Analysis Of The Impact Of The Energy Management Of Renewables And Electric Vehicles Integration On The Stability Of Multimode Microgrid

The increasing penetration of the renewables sources has larger impact on the stability of the microgrid. A number of results have shown that when the penetration of the PV or other renewables exceeds30%of the distribution grid, the grid may become unstable under certain conditions. Key questions are raised and need to be answered. Does the grid need any operating procedure? How can the PV provide the low voltage ride through services for the grid reliability and stability? How can the electric vehicles provide the transient voltage stability to the grid? How can the maximum affected load be served in emergency conditions? How can the electric vehicles be charged by choosing least energy price? How can the load balancing and load scheduling be accomplished for the safety of the distribution network?In order to answer the above questions and hedge against the above mentioned issues, first we seek low voltage ride through capability service and reactive power support to the grid during fault through the photovoltaic (PV) system. We considered necessary conditions provided by German Grid Codes for the low voltage ride through capability and reactive power support during fault without disconnecting the PV system for the sake of no compromise on the power quality and stability of the grid. We modeled the PV system in DIgSILENT Powerfactory and carried out different simulations at different short circuits levels and AC voltage support by varying the fault reactance and droop value respectively. The simulation results indicate that the proposed PV system has satisfied the German Grid Code requirements for low voltage ride through and reactive power support. Taking the lead from low voltage ride through capability and reactive power support during fault, it is important that the maximum affected load must be served during the fault for which we have considered microgrid reconfiguration problem such that continuity of supply must be retained for the affected load. The aim of microgrid reconfiguration algorithm is to sustain reliability, power quality and stability of the microgrid.Microgrid reconfiguration problem deals with improving the continuity of the power supply in the event of fault within power grid or the microgrid connected at the medium voltage distribution network. In case of a fault in power grid, intentional islanding through static switch is one possible solution while, the fault within the microgrid emphasizes microgrid reconfiguration to recover maximum affected loads in each isolated zone. In order to hedge the issue, we considered multiagent system based (MAS) approach in order to withstand stably and autonomously in the event of fault within microgrid. MAS approach includes negotiation agent (NA) for the entire microgrid and bus agent (BA) for each bus within each zone. NA is responsible for selecting a Dominant-BA from each zone and prioritizing the zones by using region weight coefficient (RWC) method. Mathematical modeling has been performed so that the zone having excessive power will recombine with the zone having lesser power for maintaining power quality of sensitive and less sensitive loads, while normal loads are shed. The results inferred from the mathematical modeling indicate that maximum loads can be recovered and power quality can be maintained by using region weight coefficient (RWC) method. Moreover, we were curious about energy management for the electric vehicles that may use real time pricing and optimize according to hourly demand response in a cost effective manner, for which we considered charging at least energy price to save money and limit the charging power for a specified time.We considered optimization of electric vehicles (EVs) charging to minimize the cost of charging and to reduce peak power drawn by EV loads in the microgrid. In order to hedge the issue, we considered charging at least energy price over total charging time. We performed mathematical modeling by defining a minimizing objective function such that minimization of total energy cost and spreading out the power equally over the charging time can be accomplished. The computational results indicate that controller stops as the price becomes high and calculates new optimized results and restarts when the electricity price becomes favorable. There is cause and effect relationship between increase in load due to increasing penetration of EV load that may lead to further degradation of power quality, voltage problems, and even damage the equipment if the system is not properly managed, for which energy supply and management system can be used for balancing and scheduling of loads.We considered optimization of total energy consumption and total energy cost of electric vehicle charging. This is accomplished in two steps, at first load balancing among the microgrid loads is performed by adopting game theoretic approach and at second step load scheduling is performed in which each EV tries to minimize the energy cost by charging at least energy price and spreading out power consumption equally over charging time. A distributed algorithm has been established in which each EV optimize itself as long as it knows the cost function and scheduled energy consumption of all other EVs. The results indicated that by adopting the load balancing and load scheduling scheme there will be decrease in total energy consumption and total energy cost, while the EV consume equal amount of energy in total time.The motor loads are random and have fluctuations in the characteristics which have significance impact on grid security. In order to analyze the impact of EV load access, complex load access and static load access on the transient voltage stability of grid we have defined transient voltage stability margin index by considering the induction motor slip. The transient voltage stability margin index is used as an indicator to measure the degree of stability of the distribution grid. The increase in load access of the above mentioned loads effect the slip of the induction motor which is directly related to transient voltage margin index in our research. First we considered the impact of increasing EV load access, complex load access and static load access separately on transient voltage stability margin index of the induction motor load. Secondly we considered the impact of increasing EV penetration rates with unity and0.9lagging power factor separately on transient voltage stability of induction motor load and finally we considered the impact of EV load penetration on the induction motor startup. The results indicate that impact of complex load access on transient voltage margin index is more dominant as compared to EV load access and static load access. As far as EV penetration is concerned the EV penetration with0.9power factor is more efficient in stabilizing the distribution system as compared to EV penetration with unity power factor. Moreover, during induction motor startup more and more EV penetration can help in improving the voltage.