Abstarct: From the past until now, one of the most important issues for humanity has been energy. Energy supply in today's world is one of the main pillars of the development of any society so as not to harm their lives and nature. The use of renewable energy in the world is evolving to replace fossil fuels. Therefore, it is necessary to create a suitable alternative for these fuels to prevent environmental pollution. The use of wind and solar energy is a proposal that has been included in the general policies of the communities in order to lead a great change in the industry. In this thesis, in order to optimize and intelligently control the production and consumption of renewable energy along with its management, planning has been done to use wind and solar energy as distributed generation sources in the private sector on the one hand and to electric car charging stations with delivery and Receiving energy in the public sector, on the other hand, has received special attention. Then, with the participation of these two sections, their optimal and simultaneous placement is dealt with, which in the issue of optimization, the goal is to obtain the highest profit in these two sections. Electricity and load price uncertainties are considered and modeled using the two-point estimation method. The multi-objective backtracking search optimization algorithm, which is an edited algorithm under the compression crowding distance, has been used in the above simulation and its efficiency has been compared and evaluated with other algorithms, which shows better accuracy and performance. The results are simulated on two IEEE standard 9 and 33 bus networks in MATLAB software environment.