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Rating consumers participation in demand response programs according to previous events

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

The energy sector, as many, is being adapted to meet environmental concerns and avoid fossil fuels. So, Smart Grids concept is promoted, penetrating Distributed Generation into the grid, namely renewable-based energy, providing an environmentally friendly alternative. Also, the consumers' role is empowered through Demand Response (DR). The consumers are incentivized to actively modify their consumption behavior receiving the proper remuneration. With this, the power system will decrease operation costs and DR can be used as an alternative to generation. However, manage these new and active resources as well as their transactions in the energy market is a complex task due to the uncertainty associated. Many factors can cause a non-response and the Aggregator must be able to manage these situations mainly when a certain target of reduction is required from the wholesale market. The authors proposed an approach including a Trustworthy Rank to select consumers for on DR events: consumers participate considering their reliability. In the present paper, the effects of the approach will be compared between two seasons, proving the viability on giving the correct information to the community manager and understanding how variable is the behavior of this rank at different times of the year.

2020Journal article

Open access

Rating the Participation of Electricity Consumers in Demand Response Events

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

To successfully enable Demand Response in the energy market, the necessity for modification of the actual business models urges. The authors present innovation from previous works with a method designed to deal with the uncertainty from active consumers in Demand Response events. The proposal has three variations designed to improve the accuracy of the actual response of the consumers in the management of a local community - Basic Rate, Cost Rate and Clustering Rate Methods. The attribution of reliability rates, according to previous Demand Response events (for example, emergency events where a certain target is needed), will decide which consumers are selected for the optimal scheduling. With this, the manager entity possesses valuable information to increase profit, choosing trustworthy consumers. The methods are compared in a case study with 548 DG units and 20,310 small consumers. The results demonstrate the viability of the approach and prove that reliability rates approach is useful to deal with the uncertainty of actual response in DR events.

2020Conference object

Open access

Using diverse sensors in load forecasting in an office building to support energy management

Publication . Ramos, Daniel; Teixeira, Brígida; Faria, Pedro; Gomes, Luis; Abrishambaf, Omid; Vale, Zita

The increasing penetration of renewable energy sources led to the development of several energy management approaches. One of the main topics in this field is related to the load forecast in buildings, which can contribute to more intelligent and sustainable energy consumption. However, it is necessary to build a proper forecast model, capable of detecting an accurate consumption profile. The minimum effort to achieve this is to extract a historic with energy consumptions to use as input. Additional information should be considered in order to achieve improvements in forecasting results. This way, information regarding the day of the week is discussed as a reliable source of information that may enhance the load forecast. In this paper, two forecasting techniques, namely neural networks and support vector machine, are used to predict the energy consumption of a building for all 5 min from a period. The proposed model finds the best forecasting technique and determines if the additional information regarding the day of the week enhances the load forecast. In this case study, a period of two years and a half data with a 5-minute time interval is used. Moreover, several tests are performed for varied inputs to understand if the insights are consistent for these tests. This data has been adapted from an office building to illustrate the advantages of the proposed methodology.

2020Journal article

Open access