SCIENTIA SINICA Informationis, Volume 48, Issue 10: 1409-1429(2018) https://doi.org/10.1360/N112018-00077

## Modeling and application of we-energy in energy Internet

• AcceptedJun 25, 2018
• PublishedOct 16, 2018
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### Abstract

This study aims to propose we-energy (WE), which is a novel energy autonomous region. WE provides an energy management strategy for the local consumption of renewable energy, the plug-and-play of distributed generators, and the multi-energy complementation of production-consumption-storage integration. A quaternary model based on the information, physics, energy, and economic subsystems (Information-Equipment-Energy-Economical System, IEEES) was established to address the problems of multi-energy coordination and WE optimization under different operating conditions. Four operating modes of the WE were presented. Using the coupling characteristics of the abovementioned four subsystems, modal transformation was performed in accordance with the operational situation of the energy internet, and the corresponding state equations of the WE were established. The operation of the WE under several typical application scenarios, such as distributed optimization and coordinated control, was analyzed. An optimal marketing strategy between multiple WEs was established through economic optimization, which realized the appropriate allocation of energy sources inside the WE. Moreover, the coordinated control of inner devices of WE ensured the stability of both the parameters and energy exchange at grid-connected spots under fluctuating conditions.

### References

[1] Zhou X, Zeng R, Gao F. Development status and prospects of the Energy InternetDevelopment status and prospects of the Energy Internet. SSI, 2017, 47: 149-170 CrossRef Google Scholar

[2] Sun Q Y, Teng F, Zhang H G. Energy Internet and its key control issues. Act Autom Sin, 2017, 43: 176--194. Google Scholar

[3] Cao J W, Meng K, Wang J Y, et al. An energy Internet and energy routers. Sci Sin Inform, 2014, 44: 714--727. Google Scholar

[4] Huang R, Ye L, Liao H L. Microelectronics technologies in renewable energy Internet. Sci Sin Inform, 2014, 44: 728--742. Google Scholar

[5] Zha Y B, Zhang T, Huang Z, et al. Analysis of energy Internet key technologies. Sci Sin Inform, 2014, 44: 702--713. Google Scholar

[6] Ilic M D, Xie L, Khan U A. Modeling of Future Cyber-Physical Energy Systems for Distributed Sensing and Control. IEEE Trans Syst Man Cybern A, 2010, 40: 825-838 CrossRef Google Scholar

[7] Pasqualetti F, Dorfler F, Bullo F. Attack Detection and Identification in Cyber-Physical Systems. IEEE Trans Automat Contr, 2013, 58: 2715-2729 CrossRef Google Scholar

[8] Xin S, Guo Q, Sun H. Cyber-Physical Modeling and Cyber-Contingency Assessment of Hierarchical Control Systems. IEEE Trans Smart Grid, 2015, 6: 2375-2385 CrossRef Google Scholar

[9] Liu X J, Kong X B. Present situation and prospect of model predictive control application in complex power industrial process. Proc CSEE, 2013, 33: 79--85. Google Scholar

[10] Son S E, Lee S H, Choi D H. Improvement of Composite Load Modeling Based on Parameter Sensitivity and Dependency Analyses. IEEE Trans Power Syst, 2014, 29: 242-250 CrossRef ADS Google Scholar

[11] Kim J K, An K, Ma J. Fast and Reliable Estimation of Composite Load Model Parameters Using Analytical Similarity of Parameter Sensitivity. IEEE Trans Power Syst, 2016, 31: 663-671 CrossRef ADS Google Scholar

[12] Duquette J, Rowe A, Wild P. Thermal performance of a steady state physical pipe model for simulating district heating grids with variable flow. Appl Energy, 2016, 178: 383-393 CrossRef Google Scholar

[13] Ahmadian Behrooz H, Boozarjomehry R B. Modeling and state estimation for gas transmission networks. J Nat Gas Sci Eng, 2015, 22: 551-570 CrossRef Google Scholar

[14] Gupta S K, Kar K, Mishra S. Collaborative Energy and Thermal Comfort Management Through Distributed Consensus Algorithms. IEEE Trans Automat Sci Eng, 2015, 12: 1285-1296 CrossRef Google Scholar

[15] Binetti G, Davoudi A, Lewis F L. Distributed Consensus-Based Economic Dispatch With Transmission Losses. IEEE Trans Power Syst, 2014, 29: 1711-1720 CrossRef ADS Google Scholar

[16] Ci S, Li H J, Chen X, et al. The cornerstone of energy Internet: research and practice of distributed energy storage technology. Sci Sin Inform, 2014, 44: 762--773. Google Scholar

[17] Zhang H, Li Y, Gao D W. Distributed Optimal Energy Management for Energy Internet. IEEE Trans Ind Inf, 2017, 13: 3081-3097 CrossRef Google Scholar

[18] Meng Y, Li T, Zhang J F. Coordination Over Multi-Agent Networks With Unmeasurable States and Finite-Level Quantization. IEEE Trans Automat Contr, 2017, 62: 4647-4653 CrossRef Google Scholar

[19] Su W, Huang A Q. A game theoretic framework for a next-generation retail electricity market with high penetration of distributed residential electricity suppliers. Appl Energy, 2014, 119: 341-350 CrossRef Google Scholar

[20] Honarvar Nazari M, Costello Z, Feizollahi M J. Distributed Frequency Control of Prosumer-Based Electric Energy Systems. IEEE Trans Power Syst, 2014, 29: 2934-2942 CrossRef ADS Google Scholar

[21] Wang Z, Zhang Q, Zhang J F. Distributed consensus over digital noisy channel through reliable communications. Sci Sin Inform, 2016, 46: 1648--1661. Google Scholar

[22] Stevanovic V D, Zivkovic B, Prica S. Prediction of thermal transients in district heating systems. Energy Convers Manage, 2009, 50: 2167-2173 CrossRef Google Scholar

[23] Choi S Y, Yoo K Y, Lee J B. Mathematical modeling and control of thermal plant in the district heating system of Korea. Appl Thermal Eng, 2010, 30: 2067-2072 CrossRef Google Scholar

[24] Jiang X S, Jing Z X, Li Y Z. Modelling and operation optimization of an integrated energy based direct district water-heating system. Energy, 2014, 64: 375-388 CrossRef Google Scholar

[25] Wang H, Wang H, Zhu T. A novel model for steam transportation considering drainage loss in pipeline networks. Appl Energy, 2017, 188: 178-189 CrossRef Google Scholar

[26] Liu C, Shahidehpour M, Wang J. Coordinated scheduling of electricity and natural gas infrastructures with a transient model for natural gas flow. Chaos, 2011, 21: 025102 CrossRef PubMed ADS Google Scholar

[27] Pambour K A, Bolado-Lavin R, Dijkema G P J. An integrated transient model for simulating the operation of natural gas transport systems. J Nat Gas Sci Eng, 2016, 28: 672-690 CrossRef Google Scholar

[28] King A C, Billingham J, Otto S R. Differential Equations: Linear, Nonlinear, Ordinary, Partial. New York: Cambridge University Press, 2003. 527--536. Google Scholar

[29] Cheah-Mane M, Sainz L, Liang J. Criterion for the Electrical Resonance Stability of Offshore Wind Power Plants Connected Through HVDC Links. IEEE Trans Power Syst, 2017, 32: 4579-4589 CrossRef ADS Google Scholar

• Figure 1

(Color online) We-energy and energy Internet. (a) Schematic diagram of we-energy; (b) structure of energy Internet

• Figure 2

(Color online) Schematic diagram of we-energy operation mode based on quaternary model

• Figure 3

(Color online) We-energy simulation system

• Figure 4

(Color online) The result of economic operation among 5 we-energies. (a) Output of we-energies; (b) distribution of electric energy; (c) distribution of thermal energy; (d) distribution of natural gas

• Figure 5

(Color online) Coordination control of we-energy. (a) Variation in load; (b) output power of MT; (c) output power of PV and EB; (d) output of GS and ES; (e) output of we-energy

• Figure 6

(Color online) Output contrast experiment of we-energy

• Table 1   Simulation parameters of we-energy
 ${{\nu}_i}$ ${\xi~_{i1,{\rm~e}}}$ ${\xi~_{i2,{\rm~e}}}$ ${\xi~_{i1,{\rm~h}}}$ ${\xi~_{i2,{\rm~h}}}$ ${\xi~_{i1,{\rm~g}}}$ ${\xi~_{i2,{\rm~g}}}$ ${{\rm~WE}_1}$ 0.021 0.051 0.011 0.110 0.210 0.712 ${{\rm~WE}_2}$ 0.040 0.028 0.029 0.120 0.031 0.051 ${{\rm~WE}_3}$ 0.022 0.021 0.010 0.010 0.012 0.041 ${{\rm~WE}_4}$ 0.013 0.029 0.012 0.031 0.001 0.011 ${{\rm~WE}_5}$ 0.210 0.032 0.710 0.045 0.069 0.022 ${E_{i,{\rm{load}}}}$ $E_{i,{\rm~e}}^{{\rm{load}},\min~}$ $E_{i,{\rm~e}}^{{\rm{load}},\max~}$ $E_{i,{\rm~h}}^{{\rm{load}},\min~}$ $E_{i,{\rm~h}}^{{\rm{load}},\max~}$ $E_{i,{\rm~g}}^{{\rm{load}},\min~}$ $E_{i,{\rm~g}}^{{\rm{load}},\max~}$ ${{\rm~WE}_1}$ $-$120 $-$30 $-$260 $-$65 $-$200 $-$30 ${{\rm~WE}_2}$ $-$100 $-$50 $-$230 $-$60 $-$180 $-$25 ${{\rm~WE}_3}$ $-$130 $-$45 $-$191 $-$30 $-$175 $-$45 ${{\rm~WE}_4}$ $-$90 0 $-$280 $-$75 $-$150 $-$20 ${{WE}_5}$ $-$60 $-$10 $-$205 $-$50 $-$185 $-$35 $\Delta~{E_{i,{\rm~line}}}$ $\Delta~E_{i,{\rm~e}}^{\min~}$ $\Delta~E_{i,{\rm~e}}^{\max~}$ $\Delta~E_{i,{\rm~h}}^{\min~}$ $\Delta~E_{i,{\rm~h}}^{\max~}$ $\Delta~E_{i,{\rm~g}}^{\min~}$ $\Delta~E_{i,{\rm~g}}^{\max~}$ ${{\rm~WE}_1}$ $-$120 120 $-$250 250 $-$265 0 ${{\rm~WE}_2}$ $-$150 150 $-$225 225 $-$225 0 ${{\rm~WE}_3}$ $-$240 240 $-$170 170 $-$250 0 ${{\rm~WE}_4}$ $-$260 260 $-$280 280 $-$230 0 ${{\rm~WE}_5}$ $-$135 135 $-$200 200 $-$265 0 $\Delta~{E_{i,{\rm{produce}}}}$ $E_{i,{\rm~e}}^{\rm~PV,max}$ $E_{i,{\rm~e}}^{\rm~EB,max}$ $E_{i,{\rm~e}}^{\rm~MT,max}$ $\xi~_{i,1}^{\rm~MT}$ $\xi~_{i,2}^{\rm~MT}$ $\xi~_{i,3}^{\rm~MT}$ ${{\rm~WE}_1}$ 90 85 50 1 0.178 247 ${{\rm~WE}_2}$ 105 90 65 1 0.115 130 ${{\rm~WE}_3}$ 85 75 45 1 0.137 185 ${{\rm~WE}_4}$ 80 150 60 1 0.125 159 ${{\rm~WE}_5}$ 100 100 55 1 0.202 225
• Table 1   Parameters of we-energy
 Parameter Value Parameter Value Parameter Value Parameter Value ${L_1}$ 20 mH ${f_w}$ 0.025 ${v_{w,{\rm~{st}}}}$ 1.4 m/s ${f_{\rm~g}}$ 0.005 ${L_2}$ 25 mH ${D_w}$ 1 m ${T_{w,{\rm~i}}}$ 90$^{\rm{o}}{\rm{C}}$ ${D_{\rm~g}}$ 0.8 m ${R_1}$ 1.2 $\Omega~$ ${L_w}$ 1000 m ${T_{w,{\rm~{st}}}}$ 75$^{\rm{o}}{\rm{C}}$ ${L_{\rm~g}}$ 1000 m ${R_2}$ 1.5 $\Omega~$ ${c_b}$ 532 ${p_{w,{\rm~i}}}$ 20 MPa ${p_{\rm~{g,s}}}$ 0.4 MPa ${C}$ 15 ${{\mu~}}F$ ${c_w}$ 4200 ${\rm{J}}{{\rm{/}}\rm{kg}\cdot^{\circ}}{\rm{C}}$ ${p_{w,{\rm~{st}}}}$ 18 MPa ${p_{\rm~{g,st}}}$ 0.38 MPa ${{a}_w}$ 1000 m/s ${v_{w,{\rm~i}}}$ 1.6 m/s ${c_{\rm~g}}$ 300 m/s

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