Research On Energy Optimal Dispatching Method Of Intelligent Community Based On Time-of-Use Electricity Price

With the gradual improvement in the quality of family life,intelligent communities have received widespread attention and research from all sectors of society.The construction of smart communities is also gradually diversifying to meet the different electricity needs of residents.However,the use of various smart appliances has caused a rapid increase in energy demand and carbon emissions.Energy management is an important component of the comprehensive service and management of smart communities.In order to make smart communities run more scientifically,this paper delves into energy optimisation and scheduling strategies,and carries out experimental verification and analysis in terms of both load curves and energy consumption costs,with the main elements including:(1)Constructs the energy structure of a smart community,builds mathematical models of different types of power generation and consumption equipment in the power system and describes their operating characteristics.The energy structure of the smart community is divided into the supply side and the load side,and the underlying theories used in the study are presented separately.The supply side provides sufficient energy for the household by means of renewable energy generation,which consists of photovoltaics,wind power and hydrogen-fired turbines.Energy storage devices are important in the realisation of the multienergy complementarity as a way of buffering the pressure on household electricity consumption.While considering the load-side demand response,smart appliances are divided into controllable and uncontrollable loads depending on the nature of the load’s work.(2)The incentive role of time-sharing tariffs in smart cells is analysed.The relationship and differences between P2 G technology and P2H(Power-to-hydrogen)technology are then further analysed and the feasibility of applying P2 H technology to smart cells is analysed in terms of economics.The stochastic nature of electric vehicles is further investigated by simulating the load profile of electric vehicles through the Monte Carlo method.Finally,the cost of electricity consumption for the whole dispatch cycle is calculated using a time-ofuse tariff-based electricity costing approach.(3)Based on the smart cell energy framework designed in this paper,an energy optimisation scheduling strategy is proposed to improve the production and application of hydrogen energy in the energy scheduling process.The multi-objective optimal scheduling objective function of the smart cell and the constraints for the safe operation of the system are established.Four typical experimental environments are considered and the CPLEX solver is invoked to calculate the load curve and cost curve for each time period in the dispatching cycle under different experimental environments.The study proves that the energy structure of the smart district and the optimal energy dispatching strategy based on time-of-use tariffs established in this paper can significantly reduce the peak-to-valley difference in electricity load,electricity cost and reduce carbon emissions.