Multi-timescale robust dispatching for coordinated automatic generation control and energy storage

The increasing penetration of renewable energy into power grids is reducing the regulation capacity of automatic generation control(AGC).Thus,there is an urgent demand to coordinate AGC units with active equipment such as energy storage.Current dispatch decision-making methods often ignore the intermittent effects of renewable energy.This paper proposes a two-stage robust optimization model in which energy storage is used to compensate for the intermittency of renewable energy for the dispatch of AGC units.This model exploits the rapid adjustment capability of energy storage to compensate for the slow response speed of AGC units,improve the adjustment potential,and respond to the problems of intermittent power generation from renewable energy.A column and constraint generation algorithm is used to solve the model.In an example analysis,the proposed model was more robust than a model that did not consider energy storage at eliminating the effects of intermittency while offering clear improvements in economy and efficiency.

Initial Exploration of Wind Farm Cluster Hierarchical Coordinated Dispatch Based on Virtual Power Generator Concept

China has made many strides in large-scale development and centralized integration of wind power in recent years.The wind power penetration of some regions has reached a high level,which brings significant challenges for power system dispatch due to the inherent variability and uncertainty of wind resources.To increase the dispatch capabilities of wind power generation,the spatial smoothing effect among adjacent wind farms needs to be fully utilized.This paper presents the concept of hierarchical coordinated dispatch for wind power based on a new concept of a virtual power generator.The spatial smoothing effect of wind power is analyzed first.Next,the virtual power generator method of a wind farm cluster is defined and established.Then,the hierarchical coordinated dispatch mode is compared with an existing wind power dispatch mode for individual wind farms.Finally,the proposed concept is implemented on a simulation case to demonstrate applicability and effectiveness.

Optimal Active Power Dispatching of Microgrid and Distribution Network Based on Model Predictive Control

First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time scale optimal scheduling of the microgrid based on Model Predictive Control（MPC） is then studied, and the optimized genetic algorithm and the microgrid multi-time rolling optimization strategy are used to optimize the datahead scheduling phase and the intra-day optimization phase. Next, based on the three-tier coordinated scheduling architecture, the operation loss model of the distribution network is solved using the improved branch current forward-generation method and the genetic algorithm. The optimal scheduling of the distribution network layer is then completed. Finally, the simulation examples are used to compare and verify the validity of the method.

Convexification Technique for Optimal Thermal-Wind-Photovoltaic Coordination Dispatch Incorporating an Energy Storage System

This paper proposes a solution to implementing acoordinated optimal day-ahead dispatch in a hybrid thermalwind-photovoltaic power system incorporating an energy storagesystem (ESS). Our aim is to minimize total generation costand restrain the frequent change of ESS charging/dischargingstatus while meeting a series of system operating constraints,including a proposed coordinated dispatch strategy for thepurpose of reducing thermal power fluctuations. A novel twostage convexification technique (TSCT) is designed and leveragedto convert the original non-convex optimal day-ahead dispatchmodel, without taking into account the constraints of the proposed coordinated dispatch strategy into two convex quadraticprogramming problems. When introducing the constraint ofthe coordinated dispatch strategy, the corresponding inequalityconstraints are transformed into a series of linear equalityconstraints, after which the original optimal day-ahead dispatchmodel can be solved by the TSCT mentioned above. Finally,numerical simulations and comparative analysis are performedon the IEEE standard test systems to verify the validity andeffectiveness of the proposed model and method.

Multi-objective optimization strategy for distribution network considering V2Genabled electric vehicles in building integrated energy system

Based on the large-scale penetration of electric vehicles(EV)into the building cluster,a multi-objective optimal strategy considering the coordinated dispatch of EV is proposed,for improving the safe and economical operation problems of distribution network.The system power loss and node voltage excursion can be effectively reduced,by taking measures of time-of-use(TOU)price mechanism bonded with the reactive compensation of energy storage devices.Firstly,the coordinate charging/discharging load model for EV has been established,to obtain a narrowed gap between load peak and valley.Next,a multi-objective optimization model of the distribution grid is also defined,and the active power loss and node voltage fluctuation are chosen to be the objective function.For improving the efficiency of optimization process,an advanced genetic algorithm associated with elite preservation policy is used.Finally,reactive compensation capacity supplied by capacitor banks is dynamically determined according to the varying building loads.The proposed strategy is demonstrated on the IEEE 33-node test case,and the simulation results show that the power supply pressure can be obviously relieved by introducing the coordinated charging/discharging behavior of EV;in the meantime,via reasonable planning of the compensation capacitor,the remarkably lower active power loss and voltage excursion can be realized,ensuring the safe and economical operation of the distribution system.