Multi-agent Electricity Markets and Smart Grids Simulation with Connection to Real Physical Resources

The increasing penetration of distributed energy sources, mainly based on renewable generation, calls for an urgent emergence of novel advanced methods to deal with the associated problems. The consensus behind smart grids (SGs) as one of the most promising solutions for the massive integration of renewable energy sources in power systems has led to the development of several prototypes that aim at testing and validating SG methodologies. The urgent need to accommodate such resources require alternative solutions. This chapter presents a multi-agent based SG simulation platform connected to physical resources, so that realistic scenarios can be simulated. The SG simulator is also connected to the Multi-Agent Simulator of Competitive Electricity Markets, which provides a solid framework for the simulation of electricity markets. The cooperation between the two simulation platforms provides huge studying opportunities under different perspectives, resulting in an important contribution to the fields of transactive energy, electricity markets, and SGs. A case study is presented, showing the potentialities for interaction between players of the two ecosystems: a SG operator, which manages the internal resources of a SG, is able to participate in electricity market negotiations to trade the necessary amounts of power to fulfill the needs of SG consumers.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement N. 641794 (project DREAM-GO). It has also received FEDER Funds through the COMPETE program and National Funds through FCT under the project UID/EEA/00760/2013. The authors gratefully acknowledge the valuable contribution of Bruno Canizes, Daniel Paiva, Gabriel Santos and Marco Silva to the work presented in the chapter.info:eu-repo/semantics/publishedVersio

Distributed Robust Model Predictive Control-Based Energy Management Strategy for Islanded Multi-Microgrids Considering Uncertainty

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 51907031); 10.13039/100008398-Villum Fonden (Grant Number: 25920); Guangdong Basic and Applied Basic Research Foundation (Grant Number: 2021A1515410009)

Wind-pv-thermal power aggregator in electricity market

This paper addresses the aggregation of wind, photovoltaic and thermal units with the aim to improve bidding in an electricity market. Market prices, wind and photovoltaic powers are assumed as data given by a set of scenarios. Thermal unit modeling includes start-up costs, variables costs and bounds due to constraints of technical operation, such as: ramp up/down limits and minimum up/down time limits. The modeling is carried out in order to develop a mathematical programming problem based in a stochastic programming approach formulated as a mixed integer linear programming problem. A case study comparison between disaggregated and aggregated bids for the electricity market of the Iberian Peninsula is presented to reveal the advantage of the aggregation

Fast, superfast, and ultra-superfast Intelligent and Smart Charging Solutions for Electric Vehicles

To Promote and meet the projected levels of electric vehicle (EV) penetration, the development of charging infrastructure, i.e., both slow charging and dc-fast charging, is essential. Slow/onboard chargers pose weight, efficiency, and thermal management challenges to the designers, while the off-board fast/superfast/ultra-superfast chargers pose efficiency, power rating, and control challenges. In particular, the installation of dc fast chargers (including fast/superfast/ultra-superfast) is also dictated by the impact on the utility grid and the existing loads. New installation or retrofitting of the existing infrastructure is another significant investment challenge jointly explored by stakeholders, utility companies, and car/charger manufacturers. Another primary concern is battery life management limiting the charging current intake by the EV battery.Scopu