Browsing by Author "Miguel, Pedro"
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- 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.