Determining the Minimal Power Capacity of Energy Storage to Accommodate Renewable Generation

The increasing penetration of renewable generation increases the need for flexibility to accommodate for growing uncertainties. The level of flexibility is measured by the available power that can be provided by flexible resources, such as dispatachable generators, in a certain time period under the constraint of transmission capacity. In addition to conventional flexible resources, energy storage is also expected as a supplementary flexible resource for variability accommodation. To aid the cost-effective planning of energy storage in power grids with intensive renewable generation, this study proposed an approach to determine the minimal requirement of power capacity and the appropriate location for the energy storage. In the proposed approach, the variation of renewable generation is limited within uncertainty sets, then a linear model is proposed for dispatchable generators and candidate energy storage to accommodate the variation in renewable generation under the power balance and transmission network constraints. The target of the proposed approach is to minimize the total power capacity of candidate energy storage facilities when the availability of existing flexible resources is maximized. After that, the robust linear optimization method is employed to convert and solve the proposed model with uncertainties. Case studies are carried out in a modified Garver 6-bus system and the Liaoning provincial power system in China. Simulation results well demonstrate the proposed optimization can provide the optimal location of energy storage with small power capacities. The minimal power capacity of allocated energy storage obtained from the proposed approach only accounts for 1/30 of the capacity of the particular transmission line that is required for network expansion. Besides being adopted for energy storage planning, the proposed approach can also be a potential tool for identifying the sufficiency of flexibility when a priority is given to renewable generation

Supplementary damping control of VSC-HVDC transmission system using a novel heuristic dynamic programming

Inter-area oscillation is a main challenge for secure and stable operation of large-scale interconnected AC/DC power system. In this paper, an innovative adaptive dynamic programming approach, namely goal representation heuristic dynamic programming (GrHDP), was proposed to design supplementary damping controller (SDC) of voltage source converter HVDC (VSC-HVDC) transmission system to suppress inter-area oscillation in large-scale AC/DC power system. Based on the two neural networks structure of HDP, GrHDP developed a new goal representation network, able to automatically generate internal adaptive reward signal to facilitate better mapping between system state and control action. Therefore, GrHDP-SDC could significantly improve dynamic performance of power system. Not necessarily knowing exact mathematic model of the power system, GrHDP-SDC possessed quick learning and universal control characteristics and strong adaptability, superior to conventional lead-lag SDC. Case study was performed based on a two-area four-machine power system with VSC-HVDC transmission line. Conventional lead-lag SDC and HDP-SDC were also studied for comparison. Simulation results show that the proposed GrHDP-SDC has better performance in damping inter-area oscillation than that of conventional lead-lag SDC and HDP-SDC in a wide range of system operating conditions

An improved two-stage optimization for network and load recovery during power system restoration

Network and load recovery (NLR)during power system restoration is a multi-step mixed-integer nonlinear programming (MINP)problem. The NLR is difficult to be solved as it is NP-hard. Thus, NLR is commonly solved step by step, which is short-sighted and will result in longer restoration time. To obtain a far-sighted NLR plan, this paper proposes an improved two-stage optimization method for NLR. The first stage adopts a mixed-integer linear programming (MILP)model to obtain optimal solutions of integer variables in NLR, namely the load pick-up schedules and transmission line charging schedules. Then in the second stage, a continuous non-linear optimization method based on AC power flow with frequency constraints and load model is established to minimize the restoration duration of the plan generated in the first stage step by step. Case studies are undertaken on a 10-machine 39-bus system and Southeast Hubei Provincial power system of China. Simulation results indicate that the restoration plan obtained from the improved two-stage optimization method is highly effective, while the computational efficient meets the intensive need for restoration scheduling after blackouts

An Improved Multi-Infeed Effective Short-Circuit Ratio for AC/DC Power Systems with Massive Shunt Capacitors Installed

The multi-infeed effective short-circuit ratio (MESCR) is widely used in indicating the strength of multi-infeed AC/DC power systems. However, when the widely used MESCR was adopted to evaluate the stability margin of the Eastern China Grid including three infeed ultra-high-voltage DC (UHVDC) and five high-voltage DC transmission lines in 2016, the MESCR result indicated the system was strong enough but in fact occasionally collapses after the N-1 contingency. To determine the reason for this conflict, this paper theoretically analyzes the limitations of the existing MESCR. The theoretical analysis reveals that when a large amount of capacitor compensations are concentratively installed in the system, the conventional MESCR will not be able to reflect the capacitor compensations’ influence on the system stability, and no matter how many capacitors are installed or where the capacitors are installed, the MESCR almost retains the same value; namely, the MESCR is saturated in such systems. To address the saturation problem of conventional MESCR, this paper proposes an improved multi-infeed effective short-circuit ratio (IMESCR) which considers the influences of all capacitor compensations by converting all capacitors installed throughout the system to virtual capacitors at the DC inverter station. Case studies are carried out based on the New England 39-bus system and the Eastern China Grid, respectively. The simulation results verify the theoretical analysis of the MESCR’s limitations in evaluating the stability of power systems with massive capacitors installed, and proves that the proposed IMESCR could accurately indicate the strength of AC/DC power systems. Therefore, the proposed IMESCR provides a new index for evaluating the stability margin of power systems with massive capacitor compensations installed

The role of TOP2A in immunotherapy and vasculogenic mimicry in non-small cell lung cancer and its potential mechanism

Abstract Type IIA topoisomerase (TOP2A) is significantly associated with malignant tumor development, invasion, treatment and its prognosis, and has been shown to be a therapeutic target against cancer. In contrast, the role of TOP2A in the immunotherapy of non-small cell lung cancer as well as in Vasculogenic mimicry (VM) formation and its potential mechanisms are unclear. The aim of this study was to investigate the role of TOP2A in proliferation, skeleton regulation, motility and VM production in non-small cell lung cancer and its mechanisms by using bioinformatics tools and molecular biology experiments. Subgroup analysis showed that the low-risk group had a better prognosis, while the high-risk group was positively correlated with high tumor mutational load, M1-type macrophage infiltration, immune checkpoint molecule expression, and immunotherapy efficacy. As confirmed by further clinical specimens, the presence of TOP2A and VM was significantly and positively correlated with poor prognosis. Our study established a model based on significant co-expression of TOP2A genes, which significantly correlated with mutational load and immunotherapy outcomes in patients with non-small cell lung cancer. Further mechanistic exploration suggests that TOP2A plays an important role in immunotherapy and VM formation in NSCLC through upregulation of Wnt3a and PD-L1 expression

Evidence of electron interaction with an unidentified bosonic mode in superconductor CsCa2Fe4As4F2

Abstract The kink structure in band dispersion usually refers to a certain electron-boson interaction, which is crucial in understanding the pairing in unconventional superconductors. Here we report the evidence of the observation of a kink structure in Fe-based superconductor CsCa2Fe4As4F2 using angle-resolved photoemission spectroscopy. The kink shows an orbital selective and momentum dependent behavior, which is located at 15 meV below Fermi level along the $$\Gamma -{{\rm{{M}}}}$$ Γ − M direction at the band with d xz orbital character and vanishes when approaching the $$\Gamma -{{\rm{{X}}}}$$ Γ − X direction, correlated with a slight decrease of the superconducting gap. Most importantly, this kink structure disappears when the superconducting gap closes, indicating that the corresponding bosonic mode (~ $$9\pm 1$$ 9 ± 1 meV) is closely related to superconductivity. However, the origin of this mode remains unidentified, since it cannot be related to phonons or the spin resonance mode (~15 meV) observed by inelastic neutron scattering. The behavior of this mode is rather unique and challenges our present understanding of the superconducting paring mechanism of the bilayer FeAs-based superconductors