Blockchain-assisted virtual power plant framework for providing operating reserve with various distributed energy resources

The paradigm shift from a coal-based power system to a renewable-energy-based power system brings more challenges to the supply-demand balance of the grid.Distributed energy resources(DERs),which can provide operating reserve to the grid,are regarded as a promising solution to compensate for the power fluctuation of the renewable energy resources.Small-scale DERs can be aggregated as a virtual power plant(VPP),which is eligible to bid in the operating reserve market.Since the DERs usually belong to different entities,it is important to investigate the VPP operation framework that coordinates the DERs in a trusted man-ner.In this paper,we propose a blockchain-assisted operating reserve framework for VPPs that aggregates various DERs.Considering the heterogeneity of various DERs,we propose a unified reserve capacity evaluation method to facilitate the aggregation of DERs.By considering the mismatch between actual available reserve capacity and the estimated value,the performance of VPP in the operating reserve market is improved.A hardware-based experimental system is developed,and numerical results are presented to demonstrate the effectiveness of the proposed framework.

An Assessment of Flexibility Reserves in Stochastic Modeling at Multiple Timescales

Due to recent technological achievements,stochastic optimization,which inherently captures the uncertainty of intermittent resources,is being used to capture the variability and uncertainty of wind and solar resources.However,due to persistent computational limitations,it is not practical to consider all possible variable generation scenarios.As a result,a reduced number of most likely scenarios is usually considered.While this helps reduce the computational burden,it also leaves the system operator vulnerable to some risk.In order to address this issue,this paper aims at providing insight into using an explicit reserve requirement in a stochastic modeling framework in order to provide system operators with greater confidence in stochastic dispatch solutions.This is accomplished by simulating a modified version of the IEEE 118 bus system in a fully stochastic,multi-timescale framework with flexibility reserve requirements.Results show that utilizing a stochastic flexibility reserve requirement within the stochastic modeling framework offers the most reliability benefit.

Ensemble Wind Power Prediction Interval with Optimal Reserve Requirement

Wind power prediction interval(WPPI)models in the literature have predominantly been developed for and tested on specific case studies.However,wind behavior and characteristics can vary significantly across regions.Thus,a prediction model that performs well in one case might underperform in another.To address this shortcoming,this paper proposes an ensemble WPPI framework that integrates multiple WPPI models with distinct characteristics to improve robustness.Another important and often overlooked factor is the role of probabilistic wind power prediction(WPP)in quantifying wind power uncertainty,which should be handled by operating reserve.Operating reserve in WPPI frameworks enhances the efficacy of WPP.In this regard,the proposed framework employs a novel bi-layer optimization approach that takes both WPPI quality and reserve requirements into account.Comprehensive analysis with different real-world datasets and various benchmark models validates the quality of the obtained WPPIs while resulting in more optimal reserve requirements.

Distributed Stochastic Scheduling of Massive Backup Batteries in Cellular Networks for Operational Reserve and Frequency Support Ancillary Services

Base station(BS)backup batteries(BSBBs),with their dispatchable capacity,are potential demand-side resources for future power systems.To enhance the power supply reliability and post-contingency frequency security of power systems,we propose a two-stage stochastic unit commitment(UC)model incorporating operational reserve and post-contingency frequency support provisions from massive BSBBs in cellular networks,in which the minimum backup energy demand is considered to ensure BS power supply reliability.The energy,operational reserve,and frequency support ancillary services are co-optimized to handle the power balance and post-contingency frequency security in both forecasted and stochastic variable renewable energy(VRE)scenarios.Furthermore,we propose a dedicated and scalable distributed optimization framework to enable autonomous optimizations for both dispatching center(DC)and BSBBs.The BS model parameters are stored and processed locally,while only the values of BS decision variables are required to upload to DC under the proposed distributed optimization framework,which safeguards BS privacy effectively.Case studies on a modified IEEE 14-bus system demonstrate the effectiveness of the proposed method in promoting VRE accommodation,ensuring post-contingency frequency security,enhancing operational economics,and fully utilizing BSBBs'energy and power capacity.Besides,the proposed distributed optimization framework has been validated to converge to a feasible solution with near-optimal performance within limited iterations.Additionally,numerical results on the Guangdong 500 kV provincial power system in China verify the scalability and practicality of the proposed distributed optimization framework.

Day-ahead allocation of operation reserve in composite power systems with large-scale centralized wind farms

This paper focuses on the day-ahead allocation of operation reserve considering wind power prediction error and network transmission constraints in a composite power system.A two-level model that solves the allocation problem is presented.The upper model allocates operation reserve among subsystems from the economic point of view.In the upper model,transmission constraints of tielines are formulated to represent limited reserve support from the neighboring system due to wind power fluctuation.The lower model evaluates the system on the reserve schedule from the reliability point of view.In the lower model,the reliability evaluation of composite power system is performed by using Monte Carlo simulation in a multi-area system.Wind power prediction errors and tieline constraints are incorporated.The reserve requirements in the upper model are iteratively adjusted by the resulting reliability indices from the lowermodel.Thus,the reserve allocation is gradually optimized until the system achieves the balance between reliability and economy.A modified two-area reliability test system (RTS) is analyzed to demonstrate the validity of the method.

Monitoring iodine adsorption onto zeolitic-imidazolate framework-8 film using a separated-electrode piezoelectric sensor

In this work, a separated-electrode piezoelectric sensor（SEPS）, constructed by a naked quartz crystal mounted between two electrodes, is reported for applications in a corrosive gaseous phase. The response of SEPS was measured by an impedance analysis method. It was shown that SEPS has an excellent frequency stability because its quality factor is in the order of 10^5. The SEPS can be operated even with the electrode gap in air larger than 1 cm. Compared with a conventional quartz crystal microbalance, the resonant frequency of the SEPS is independent of the mass change in the electrode. The SEPS was applied to monitor the adsorption of iodine on quartz surface and zeolitic-imidazolate framework-8（ZIF-8） film as well as in the transfer of iodine between two ZIF-8 films. The SEPS offers the advantages of easy preparation, corrosion-resistant and convenience in combination with mass and optical measurements.