An increase in carbon emission which mostly caused by the transportation sector and electric power generation has been a hot topic nowadays in most countries in the world. To tackle this problem, the share of renewable energy use has been increased by up to 14% in the Netherlands. Moreover, the number of electric vehicles (EVs) on the road also reaches a total of 120,000 EVs in 2018. However, the high penetration of renewable energy sources (RESs) such as solar & wind power and the EVs charging in the distribution network could result in a severe problem. One of the solutions to avoid this problem is that switching the uncontrolled charging of EVs into a controlled charging or called as smart charging. Further, an integration between the EVs, RESs and the distribution grid could potentially lead to technical and economic benefits. The focus of this thesis is to develop an optimal power management system (PMS) between the EVs, PV system, and the distribution network. The goal of the power management system is to obtain the minimum operational cost while also considering the technical grid constraints, which subsequently could avoid the grid violation. The proposed power management system will be modeled in a mixed integer non-linear programming (MINLP) optimization problem and executed in General Algebraic Modelling System (GAMS) software. To evaluate the performance of the proposed power management system, a comparison between the with-grid and the no-grid constraints case will be performed through several case studies. This study shows that by implementing the proposed power management system of EVs charging from PV system considering the grid constraints, it could decrease the total operational cost remarkably by 18.16% - 214.08% when compared to the uncontrolled charging scheme. Besides, the grid problem caused by the uncontrolled charging process such as exceeding the allowable voltage deviation and the transformer rated power could be prevented. However, in comparison to the smart charging without considering the grid constraints, the operational cost is increased by 1.43% - 113.20%.