Research on Virtual DC Generator-Based Control Strategy of DCMicrogrid with Photovoltaic and Energy Storage

With the penetration of a large number of photovoltaic power generation units and power electronic converters,the DC microgrid shows low inertia characteristics,which might affect the stable operation of the microgrid in extreme cases.In order to enhance the“flexible features”of the interface converter connected to the DC bus,a control strategy of DCmicrogrid with photovoltaic and energy storage based on the virtual DC generator(VDCG)is proposed in this paper.The interface converters of the photovoltaic power generation system and the energy storage system simulates the inertia and damping characteristics of the DC generator to improve the stability of the DC bus voltage.The impedance ratio of DC microgrid was obtained by establishing the small-signal model of photovoltaic power generation system and energy storage system,and the Nyquist curves was applied to analyze the small-signal stability of the system.Finally,the simulation results were verified with MATLAB/Simulink.The results show that the proposed control strategy can slow down the fluctuation of bus voltage under the conditions of photovoltaic power fluctuation and load mutation,thus enhancing the system stability.

Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems

Microgrid with hybrid renewable energy sources is a promising solution where the distribution network expansion is unfeasible or not economical.Integration of renewable energy sources provides energy security,substantial cost savings and reduction in greenhouse gas emissions,enabling nation to meet emission targets.Microgrid energy management is a challenging task for microgrid operator(MGO)for optimal energy utilization in microgrid with penetration of renewable energy sources,energy storage devices and demand response.In this paper,optimal energy dispatch strategy is established for grid connected and standalone microgrids integrated with photovoltaic(PV),wind turbine(WT),fuel cell(FC),micro turbine(MT),diesel generator(DG)and battery energy storage system(ESS).Techno-economic benefits are demonstrated for the hybrid power system.So far,microgrid energy management problem has been addressed with the aim of minimizing operating cost only.However,the issues of power losses and environment i.e.,emission-related objectives need to be addressed for effective energy management of microgrid system.In this paper,microgrid energy management(MGEM)is formulated as mixedinteger linear programming and a new multi-objective solution is proposed for MGEM along with demand response program.Demand response is included in the optimization problem to demonstrate it’s impact on optimal energy dispatch and techno-commercial benefits.Fuzzy interface has been developed for optimal scheduling of ESS.Simulation results are obtained for the optimal capacity of PV,WT,DG,MT,FC,converter,BES,charging/discharging scheduling,state of charge of battery,power exchange with grid,annual net present cost,cost of energy,initial cost,operational cost,fuel cost and penalty of greenhouse gases emissions.The results show that CO_(2) emissions in standalone hybrid microgrid system is reduced by 51.60%compared to traditional system with grid only.Simulation results obtained with the proposed method is compared with various evolutionary algorithms to verify it’s effectiveness.

Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand

This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.