Loading...
4 results
Search Results
Now showing 1 - 4 of 4
- Demand response model for hardware implementationPublication . Capitão, B.; Lagarto, João; Pereira, Rita; Almeida, P.; Fonte, Pedro MDemand response actions allow to support an adequate domestic load management, considering consumer preferences. In order to develop a hardware tool based on Arduino used to support consumers load management and decisions, an optimization mathematical model is developed and detailed in this paper. In the developed mathematical model, household appliances and electric vehicle are considered as controllable loads. The existence of a storage system based on batteries is considered as well as energy provided by the power grid and solar panel self-generation. The model is implemented using optimization software GAMS (General Algebraic Modeling System) as a Mixed Integer Programming (MIP) problem, where its outputs are used as inputs applied to the hardware used as interface between the optimization mathematical model and controllable loads.
- Short-term load forecasting using time series clusteringPublication . Martins, Ana Alexandra; Lagarto, João; Canacsinh, Hiren; Reis, Francisco; Cardoso, Maria MargaridaShort-term load forecasting plays a major role in energy planning. Its accuracy has a direct impact on the way power systems are operated and managed. We propose a new Clustering-based Similar Pattern Forecasting algorithm (CSPF) for short-term load forecasting. It resorts to a K-Medoids clustering algorithm to identify load patterns and to the COMB distance to capture differences between time series. Clusters' labels are then used to identify similar sequences of days. Temperature information is also considered in the day-ahead load forecasting, resorting to the K-Nearest Neighbor approach. CSPF algorithm is intended to provide the aggregate forecast of Portugal's national load, for the next day, with a 15-min discretization, based on data from the Portuguese Transport Network Operator (TSO). CSPF forecasting performance, as evaluated by RMSE, MAE and MAPE metrics, outperforms three alternative/baseline methods, suggesting that the proposed approach is promising in similar applications.
- SWHORD simulator: A platform to evaluate energy transition targets in future energy systems with increasing renewable generation, electric vehicles, storage technologies, and hydrogen systemsPublication . Sousa, Jorge A. M.; Lagarto, João; Carvalho, Ezequiel; Martins, AnaThis paper presents the simulation platform SWHORD, specially designed for the analysis of future energy systems under energy transition targets. The model is implemented in GAMS as a cost minimization mixed integer programming problem of a hydro-thermal power system, which includes high penetration of non-dispatchable renewable generation, storage technologies, electric vehicles, and hydrogen systems. Simulations are performed on an hourly basis for one year of operation, enabling the evaluation of both short-term dynamics and the seasonal behaviour of the system and including the hourly power generation profile by technology, fuel and emission costs, CO2 emissions and storage levels, as well as the renewable curtailment needed to balance the system. The model was validated by backtesting with historical data of the Portuguese power system and, from a comprehensive statistical analysis of the dispatchable generation, it is concluded that the simulation results present a good fit with the real data. An illustrative use case is presented to evaluate the consistency of the Portuguese targets for 2030. Simulation results put in evidence the advantages of the SWHORD simulator to study the complex interactions among the new drivers of future energy systems, such as electric vehicles, storage technologies, and hydrogen systems.
- Optimal investment and sharing decisions in renewable energy communities with multiple investing membersPublication . Barbosa, Inês; Sousa, Jorge A. M.; Villar, José; Lagarto, João; Viveiros, Carla; Barata, FilipeThe Renewable Energy Communities (RECs) and self-consumption frameworks defined in Directive (EU) 2023/2413 and Directive (EU) 2024/1711 are currently being integrated into national regulations across EU member states, adapting legislation to incorporate these new entities. These regulations establish key principles for individual and collective self-consumption, outlining operational rules such as proximity constraints, electricity sharing mechanisms, surplus electricity management, grid tariffs, and various organizational aspects, including asset sizing, licensing, metering, data exchange, and role definitions. This study introduces a model tailored to optimize investment and energy-sharing decisions within RECs, enabling multiple members to invest in solar photovoltaic (PV) and wind generation assets. The model determines the optimal generation capacity each REC member should install for each technology and calculates the energy shared between members in each period, considering site-specific constraints on renewable deployment. A case study with a four-member REC is used to showcase the model’s functionality, with simulation results underscoring the benefits of CSC over ISC.