Flexible energy load identification in intelligent manufacturing for demand response using a neural network integrated particle swarm optimization
暂无分享,去创建一个
Haoyi Xiong | Ruwen Qin | Wenqing Hu | Zeyi Sun | Kaibo Xu | Monirul Islam
[1] Amir F. Atiya,et al. Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances , 2011, IEEE Transactions on Neural Networks.
[2] M. M. Ardehali,et al. Utility demand response operation considering day-of-use tariff and optimal operation of thermal energy storage system for an industrial building based on particle swarm optimization algorithm , 2016 .
[3] S. Bhattacharya,et al. Control Strategies for Battery Energy Storage for Wind Farm Dispatching , 2009, IEEE Transactions on Energy Conversion.
[4] Carlos A. Coello Coello,et al. Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.
[5] Ranjit Roy,et al. Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm , 2015 .
[6] Narayanan Kumarappan,et al. Day-Ahead Deregulated Electricity Market Price Forecasting Using Recurrent Neural Network , 2013, IEEE Systems Journal.
[7] Alireza Askarzadeh,et al. A Memory-Based Genetic Algorithm for Optimization of Power Generation in a Microgrid , 2018, IEEE Transactions on Sustainable Energy.
[8] Lin Li,et al. “Just-for-Peak” buffer inventory for peak electricity demand reduction of manufacturing systems , 2013 .
[9] Anula Khare,et al. Sizing and performance analysis of standalone wind-photovoltaic based hybrid energy system using ant colony optimisation , 2016 .
[10] Monirul Islam,et al. Reward/Penalty Design in Demand Response for Mitigating Overgeneration Considering the Benefits from both Manufacturers and Utility Company , 2017 .
[11] Ming Jin,et al. Microgrid to enable optimal distributed energy retail and end-user demand response , 2018 .
[12] X.Y. Wang,et al. Determination of Battery Storage Capacity in Energy Buffer for Wind Farm , 2008, IEEE Transactions on Energy Conversion.
[13] Ada Che,et al. Energy-conscious unrelated parallel machine scheduling under time-of-use electricity tariffs , 2017 .
[14] Yuan Zhang,et al. Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network , 2019, IEEE Transactions on Smart Grid.
[15] Zita Vale,et al. Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization , 2012 .
[16] C. Dagli,et al. Biofuel supply chain optimal design considering economic, environmental, and societal aspects towards sustainability , 2018 .
[17] Lin Li,et al. Plant-level electricity demand response for combined manufacturing system and heating, venting, and air-conditioning (HVAC) system , 2016 .
[18] Haoyi Xiong,et al. Optimal scheduling of manufacturing and onsite generation systems in over-generation mitigation oriented electricity demand response program , 2018, Comput. Ind. Eng..
[19] Paul Denholm,et al. Overgeneration from Solar Energy in California - A Field Guide to the Duck Chart , 2015 .
[20] Dennice F. Gayme,et al. Grid-scale energy storage applications in renewable energy integration: A survey , 2014 .
[21] Ralph E.H. Sims,et al. Carbon emission and mitigation cost comparisons between fossil fuel, nuclear and renewable energy resources for electricity generation , 2003 .
[22] Jinwoo Park,et al. Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency , 2013 .
[23] Lin Li,et al. Potential capability estimation for real time electricity demand response of sustainable manufacturing systems using Markov Decision Process , 2014 .
[24] Abbas Khosravi,et al. Uncertainty handling using neural network-based prediction intervals for electrical load forecasting , 2014 .
[25] Jeffrey W. Herrmann,et al. Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods , 2003, J. Sched..
[26] V. P. Kozyrev. Estimation of the execution time in real-time systems , 2016, Programming and Computer Software.
[27] Kelum A. A. Gamage,et al. Demand side management in smart grid: A review and proposals for future direction , 2014 .
[28] Zahra Fallahi,et al. Economic and emission-saving benefits of utilizing demand response and distributed renewables in microgrids , 2017 .
[29] Ki-Hyun Kim,et al. Solar energy: Potential and future prospects , 2018 .
[30] Zeyi Sun,et al. Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system , 2015 .
[31] Sami Kara,et al. Towards Energy and Resource Efficient Manufacturing: A Processes and Systems Approach , 2012 .
[32] Youngdeok Hwang,et al. Artificial neural network model for forecasting sub-hourly electricity usage in commercial buildings , 2016 .
[33] Raymond Chiong,et al. Parallel Machine Scheduling Under Time-of-Use Electricity Prices: New Models and Optimization Approaches , 2016, IEEE Transactions on Automation Science and Engineering.
[34] Shaghayegh Bahramirad,et al. Reliability-Constrained Optimal Sizing of Energy Storage System in a Microgrid , 2012, IEEE Transactions on Smart Grid.
[35] Zeyi Sun,et al. Inventory control for peak electricity demand reduction of manufacturing systems considering the tradeoff between production loss and energy savings , 2014 .
[36] Haoyi Xiong,et al. Optimal Sizing and Planning of Onsite Generation System for Manufacturing in Critical Peaking Pricing Demand Response Program , 2018 .
[37] Thillainathan Logenthiran,et al. Demand Side Management in Smart Grid Using Heuristic Optimization , 2012, IEEE Transactions on Smart Grid.