## 1 Introduction  
With the rapid development of the global economy in the 21 st century, the demand for energy in various countries is also increasing. The excessive use of traditional energy sources like petroleum and coal has caused serious environmental pollution. Under such circumstances, it is necessary to improve the development and utilization of existing non-renewable energy resources, develop and utilize new environmentally friendly energy resources, and provide necessary supplementary power and innovations to the existing energy system. Therefore, distributed generation (DG) has received extensive attention and support [1; 2; 3]. It is of great significance to vigorously develop distributed energy and give full play to the role of DG in the power grid [4; 5; 6; 7; 8]. At this stage, a lot of research work [9; 10; 11] has been done on the output of distributed generation considering uncertainties, including DG location and capacity, demand side response, network reconfiguration, power and voltage quality, etc. A control algorithm based on improved amplitude adaptive notch filter (AANF) is proposed for generation management of different energy sources in autonomous micro-grid. The main objective of the proposed modified AANF (MAANF)-based control algorithm is to control the flow of active and reactive powers among the different energy sources and the load, along with the regulation of the point of common coupling (PCC) voltages and mitigation of the source current harmonics [9]. The voltage-controlled oscillator (VCO) less phase-locked loop (PLL)-based control of voltage source converter was presented to improve power quality. Using the proposed control, the reactive power compensation, harmonics reduction and load balancing are carried out in the system [10]. A new attempt of utilizing the sunflower optimization (SFO) algorithm in solving the problem of optimal power flow (OPF) in the field of power systems was introduced in order to optimize the generating units' fuel cost under the system constraints. The SFO algorithm is used to minimize the fitness function and yields the best solutions of the problem [11]. A decision-making algorithm that has been developed for the optimum size and placement of DG units in distribution networks. The algorithm that is very flexible to changes and modifications can define the optimal location for a DG unit (of any type) and can estimate the optimum DG size to be installed, based on the improvement of voltage profiles and the reduction of the network's total real and reactive power losses [12]. An economic study is carried out to analyze the economic feasibility for the integration of flywheel energy storage systems (FESS) with a wind power plant. It was concluded that the installation of the FESS is only feasible with the government subsidy in renewable energy projects, if considering that installation costs would not be reduced more than 10% of the estimated value [13]. The impact of three different types of distributed generation (diesel generator, wind turbine and photovoltaic (PV)) on distribution networks' voltage profile and power losses is studied. The obtained results show that different types of DG influence differently the distribution network and that their precise location and size are vital in reducing power losses and improving the voltage stability [14]. Wind power output and photovoltaic output have seasonal and diurnal periodicity [15; 16]. Based on the daily and annual characteristics of wind and solar energy resources, a large number of scenarios need to be calculated and analyzed in order to comprehensively evaluate the feasibility and rationality of the planning and operation scheme. In power systems with large-scale distributed energy, if we can extract representative typical scenarios from a large number of historical resources data of distributed energy, then we can use typical scenario sets to reflect the changing characteristics of distributed energy in the cycle.