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In a previous paper, we have introduced a simulation and optimization framework for the integration of renewable generators into an electrical distribution network. The framework searches for the optimal size and location of the distributed renewable generation units (DG). Uncertainties in renewable resources availability, components failure and repair events, loads and grid power supply are incorporated. A Monte Carlo simulation–optimal power flow (MCS–OPF) computational model is used to generate scenarios of the uncertain variables and evaluate the network electric performance with respect to the expected value of the global cost ( ECG ). The framework is quite general and complete, but at the expenses of large computational times for the analysis of real systems. In this respect, the work of the present paper addresses the issue and introduces a purposely tailored, original technique for reducing the computational efforts of the analysis. The originality of the proposed approach lies in the development of a new search engine for performing the minimization of the ECG , which embeds hierarchical clustering analysis (HCA) within a differential evolution (DE) search scheme to identify groups of similar individuals in the DE population and, then, ECG is calculated for selected representative individuals of the groups only, thus reducing the number of objective function evaluations. For exemplification, the framework is applied to a distribution network derived from the IEEE 13 nodes test feeder. The results show that the newly proposed hierarchical clustering differential evolution (HCDE) MCS–OPF framework is effective in finding optimal DG-integrated network configurations with reduced computational efforts. [ABSTRACT FROM AUTHOR]

In future active distribution networks (ADNs), microgrids (MGs) may have the possibility to control the power dispatched to the ADN by coordinating the output power of their multiple renewable generation units and energy storage units (ESUs). In this way, each MG may support the active distribution network, while promoting the penetration of renewable energy sources in a rational way. In this paper, we propose a tie-line power flow control of a hybrid MG, including photovoltaic (PV) generator, small wind turbines (WT), and ESUs. Firstly, the structure of the hybrid PV/WT/ESU MG is presented. In this power architecture, the battery is directly connected to the PV side through a DC/DC converter, thus reducing the number of conversions. Secondly, a hierarchical control is proposed to coordinate all those elements of the MG, making the tie-line power flow constant for a period of time, e.g. 15 min. Also, a method to calculate the tie-line power flow to be exchanged between the MG and the ADN is explored, and a power ramp rate is given between different dispatch intervals. Finally, a simulation model of the hybrid MG is built and tested. Simulation results show that the proposed hierarchical control strategy can select the proper operational mode and achieve seamless transfer between different modes. It also presents power curtailment functionality when the difference between the WT/PV output power and tie-line exchanged power flow is too large. [ABSTRACT FROM AUTHOR]