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Operations of a microgrid with renewable energy integration and line switching

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Abstract

With the development of new technologies and their integration to the conventional power grid, the smart grid with the capacity of satisfying power demand by large amount of renewable energy is emerging. Microgrid, a small-scale power system with clearly defined electrical boundaries and ability of self-supply, especially by distributed renewable energy, plays a big role in this process. In this paper, we study the operations of a microgrid with solar photovoltaic generators, energy storage system, and power exchanges with main power grid. More specifically, a mixed integer programming model is formulated for decision-making, such as scheduling of generators within the microgrid, islanding operations through line switching and power trades between microgrid and the main grid, charging and discharging operations of storage system, and also line switching within the microgrid, by robust optimization for capturing the uncertainties of solar power generation. To solve the robust optimization formulation, we formulate our model in order to apply the column-and-constraint generation algorithm, and perform numerical experiments on several test cases to validate the proposed model and algorithm.

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References

  1. Ackermann, T., Andersson, G., Sder, L.: Distributed generation: a definition. Electr. Power Syst. Res. 57(3), 195–204 (2001)

    Article  Google Scholar 

  2. Golari, M., Fan, N., Wang, J.: Two-stage stochastic optimal islanding operations under severe multiple contingencies in power grids. Electr. Power Syst. Res. 114, 68–77 (2014)

    Article  Google Scholar 

  3. Fürsch, M., Nagl, S., Lindenberger, D.: Optimization of power plant investments under uncertain renewable energy deployment paths: a multistage stochastic programming approach. Energy Syst. 5(1), 85–121 (2014)

    Article  Google Scholar 

  4. Pinto, S.J., Panda, G.: Performance evaluation of WPT based islanding detection for grid-connected PV systems. Int. J. Electr. Power Energy Syst. 78, 537–546 (2016)

    Article  Google Scholar 

  5. Okido, S., Takeda, A.: Economic and environmental analysis of photovoltaic energy systems via robust optimization. Energy Syst. 4(3), 239–266 (2013)

    Article  Google Scholar 

  6. Fan, N., Izraelevitz, D., Pan, F., Pardalos, P.M., Wang, J.: A mixed integer programming approach for optimal power grid intentional islanding. Energy Syst. 3(1), 77–93 (2012)

    Article  Google Scholar 

  7. Brown, H.E., Suryanarayanan, S., Natarajan, S.A., Rajopadhye, S.: Improving reliability of islanded distribution systems with distributed renewable energy resources. IEEE Trans. Smart Grid 3(4), 2028–2038 (2012)

    Article  Google Scholar 

  8. Maknouninejad, A., et al.: Cooperative control for self-organizing microgrids and game strategies for optimal dispatch of distributed renewable generations. Energy Syst. 3(1), 23–60 (2012)

    Article  Google Scholar 

  9. Awad, A.S.A., EL-Fouly, T.H.M., Salama, M.M.A.: Optimal ESS allocation and load shedding for improving distribution system reliability. IEEE Trans. Smart Grid 5(5), 2339–2349 (2014)

    Article  Google Scholar 

  10. Genoese, F., Genoese, M.: Assessing the value of storage in a future energy system with a high share of renewable electricity generation. Energy Syst. 5(1), 19–44 (2014)

    Article  Google Scholar 

  11. Siddiqui, J., Hittinger, E.: Forecasting price parity for stand-alone hybrid solar microgrids: an international comparison. Energy Syst. (2017). https://doi.org/10.1007/s12667-017-0237-9

  12. Khodaei, A.: Resiliency-oriented microgrid optimal scheduling. IEEE Trans. Smart Grid 5(4), 1584–1591 (2014)

    Article  Google Scholar 

  13. Laghari, J.A., Mokhlis, H., Karimi, M., Bakar, A.H.A., Mohamad, Hasmaini: Computational intelligence based techniques for islanding detection of distributed generation in distribution network: a review. Energy Convers. Manag. 88, 139–152 (2014)

    Article  Google Scholar 

  14. Assis, T.M.L., et al.: Pilot field test of intentional islanding in distribution network. Energy Syst. 6(4), 585–602 (2015)

    Article  Google Scholar 

  15. Hytowitz, R.B., Hedman, K.W.: Managing solar uncertainty in microgrid systems with stochastic unit commitment. Electr. Power Syst. Res. 119, 111–118 (2015)

    Article  Google Scholar 

  16. Guo, Y., Zhao, C.: Islanding-aware robust energy management for microgrids. IEEE Trans. Smart Grid (2016). https://doi.org/10.1109/TSG.2016.2585092

  17. Zelazo, D., Dai, R., Mesbahi, M.: An energy management system for off-grid power systems. Energy Syst. 3(2), 153–179 (2012)

    Article  Google Scholar 

  18. Alharbi, W., Raahemifar, K.: Probabilistic coordination of microgrid energy resources operation considering uncertainties. Electr. Power Syst. Res. 128, 1–10 (2015)

    Article  Google Scholar 

  19. Rezvani, A., Izadbakhsh, M., Gandomkar, M.: Enhancement of microgrid dynamic responses under fault conditions using artificial neural network for fast changes of photovoltaic radiation and FLC for wind turbine. Energy Syst. 6(4), 551–584 (2015)

    Article  Google Scholar 

  20. Heymann, B., et al.: Continuous optimal control approaches to microgrid energy management. Energy Syst. (2017). https://doi.org/10.1007/s12667-016-0228-2

  21. Wang, H., Huang, J.: Joint investment and operation of microgrid. IEEE Trans. Smart Grid 8(2), 833–845 (2017)

    Google Scholar 

  22. Parisio, A., Rikos, E., Glielmo, L.: A model predictive control approach to microgrid operation optimization. IEEE Trans. Control Syst. Technol. 22(5), 1813–1827 (2014)

    Article  Google Scholar 

  23. Zhao, L., Zeng, B.: Vulnerability analysis of power grids with line switching. IEEE Trans. Power Syst. 28(3), 2727–2736 (2013)

    Article  Google Scholar 

  24. Zeng, B., Zhao, L.: Solving two-stage robust optimization problems using a column-and-constraint generation method. Oper. Res. Lett. 41(5), 457–461 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  25. Kazemzadeh, N., Ryan, S.M., Hamzeei, M.: Robust optimization vs. stochastic programming incorporating risk measures for unit commitment with uncertain variable renewable generation. Energy Syst. (2017). https://doi.org/10.1007/s12667-017-0265-5

  26. Vladimirou, H., Zenios, S.A.: Stochastic Programming and Robust Optimization, pp. 395–447. Springer, Boston (1997)

    MATH  Google Scholar 

  27. Melgar Dominguez, O.D., et al.: Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems. Energy Syst. (2017). https://doi.org/10.1007/s12667-017-0254-8

  28. Chen, R.L., Fan, N., Pinar, A., Watson, J.P.: Contingency-constrained unit commitment with post-contingency corrective recourse. Ann. Oper. Res. 249(1), 381–407 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  29. TEP. Tucson Electricity Power. Demand time-of-use (2017). https://www.tep.com/demand-tou/. Accessed 26 Apr 2017

  30. TEP. Tucson Electricity Power. 2017 Integrated resource plan (2017). https://www.tep.com/wp-content/uploads/2016/04/TEP-2017-Integrated-Resource-FINAL-Low-Resolution.pdf. Accessed 26 Apr 2017

  31. NREL. National Renewable Energy Laboratory. National solar radiation data base 1991–2010 update (2010). http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2010/statistics/hsf/722740_2010.hsf. Accessed 26 Apr 2017

  32. Grigg, C., et al.: The IEEE reliability test system-1996. A report prepared by the reliability test system task force of the application of probability methods subcommittee. IEEE Trans. Power Syst. 14(3), 1010–1020 (1999)

    Article  Google Scholar 

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Acknowledgements

J.L. Ruiz Duarte is supported by the Mexican National Council of Science and Technology (CONACYT) and the Mexican Department of Energy (SENER) for his PhD program. N. Fan is supported by University of Arizona Faculty Seed Grant (2016–2017).

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Correspondence to Neng Fan.

Appendices

Appendix A

The third level for the optimization model is shown complete as follows

$$\begin{aligned} \max _{(\mathbf p ,\mathbf f ,\mathbf o ,\theta , \mathbf{pm },\mathbf y ,\mathbf r ,\mathbf q )}~&\sum _{t\in \mathscr {T}}\Big (C^{+F}_{m,t} p^{+F}_{m,t} + C^{+N}_{m,t} p^{+N}_{m,t} - (C^{-F}_{m,t} p^{-F}_{m,t} + C^{-N}_{m,t} p^{-N}_{m,t}) \\&-\sum _{g\in \mathscr {G}}(C_g^p p_{g,t} + c_{g,t}^u + c_{g,t}^d) \\&-\sum _{s\in \mathscr {S}}(C_s^+ r_{s,t}^+ + C_s^- r_{s,t}^-) - \sum _{i\in \mathscr {I}}C^{sh}_{i,t} q_{i,t}\Big )\\ s.t.~&-c^u_{g,t}\le -C^u_g\big (\hat{x}_{g,t}-\hat{x}_{g,t-1}\big ) ,~~\forall g\in \mathscr {G},t\in \{2,\dots ,T\}\\&-c^d_{g,t}\le -C^d_g\big (\hat{x}_{g,t-1}-\hat{x}_{g,t}\big ) ,~~\forall g\in \mathscr {G},t\in \{2,\dots ,T\}\\&-c^u_{g,1}\le -C^u_g\big (\hat{x}_{g,1}-\overline{x}_{g,0}\big ) ,~~\forall g\in \mathscr {G}\\&-c^d_{g,1}\le -C^d_g\big (\overline{x}_{g,0}-\hat{x}_{g,1}\big ) ,~~\forall g\in \mathscr {G}\\&p_{g,t}-p_{g,t-1}\le R^u_g\hat{x}_{g,t-1}+\tilde{R}^u_g\big (\hat{x}_{g,t}-\hat{x}_{g,t-1}\big )+P_g^{max}\big (1-\hat{x}_{g,t}\big ), \\&~~\forall g\in \mathscr {G},t\in \{2,\dots ,T\}\\&p_{g,t-1}-p_{g,t}\le R^d_g\hat{x}_{g,t}+\tilde{R}^d_g\big (\hat{x}_{g,t-1}-\hat{x}_{g,t}\big )+P_g^{max}\big (1-\hat{x}_{g,t-1}\big ), \\&~~\forall g\in \mathscr {G},t\in \{2,\dots ,T\}\\&p_{g,1}\le \overline{p}_{g,0}+R^u_g\overline{x}_{g,0}+\tilde{R}^u_g\big (\hat{x}_{g,1}-\overline{x}_{g,0}\big )+P_g^{max}\big (1-\hat{x}_{g,1}\big ),~~\forall g\in \mathscr {G}\\&-p_{g,1}\le -\overline{p}_{g,0}+R^d_g\hat{x}_{g,1}+\tilde{R}^d_g\big (\overline{x}_{g,0}-\hat{x}_{g,1}\big )+P_g^{max}\big (1-\overline{x}_{g,0}\big ),~~\forall g\in \mathscr {G}\\ \end{aligned}$$
$$\begin{aligned}&-p_{g,t}\le -\hat{x}_{g,t}P_g^{min} ,~~\forall g\in \mathscr {G},t\in \mathscr {T}\\&p_{g,t}\le \hat{x}_{g,t}P_g^{max} ,~~\forall g\in \mathscr {G},t\in \mathscr {T}\\&-f_{e,t} \le \hat{z}_{e,t}F_e ,~~\forall e\in \mathscr {E},t\in \mathscr {T}\\&f_{e,t} \le \hat{z}_{e,t}F_e ,~~\forall e\in \mathscr {E},t\in \mathscr {T}\\&-f_{e,t}+B_e\theta _{i_e}-B_e\theta _{j_e}\le (1-\hat{z}_{e,t})M_e ,~~\forall e \notin \mathscr {E}',t\in \mathscr {T} \\&f_{e,t}-B_e\theta _{i_e}+B_e\theta _{j_e}\le (1-\hat{z}_{e,t})M_e ,~~\forall e \notin \mathscr {E}',t\in \mathscr {T} \\&(p_{m,t}^{-N}+p_{m,t}^{-F})-(p_{m,t}^{+N}+p_{m,t}^{+F})-\sum _{e\in \mathscr {E}'}f_{e,t}\le 0 ,~~\forall t\in \mathscr {T}\\&-(p_{m,t}^{-N}+p_{m,t}^{-F})+(p_{m,t}^{+N}+p_{m,t}^{+F})+\sum _{e\in \mathscr {E}'}f_{e,t}\le 0 ,~~\forall t\in \mathscr {T}\\&-p_{m,t}^{-N}-p_{m,t}^{-F}\le \hat{m}_t\sum _{e\in \mathscr {E}'}F_e ,~~\forall t\in \mathscr {T}\\&p_{m,t}^{-N}+p_{m,t}^{-F}\le \hat{m}_t\sum _{e\in \mathscr {E}'}F_e ,~~\forall t\in \mathscr {T}\\&-p_{m,t}^{+N}-p_{m,t}^{+F}\le \hat{m}_t\sum _{e\in \mathscr {E}'}F_e ,~~\forall t\in \mathscr {T}\\&p_{m,t}^{+N}+p_{m,t}^{+F}\le \hat{m}_t\sum _{e\in \mathscr {E}'}F_e ,~~\forall t\in \mathscr {T}\\&p_{m,t}^{-F}\le \overline{Pt}^{-F}_t ,~~\forall t\in \mathscr {T}\\&p_{m,t}^{+F}\le \overline{Pt}^{+F}_t ,~~\forall t\in \mathscr {T}\\&-y_{s,t}\le -S_s^{min} ,~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&y_{s,t}\le S_s^{max} ,~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&y_{s,1}-r_{s,1}^+\eta _s^++r_{s,1}^-/\eta _s^-\le S_{s,0} ,~~\forall s\in \mathscr {S}\\&-y_{s,1}+r_{s,1}^+\eta _s^+-r_{s,1}^-/\eta _s^-\le -S_{s,0} ,~~\forall s\in \mathscr {S}\\&y_{s,T}\le S_{s,0} ,~~\forall s\in \mathscr {S}\\&-y_{s,T}\le -S_{s,0} ,~~\forall s\in \mathscr {S}\\&y_{s,t}-y_{s,t-1}-r_{s,t}^+\eta _s^++r_{s,t}^-/\eta _s^-\le 0 ,~~\forall s\in \mathscr {S},t\in \{2,\dots ,T\}\\&-y_{s,t}+y_{s,t-1}+r_{s,t}^+\eta _s^+-r_{s,t}^-/\eta _s^-\le 0 ,~~\forall s\in \mathscr {S},t\in \{2,\dots ,T\}\\&r_{s,t}^+ \le R_s^+ ,~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&r_{s,t}^- \le R_s^- ,~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&\sum _{e:j_e=i}f_{e}+\sum _{g:i_g=i}p_{g,t}+\sum _{s:i_s=i}r_{s,t}^-+q_{i,t}-\sum _{e:i_e=i}f_{e}-\sum _{s:i_s=i}r_{s,t}^+\\&\le D_{i,t}-\sum _{pv:i_{pv}=i}\hat{PV}_{pv,t} ,~~\forall i\in \mathscr {I},t\in \mathscr {T}\\&-\sum _{e:j_e=i}f_{e}-\sum _{g:i_g=i}p_{g,t}-\sum _{s:i_s=i}r_{s,t}^--q_{i,t}+\sum _{e:i_e=i}f_{e}+\sum _{s:i_s=i}r_{s,t}^+\\&\le -D_{i,t}+\sum _{pv:i_{pv}=i}\hat{PV}_{pv,t} ,~~\forall i\in \mathscr {I},t\in \mathscr {T}\\&q_{i,t}\le D_{i,t} ,~~\forall i\in \mathscr {I},t\in \mathscr {T}\\&p_{g,t},c^u_{g,t},c^d_{g,t}\ge 0 ,~~\forall g\in \mathscr {G},t\in \mathscr {T}\\&p_{m,t}^{-N},p_{m,t}^{-F},p_{m,t}^{+N},p_{m,t}^{+F}\ge 0 ,~~\forall t\in \mathscr {T}\\&y_{s,t},r_{s,t}^+,r_{s,t}^-\ge 0 ,~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&q_{i,t}\ge 0 ,~~\forall i\in \mathscr {I},t\in \mathscr {T} \end{aligned}$$

Appendix B

The dual problem for the third part of the tri-level problem can be written as

$$\begin{aligned} \min _{\alpha ,\beta ,\gamma ,\delta ,\zeta ,\iota ,\kappa ,\lambda ,\mu ,\nu ,\xi ,\pi ,\tau ,\rho }~&\sum _{g}\big (\alpha _{g,1}\big (-C^u_g\big (\hat{x}_{g,1}-\overline{x}_{g,0}\big )\big )+\alpha '_{g,1}(-C^d_g\big (\overline{x}_{g,0}-\hat{x}_{g,1}\big )\big )\big )\\&+\sum _{g}\sum _{t=2}^{T}\big (\alpha _{g,t}\big (-C^u_g\big (\hat{x}_{g,t}-\hat{x}_{g,t-1}\big )\big )\\&+\alpha '_{g,t}\big (-C^d_g\big (\hat{x}_{g,t-1}-\hat{x}_{g,t}\big )\big )\big )\\&+\sum _{g}\big (\beta _{g,1}\big (\overline{p}_{g,0}+R^u_g\overline{x}_{g,0}+\tilde{R}^u_g\big (\hat{x}_{g,1}-\overline{x}_{g,0}\big )+P_g^{max}\big (1-\hat{x}_{g,1}\big )\big )\\&+\beta '_{g,1}\big (-\overline{p}_{g,0}+R^d_g\hat{x}_{g,1}+\tilde{R}^d_g\big (\overline{x}_{g,0}-\hat{x}_{g,1}\big )+P_g^{max}\big (1-\overline{x}_{g,0}\big )\big )\big )\\&+\sum _{g}\sum _{t=2}^{T}\big (\beta _{g,t}\big (R^u_g\hat{x}_{g,t-1}+\tilde{R}^u_g\big (\hat{x}_{g,t}-\hat{x}_{g,t-1}\big )+P_g^{max}\big (1-\hat{x}_{g,t}\big )\big )\\&+\beta '_{g,t}\big (R^d_g\hat{x}_{g,t}+\tilde{R}^d_g\big (\hat{x}_{g,t-1}-\hat{x}_{g,t}\big )+P_g^{max}\big (1-\hat{x}_{g,t-1}\big )\big )\big )\\&+\sum _{g}\sum _{t}(-\gamma _{g,t}\hat{x}_{g,t}P_g^{min} + \gamma '_{g,t}\hat{x}_{g,t}P_g^{max})\\&+\sum _{e}\sum _{t}(\hat{z}_{e,t}F_e(\delta _{e,t}+\delta '_{e,t}))+\sum _{e\notin \mathscr {E}'}\sum _{t}(1-\hat{z}_{e,t})M_e(\zeta _{e,t}+\zeta '_{e,t})\\&+\sum _{t}(\iota _{t}(0)+\iota '_{t}(0))+\sum _{t}\big (\sum _{e\in \mathscr {E}'}F_e\hat{m}_t(\kappa _{t}+\lambda _{t}+\kappa '_{t}+\lambda '_{t})\big )\\&+\sum _{t}(\mu _t\overline{Pt}^{-F}_t+\mu '_t\overline{Pt}^{+F}_t)+\sum _{s}\sum _{t}(-\nu _{s,t}S_s^{min}+\nu '_{s,t}S_s^{max})\\&+\sum _{s}S_{s,0}(\xi _{s,1}+\xi _{s,T+1}-\xi '_{s,1}-\xi '_{s,T+1})\\&+\sum _{s}\sum _{t=2}^{T}(\xi _{s,t}-\xi '_{s,t})(0)+\sum _{s}\sum _{t}(\pi _{s,t}R_s^++\pi '_{s,t}R_s^-)\\&+\sum _{i}\sum _{t}(\tau _{i,t}D_{i,t})+\sum _{i}\sum _{t}(\rho _{i,t}-\rho '_{i,t})(D_{i,t}-\sum _{pv:i_{pv}=i}\hat{PV}_{pv,t})\\ s.t.~&-\alpha _{g,t}\ge -1 ,~~\forall g\in \mathscr {G},t\in \mathscr {T}\\&-\alpha '_{g,t}\ge -1 ,~~\forall g\in \mathscr {G},t\in \mathscr {T}\\&\beta _{g,t}-\beta '_{g,t}-\beta _{g,t+1}+\beta '_{g,t+1}-\gamma _{g,t}+\gamma '_{g,t}+\rho _{i_g=i,t}-\rho '_{i_g=i,t}\\&\ge -C_g^p ,~~\forall g\in \mathscr {G}, t \in \{ 1,\dots ,T-1\} \\&\beta _{g,T}-\beta '_{g,T}-\gamma _{g,T}+\gamma '_{g,T}+\rho _{i_g=i,T}-\rho '_{i_g=i,T}\ge -C_g^p ,~~\forall g\in \mathscr {G}\\&-\delta _{e,t}+\delta '_{e,t}-\zeta _{e,t}+\zeta '_{e,t}+\rho _{j_e=i,t}-\rho '_{j_e=i,t}\\&-\rho _{i_e=i,t}+\rho '_{i_e=i,t}=0 ,~~\forall e\notin \mathscr {E}',t\in \mathscr {T}\\&-\delta _{e,t}+\delta '_{e,t}-\iota _{t}+\iota '_{t}+\rho _{j_e=i,t}-\rho '_{j_e=i,t}\\&-\rho _{i_e=i,t}+\rho '_{i_e=i,t}=0 ,~~\forall e\in \mathscr {E}',t\in \mathscr {T}\\ \end{aligned}$$
$$\begin{aligned}&B_e\zeta _{e,t}-B_e\zeta '_{e,t}= 0 ,~~\forall e\notin \mathscr {E}',t\in \mathscr {T}\\&-B_e\zeta _{e,t}+B_e\zeta '_{e,t}= 0 ,~~\forall e\notin \mathscr {E}',t\in \mathscr {T}\\&\iota _t-\iota '_t-\kappa _t+\kappa '_t+\mu _t\ge -C^{-F}_{m,t} ,~~\forall t\in \mathscr {T}\\&\iota _t-\iota '_t-\kappa _t+\kappa '_t\ge -C^{-N}_{m,t} ,~~\forall t\in \mathscr {T}\\&-\iota _t+\iota '_t-\lambda _t+\lambda '_t+\mu '_t\ge C^{+F}_{m,t} ,~~\forall t\in \mathscr {T}\\&-\iota _t+\iota '_t-\lambda _t+\lambda '_t\ge C^{+N}_{m,t} ,~~\forall t\in \mathscr {T}\\&-\nu _{s,t}+\nu '_{s,t}+\xi _{s,t}-\xi '_{s,t}-\xi _{s,t+1}+\xi '_{s,t+1}\ge 0 ,\\&~~\forall s\in \mathscr {S}, t\in \{1\dots ,T-1\}\\&-\nu _{s,T}+\nu '_{s,T}+\xi _{s,T}-\xi '_{s,T}+\xi _{s,T+1}-\xi '_{s,T+1}\ge 0 ,~~\forall s\in \mathscr {S}\\&-\eta ^+_s\xi _{s,t}+\eta ^+_s\xi '_{s,t}+\pi _{s,t}-\rho _{i_s,t}+\rho '_{i_s,t}\ge -C_s^+ ,\\&~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&\xi _{s,t}/\eta ^-_s-\xi '_{s,t}/\eta ^-_s+\pi '_{s,t}+\rho _{i_s,t}-\rho '_{i_s,t}\ge -C_s^- ,\\&~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&\tau _{i,t}+\rho _{i,t}-\rho '_{i,t}\ge -C^{sh}_{i,t} ,~~\forall i\in \mathscr {I},t\in \mathscr {T}\\&\alpha _{g,t},\alpha '_{g,t},\beta _{g,t},\beta '_{g,t},\gamma _{g,t},\gamma '_{g,t}\ge 0 ,~~\forall g\in \mathscr {G},t\in \mathscr {T}\\&\delta _{e,t},\delta '_{e,t}\ge 0 ,~~\forall e\in \mathscr {E},t\in \mathscr {T}\\&\zeta _{e,t},\zeta '_{e,t}\ge 0 ,~~\forall e\notin \mathscr {E}',t\in \mathscr {T}\\&\iota _t,\iota '_t,\kappa _t,\kappa '_t,\lambda _t,\lambda '_t,\mu _t,\mu '_t\ge 0 ,~~\forall t\in \mathscr {T}\\&\nu _{s,t},\nu '_{s,t},\xi _{s,t},\xi '_{s,t},\pi _{s,t},\pi '_{s,t}\ge 0 ,~~\forall s\in \mathscr {S},t\in \mathscr {T}\\&\tau _{i,t},\rho _{i,t},\rho '_{i,t}\ge 0,\forall ~~i\in \mathscr {I},t\in \mathscr {T} \end{aligned}$$

Appendix C

For reading purposes, some of the subindexes were removed in the following paragraphs. Note that, as \((\rho ^{(\omega )}_i-\rho '^{(\omega )}_i)(D_i-\sum _{pv:i_{pv}=i}PV_{pv})\) is a bilinear term, we need to use some linearization techniques in order to have a mixed-integer linear program. The uncertainty set \(\mathscr {PV}\), expressed in (10), only depending on variables \(a_{pv,t}\in [0,1]\) and \(b_{pv,t}\in [0,1]\), is a convex set. Then, the optimal value for \(PV_{pv,t}\) must be an extreme points of this set, i.e. \(a_{pv,t}\in \{0,1\}\) and \(b_{pv,t}\in \{0,1\}\). Then, the extreme point of \(PV_{pv,t}\) is given by

$$\begin{aligned}&PV_{pv}^* =PV^{mean}_{pv}-a_{pv}\sigma _{pv}+b_{pv}\sigma _{pv} ,\quad \forall pv \end{aligned}$$
(22)
$$\begin{aligned}&a_{pv},b_{pv}\in \{0,1\},\quad \forall pv \end{aligned}$$
(23)

Then, plugging (22) in the above mentioned bilinear term, we get

$$\begin{aligned}&(\rho ^{(\omega )}_i-\rho '^{(\omega )}_i)(D_i-\sum _{pv:i_{pv}=i}PV^{mean}_{pv})\nonumber \\&+\sum _{pv:i_{pv}=i}\sigma _{pv}(\rho ^{(\omega )}_ia_{pv}-\rho ^{(\omega )}_ib_{pv}-\rho '^{(\omega )}_ia_{pv}+\rho '^{(\omega )}_ib_{pv}) \end{aligned}$$
(24)

The terms involving \(\rho ^{(\omega )}_ia_{pv}\), \(\rho ^{(\omega )}_ib_{pv}\), \(\rho '^{(\omega )}_ia_{pv}\), and \(\rho '^{(\omega )}_ib_{pv}\) are still nonlinear. They can be linearized by replacing \(u^{(\omega )}_{pv}=\rho ^{(\omega )}_{i:i_{pv}=i,t}a_{pv}\), \(v^{(\omega )}_{pv}=\rho ^{(\omega )}_{i:i_{pv}=i,t}b_{pv}\), \(u'^{(\omega )}_{pv}=\rho '^{(\omega )}_{i:i_{pv}=i,t}a_{pv}\), and \(v'^{(\omega )}_{pv}=\rho '^{(\omega )}_{i:i_{pv}=i,t}b_{pv}\).

Then, (24) can be replaced by:

$$\begin{aligned} (\rho ^{(\omega )}_i-\rho '^{(\omega )}_i)(D_i-\sum _{pv:i_{pv}=i}PV^{mean}_{pv})+ \sum _{pv:i_{pv}=i}\sigma _{pv}(u^{(\omega )}_{pv}- v^{(\omega )}_{pv}- u'^{(\omega )}_{pv}+ v'^{(\omega )}_{pv}) \end{aligned}$$

and adding the following constraints, that also must be included in the reformulated problem, as part of uncertainty set, such that \(\mathbf U ^{(\omega )},\mathbf{PV }\in \mathscr {PV}\)

$$\begin{aligned}&u^{(\omega )}_{pv,t} \le a_{pv,t}M ,\quad \forall pv,t\in \mathscr {T}\\&u^{(\omega )}_{pv,t} \ge \rho ^{(\omega )}_{i:i_{pv}=i,t}-M(1-a_{pv,t}) ,\quad \forall pv,t\in \mathscr {T}\\&u^{(\omega )}_{pv,t} \le \rho ^{(\omega )}_{i:i_{pv}=i,t} ,\quad \forall pv,t\in \mathscr {T}\\&v^{(\omega )}_{pv,t} \le b_{pv,t}M ,\quad \forall pv,t\in \mathscr {T}\\&v^{(\omega )}_{pv,t} \ge \rho ^{(\omega )}_{i:i_{pv}=i,t}-M(1-b_{pv,t}) ,\quad \forall pv,t\in \mathscr {T}\\&v^{(\omega )}_{pv,t} \le \rho ^{(\omega )}_{i:i_{pv}=i,t} ,\quad \forall pv,t\in \mathscr {T}\\&u'^{(\omega )}_{pv,t} \le a_{pv,t}M ,\quad \forall pv,t\in \mathscr {T}\\&u'^{(\omega )}_{pv,t} \ge \rho '^{(\omega )}_{i:i_{pv}=i,t}-M(1-a_{pv,t}) ,\quad \forall pv,t\in \mathscr {T}\\&u'^{(\omega )}_{pv,t} \le \rho '^{(\omega )}_{i:i_{pv}=i,t} ,\quad \forall pv,t\in \mathscr {T}\\&v'^{(\omega )}_{pv,t} \le b_{pv,t}M ,\quad \forall pv,t\in \mathscr {T}\\&v'^{(\omega )}_{pv,t} \ge \rho '^{(\omega )}_{i:i_{pv}=i,t}-M(1-b_{pv,t}) ,\quad \forall pv,t\in \mathscr {T}\\&v'^{(\omega )}_{pv,t} \le \rho '^{(\omega )}_{i:i_{pv}=i,t} ,\quad \forall pv,t\in \mathscr {T}\\&b_{pv,t},a_{pv,t} \in \{0,1\} ,\quad \forall pv,t\in \mathscr {T}\\&PV_{pv,t}=PV^{mean}_{pv,t}+\sigma _{pv,t}(-a_{pv,t}+b_{pv,t}),\quad \forall pv,t\in \mathscr {T}\\&PV_{pv,t} \ge 0,\quad \forall pv,t\in \mathscr {T}\\&PV_{pv,t} \le \overline{PV_{pv}},\quad \forall pv,t\in \mathscr {T}\\&\sum _{pv}\sum _{t\in \mathscr {T}} (a_{pv,t}+b_{pv,t})\le \varGamma \end{aligned}$$

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Ruiz Duarte, J.L., Fan, N. Operations of a microgrid with renewable energy integration and line switching. Energy Syst 10, 247–272 (2019). https://doi.org/10.1007/s12667-018-0286-8

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