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: "joint investment and operation of microgrid"
  Abstract: In this paper, we propose a theoretical framework for the joint optimization of investment and operation of a microgrid, taking the impact of energy storage, renewable energy integration, and demand response into consideration. We first study the renewable energy generations in Hong Kong, and identify the potential benefit of mixed deployment of solar and wind energy generations.Then, we model the joint investment and operation as a two-period stochastic programming program. In period-1, the microgrid operator makes the optimal investment decisions on the capacities of solar power generation, wind power generation, and energy storage. In period-2, the operator coordinates the power supply and demand in the microgrid to minimize the operating cost.We design a decentralized algorithm for computing the optimal pricing and power consumption in period-2 based on which we solve the optimal investment problem in period-1. We also study the impact of prediction error of renewable energy generation on the portfolio investment using robust optimization framework. Using realistic meteorological data obtained from the Hong Kong observatory, we numerically characterize the optimal portfolio investment decisions, optimal day-ahead pricing, and power scheduling, and demonstrate the advantage of using mixed renewable energy and demand response in terms of reducing investment cost.

Connected through hyperedge HE-1 (induced by source paper "reinforcement learning based energy trading for microgrids"):
  with members:
    - "incentivizing energy trading for interconnected microgrids"
    - "hierarchical decision making in electricity grid management"
    - "three party energy management with distributed energy resources in smart grid"
    - "a game theoretic approach to energy trading in the smart grid"

Connected through hyperedge HE-2 (induced by source paper "using battery storage for peak shaving and frequency regulation joint optimization for superlinear gains"):
  with members:
    - "cooperative planning of renewable generations for interconnected microgrids"
    - "leveraging energy storage to optimize data center electricity cost in emerging power markets"

Connected through hyperedge HE-3 (induced by source paper "cooperative planning of renewable generations for interconnected microgrids"):
  with members:
    - "optimal power cost management using stored energy in data centers"

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.SY(Systems and Control)