The use of Plug-in Hybrid Electric Vehicles (PHEV) can be known as an efficient factor for reducing the pollution caused by fossil fuels. It is obvious that with increasing the number of these vehicles, charging stations are needed to be established on the network. Therefore, in this paper, the problem of locating fast charging stations for Plug-in Hybrid Electric Vehicles using a new Multi-agent Harmony Search Algorithm is completely studied. According to the fact that the load uncertainties caused by charging hybrid electric vehicles are an effective and important factor to determine the number and also suitable locations of charging stations, the Poison and normal distributions are here used for considering uncertainties about the number of hybrid electric vehicles per hour and the charging demand for each hybrid electric vehicle, respectively. To study the problem in this paper, first, 10,000 different scenarios are made per hour and then, using Latin Hypercube, the number of the scenarios of each hour is dropped to 10. Finally, a new Multi-Agent Harmony Search Algorithm is applied to reduce network losses in different scenarios. The obtained results show that determining the number and the suitable locations for vehicle charging stations can greatly reduce the risk of overloading in the network caused by charging hybrid electric vehicles Manuscript profile

Nowadays, the use of networked control system (NCS) technologies in modern power systems is on the rise owing to the expansion of electric energy distribution systems and the advent and development of new communication-based technologies. However, the modern network-based energy systems are constructed from some coupled subsystems interconnected via their states and share their information through the communication networks featuring inherent time delays. In this article, an efficacious multi-agent-based cooperative distributed economic model predictive control is developed to damp the frequency fluctuations and reduce the cost of consumed electricity in networked-based smart energy systems by considering communication network inherent delays. In this regard, a buffer-based moving horizon strategy with an estimator is suggested to estimate the own states of every sub-system and the coupled states, i.e., those that their information exchange among sub-systems and their values are not accessible due to communication time delays. Moreover, the boundedness of the estimation error and the stability of the closed-loop system are established by this method. The usability and proficiency of the suggested scheme are proved by applying the developed approach for an interconnected power grid. Manuscript profile

The generation rescheduling is one of the most important methods used in correctional congestion management, which has been the subject of many studies. In the deregulated environment, relieving congestion has a significant impact on the operation and security of the transmission system. Consequently, alleviation of transmission network congestion in all power systems is imperative. In addition, the cost is a top priority in all markets, both electrical and non-electrical. In this paper, the problem of managing congestion is solved using rescheduling (increasing or decreasing) of the active power output of the generators. However, the change in the active power generation imposes a cost depending on the prices offered by the generation companies. The objective is to reschedule the power generation of power plants in such a way as to minimize the congestion cost. The crow search optimization algorithm is employed to determine the optimal solution. Different constraints including those related to the network, transmission lines, and power plants are all modeled and considered in this study. Moreover, various contingencies related to line outage are taken into consideration to cause congestion and necessary measure are applied to relieve the congested lines with the least possible cost. In order to evaluate the accuracy and effectiveness of the proposed approach in finding the optimal solution, it is conducted on IEEE 30 and 57 bus test systems. The results obtained for the various cases studies indicate the superiority of the proposed method in comparison with other techniques presented in the literature. Manuscript profile