Microgrid Economic Performance Optimization When Incorporating Battery Storage And Demand Response

Energy crisis, environmental pollution and higher reliability of power supply arepushing forward the transformation of tomorrow’s grid, smart grid. Distributedgenerators, treated as alternative energy, are ushering its development boom, especiallyfor the PV, wind power, fuel cell, gas turbine and battery storage technologies.Researches have indicated the effectiveness of incorporating the distributed generatorsin the form of micro grid when unleashing their potentials. In order to promote theirfurther integration into the main grid, its economy stands to be critical.The economy of micro grid is not only accounted by its encompassed facilities butalso closely correlated with the market environment, such as pricing mechanism, fuelprice, feed-in tariff and so on. From the perspective of the model, it can be deemed asa mixed integer programing involving unit commitment problem, whereGAMS/CPLEX solver is deserved to be employed. Given the fact of advancing batterystorage techniques and pressing demand side management plan, this paper exhaustivelyconducted an economic analysis with the consideration of above-mentioned modals.Initially, the models regarding operating environment and distributed generatorswere established together with a general presentation of GAMS. Secondly, a modelembodying the battery storage system was formulated and the study was spanned fromunit output, trading behavior, state of charge, load curve problem to running costconfiguration. At the same time, return on investment analysis for the application ofbattery is analyzed, so is the optimal capacity section strategy. As far as demandresponse plan is concerned, the residential load was classified in three categories whereelectric vehicle charging is assumed as transferable load. Afterwards, the modespertaining to the transferable and controllable loads were put forward. Subsequently, amulti-angle investigation was casted, in particular to the transferable load redistributionand controllable load reduction. In addition, the influence of demand response on thedistribution network was highlighted. Finally, in order to unveil the collective action ofdemand response and battery storage, a corresponding model was thus developed, where multiple comparative analysis respecting purchasing behavior, selling activity,and load curve transformation, operating and saved cost in both summer and winterwere mirrored.In conclusion, micro grid favors to give priority to exploit the renewable energies.During the low price period, the demand is largely satisfied by purchasing from themain grid, as the price goes higher, the distributed generators are started consecutivelydepending on its generational cost. In case of battery storage system utilized, runningcost is decreased, a remarkable performance in summer. The load curve is partiallysmoothed, that is to say, peak load shaving and valley filling. In terms of its investment,a variety of factors are required to be concerned, including the cost price, life spanning,interest rate, electricity price, etc.. In the circumstance of demand response activated,the cost is apparently cut down, especially in summer, the load curve is significantlystabilized. As the load is endowed with the trait of dynamism, it will be quite beneficialfor deferring distribution network upgrade, behaving as a referential element for futurenetwork plan and design.