Percorrer por autor "Martins, A. Gomes"
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- Influence of the management perspective for choosing the best location for Distributed electric energy storage unitsPublication . Gonçalves, José; Pires Neves, Luís; Martins, A. GomesA methodology to assist a decision maker (DM) on the assessment of feasible solutions to implement a distributed electric energy storage system (DEESS) is presented. The chosen system is based on the nanophosphate lithium-ion battery technology due to its increasing use in electricity networks and to the advantages when compared to other commercially available technologies. The proposed methodology perfoms the choice of locations, using a definition of the best schedule of operation, while simultaneously optimizing four objective functions: the minimization of losses, voltage deviations and investment cost, and the maximization of the net gains of exploiting the differences among time varying energy prices. Results show that the best DEESS location depends on the energy service to be provided, namely of the goal of the DM that defines the management scheme of the DEESS, suggesting the need to incorporate this level of decision on the multiple objective formulation and making this methodology appropriate for different types of stakeholders.
- Methodology to simulate the impact of a large deployment of a residential energy management system in the electricity gridPublication . Miguel, Pedro; Neves, Luís; Martins, A. GomesThe purpose of this work is to provide an insight for a possible methodology to implement demand response strategies at a city scale. The objective is to determine a range of values for the energy and power that can be made available through the large deployment of a residential energy management system. This work can help the distribution system operator to assess the impact of the usage of such technology at the grid level. The paper describes a methodology that identifies the start of operation cycles of appliances and other loads on a given general load diagram, enabling the simulation of load shifting caused by the operation of residential energy management systems. A simulation of an hypothetical 20% deployment of a residential energy management system on the city of Coimbra in Portugal, was performed. The results show the release of almost 3% of the demand on periods of higher price, but also the occurrence of a pronounced peak during the night period, an occurrence which may need to be dealt with, and for which some solutions are proposed.
- Network impact of residential energy management systems at city scalePublication . Miguel, Pedro; Neves, Luís; Martins, A. GomesThe impact on the electricity distribution system of residential energy management systems will result of changes in the electricity usage by consumers in response to stimuli like real-time changes in the electricity price. However, due to the dispersed and uncontrolled nature of the management of end-use appliances, estimating the energy and power output of an aggregation of such devices requires a specific approach. The proposed methodology makes use of information regarding total electricity consumption, queried data regarding the willingness of consumers to postpone the starting time of appliances operation and prototypes of hourly electricity price diagrams. The output of the methodology includes information on the released network capacity as well as on load rebound, both caused by the aggregated demand response. In particular, load rebound is a relevant phenomenon that presents new challenges to the management of the grid, and for which some preventive measures are suggested.
- Using clustering techniques to provide simulation scenarios for the smart gridPublication . Miguel, Pedro; Gonçalves, José; Pires Neves, Luís; Martins, A. GomestThe objective of this work is to obtain characteristic daily profiles of consumption, wind generationand electricity spot prices, needed to develop assessments of two different options commonly regardedunder the smart grid paradigm: residential demand response, and small scale distributed electric energystorage. The approach consists of applying clustering algorithms to historical data, namely using a hierar-chical method and a self-organizing neural network, in order to obtain clusters of diagrams representingcharacteristic daily diagrams of load, wind generation or electricity price. These diagrams are useful notonly to analyze different scenarios of combined existence, but also to understand their individual relativeimportance. This study enabled also the identification of a probable range of variation around an averageprofile, by defining boundary profiles with the maximum and minimum values of any cluster prototypes.