Automatic and linearized modeling of energy hub and its flexibility analysis

Applied Energy - Tập 211 - Trang 705-714 - 2018
Yi Wang1, Jiangnan Cheng1, Ning Zhang1, Chongqing Kang1
1Department of Electrical Engineering, Tsinghua University, Beijing 100084, China

Tài liệu tham khảo

International Energy Agency. World energy outlook 2016. [Online]. Available: http://www.worldenergyoutlook.org/publications/weo-2016. Wang, 2017, Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch, Appl Energy Mancarella, 2014, MES (multi-energy systems): an overview of concepts and evaluation models, Energy, 65, 1, 10.1016/j.energy.2013.10.041 Heinen, 2016, Electricity, gas, heat integration via residential hybrid heating technologies – an investment model assessment, Energy, 109, 906, 10.1016/j.energy.2016.04.126 Haghighi, 2016, An integrated steady-state operation assessment of electrical, natural gas, and district heating networks, IEEE Trans Power Syst, 31, 3636, 10.1109/TPWRS.2015.2486819 Shao, 2016, An MILP-based optimal power flow in multi-carrier energy systems, IEEE Trans Sustain Energy, 99 Geidl, 2007, Optimal power flow of multiple energy carriers, IEEE Trans Power Syst, 22, 10.1109/TPWRS.2006.888988 Bai, 2016, Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty, Appl Energy, 167, 270, 10.1016/j.apenergy.2015.10.119 Holjevac, 2017, Corrective receding horizon scheduling of flexible distributed multi-energy microgrids, Appl Energy, 10.1016/j.apenergy.2017.06.045 Li, 2017, Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process, Appl Energy, 194, 696, 10.1016/j.apenergy.2016.07.077 Qadrdan, 2017, Benefits of demand-side response in combined gas and electricity networks, Appl Energy, 192, 360, 10.1016/j.apenergy.2016.10.047 Skarvelis-Kazakos, 2016, Multiple energy carrier optimisation with intelligent agents, Appl Energy, 167, 323, 10.1016/j.apenergy.2015.10.130 O’Malley, 2013, Energy comes together: the integration of all systems, IEEE Power Energ Mag, 11, 18, 10.1109/MPE.2013.2266594 Meibom, 2013, Energy comes together in Denmark: the key to a future fossil-free Danish power system, IEEE Power Energy Mag, 11, 46, 10.1109/MPE.2013.2268751 Clegg, 2016, Integrated electrical and gas network flexibility assessment in low-carbon multi-energy systems, IEEE Trans Sustain Energy, 7, 718, 10.1109/TSTE.2015.2497329 Qiu Y, Jiang J, Chen D. Development and present status of multi-energy distributed power generation system. In: IEEE 8th international power electronics and motion control conference (IPEMC-ECCE Asia); 2016. Jiang, 2013, Wavelet-Based capacity configuration and coordinated control of hybrid energy storage system for smoothing out wind power fluctuations, IEEE Trans Power Syst, 28, 1363, 10.1109/TPWRS.2012.2212252 Belderbos A, Delarue E, D’haeseleer W. Possible role of power-to-gas in future energy systems. In: 12th International conference on the european energy market, Lisbon, Portugal; May 2015. Du E, Zhang N, Kang C, Miao M, Tian X. Exploring the flexibility of CSP for wind power integration using interval optimization. In: Power and energy society general meeting (PESGM), Boston, US; 2016 [2016.7.17–22]. Chen, 2015, Reducing generation uncertainty by integrating CSP with wind power: an adaptive robust optimization-based analysis, IEEE Trans Sustain Energy, 6, 583, 10.1109/TSTE.2015.2396971 Aghtaie, 2013, Multiagent genetic algorithm: an online probabilistic view on economic dispatch of energy hubs constrained by wind availability, IEEE Trans Sustain Energy, 5, 699, 10.1109/TSTE.2013.2271517 Li, 2016, Combined heat and power dispatch considering pipeline energy storage of district heating network, IEEE Trans Sustain Energy, 7, 12, 10.1109/TSTE.2015.2467383 Meibom, 2007, Value of electric heat boilers and heat pump for wind power integration, Wind Energy, 10, 321, 10.1002/we.224 Holjevac, 2015, Adaptive control for evaluation of flexibility benefits in microgrid systems, Energy, 92, 487, 10.1016/j.energy.2015.04.031 Kiviluoma, 2017, Harnessing flexibility from hot and cold: heat storage and hybrid systems can play a major role, IEEE Power Energy Mag, 15, 25, 10.1109/MPE.2016.2626618 Martinez Cesena, 2016, Flexible Distributed Multienergy Generation System Expansion Planning Under Uncertainty, IEEE Trans Smart Grid, 7, 348, 10.1109/TSG.2015.2411392 Geidl, 2007, Energy hubs for the future, IEEE Power Energy Mag, 5, 24, 10.1109/MPAE.2007.264850 Chicco, 2009, Matrix modeling of small-scale trigeneration systems and application to operational optimization, Energy, 34, 261, 10.1016/j.energy.2008.09.011 Beccuti G, Demiray T, Batic M, Tomasevic N, Vranes S. Energy hub modelling and optimization: an analytical case-study. In: IEEE Eindhoven PowerTech; 2015. Yu D, Lian B, Dunn R, Le S. Using control methods to model energy hub systems. In: 49th international universities power engineering conference (UPEC); 2014. Gaulus MD, Andersson G. Power system considerations of plug-in hybrid electric vehicles based on a multi-energy carrier model. In: Power & energy society general meeting; 2009. Sheikhi, 2015, Intergrated demand side management game in smart energy hubs, IEEE Trans Smart Grid, 6, 10.1109/TSG.2014.2377020 Neyestani, 2015, Stochastic modeling of multienergy carriers dependencis in smart local networks with distributed energy resources, IEEE Trans Smart Grid, 6, 1748, 10.1109/TSG.2015.2423552 Mancarella, 2013, Real-Time demand response from energy shifting in distributed multi-generation, IEEE Trans Smart Grid, 4, 1928, 10.1109/TSG.2013.2258413 Almassalkhi K, Hiskens I. Optimization framework for the analysis of large-scale networks of energy hubs. In: Power systems computation conference; 2011. p. 1–7. Beccuti G, Demiray T, Batic M, Tomasevic N, Vranes S. Energy hub modelling and optimisation: an analytical case-study. In: IEEE Eindhoven PowerTech, Eindhoven; 2015. p. 1–6. Almassalkhi MR, Towle A. Enabling city-scale multi-energy optimal dispatch with energy hubs. In: Power systems computation conference (PSCC), Genoa; 2016. p. 1–7. Cochran, 2014