A Study on the Transmission Line Transient Protection Containing Static Synchronous Compensator

This paper focuses on the transient protection of transmission line with FACTS Devices;the principle and mathematical model of static synchronous compensator (STATCOM) has been analyzed. And feasible control strategy has been proposed considering the voltage source inverter (VSI) as a core part of the FACTS components. The simulation results verify the rightness using electromagnetic transient simulation software PSCAD/EMTDC to set up electromagnetic transient model.

Dynamic Setting Method of Assessment Indicators for Power Curves of Renewable Energy Sources Considering Scarcity of Reserve Resources

With the increasing proportion of renewable energy sources(RESs)in power grid,the reserve resource(RR)scarcity for correcting power deviation of RESs has become a potential issue.Consequently,the power curve of RES needs to be more rigorously assessed.The RR scarcity varies during different time periods,so the values of assessment indicators should be dynamically adjusted.The assessment indicators in this paper include two aspects,i.e.,deviation exemption ratio and penalty price.Firstly,this paper proposes a method for dynamically calculating the supply capacity and RR cost,primarily taking into account the operating status of thermal units,forecast information of RES,and load curve.Secondly,after clarifying the logical relationship between the degree of RR scarcity and the values of assessment indicators,this paper establishes a mapping function between them.Based on this mapping function,a dynamic setting method for assessment indicators is proposed.In the future,RES will generally be equipped with battery energy storage systems(BESSs).Reasonably utilizing BESSs to reduce the power deviation of RESs can increase the expected income of RESs.Therefore,this paper proposes a power curve optimization strategy for RESs considering self-owned BESSs.The case study demonstrates that the dynamic setting method of assessment indicators can increase the revenue of RESs while ensuring that the penalty fees paid by RESs to the grid are sufficient to cover the RR costs.Additionally,the power curve optimization strategy can help RESs further increase income and fully utilize BESSs to reduce power deviation.

Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration

The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen(P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub(EH) with both a P2H facility(electrolyzer) and a gas-to-power(G2P) facility(hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment(SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming(MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration(HWP).

Identification of charging behavior characteristic for large-scale heterogeneous electric vehicle fleet

This paper aims to accurately identify parameters of the natural charging behavior characteristic(NCBC)for plug-in electric vehicles(PEVs) without measuring any data regarding charging request information of PEVs. To this end, a data-mining method is first proposed to extract the data of natural aggregated charging load(ACL) from the big data of aggregated residential load. Then, a theoretical model of ACL is derived based on the linear convolution theory. The NCBC-parameters are identified by using the mined ACL data and theoretical ACL model via the derived identification model. The proposed methodology is cost-effective and will not expose the privacy of PEVs as it does not need to install sub-metering systems to gather charging request information of each PEV. It is promising in designing unidirectional smart charging schemes which are attractive to power utilities. Case studies verify the feasibility and effectiveness of the proposed methodology.

Optimal sizing of PV and battery-based energy storage in an offgrid nanogrid supplying batteries to a battery swapping station

Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fullycharged batteries to a battery swapping station(BSS)serving regional electric vehicles(EVs), it will help establish a structure for implementing renewable-energyto-vehicle systems. A capacity planning problem is formulated to determine the optimal sizing of photovoltaic(PV) generation and battery-based energy storage system(BESS) in such a nanogrid. The problem is formulated based on the mixed-integer linear programming(MILP)and then solved by a robust optimization approach. Flexible uncertainty sets are employed to adjust the conservativeness of the robust optimization, and Monte Carlo simulations are carried out to compare the performance of the solutions. Case studies demonstrate the merits of the proposed applications and verify the approach.

Joint Optimal Scheduling for Electric Vehicle Battery Swapping-charging Systems Based on Wind Farms

Insufficiencies in charging facilities limit the broad application of electric vehicles(EVs).In addition,EV can hardly represent a green option if its electricity primarily depends on fossil energy.Considering these two problems,this paper studies a battery swapping-charging system based on wind farms(hereinafter referred to as W-BSCS).In a W-BSCS,the wind farms not only supply electricity to the power grid but also cooperate with a centralized charge station(CCS),which can centrally charge EV batteries and then distribute them to multiple battery swapping stations(BSSs).The operational framework of the W-BSCS is analyzed,and some preprocessing technologies are developed to reduce complexity in modeling.Then,a joint optimal scheduling model involving a wind power generation plan,battery swapping demand,battery charging and discharging,and a vehicle routing problem(VRP)is established.Then a heuristic method based on the exhaustive search and the Genetic Algorithm is employed to solve the formulated NP-hard problem.Numerical results verify the effectiveness of the joint optimal scheduling model,and they also show that the W-BSCS has great potential to promote EVs and wind power.

Procedural simulation method for aggregating charging load model of private electric vehicle cluster

The usage of each private electric vehicle(PrEV)is a repeating behavior process composed by driving,parking,discharging and charging,in which PrEV shows obvious procedural characteristics.To analyze the procedural characteristics,this paper proposes a procedural simulation method.The method aggregates the behavior process regularity of the PrEV cluster to model the cluster’s charging load.Firstly,the basic behavior process of each PrEV is constructed by referring the statistical datasets of the traditional private non-electric vehicles.Secondly,all the basic processes are set as a simulation starting point,and they are dynamically reconstructed by several constraints.The simulation continues until the steady state of charge(SOC)distribution and behavior regularity of the PrEV cluster are obtained.Lastly,based on the obtained SOC and behavior regularity information,the PrEV cluster’s behavior processes are simulated again to make the aggregating charging load model available.Examples for several scenarios show that the proposed method can improve the reliability of modeling by grasping the PrEV cluster’s procedural characteristics.