Research On On-line Monitoring And Dispatching Of Power Distributed Equipment

In recent years,the crisis of global energy and the problem of environmental pollution have been highlighted,making the micro-grid one of the focus of attention.Most of the distributed power sources in micro-networks use renewable energy to generate electricity,the clean energy is accord with the strategic requirements of the state's sustainable development,at present,a lot of distributed power generation technology is very mature and is gradually commercialized,such as wind power,micro gas turbine,fuel cell,photovoltaic power generation,and so on.With the gradual maturity of micro-grid technology and the deepening of engineering application practice,the dispatching and economic operation of micro-grid is attracting more and more attention,and its economic dispatch problem needs to be solved urgently.This paper studies the two aspects of the monitoring of the operating state of the equipment and the optimization and scheduling of energy.Firstly,through the acquisition of distributed energy equipment operation data,using support vector machine clustering algorithm to determine the assessment of the state of the host computer and MATLAB Lab VIEW interaction can observe the running state of the equipment,which can guarantee the efficient operation of the equipment in normal working condition.Secondly,based on data collection and on-line monitoring,the output models of various power sources is established by taking the variety of distributed power sources,the power generation principles and environmental benefits into account in this paper.Using the optimization characteristics of particle swarm optimization(PSO),an economic scheduling model based on extended real time electricity price and user response is established on the premise of considering the demand side.At the same time,the feasibility of the optimization model and the scheduling scheme is verified by an example.The first day before scheduling in 15 min,the day is divided into 96 periods,with the lowest cost of power generation and electricity costs as the goal,the use of reasonable scheduling strategy for scheduling each time period.Next is the weekly optimal scheduling.We select one week in each season,and divide it into 168 time periods per week.We should consider the influence of different seasons on the output of each unit,and give different scheduling schemes based on the economic optimization.In the grid connected mode,we should take full account of the role of the battery,and reasonably purchase electricity from the distribution network.We can find the optimal solution through particle swarm optimization,and allocate the output of each unit in different periods.Compared with the original data,the new scheduling strategy is less expensive on the basis of the power consumption.The results show that: when the real time electricity price is low,the electricity will be supplied to the system,and at the same time,the battery will be used for energy storage,and the full use of distributed energy will be generated during the peak period of electricity consumption.If we meet the constraints,we can access the battery pack and achieve the role of peak load shifting and valley filling;and it is better to adopt the real time price scheme than the average price scheme,and increase the purchase ratio of the electricity price period can effectively reduce the cost of electricity purchase.