DOI: 10.14704/nq.2018.16.6.1644

Energy Consumption Control and Optimization of Large Power Grid Operation Based on Artificial Neural Network Algorithm

Xuan Gong

Abstract


Green, energy-saving, efficient and reliable smart grids have become one of the most important development areas in the world. An artificial neural network algorithm based on cranial nerve principle proposed in this paper provides reference for power flow analysis, reasonable dispatching and control decision-making of smart grids. At the same time, new EMS (Energy Management System) structure and strategy are introduced to optimize resource allocation and energy management. Based on the single-layer network control theory of large power grid, BP neural network including genetic algorithm is constructed and combined with regression analysis to realize the optimization of power analysis. In addition, a neuron controller is set up in the distributed unit to collect, monitor and control the parameters and send them to the high-level central controller, forming a multi-level three-dimensional network to analyze and make decisions, accurately predict the energy consumption of power grids, and improve the control level of the energy consumption of smart grids.

Keywords


Smart Grids, GA-BP Neural Network, Genetic Algorithm, Regression Analysis, EMS

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References


Barnett AJ, Finlay K, Beisner BE. Functional diversity of crustacean zooplankton communities: towards a trait-based classification. Freshwater Biology 2013; 52: 796-813.

Cloern JE, Hieb KA, Jacobson T, Sansó B, Lorenzo ED, Stacey MT. Biological communities in san francisco bay track large-scale climate forcing over the north pacific. Geophysical Research Letters 2010; 37(21): 389-400.

Díaz FJ, Chow AT, O'Geen AT, Dahlgren RA, Wong PK. Restored wetlands as a source of disinfection byproduct precursors. Environmental Science & Technology 2008; 42(16): 5992-97.

Gleitsmann BA, Kroma MM, Steenhuis T. Analysis of a rural water supply project in three communities in Mali: participation and sustainability. Natural Resources Forum 2007; 31(2): 142-50.

Grote EE, Belnap J, Housman DC, Sparks JP. Carbon exchange in biological soil crust communities under differential temperatures and soil water contents: implications for global change. Global Change Biology 2010; 16(10): 2763-74.

Harpold AA, Burns DA, Walter MT, Steenhuis TS. Hydrogeomorphology explains acidification-driven variation in aquatic biological communities in the neversink basin, USA. Ecological Applications 2013; 23(4): 791-800.

Harvey JW, Mccormick PV. Groundwater’s significance to changing hydrology, water chemistry, and biological communities of a floodplain ecosystem, everglades, South Florida, USA. Hydrogeology Journal 2009; 17(1): 185-201.

Hu LJ, Tang L, Pan Q, Song H, Wen PG. Research and analysis of PI control strategy based on neural network in power grid. Mathematical Modelling of Engineering Problems 2016; 3(1): 25-28.

Irina H, Juha H. Agricultural drainage ditches, their biological importance and functioning. Biological Conservation 2088; 141(5): 1171-83.

Isah OR, Usman AD, Tekanyi AMS. A hybrid model of PSO algorithm and artificial neural network for automatic follicle classification. International Journal Bioautomation 2017; 21(1): 43-58

Liao X, Chen C, Wang Z, Wan R, Chang CH, Zhang X. Changes of biomass and bacterial communities in biological activated carbon filters for drinking water treatment. Process Biochemistry 2013; 48(2): 312-16.

Mckee LJ, Lewicki M, Schoellhamer DH, Ganju NK. Comparison of sediment supply to san francisco bay from watersheds draining the bay area and the central valley of california. Marine Geology 2013; 345(2013): 47-62.

Mueller M, Geist J. The effects of weirs on structural stream habitat and biological communities. Journal of Applied Ecology 2011; 48(6): 1450-61.

Salomoni S, Rocha O., Hermany G, Lobo E. Application of water quality biological indices using diatoms as bioindicators in the gravataí river, rs, brazil aplicação de índices biológicos da qualidade água utilizando diatomáceas como bioindicadoras no rio gravataí, rs, brazil. Brazilian Journal of Biology 2011; 71(4): 949-59.

Tarasov VG. Effects of shallow-water hydrothermal venting on biological communities of coastal marine ecosystems of the western pacific. Advances in Marine Biology 2006; 50: 267-421.

Tichanek F, Tropek R. Conservation value of post-mining headwaters: drainage channels at a lignite spoil heap harbour threatened stream dragonflies. Journal of Insect Conservation 2015; 19(5): 975-85.

Wang TC, Xie YZ. BP-GA data fusion algorithm studies oriented to smart home, Mathematical Modelling of Engineering Problems 2016; 3(3): 135-40.

Zhang Y, Dudgeon D, Cheng D, Thoe W, Fok L, Wang Z. Impacts of land use and water quality on macroinvertebrate communities in the pearl river drainage basin, China. Hydrobiologia 2010; 652(1): 71-88.


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