Service scheduling strategy for microservice and heterogeneous multi-cores-based edge computing apparatus in smart girds with high renewable energy penetration

The microservice-based smart grid service (SGS) organization and the heterogeneous multi-cores-based computing resource supply are the development direction of edge computing in smart grid with high penetration of renewable energy sources and high market-oriented. However, their application also challenges the service schedule for edge computing apparatus (ECA), the physical carrier of edge computing. In the traditional scheduling strategy of SGS, an SGS usually corresponds to an independent application or component, and the heterogeneous multi-core computing environment is also not considered, making it difficult to cope with the above challenges. In this paper, we propose an SGS scheduling strategy for the ECA. Specifically, we first present an SGS scheduling framework of ECA and give the essential element of meeting SGS scheduling. Then, considering the deadline and importance attributes of the SGS, a microservice scheduling prioritizing module is proposed. On this basis, the inset-based method is used to allocate the microservice task to the heterogeneous multi-cores to utilize computing resources and reduce the service response time efficiently. Furthermore, we design the scheduling unit dividing module to balance the delay requirement between the service with early arrival time and the service with high importance in high concurrency scenarios. An emergency mechanism (EM) is also presented for the timely completion of urgent SGSs. Finally, the effectiveness of the proposed service scheduling strategy is verified in a typical SGS scenario in the smart distribution transformer area

Does Financial Development Hamper or Improve the Resource Curse? Analysis Based on the Panel Threshold Effect Model

This paper analyzes the “resource curse” and “financial threshold effect” that may exist in China and then uses the data from 30 provinces from 2004 to 2018 as research samples. We used linear regression and nondynamic panel threshold models to analyze the financial threshold effects of the “resource curse” hypothesis and the “resource curse” phenomenon. At the same time, we divided the level of financial development to verify the robustness of the research conclusions in this paper. The study found the following: (1) There is a certain correlation between the abundance of resources and economic growth. Whether this can be seen as a “curse” or a “blessing” of resources is significantly related to the degree of financial development. (2) Whether financial development can alleviate the “resource curse” depends on the degree of financial development. In the extremely scarce stage of financial resources, the resource endowment effect is obvious, and the level of economic development in resource-based regions will be higher than in other regions; when the level of financial development is low (financial resources are not scarce and have not reached a reasonable level), the phenomenon of the “resource curse” appears; when the level of financial development is highly developed, economic development benefits more from financial development, and the effects of resource endowment decline. Only when financial development is at a reasonable level can resource endowments effectively raise the level of economic development

Durable freestanding hierarchical porous electrode for rechargeable zinc-air batteries

The development of freestanding bifunctional air cathodes for the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) is highly desirable for the next generation of flexible rechargeable metal-air batteries. It remains challenging to achieve efficient OER and ORR bifunctionality on a single lightweight and inexpensive electrode. In this article, a metal-free, and freestanding air cathode based on vertically aligned carbon nanotubes (VACNTs) functionalized with N, P heteroatoms doped carbon is first reported. In addition to the high catalytic activity caused by N, P heteroatoms doping, the importance of efficient gas diffusion and electron transfer provided by the VACNT-GF hierarchical structure is highlighted. The carbonization temperature has been identified to have pronounced effect on catalytic activity, and the samples with P-N bonds have smaller ORR and OER overpotentials, while the quantitative atomic ratio of either P or N has little effect on catalytic activity. The resulting air electrode achieved a high peak power density of 56 mW cm-2 at a current density of 120 mA cm-2, outperforming Pt/C- and IrO2-based rechargeable Zn-air batteries. The zinc-air battery assembled with the air electrode also showed good cyclability, which exceeded that of cells with the Pt/C//IrO2 catalyst. The increase of voltage difference between the charge and discharge platform was 0.2 V for the cell assembled with N,P-doped VACNT-based freestanding air cathode after 75 h of operation at 10 mA cm-2, which was less than half of that of cells with Pt/C//IrO2 catalyst. Impedance analysis further reveals the good performance results from the favorable mass transfer of the electrode.Ministry of Education (MOE)We gratefully acknowledge the National Natural Science Foundation of China for supporting this research through Grant No. 51502135 and the Singapore Ministry of Education for supporting this research through Grant AcRF Tier 1 (Reference No. RG103/16)

Assessment of commutation failure in HVDC systems considering spatial-temporal discreteness of AC system faults

Abstract This paper presents a novel commutation failure (CF) assessment method considering the influences of voltage magnitude drop, phase shift, and spatial-temporal discreteness of AC system faults. The commutating voltage-time area is employed to analyze the spatial-temporal discreteness of AC system faults causing CF in high-voltage direct current systems, and the influences of fault position and fault time on CF are revealed. Based on this, a novel CF criterion is proposed, further considering the influence of voltage phase shift and the spatial-temporal discreteness. Then this research develops a new CF assessment method, which does not rely on electromagnetic transient simulations. A real case from the China Southern Power Grid is used to verify the practicability of the proposed method by comparing with simulation results obtained using PSCAD/EMTDC

Study on frequency characteristics of receiving power system with large-scale offshore wind power generation

With the rapid development of offshore wind power and large-scale grid connection, the mechanical inertia and frequency regulation ability of the power system are greatly reduced, which seriously affects the frequency stability of the receiving end power grid. Aiming at the frequency stability analysis of large-scale offshore wind power connected to the receiving end power grid, this paper proposes a frequency response aggregation model which includes the frequency limiting controller (FLC) and the wind turbine generator (WTG) with frequency modulation (FM) capability. The rationality of model aggregation and the stability of transfer function are proved by theoretical analysis. Taking a southern province in China as an example, the effects of wind turbine generator access form and DC block capacity on different frequency response indexes are analyzed by using the proposed frequency response aggregation model. Through theoretical and simulation analysis, the correlation of system inertia, FM capacity and DC FLC capacity with frequency deviation nadir and quasi-steady state frequency index is obtained, and the relevant conclusions affecting frequency stability indexes are drawn. Finally, through the model simulation method, the improvement of the system frequency stability when the wind turbine provides inertia and primary FM support is analyzed. This paper concludes that when the wind power penetration is in the range of 10%∼40% and the wind power assisted frequency modulation capacity reaches 5% of the installed capacity, the minimum frequency of the system can be maintained above 49.5 Hz

A soft actor-critic deep reinforcement learning method for multi-timescale coordinated operation of microgrids

This paper develops a multi-timescale coordinated operation method for microgrids based on modern deep reinforcement learning. Considering the complementary characteristics of different storage devices, the proposed approach achieves multi-timescale coordination of battery and supercapacitor by introducing a hierarchical two-stage dispatch model. The first stage makes an initial decision irrespective of the uncertainties using the hourly predicted data to minimize the operational cost. For the second stage, it aims to generate corrective actions for the first-stage decisions to compensate for real-time renewable generation fluctuations. The first stage is formulated as a non-convex deterministic optimization problem, while the second stage is modeled as a Markov decision process solved by an entropy-regularized deep reinforcement learning method, i.e., the Soft Actor-Critic. The Soft Actor-Critic method can efficiently address the exploration–exploitation dilemma and suppress variations. This improves the robustness of decisions. Simulation results demonstrate that different types of energy storage devices can be used at two stages to achieve the multi-timescale coordinated operation. This proves the effectiveness of the proposed method.Published versionThe work was supported by Guangdong Provincial Key Laboratory of New Technology for Smart Grid Funded Project under Grant No. 2020b1212070025

Modeling of IEEE1588 on OPNET and Analysis of Asymmetric Synchronizing Error in Smart Substation

The IEEE1588 network time synchronization, matched with smart substation information network transmission, is be-coming the next generation advanced data synchronization of the smart substation. It is known that the inherent asym-metry error of the network synchronization approach in the smart substation is highlighted, which is concerned particu-larly. This paper models the synchronization process of the IEEE1588 based on the communication simulation software of OPNET Modeler. Firstly, it builds the models of master-slave clock, IEEE1588 protocol and network synchroniza-tion model, and analyzes the composition and influencing factors of the asymmetry error. Secondly, it quantitatively analyzes the influence of the synchronous asymmetric error of the IEEE1588 affected by the network status differences and the clock synchronization signal transmission path differences. Then its correction method is analyzed, in order to improve the IEEE1588 synchronization reliability and gives the solutions to its application in smart substation

A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process

Battery storage (BS) sizing problems for grid-connected microgrids (GCμGs) commonly use stochastic scenarios to represent uncertain natures of renewable energy and load demand in the GCμG. Though taking a large number of stochastic scenarios into consideration can deliver a relatively accurate optimal result, it can also highly deteriorate the computational efficiency of the sizing problem. To make an accuracy-efficiency trade-off, a computationally efficient optimization method to optimize the BS capacities based on the power exchanging process of the GCμG is proposed in this paper. According to the imbalanced power of the GCμG, this paper investigates the power exchanging process between the GCμG, BS and external grid. Motivated by the BS dynamics, a forward/backward sweep-based energy management scheme is proposed based on the power exchanging process. A heuristic two-level optimization model is developed with sizing BS as the upper-level problem and optimizing the operational cost of the GCμG as the lower-level problem. The lower-level problem is solved by the proposed energy management scheme and the objective function of the upper-level is minimized by the pattern search (PS) algorithm. To validate the accuracy and computational efficiency of the proposed method, the numerical results are compared with the mixed integer linear programming (MILP) method. The comparison shows that the proposed method shares similar accuracy but is much more time-efficient than the MILP method

Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded

Abstract As power to gas (P2G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically. With the intent of characterizing market behaviors of integrated electric power and natural gas networks (IPGNs) with P2G facilities, this paper establishes a steady-state model of P2G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow (SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network. The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2G facilities, will contribute more to renewable energy utilization and carbon emission reduction