human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "optimal inverter var control in distribution systems with high pv penetration"
  Abstract: The intent of the study detailed in this paper is to demonstrate the benefits of inverter var control on a fast timescale to mitigate rapid and large voltage fluctuations due to the high penetration of photovoltaic generation and the resulting reverse power flow. Our approach is to formulate the volt/var control as a radial optimal power flow (OPF) problem to minimize line losses and energy consumption, subject to constraints on voltage magnitudes. An efficient solution to the radial OPF problem is presented and used to study the structure of optimal inverter var injection and the net benefits, taking into account the additional cost of inverter losses when operating at non-unity power factor. This paper will illustrate how, depending on the circuit topology and its loading condition, the inverter's optimal reactive power injection is not necessarily monotone with respect to their real power output. The results are demonstrated on a distribution feeder on the Southern California Edison system that has a very light load and a 5 MW photovoltaic (PV) system installed away from the substation.

Connected through hyperedge HE-1 (induced by source paper "a tractable ellipsoidal approximation for voltage regulation problems"):
  with members:
    - "an optimal treatment assignment strategy to evaluate demand response effect"

Connected through hyperedge HE-2 (induced by source paper "towards distributed energy services decentralizing optimal power flow with machine learning"):
  with members:
    - "regression based inverter control for decentralized optimal power flow and voltage regulation"
    - "fully decentralized policies for multi agent systems an information theoretic approach"
    - "minimax estimation of functionals of discrete distributions"

Connected through hyperedge HE-3 (induced by source paper "impacts of community and distributed energy storage systems on unbalanced low voltage networks"):
  with members:
    - "optimal sizing and placement of distributed storage in low voltage networks"

Connected through hyperedge HE-4 (induced by source paper "vader visualization and analytics for distributed energy resources"):
  with members:
    - "patopa a data driven parameter and topology joint estimation framework in distribution grids"
    - "distribution system topology detection using consumer load and line flow measurements"
    - "topology detection in microgrids with micro synchrophasors"
    - "outage detection in power distribution networks"

Connected through hyperedge HE-5 (induced by source paper "decentralized dynamic optimization for power network voltage control"):
  with members:
    - "a class of prediction correction methods for time varying convex optimization"
    - "voltage regulation algorithms for multiphase power distribution grids"
    - "incremental gradient subgradient and proximal methods for convex optimization a survey"

Connected through hyperedge HE-6 (induced by source paper "feeder topology identification"):
  with members:
    - "topology detection in microgrids with micro synchrophasors"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.ET(Emerging Technologies)