Related papers: Predictive Optimization of Hybrid Energy Systems w…
Since hydrogen has many advantages (e.g., free pollution, extensive sources, convenient storage and transportation), hydrogen-based multi-energy systems (HMESs) have received wide attention. However, existing works on the optimal operation…
Heat pump and thermal energy storage (HPTES) systems, which are widely utilized in modern buildings for providing domestic hot water, contribute to a large share of household electricity consumption. With the increasing integration of…
This paper presents an energy-optimal hybrid control framework for thermal management of heat-pump battery electric vehicles (BEVs). The controller coordinates the compressor, coolant pumps, and cabin blower across the coupled refrigerant,…
The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such…
This paper investigates battery preheating before fast charging, for a battery electric vehicle (BEV) driving in a cold climate. To prevent the battery from performance degradation at low temperatures, a thermal management (TM) system has…
The increasing penetration of renewable energy necessitates improved power system flexibility, driving the deployment of independent energy storage operators (ESOs). Existing research extensively investigates capacity sizing for price-taker…
The modeling of multi-energy systems (MES) is the basic task of analyzing energy systems integration. The variable energy efficiencies of the energy conversion and storage components in MES introduce nonlinearity to the model and thus…
This paper proposes a coordinated home energy management system (HEMS) architecture where the distributed residential units cooperate with each other to achieve real-time power balancing. The economic benefits for the retailer and…
The recent development of advanced machine learning methods for hybrid models has greatly addressed the need for the correct prediction of electrical prices. This method combines AlexNet and LSTM algorithms, which are used to introduce a…
In this paper we provide non-simultaneous charging and discharging guarantees for a linear energy storage system (ESS) model for a model predictive control (MPC) based home energy management system (HEMS) algorithm. The HEMS optimally…
Home energy management systems (HEMSs) are expected to become a crucial part of future smart grids. However, there is a limited number of studies that comprehensively assess the potential economic benefits of HEMS for consumers under real…
Effective power and thermal management are essential for ensuring battery efficiency, safety, and longevity in Connected and Automated Electric Vehicles (CAEVs). However, real-time implementation is challenging due to the multi-timescale…
Incorporating Renewable Energy Sources (RES) incurs a high level of uncertainties to electric power systems. This level of uncertainties makes the conventional energy management methods inefficient and jeopardizes the security of…
Energy management of plug-in Hybrid Electric Vehicles (HEVs) has different challenges from non-plug-in HEVs, due to bigger batteries and grid recharging. Instead of tackling it to pursue energetic efficiency, an approach minimizing the…
This Ph.D. thesis deals with the optimization of several renewable energy resources development as well as the improvement of facilities management in oceanic engineering and airports, using computational hybrid methods belonging to AI to…
This study addresses the challenges of energy deficiencies and high impact low probability (HILP) events in modern electrical grids by developing resilient microgrid energy management strategies. It introduces a sliding Model Predictive…
The energy and thermal management systems of hybrid electric vehicles (HEVs) are inherently interdependent. With the ongoing deployment of intelligent transportation systems (ITSs) and increasing vehicle connectivity, the integration of…
Latent heat thermal energy storage (LHTES) systems are compelling candidates for energy storage, primarily owing to their high storage density. Improving their performance is crucial for developing the next-generation efficient and cost…
Environmentally-powered computer systems operate on renewable energy harvested from their environment, such as solar or wind, and stored in batteries. While harvesting environmental energy has long been necessary for small-scale embedded…
The optimal selection, sizing, and location of small-scale technologies within a grid-connected distributed energy system (DES) can contribute to reducing carbon emissions, consumer costs, and network imbalances. This is the first study to…