Qi, JinJinQiLai, ChunyuanChunyuanLaiXu, BinBinXuSun, YanfeiYanfeiSunProf. LEUNG Kwong Sak2023-02-222023-02-222018IEEE Transactions on Industrial Informatics, 2018, vol. 14(12),8264729, pp. 5410-54181551-32031941-0050http://hdl.handle.net/20.500.11861/7418Rapid economic development has been observed worldwide, which has caused environmental problems to worsen. Thus, the Energy Internet (EI), which accesses renewable energy and provides high-quality power services, has recently become a hot issue. As a subnet of the EI, an energy local area network (ELAN) consists of renewable power generation equipment, controllable distributed power generation equipment, storage systems, electric vehicles, and a large number of loads. Energy management is required for economic, environmental, and safety considerations. This paper proposes an energy management optimization model that addresses ELAN operations and includes pollution treatment fees; this model provides intelligent control of the charging and discharging of plug-in hybrid electric vehicles (PHEVs). This model achieves a nonlinear energy management optimization for an ELAN. To promote optimal performance, an improved comprehensive learning particle swarm optimization (CLPSO) algorithm is presented; it combines Tabu Search (TS) and CLPSO to avoid local optima. To verify the performance of our model, two experimental scenarios are built. The simulation results show that our energy management optimization model fulfills the optimal allocation of energy and that the PHEV intelligent charging/discharging strategy promotes economic benefits for the network.enRenewable EnergyLocal NetworkEnergy ManagementEnergy Management OptimizationSimulation ResultsOptimization AlgorithmOptimal ModelPower GenerationElectric VehiclesEnergy DistributionLocal OptimumParticle SwarmMicrogridExperimental ScenariosTabu SearchPollution TreatmentHybrid Electric VehiclesIntelligent StrategyPlug-in Electric VehiclesPlug-in Hybrid Electric VehiclesOperational CostsTotal CostParticle PositionParticle VelocityNetwork LoadPower GridPeak LoadElectricity ProductionCharging TimeBattery CapacityPeer Reviewed Journal Article10.1109/TII.2018.2796021