Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development

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Organizational Unit

Publications

Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods

Publication . Silva, Cátia; Faria, Pedro; Vale, Zita

Nowadays, the data can be considered an asset when properly managed. An entity with the right tool to analyse the amount of data existent and withdraw crucial information will have the power to obliterate the competition. In the Energy sector, with Smart Grid introduction, small resources have more influence in the market through Demand Response and bidirectional communication. However, none of the actual business models is prepared to deal with the uncertainty related to these resources. The authors, in order to find a solution for this complex problem, proposed a methodology which the goal is to minimize operation costs and give fair compensation for resources who participate in the management of local markets. With this fair payment, it is expected continuous participation. Through clustering methods, remuneration groups are created. In the present paper, a study about the optimal number of clusters is performed. The information gives the Aggregator control in results of the following phases, understanding the impact in the remuneration of the resources.

2019Conference object

Open access

A Consumer Trustworthiness Rate for Participation in Demand Response Programs

Publication . Silva, Cátia; Faria, Pedro; Vale, Zita

Local energy communities with information from the real-time market may improve the market operation but also increase the complexity of the management problem thanks to the uncertainty associated with the actual response of these resources. For instance, consumers with price knowledge may change their power consumption to lower-cost periods. The authors present a model to deal with uncertainty from the point of view of the Aggregator: apply reliability rates to each consumer according to their actual response in events of Demand Response (DR). The consumers with higher rates are chosen to participate in the energy market. To compute the final rate, three different independent rates are used: Historical rate with past information, Cut-rate from the response in the actual period and the Last Day Rate which is the final reliability rate from the previous day. In the present paper, the influence of each independent rate, through the weight used, is studied.

2020Journal article

Open access

Multiagent Simulation of Demand Flexibility Integration in Local Energy Markets

Publication . Pinto, Tiago; Boeno, Nathalia; Vale, Zita; Sica, Everthon

Overcoming the issues associated with the variability of renewable generation has become a constant challenge in power and energy systems. The use of load flexibility is one of the most promising ways to face it. Suitable ways to incorporate flexibility in the electricity market, in addition to the already challenging integration of distributed generation primary sources, are therefore crucial. The integration of prosumers and consumers flexibility in the market is, however, not straightforward, as current wholesale and retail market structures are not prepared to deal with the current and future needs of the system. Several models for local energy markets have been studied and experimented; but there it is still not clear what is the most efficient way to integrate the dynamic participation of demand flexibility in this type of local markets.

2020Conference object

Open access

Aggregation of Consumers and Producers in a Community with different Clustering Methods

Publication . Silva, Cátia; Faria, Pedro; Vale, Zita; Starzacher, Nikolaus

The consumer concept is shaping up as the grid is improving to a smart way. Moving from an actor with little information about what was happening in the energy market, to player with an active and important role in its management. The term prosumer will revolutionize the way the electrical system operates. The possibility of the participation of distributed small-scale energy resources in the network infrastructure changes the current management model. The authors propose a model that optimally associates all concepts. Scheduling, aggregation and compensation are the main phases that compose this model. In this paper, the author focusses only on the second, being the main goal compare between being a consumer, a producer or a prosumer in this method. In this way, two partitional clustering methods were used, testing different k clusters.

2019-01Conference object

Open access

An Optimization Algorithm for Cost Minimization in Residential Buildings

Publication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, Zita

The increment of the electricity consumption around the world has led many efforts on the network operators to reduce the consumption in the demand side and encourage to increase the use of renewable energies. Since the buildings have a significant part in energy consumption, and lighting systems have an important role in the energy consumption of the buildings, the optimization of the lighting system should be effective. Hence, the focus of this paper is to minimize the lamps consumption of a residential house based on electricity price and try to take advantages from photovoltaic generation as much as possible. The methodology of this work is proposed as a linear optimization problem that manages the generation of a renewable energy resource, which supplies a part of the energy consumption of the house. For the case studies, the amount of the renewable energy generation, total consumption of building, consumption of the lights, and electricity price are considered.

2019-01Conference object

Open access