Browsing by Author "Gazafroudi, Amin Shokri"
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- D7.3 Proceedings of the Second DREAM-GO Workshop: Real-Time Demand Response and Intelligent Direct Load ControlPublication . Vale, Zita; Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Spínola, João; Canizes, Bruno; Pinto, Tiago; Soares, João; Chamoso, Pablo; Santos, Daniel; Garcia, Oscar; Catalina, Jorge; Guevarra, Fabio; Navarro-Cáceres, María; Gazafroudi, Amin Shokri; Prieto-Castrillo, Francisco; Corchado, Juan Manuel; Santos, Gabriel; Teixeira, Brígida; Praça, Isabel; Sousa, Filipe; Zawislak, Krzysztof; Iglesia, Daniel Hernández de la; Barriuso, Alberto Lopez; Lozano, Alvaro; Herrero, Jorge Revuelta; Landeck, Jorge; Paz, Juan F. de; Corchado, Juan M.; Garcia, Ruben Martin; González, Gabriel Villarrubia; Bajo, Javier; Matos, Luisa; Klein, L. Pires; Carreira, R.; Torres, I.; Landeck, JorgeProceedings of the Second DREAM-GO Workshop Real-Time Demand Response and Intelligent Direct Load Control
- D7.4 - Proceedings of the Third DREAM-GO Workshop: Intelligent load management in local and wholesale demand response marketsPublication . Barriuso, Alberto L.; Briones, Alfonso González; Lozano, Álvaro; Gazafroudi, Amin Shokri; Iglesia, Daniel H. de la; Sousa, Filipe; Villarrubia, Gabriel; Spínola, João; Revuelta Herrero, Jorge; Paz, Juan F. de; Corchado, Juan Manuel; Venyagamoorthy, Kumar G.; Gomes, Luis; Khorram Ghahfarrokhi, Mahsa; Navarro-Cáceres, María; Abrishambaf, Omid; Faria, Pedro; Castro, Rafael; Silva, Sergio; Coppens, Tom; Vale, ZitaProceedings of the Third DREAM-GO Workshop: Intelligent load management in local and wholesale demand response markets - Deliverable 7.4
- Economic Evaluation of Predictive Dispatch Model in MAS-Based Smart HomePublication . Gazafroudi, Amin Shokri; Prieto-Castrillo, Francisco; Pinto, Tiago; Jozi, Aria; Vale, ZitaThis paper proposes a Predictive Dispatch System (PDS) as part of a Multi-Agent system that models the Smart Home Electricity System (MASHES). The proposed PDS consists of a Decision-Making System (DMS) and a Prediction Engine (PE). The considered Smart Home Electricity System (SHES) consists of different agents, each with different tasks in the system. A Modified Stochastic Predicted Bands (MSPB) interval optimization method is used to model the uncertainty in the Home Energy Management (HEM) problem. Moreover, the proposed method to solve HEM problem is based on the Moving Window Algorithm (MWA). The performance of the proposed Home Energy Management System (HEMS) is evaluated using a JADE implementation of the MASHES.
- Energy flexibility assessment of a multi agent-based smart home energy systemPublication . Gazafroudi, Amin Shokri; Pinto, Tiago; Prieto-Castrillo, Francisco; Corchado, Juan Manuel; Abrishambaf, Omid; Jozi, Aria; Vale, ZitaPower systems worldwide are complex and challenging environments. The increasing necessity for an adequate integration of renewable energy sources is resulting in a rising complexity in power systems operation. Multi-agent based simulation platforms have proven to be a good option to study the several issues related to these systems. In a smaller scale, a home energy management system would be effective for the both sides of the network. It can reduce the electricity costs of the demand side, and it can assist to relieve the grid congestion in peak times. This paper represents a domestic energy management system as part of a multi-agent system that models the smart home energy system. Our proposed system consists of energy management and predictor systems. This way, homes are able to transact with the local electricity market according to the energy flexibility that is provided by the electric vehicle, and it can manage produced electrical energy of the photovoltaic system inside of the home.
- Reserve costs allocation model for energy and reserve market simulationPublication . Pinto, Tiago; Gazafroudi, Amin Shokri; Prieto-Castrillo, Francisco; Santos, Gabriel; Silva, Francisco; Corchado, Juan Manuel; Vale, ZitaThis paper proposes a new model to allocate reserve costs among the involved players, considering the characteristics of the several entities, and the particular circumstances at each moment. The proposed model is integrated in the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which enables complementing the multi-agent simulation of diverse electricity market models, by including the joint simulation of energy and reserve markets. In this context, the proposed model allows allocating the payment of reserve costs that result from the reserve market. A simulation based on real data from the Iberian electricity market - MIBEL, is presented. Simulation results show the advantages of the proposed model in sharing the reserve costs fairly and accordingly to the different circumstances. This work thus contributes the study of novel market models towards the evolution of power and energy systems by adapting current models to the new paradigm of high penetration of renewable energy generation.