Research On The Distributed Optimization Method Of Energy Storage System In Microgrid

In microgrid,the general use of energy storage system is to meet the load or keep the power balance and frequency stability by charging and discharging.In the process of charging and discharging of battery energy storage,there is always a power loss.This paper uses the distributed network optimization to minimize the loss and maximize power of energy storage system.In the actual communication network,energy storage system will be very easily affected by some disturbances.That is to say,energy storage system can be in a state of non-ideal communication network,such as time-varying topology and channel disturbance.This paper is to iterate the input powers of energy storage units by using distributed gradient algorithm and keep the input powers convergence.At the same time,this paper does some simulations in several cases and compares to results before and after suppressing disturbance.The result tends to be convergent after suppressing disturbance.The simulation results show that the algorithm can suppress channel disturbance nicely and obviously.In addition,there is a condition that there is a shortage of distributed generation in microgrid.The use of the energy storage system is very cost-effective.It can save the cost effectively.In this setting,this paper analyzes the potential of ESSs to support the adequate operation of distribution networks by providing capacity services.Particularly,the ability of multiple ESSs to provide security of supply through a coordinated operation.The proposed solution is compared against traditional methods and assessed in the study: different demand conditions.In addition,a sensitivity analysis,regarding ESS power and energy capacity,is carried out.The results demonstrate that a coordinated operation of multiple ESSs can further support distribution network operators(DNOs)managing peaks of demand.The most striking result is the fact that a variation in energy capacity has a higher impact in the contribution that ESS can provide to reduce distribution peak demand.In winter,demand profile is typically more spikier comparatively to the demand profile in a summer day.Fundamentally,the difference between the peak and off-peak demand are larger in winter days,which indicates that ESS should be able to provide similar levels of peak demand reduction.