A Game-Theoretic Loss Allocation Approach in Power Distribution Systems with High Penetration of Distributed Generations

Allocation of the power losses to distributed generators and consumers has been a challenging concern for decades in restructured power systems. This paper proposes a promising approach for loss allocation in power distribution systems based on a cooperative concept of game-theory, named Shapley Value allocation. The proposed solution is a generic approach, applicable to both radial and meshed distribution systems as well as those with high penetration of renewables and DG units. With several different methods for distribution system loss allocation, the suggested method has been shown to be a straight-forward and efficient criterion for performance comparisons. The suggested loss allocation approach is numerically investigated, the results of which are presented for two distribution systems and its performance is compared with those obtained by other methodologies

Fueling the seaport of the future: Investments in low‐carbon energy technologies for operational resilience in seaport multi‐energy systems

Abstract The ability to withstand and recover from disruptions is essential for seaport energy systems, and in light of the growing push for decarbonization, incorporating clean energy sources has become increasingly imperative to ensure resilience. This paper proposes a resilience enhancement planning strategy for a seaport multi‐energy system that integrates various energy modalities and sources, including heating, cooling, hydrogen, solar, and wind power. The planning strategy aims to ensure the reliable operation of the system during contingency events, such as power outages, equipment failures, or extreme weather incidents. The proposed optimization model is designed as a mixed‐integer nonlinear programming formulation, in which McCormick inequalities and other linearization techniques are utilized to tackle the model nonlinearities. The model allocates fuel cell electric trucks (FCETs), renewable energy sources, hydrogen refueling stations, and remote control switches such that the system resilience is enhanced while incorporating natural‐gas‐powered combined cooling, heating, and power system to minimize the operation and unserved demand costs. The model considers various factors such as the availability of renewable energy sources, the demand for heating, cooling, electricity, and hydrogen, the operation of remote control switches to help system reconfiguration, the travel behaviour of FCETs, and the power output of FCETs via vehicle‐to‐grid interface. The numerical results demonstrate that the proposed strategy can significantly improve the resilience of the seaport multi‐energy system and reduce the risk of service disruptions during contingency scenarios

Coordinated Planning of Electric Vehicle Charging Infrastructure and Renewables in Power Grids

This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual electric vehicle (EV) charging behaviours are modeled considering EV customers adopting smart charging services as the main charging method and those using fast charging, super fast charging and battery swapping services as a complementary charging approach. Next, EV aggregation and the associated system economic dispatch model are built. A novel model predictive control (MPC) learning approach is then proposed to iteratively learn the correlation between different types of EV charging loads and the EV interactions with renewables and other generating units in modern power grids of the future. The simulation results demonstrate that the proposed approach can be used to quantify the ratio of different types of charging loads in a region and strategically guide on the integration of EVs and renewables to achieve the clean energy transition goals. The proposed framework can also be used to decide charging capacity needs in a charging demand zone