7 research outputs found
Plug-in Electric Vehicle Behavior Modeling in Energy Market:A Novel Deep Learning-Based Approach with Clustering Technique
Economic Selection of Generators for a Wind Farm
The selection suitable generator for wind turbines will be done based on technical criteria and priorities of the project. In this paper, a method for determining the type of wind turbine generator with an example is explained. In the paper, for a 10kW wind turbine, two generators have been proposed. The first case is a squirrel-cage asynchronous generator coupled to the turbine through the gearbox and directly connected to three phase output. Other PM generators that are directly coupled to the turbine and it is connected to the grid using the inverter. The results show that according to wind conditions, a 10kW permanent magnet generator is more advantageous in terms of energy production
Risk-Averse Optimal Bidding of Electric Vehicles and Energy Storage Aggregator in Day-Ahead Frequency Regulation Market
Integrated Forecasting and Scheduling of Implicit Demand Response in Balancing Markets Using Inverse Optimization
Demand Response (DR) programs offer flexibility that is considered to hold significant potential for enhancing power system reliability and promoting the integration of renewable energy sources. Nevertheless, the distributed nature of DR resources presents challenges in developing scalable optimization tools. This paper explores a novel data-driven approach in which DR resources are modeled through their aggregate forecasts using Inverse Optimization. The proposed method utilizes historical price-consumption data to deduce DR price-response behavior via a flexibility curve. The model is assessed within the Belgian single imbalance market context, where a Balance Responsible Party (BRP) employs the inferred flexibility curve to optimize its strategic imbalance positions by managing DR resources through suitable real-time price signals. The accuracy of the estimated flexibility provided by the proposed algorithm is evaluated by comparing it with the XGboost method. The results demonstrate that the model can effectively capture DR behavior and generate profit from providing balancing energy.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Energy and Industr