A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

A cluster-autonomous partitioning algorithm in electrical power grid using Monte Carlo simulation

Power grid partitioning decomposes a large power grid into several clusters.Most of the existing partitioning methods suffer from a limitation that the buses within a cluster are severely topologically disconnected after partitioning in some cases.As a result,a cluster will inevitably be assigned to two or more power grid corporations.This assignment obstructs inner-cluster monitoring and control applications of the transmission system.To overcome the limitation,this paper proposes a multi-index power grid partitioning approach using Monte Carlo simulation guaranteeing cluster connectivity to ensure the cluster autonomy.A line-based binary coding technique is developed to ensure the cluster connectivity.Three partitioning indices are considered:the coherency,the cluster connectivity,and the number of clusters.Finally,the proposed partitioning method is applied to IEEE 9-bus system,IEEE 39-bus system and IEEE 145-bus system and compared with Fuzzy C-medoid(FCMdd)algorithm.

Effect of sample temperature on laser-induced semiconductor plasma spectroscopy

We investigate the temperature dependence of the emission spectrum of a laser-induced semiconductor（Ge and Si） plasma. The change in spectral intensity with the sample temperature indicates the change of the laser ablation mass. The reflectivity of the target surface is reduced as the sample is heated, which leads to an increase in the laser energy coupled to the surface of the sample and eventually produces a higher spectral intensity.The spectral intensities are enhanced by a few times at high temperatures compared with the cases at low temperatures. The spectral intensity of Ge is enhanced by 1.5 times at 422.66 nm, and 3 times at589.33 nm when the sample temperature increases from 50°C to 300°C. We can obtain the same emission intensity by a more powerful laser or by less pulse energy with a higher sample temperature. Based on experimental observations we conclude that the preheated sample can improve the emission intensity of laser-induced semiconductor plasma spectroscopy.