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Modern society is becoming more dependent on secure and reliable power energy and increasing consumption power energy simultaneously. Rising fuel prices and growing environmental damage motivate Generation companies to use renewable energy. In this regard, Microgrids are being considered to build a future power network system and are being implemented widely due to its various advantages. It is made more promising by connecting it in parallel with nonrenewable distributed generators (e.g. Micro turbine and Fuel cell). Modern society needs more reliable, secure, and safe power. A Rising number of natural disasters that caused large blackouts put change of structure of the current power system. This paper investigates the impact of Microgrids to enhance the power system resiliency. The impact of networked Microgrids and distributed generators to enhance resilience and using theirs effectively during and after outages are also considered in this paper.

Generation expansion planning (GEP) problem involves determining new power plants in terms of type, capacity and allocation for meeting future load demands. The GEP problem incorporates large number of constraints and it is a highly complex, large scale, non linear optimization problem. Large scale integration of Renewable Energy systems (RES) in GEP problem has always been averted by the high cost and poor availability rates of RES as compared to conventional fossil fuel fired power plants. However internalizing environmental externalities in GEP problem could help to promote large scale integration of RES. The proposed model in this paper examines the effect of internalizing externalities on the GEP problem. External cost values for China are evaluated using the unit damage costs of pollutants. The model has been implemented in MATLAB using Genetic Algorithm and is applied to a case study of one of the district power companies of China. The results show significant structural changes in favor of RES confirming that internalizing externalities can be used as a driving policy tool for large scale integration of RES.

With the development of Smart Grids worldwide, efforts have been focused on optimizing the role of Smart Grid in the present electrical system. The integration of renewable energy resources to the grid presents a great challenge since they are intermittent and vary constantly causing frequency fluctuations. Automatic Generation Control (AGC) solves this problem by keeping the frequency close to nominal value and maintaining the balance between generation and demand. AGC has been implemented in various softwares as an added functionality. Power Systems Analysis Toolbox (PSAT) is a MATLAB toolbox designed for power flow computations but it lacks AGC implementation. This paper presents AGC implementation on PSAT using Artificial Neural Networks (ANN) controller and PID controller. The goal is to optimize PSAT by adding extra functionalities to it. The AGC design is implemented on IEEE 14-bus system on PSAT. A comparison of ANN controller and PID controller is also presented. The results show successful addition of AGC to PSAT library. The AGC design helps to control the frequency, has high performance and can be extended to other power systems.