COLORS - CONTEXTUAL LOAD FLEXIBILITY REMUNERATION STRATEGIES

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Publications

Short Time Electricity Consumption Forecast in an Industry Facility

Publication . Ramos, Daniel; Faria, Pedro; Vale, Zita; Correia, Regina

The work in this article uses artificial neural networks and support vector machine to forecast electricity consumption in an industrial facility. The main objective is to show that such a problem should be treated with a contextual approach that identifies the most adequate technic in each moment for a single building, contrary to the previous works in the literature that compare the accuracy of each method for the complete data set representing aggregated loads. 72 different algorithms have been implemented and tested. After that, the three most suitable ones are selected in order to support the automated decisions of the best algorithm according to the context. In this way, the implemented methodology finds the best method for the prediction of each 5 min. It can be later used to update the production planning in the industrial facility. It also discussed the size of historical data and the most suitable learning parameters for each method. The case study includes test data for one week and more than one year of training data.

2022Journal article

Restricted access

Effects of elasticity parameter definition for real-time pricing remuneration considering different user types

Publication . Corsi, Pierfrancesco; Faria, Pedro; Vale, Zita

In the last decade Demand Response (DR) programs have been influencing loads’ profiles of electric users who participate in these programs. The evolution of the simulations able to study them brought to the possibility of defining new models that can consider power consumption profiles for different types of user (MAT, AT, MT, BTE, BTN-2, BTN-1) but, in order to better match consumption and production energy curves, highly precise predictions of loads’ profiles are still needed. This goal can be achieved also thanks to the study of the price elasticity factor. A way to obtain it will be examined in this paper: price and power absorption variations will be considered because it is defined as the ratio of their relative variations before and after DR. This work focuses on the profiles of price variations P with respect to the absorbed power variation Q: users indeed are expected to vary their consumptions according to different values of remunerations. Moreover, different ranges of elasticities have been evaluated in order to study the behavior of P profiles for the more representing users. Finally, effects of a wrong interpolation have been discussed in order to see their consequences on the actual available power.

2020Conference object

Open access

Modeling of Consumer Preferences and Constraints for the Optimal Schedule of Consumption Shifting

Publication . Faria, Pedro; Spinola, Joao; Vale, Zita

The actual context for smart grid implementation implies the development of tools to support the diverse player's decisions. The present paper addresses a multi-period consumer's management methodology for the scheduling of demand flexibility initiatives and on-site generation. The objective is to minimize the energy costs for the consumer, taking into account his resources. The paper also considers the use of dynamic pricing with the intent of studying its effect on load shifting schedule. The results obtained show how the consumers can use this methodology to achieve new efficiency levels regarding their energy use, and therefore costs.

2019Conference object

Open access

Lighting Consumption Optimization in a SCADA Model of Office Building Considering User Comfort Level

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

Due to the high penetration of the buildings in energy consumption, the use of optimization algorithms plays a key role. Therefore, all the producers and prosumers should be equipped with the automation infrastructures as well as intelligent decision algorithms, in order to perform the management programs, like demand response. This paper proposes a multi-period optimization algorithm implemented in a multi-agent Supervisory Control and Data Acquisition system of an office building. The algorithm optimizes the lighting power consumption of the building considering the user comfort constraints. A case study is implemented in order to validate and survey the performance of the implemented optimization algorithm using real consumption data of the building. The outcomes of the case study show the great impact of the user comfort constraints in the optimization level by respect to the office user’s preferences.

2020Book part

Open access

Study of Multi-Tariff Influence on the Distributed Generation Remuneration

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

The energy market, with the introduction of the smart grids concept, opens the door to small distributed energy resources. However, these resources introduce an added level of difficulty to market management, requiring an entity to aggregate and manage them optimally. This paper proposes an approach that integrates these small resources. The methodology is composed of optimal scheduling, aggregation and remuneration based on aggregation. The method chosen for aggregation is k-means. In relation to previous works, the innovation goes through the multi-period and the comparison that this can have in the formation of groups. Thus, three scenarios were created: Whole Week, Work Days and Weekend. Profiles were added for 548 units of DG. The justification for the formation of groups will be a fairer remuneration and according to the contribution of each resource to the management of the network.

2019Conference object

Open access