the demand side with Demand Response (DR) programs has gained significant attention in recent years. In this regard, Thermostatically Controlled Loads (TCLs) are interesting appliances, due to their inherent storage capacity. In this paper, double Q-learning is applied to an Electric Water Heater (EWH) in two different DR settings. The first assumes the EWH's energy consumption is billed according to a Time-of-Use (ToU) price. The second scenario assumes households have a power consumption limit. In both cases, the control policy learned with double Q-learning is compared to a thermostat controller. With ToU pricing the EWH consumes 35% less energy during peak hours. When the EWH is charged according to a capacity tariff Q-learning reduces power consumption limit surpasses by 31%.

Geert Deconinck

Papers

The role of long-term energy storage in investment planning of renewable power systems

Barriers and recommendations for enabling ICT based intra-grid control applications in smart grids

A hybrid electric kart with energy flow management as a student project

QoS monitoring at middleware level for depandable distributed automation systems

Double Q-learning for Demand Response of an Electric Water Heater