Loading...
6 results
Search Results
Now showing 1 - 6 of 6
- A Local Electricity Market Model for DSO Flexibility TradingPublication . Faia, R.; Pinto, Tiago; Vale, Zita; Corchado, Juan ManuelThe necessity of end-user engagement in power systems have become a reality in recent times. One of the solutions to this engagement is the creation of local energy markets. The distribution systems operators are compelled to investigate and optimize their asset investment cost in reinforcement of grids by introducing smart grid functionalities in order to avoid investments. The congestion management is the one of the most promising strategies to deal with the network issues. This paper presents a local electricity market or flexibility negotiation as a strategy in order to help the distribution system operator in congestion management. The local market is performed considering an asymmetric action model and is coordinated by an aggregator. A case study is presented considering a simulation that uses a low voltage network with 17 buses, which includes 9 consumers and 3 prosumers, all domestic users. Results show that using the proposed market model, the network congestion is avoided by taking advantage from the trading of consumers flexibility.
- Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy managementPublication . Faia, R.; Pinto, Tiago; Abrishambaf, Omid; Fernandes, Filipe; Vale, Zita; Corchado, Juan ManuelThis paper proposes a novel Case Based Reasoning (CBR) application for intelligent management of energy resources in residential buildings. The proposed CBR approach enables analyzing the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. The innovations of the proposed CBR model are the application of the k-Nearest Neighbors algorithm (k-NN) clustering algorithm to identify similar past cases, the adaptation of Particle Swarm Optimization (PSO) meta-heuristic optimization method to optimize the choice of the variables that characterize each case, and the development of expert systems to adapt and refine the final solution. A case study is presented, which considers a knowledge base containing a set of scenarios obtained from the consumption of a residential building. In order to provide a response for a new case, the proposed CBR application selects the most similar cases and elaborates a response, which is provided to the SCADA House Intelligent Management (SHIM) system as input data. SHIM uses this specification to determine the loads that should be reduced in order to fulfill the reduction suggested by the CBR approach. Results show that the proposed approach is capable of suggesting the most adequate levels of reduction for the considered house, without compromising the comfort of the users.
- Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart CityPublication . Canizes, Bruno; Soares, João; Vale, Zita; Corchado, Juan ManuelThe use of electric vehicles (EVs) is growing in popularity each year, and as a result, considerable demand increase is expected in the distribution network (DN). Additionally, the uncertainty of EV user behavior is high, making it urgent to understand its impact on the network. Thus, this paper proposes an EV user behavior simulator, which operates in conjunction with an innovative smart distribution locational marginal pricing based on operation/reconfiguration, for the purpose of understanding the impact of the dynamic energy pricing on both sides: the grid and the user. The main goal, besides the distribution system operator (DSO) expenditure minimization, is to understand how and to what extent dynamic pricing of energy for EV charging can positively affect the operation of the smart grid and the EV charging cost. A smart city with a 13-bus DN and a high penetration of distributed energy resources is used to demonstrate the application of the proposed models. The results demonstrate that dynamic energy pricing for EV charging is an efficient approach that increases monetary savings considerably for both the DSO and EV users.
- Optimal expansion planning considering storage investment and seasonal effect of demand and renewable generationPublication . Canizes, Bruno; Soares, João; Lezama, Fernando; Silva, Cátia; Vale, Zita; Corchado, Juan ManuelA new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lines locations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems.
- 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
- Hybrid approach based on particle swarm optimization for electricity markets participationPublication . Faia, R.; Pinto, Tiago; Vale, Zita; Corchado, Juan ManuelIn many large-scale and time-consuming problems, the application of metaheuristics becomes essential, since these methods enable achieving very close solutions to the exact one in a much shorter time. In this work, we address the problem of portfolio optimization applied to electricity markets negotiation. As in a market environment, decision-making is carried out in very short times, the application of the metaheuristics is necessary. This work proposes a Hybrid model, combining a simplified exact resolution of the method, as a means to obtain the initial solution for a Particle Swarm Optimization (PSO) approach. Results show that the presented approach is able to obtain better results in the metaheuristic search process.