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An Intelligent Smart Plug with Shared Knowledge Capabilities

Publication . Gomes, Luis; Sousa, Filipe; Vale, Zita

The massive dissemination of smart devices in current markets provides innovative technologies that can be used in energy management systems. Particularly, smart plugs enable efficient remote monitoring and control capabilities of electrical resources at a low cost. However, smart plugs, besides their enabling capabilities, are not able to acquire and communicate information regarding the resource's context. This paper proposes the EnAPlug, a new environmental awareness smart plug with knowledge capabilities concerning the context of where and how users utilize a controllable resource. This paper will focus on the abilities to learn and to share knowledge between different EnAPlugs. The EnAPlug is tested in two different case studies where user habits and consumption profiles are learned. A case study for distributed resource optimization is also shown, where a central heater is optimized according to the shared knowledge of five EnAPlugs.

2018Journal article

Open access

Differential Evolution Aplication in Portfolio optimization for Electricity Markets

Publication . Faia, R.; Lezama, Fernando; Soares, João; Vale, Zita; Pinto, Tiago; Corchado, Juan Manuel

Smart Grid technologies enable the intelligent integration and management of distributed energy resources. Also, the advanced communication and control capabilities in smart grids facilitate the active participation of aggregators at different levels in the available electricity markets. The portfolio optimization problem consists in finding the optimal bid allocation in the different available markets. In this scenario, the aggregator should be able to provide a solution within a timeframe. Therefore, the application of metaheuristic approaches is justified, since they have proven to be an effective tool to provide near-optimal solutions in acceptable execution times. Among the vast variety of metaheuristics available in the literature, Differential Evolution (DE) is arguably one of the most popular and successful evolutionary algorithms due to its simplicity and effectiveness. In this paper, the use of DE is analyzed for solving the portfolio optimization problem in electricity markets. Moreover, the performance of DE is compared with another powerful metaheuristic, the Particle Swarm optimization (PSO), showing that despite both algorithms provide good results for the problem, DE overcomes PSO in terms of quality of the solutions.

2018Conference object

Open access

Optimization-Based Home Energy Management System Under Different Electricity Pricing Schemes

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

This paper presents an optimization-based home energy management system, by taking advantages of renewable resources and energy storage system for optimally managing the energy consumption and generation of the house. The surplus of renewable generation will be stored in energy storage system or will be injected into the main grid. An optimization algorithm is developed for this system in order to minimize the electricity bill of the house considering electricity tariffs. Four home appliances are considered to be controlled by this system for reducing the consumption in critical periods. The outcomes of optimization problem are the optimal scheduling of the resources including renewable generation, energy storage system, consumption reduction, and power transactions with the grid. In the case study, the developed model will be employed in three different scenarios, which considers simple electricity prices and time-of- use tariffs in order to test and validate the performance of the developed model.

2018Conference object

Open access

Iberian electricity market ontology to enable smart grid market simulation

Publication . Santos, Gabriel; Pinto, Tiago; Praça, Isabel; Vale, Zita

Several approaches have been proposed to enhance the potential of distributed generation (DG). Some of the most prominent solutions include the aggregation of DG units and other players, culminating in the concept of and Smart Grid (SG). In this context, several simulation tools arose to study and test the new market mechanisms. However, all of these simulators are closed and centred in their object of study, neglecting the potential advantages of interoperating with other systems from the same domain. This work proposes the use of ontologies for systems interoperability in the power and energy systems domain. The ontologies have been developed and implemented in MASCEM and MASGriP - multi-agent simulators of electricity markets, and SG operation and management,respectively; thus enabling joint electricity market and SG simulations.

2018Journal article

Open access

Two-stage algorithm for the management of distributed energy resources included in an aggregator's activities

Publication . Spínola, João; Gazafroudi, Amin; Faria, Pedro; Vale, Zita

The growing number of distributed energy resources in power systems, leads to the appearance of new entities and roles for the existing ones that affect the operation of the network. One of these entities with more relevance, is the aggregator, either independent or represented by public organizations. An aggregator manages small-sizemdistributed energy resources, creating a virtual amount of energy flexibility that can be used by it, to enablem participation in energy markets and capitalize the integration of distributed energy resources. This paperm proposes a two-stage optimization methodology for the operation of an aggregator regarding distributed energy mresources. In a first stage, the network part managed by the aggregator is scheduled, meaning at a macrom perspective, while in the second stage, it is assumed that the distributed energy resources are also scheduled mconsidering their operation. It is assumed that this second stage is enabled due to an aggregator’s communication infrastructure and interconnected management systems.

2018-01Conference object

Open access