Research On Load Optimal Scheduling Of Residents In Smart Community Considering New Energy

In recent years,as people start to pursue more comfortable,intelligent and convenient living environment,intelligent community arises at the historic moment,The development of smart grid has attracted wide attention of intelligent community.How to combine intelligent community and the demand response has been a prospective research problems.The power shortage and the traditional energy exhaustion has been threatening the sustainable development of society,and new energy is the clean energy that is renewable and pollution-free.The massive use of new energy has been widely expected.The residential side has became the core of smart grid's development.The purpose of this paper is to schedule intelligent household electricity equipment and optimize new energy allocation plan,it is combined with the user demand side response to realize the load dispatching optimal scheme.Thus,the efficiency of energy utilization can be improved,peak load can be shifted and the goal of reducing the cost of electricity for community users also can be reduced.First of all,this paper introduced the GridLAB-D's main modules and functions in detail,it's superior performance can analysis millions of independent equipment's running status at the same time,which is very suitable for modeling a smart community.Then,this paper studied the feasibility of the residents participate in demand response from response mode,response cost and responsiveness.Example analysis proved that optimizing strategy can optimize the use of new energy sources.and alleviating the social electricity pressure.Secondly,this paper studied the optimal scheduling of intelligent household electrical equipment considering new energy.The new energy and smart home are the inevitable trend of future development,which attracted the attention from home and abroad.Base on a photovoltaic power generation systems and wind power generation system incorporating into the intelligent household,this paper formulated a residential load optimization model,and also modeling interruptible,uninterruptible and time-varying load.The purpose of the model is to minimize the cost and maximize consumer's comfort.And using the SCIP solver in the Yalmip toolbox and with inconvenience cost coefficient to solve it.This paper also analyzed the influence on the calculation result when setting different inconvenience cost coefficient.In the practical application,consumers can choose varying inconvenience cost coefficient according to their preferences.The simulation results show that the model is feasible and effective,which provides a new idea for the optimal schedule of household appliances.Finally,this paper studied allocation strategy of the community level renewable energy which merges into a smart community's electric power system,and then models of the centralized intelligent community and the distributed smart community load scheduling is formulated.An improved cross entropy optimization technique is proposed to compute such a allocation strategy,which makes the optimization process more efficient.Based on different allocated factors,different smart community load scheduling scheme can be computed,therefore,finding the most appropriate allocation factors can use new energy in reason,which is also integrated with smart home scheduling.The simulation results show the effectiveness and efficiency of the allocation strategy of the community level renewable energy.The work can provide a reference for the renewable energy allocation strategy and load scheduling scheme in smart community.