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You searched for +publisher:"Delft University of Technology" +contributor:("Pippia, Tomas"). Showing records 1 – 2 of 2 total matches.

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Delft University of Technology

1. Laudiero, Nico (author). Stochastic Control Strategies for Residential Microgrids: Potential Benefits of Micro-CHP Installation in Multifamily Buildings.

Degree: 2018, Delft University of Technology

Fast depleting fossil fuels and growing awareness for environmental protection have led us to the urgency of a long-term energy planning where reduction of emissions, integration of renewable supply, and energy efficiency improvement represent the main targets of a ‘smarter’ employment of primary resources. Research is needed nowadays to drive a transient phase towards the construction of future ‘smart grids’, where multiple actors will be able to communicate with each other and efficiently adapt their production/consumption with respect to the dynamic evolution of the increasingly complex power network. In this scenario, operational management of small, local electricity networks (microgrids) and their two-way interconnection to the main grid are creating new opportunities and, at the same time, new technological challenges. Advanced control schemes are being investigated to smoothen the integration of distributed generation and to achieve optimal operation at microgrid level, through coordination and dispatching of power generation, flexible loads, and storage elements. The residential sector is responsible for about 30% of the global energy consumption and has historically played a passive role in the unidirectional centralised power infrastructure. A residential microgrid that utilises controllable prime movers, such as gas engines, to compensate fluctuating demand and output of renewable energy would represent a fundamental step towards a more economic, efficient, and environment friendly energy infrastructure. This MSc thesis project focuses on the design of energy management systems in residential buildings where micro-Combined Heat and Power (CHP) generators are installed. Micro-CHP technology is able to produce electrical energy locally in a controllable way, having at the same time the advantage of efficiently employing by-product heat to satisfy thermal demand of the building where it is located. The purpose of our work is an economic analysis regarding the profitability of investment in distributed energy resources for Dutch households and a subsequent investigation about the benefits that advanced control techniques would lead to microgrid operation on the long run. For this reason, specific case studies are built based on real data of thermal and electric consumption, which have been collected through smart meters in various Dutch houses. Two different versions of the microgrid are considered: a first case only involves micro-CHP and thermal energy storage, whereas a second one is expanded to include solar panels. Advanced techniques employed for supervisory control of power flows in microgrids generally aim to take into account relevant information about the consequences of choosing specific actions, by considering future predictions of system evolution. Model Predictive Control (MPC) is a well-known, established and widely used control technique that is often considered as a natural approach to adopt in microgrids. Its main strength is the ability to turn a control problem into an optimisation… Advisors/Committee Members: Pippia, Tomas (mentor), De Schutter, Bart (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: MPC; Stochastic Process; CHP; Microgrids

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Laudiero, N. (. (2018). Stochastic Control Strategies for Residential Microgrids: Potential Benefits of Micro-CHP Installation in Multifamily Buildings. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:5b3305dc-61d7-49e7-94f2-274b0ffd3c3c

Chicago Manual of Style (16th Edition):

Laudiero, Nico (author). “Stochastic Control Strategies for Residential Microgrids: Potential Benefits of Micro-CHP Installation in Multifamily Buildings.” 2018. Masters Thesis, Delft University of Technology. Accessed March 08, 2021. http://resolver.tudelft.nl/uuid:5b3305dc-61d7-49e7-94f2-274b0ffd3c3c.

MLA Handbook (7th Edition):

Laudiero, Nico (author). “Stochastic Control Strategies for Residential Microgrids: Potential Benefits of Micro-CHP Installation in Multifamily Buildings.” 2018. Web. 08 Mar 2021.

Vancouver:

Laudiero N(. Stochastic Control Strategies for Residential Microgrids: Potential Benefits of Micro-CHP Installation in Multifamily Buildings. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Mar 08]. Available from: http://resolver.tudelft.nl/uuid:5b3305dc-61d7-49e7-94f2-274b0ffd3c3c.

Council of Science Editors:

Laudiero N(. Stochastic Control Strategies for Residential Microgrids: Potential Benefits of Micro-CHP Installation in Multifamily Buildings. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:5b3305dc-61d7-49e7-94f2-274b0ffd3c3c


Delft University of Technology

2. Wahid, Markos (author). Comparing electric vehicle charging strategies in stochastic microgrid optimization.

Degree: 2019, Delft University of Technology

Renewable energy sources, e.g. solar energy and wind energy, have gained popularity as an alternative means of energy production as they do not reinforce global warming. In addition, more and more electrical appliances (e.g. electric vehicles, induction cookers, and heat pumps) are used as a substitute for appliances that need non-renewable energy sources. This increase in the use of renewable energy resources pushes the electricity grid to its limits due to new induced load peaks. The grid is not designed for these developments and as a result, asset deterioration, higher transport losses, and outages are expected to occur. The most straightforward solution for the distributed system operator, i.e. the operating manager of the distribution network, is to expand the grid. However, grid expansion is a costly operation and there are additional promising methods to decrease grid load peaks, e.g. by using different charging strategies for electric vehicles. The conventional charging strategy for electric vehicles is uncontrolled charging. With uncontrolled charging, the charging of the electric vehicle immediately commences once a connection with the charging pole is established. The smart charging strategy, however, is able to delay the charging moment to a more optimal time instant in view of, e.g. variable electricity prices. The vehicle-to-home (V2H) charging strategy is similar to smart charging, but in addition, the V2H strategy allows the electric vehicle to discharge electricity to power a nearby residential home. This research aims to compare smart charging and V2H charging on their economical effects for their users. The charging strategies are implemented using two control algorithms: a rule-based controller and a model predictive control (MPC) algorithm. The rule-based controller is implemented due to its simplicity and the MPC algorithm is used for its ability to take into account predictions of system related variables, e.g. household loads. The MPC algorithm is implemented with two different forecasts namely, perfect information, i.e. uncertain variables are forecasted perfectly, and certainty equivalent, i.e. uncertain variables are predicted using a persistence forecast model. The persistence forecast model assumes that the future values of an uncertain variable remain equal to the latest measurements, e.g. the solar generation of tomorrow is expected to be equal to that of today. The control problem is non-linear as an electric vehicle behaves differently depending on its status, e.g. driving or charging. The control problem is therefore reformulated into a mixed logical dynamical framework such that it can be solved efficiently using mixed integer linear programming. An extensive comparison in performance for a microgrid case study is done using real data of solar generation, electric vehicles, and household loads for simulation. The results show that the V2H charging strategy can outperform smart charging by reducing both the peak loads and the electricity costs. However, the V2H strategy only gives a… Advisors/Committee Members: Pippia, Tomas (mentor), De Schutter, Bart (graduation committee), van Voorden, Arjan (mentor), Cvetkovic, Milos (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Microgrid; MPC; Scenario-based MPC; V2H; Smart Charging; scenario generation; persistence forcast model; EV; Mixed Logical Dynamical Model

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wahid, M. (. (2019). Comparing electric vehicle charging strategies in stochastic microgrid optimization. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:386aaa63-54f7-446e-8cde-68e74df5d0cc

Chicago Manual of Style (16th Edition):

Wahid, Markos (author). “Comparing electric vehicle charging strategies in stochastic microgrid optimization.” 2019. Masters Thesis, Delft University of Technology. Accessed March 08, 2021. http://resolver.tudelft.nl/uuid:386aaa63-54f7-446e-8cde-68e74df5d0cc.

MLA Handbook (7th Edition):

Wahid, Markos (author). “Comparing electric vehicle charging strategies in stochastic microgrid optimization.” 2019. Web. 08 Mar 2021.

Vancouver:

Wahid M(. Comparing electric vehicle charging strategies in stochastic microgrid optimization. [Internet] [Masters thesis]. Delft University of Technology; 2019. [cited 2021 Mar 08]. Available from: http://resolver.tudelft.nl/uuid:386aaa63-54f7-446e-8cde-68e74df5d0cc.

Council of Science Editors:

Wahid M(. Comparing electric vehicle charging strategies in stochastic microgrid optimization. [Masters Thesis]. Delft University of Technology; 2019. Available from: http://resolver.tudelft.nl/uuid:386aaa63-54f7-446e-8cde-68e74df5d0cc

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