# A Comparison of Energy Management System for a DC Microgrid

^{1}

^{2}

^{*}

## Abstract

**:**

## 1. Introduction

^{®}optimization toolbox [13]. The solution of this model then allows us to evaluate the optimal management of energy storage devices. In addition to the geometric model of solar radiation, it is possible to evaluate the impact of the solar resource on energy management in that of storage systems. The analysis of optimal use of the storage system is illustrated by means of a numerical example, which considers a microgrid of four nodes.

## 2. Mathematical Modeling for DC Microgrid Components

#### 2.1. Batteries

_{S}the batteries variables, while $\left[{\mathrm{V}}_{\mathrm{j}}^{{\mathrm{t}}_{\mathrm{i}}}\right]\in {\mathrm{x}}_{\mathrm{R}}(\forall {t}_{i}\in T)$ The state of charge (SOC) of the j battery in the stage t

_{i}${SOC}_{Sj}^{{t}_{i}}$ can be calculated by means of Equation (2).

#### 2.2. Photovoltaic Modules

#### 2.3. Electrical Load

_{i}[18].

#### 2.4. Solar Radiation

## 3. DC Microgrid Model

#### 3.1. Specific Model of the DC Microgrid

#### 3.2. Algorithms

^{®}‘Direct Search and Genetic Algorithm Toolbox’ and is especially useful for the optimization of global non-linear problems with or without constraints. Furthermore, it provides a better flexibility since it contains multiple parameters of configuration [13,22].

^{®}‘Particle Swarm Toolbox’ and is especially useful for the optimization of global non-linear problems with or without constraints. Furthermore, it provides a better flexibility since it contains multiple parameters of configuration [13].

## 4. Results

^{2}) two store office block, which in fact forms part of a facility called the Hydrogen Center (University of Glamorgan at Baglan Energy Park, Port Talbot, United Kingdom).

^{®}. Figure 6 shows the comparison of the active power supplied by the photovoltaic panel and the battery for the two solar radiation conditions of a clean summer day in Cancun and Baglan. This figure shows that between the stages 8–20 h a demand profile is presented in the office block. In the demand that ranges between 1 and 6 KW, it is observed that the demand peaks occur at 9:30, 11:30, 13, 15 and 17 h.

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Nomenclature

Symbol | Description |

${t}_{i}$ | Time stage |

T | Time stages set |

${p}_{Snj}^{{t}_{i}}$ | Battery total power |

${p}_{Scj}^{{t}_{i}}$ | Battery charge power |

${p}_{Sdj}^{{t}_{i}}$ | Battery discharge power |

$so{c}_{sj}^{{t}_{i}}$ | State of charge |

$so{c}_{Sj}^{{t}_{0}}$ | Initial state of charge |

${\epsilon}_{cj}$ | Battery charge coefficient |

${\epsilon}_{dj}$ | Battery discharge coefficient |

${E}_{Snomj}$ | Nominal battery capacity |

${\mathrm{V}}_{\mathrm{sj}}^{{\mathrm{t}}_{\mathrm{i}}}$ | Voltage in the battery |

${\mathit{I}}_{CDk}^{{t}_{i}}$ | Current in panel terminals |

${I}_{PV}$ | Current of the photovoltaic panel |

${I}_{S}$ | Current of saturation |

${V}_{CD\text{}k}^{{t}_{i}}$ | DC voltage in the module PV |

${R}_{S}$ | Resistance in series |

${V}_{oc}$ | Voltage open circuit |

${n}_{s}$ | The number of cells in series |

${n}_{p}$ | The number of cell in parallel |

${V}_{mppt}$ | Voltage of the point of maximum power |

${I}_{SC}$ | Current of short circuit electricity |

${I}_{mppt}$ | Current maximum power point electricity |

${I}_{SC,stc}$ | Short circuit electricity standard under conditions of test |

$G$ | Irradiance |

${G}_{stc}$ | Irradiance under test electricity |

${k}_{l}$ | Temperature coefficient |

$\Im $, | Temperature of the panel |

${T}_{stc}$ | Standard temperature under test |

${V}_{oc,stc}$, | Standard low open circuit voltage conditions test |

${k}_{v}$ | Temperature coefficient |

${p}_{lm}^{{t}_{i}}$ | Load power |

${p}_{CDk}^{{t}_{i}}$ | Panel terminal power |

${F}_{T}$ | Objective function |

${n}^{{t}_{i}}$ | Equality constrains |

${z}^{{t}_{i}}$ | Inequalities constraints |

${x}^{{t}_{i}}$ | Variable inequalities constraints |

${p}_{pvj}^{{t}_{i}}$ | PV system power |

${\mathrm{V}}_{\mathrm{j}}^{{\mathrm{t}}_{\mathrm{i}}}$ | Grid nodal voltage |

${p}_{{R}_{j}}^{{t}_{i}}$ | Microgrid power |

${p}_{lj}^{{t}_{i}}$ | Line power |

## Appendix A

Node | Battery | Loads | PV |
---|---|---|---|

4 | 1 | 1 | 1 |

## References

- Owusu, P.A.; Asumadu-Sarkodie, S. A review of renewable energy sources, sustainability issues and climate change mitigation. Cogent Eng.
**2016**, 3, 1167990. [Google Scholar] [CrossRef] - Jiang, Q.; Xue, M.; Geng, G. Energy management of microgrid in grid-connected and ctand-alone modes. IEEE Trans. Power Syst.
**2013**, 28, 3380–3389. [Google Scholar] [CrossRef] - Hirsch, A.; Parag, Y.; Guerrero, J. Microgrids: A review of technologies, key drivers, and outstanding issues. Renew. Sustain. Energy Rev.
**2018**, 90, 402–411. [Google Scholar] [CrossRef] - García Vera, Y.E.; Dufo-López, R.; Bernal-Agustín, J.L. Energy management in microgrids with renewable energy sources: A literature review. Appl. Sci.
**2019**, 9, 3854. [Google Scholar] - Olivares, D.E.; Cañizares, C.A.; Kazerani, M. A centralized energy management system for isolated microgrids. IEEE Trans. Smart Grid
**2014**, 5, 1864–1875. [Google Scholar] [CrossRef] - Wang, X.; He, H.; Sun, F.; Sun, X.; Tang, H. Comparative study on different energy management strategies for plug-in hybrid electric vehicles. Energies
**2013**, 6, 5656–5675. [Google Scholar] [CrossRef] - Zia, M.F.; Elbouchikhi, E.; Benbouzid, M. Microgrids energy management systems: A critical review on methods, solutions, and prospects. Appl. Energy
**2018**, 222, 1033–1055. [Google Scholar] [CrossRef] - Fregosi, D.; Ravula, S.; Brhlik, D.; Saussele, J.; Frank, S.; Bonnema, E.; Wilson, E. A comparative study of DC and AC microgrids in commercial buildings across different climates and operating profiles. In Proceedings of the 2015 IEEE First International Conference on DC Microgrids (ICDCM), Atlanta, GA, USA, 7–10 June 2015; pp. 159–164. [Google Scholar]
- Zafar, A.; Shafique, A.; Nazir, Z.; Zia, M.F. A comparison of optimization techniques for energy scheduling of hybrid power generation system. In Proceedings of the 2018 IEEE 21st International Multi-Topic Conference (INMIC), Karachi, Pakistan, 1–2 November 2018; pp. 1–6. [Google Scholar]
- Keles, C.; Alagoz, B.B.; Kaygusuz, A. Multi-source energy mixing for renewable energy microgrids by particle swarm optimization. In Proceedings of the 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Turkey, 16–17 September 2017; pp. 1–5. [Google Scholar]
- Keles, C.; Kaygusuz, A.; Alagoz, B.B. Multi-source energy mixing by time rate multiple PWM for microgrids. In Proceedings of the 2016 4th International Istanbul Smart Grid Congress and Fair (ICSG), Istanbul, Turkey, 20–21 April 2016; pp. 1–5. [Google Scholar]
- Askarzadeh, A. A memory-based genetic algorithm for optimization of power generation in a microgrid. IEEE Trans. Sustain. Energy
**2018**, 9, 1081–1089. [Google Scholar] [CrossRef] - Mathworks, C. Optimization Toolbox ™ User’s Guide R2014b. Available online: https://www.mathworks.com/help/pdf_doc/gads/gads_tb.pdf (accessed on 1 January 2020).
- Tamrakar, V.; Gupta, S.C.; Sawle, Y. Study of characteristics of single and double diode electrical equivalent circuit models of solar PV module. In Proceedings of the 2015 International Conference on Energy Systems and Applications, Pune, India, 30 October–1 November 2015; pp. 312–317. [Google Scholar]
- Bellini, A.; Bifaretti, S.; Iacovone, V.; Cornaro, C. Simplified model of a photovoltaic module. In Proceedings of the 2009 Applied Electronics, Pilsen, Czech Republic, 9–10 September 2009; pp. 47–51. [Google Scholar]
- Polanco Vasquez, L.O.; Carreño Meneses, C.A.; Pizano Martínez, A.; López Redondo, J.; Pérez García, M.; Álvarez Hervás, J.D. Optimal energy management within a microgrid: A comparative study. Energies
**2018**, 11, 2167. [Google Scholar] [CrossRef][Green Version] - Wp, S. SLA-M 300 Wp Silfab Solar Inc., Data sheet module Silfab. 1 December 2018. Available online: https://silfabsolar.com/sla-300-m/ (accessed on 31 January 2020).
- Zhang, F.; Thanapalan, K.; Procter, A.; Carr, S.; Maddy, J.; Premier, G. Power management control for off-grid solar hydrogen production and utilisation system. Int. J. Hydrogen Energy
**2013**, 38, 4334–4341. [Google Scholar] [CrossRef] - Ramírez Basalo, M.Á. Diseño de un modelo informático para la estimación de la energía generada en el vehículo solar Aníbal. Universidad Politécnica de Cartagena. 2012. Available online: http://repositorio.upct.es/handle/10317/2974 (accessed on 31 January 2020).
- Iturriaga, E.; Aldasoro, U.; Campos-Celador, A.; Sala, J.M. A general model for the optimization of energy supply systems of buildings. Energy
**2017**, 138, 954–966. [Google Scholar] [CrossRef] - Silva, M.; Morais, H.; Vale, Z. An integrated approach for distributed energy resource short-term scheduling in smart grids considering realistic power system simulation. Energy Convers. Manag.
**2012**, 64, 273–288. [Google Scholar] [CrossRef][Green Version] - Ackermann, T.; Andersson, G.; Söder, L. Distributed generation: A definition. Electr. Power Syst. Res.
**2001**, 57, 195–204. [Google Scholar] [CrossRef]

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Vásquez, L.O.P.; Ramírez, V.M.; Thanapalan, K. A Comparison of Energy Management System for a DC Microgrid. *Appl. Sci.* **2020**, *10*, 1071.
https://doi.org/10.3390/app10031071

**AMA Style**

Vásquez LOP, Ramírez VM, Thanapalan K. A Comparison of Energy Management System for a DC Microgrid. *Applied Sciences*. 2020; 10(3):1071.
https://doi.org/10.3390/app10031071

**Chicago/Turabian Style**

Vásquez, Luis O. Polanco, Víctor M. Ramírez, and Kary Thanapalan. 2020. "A Comparison of Energy Management System for a DC Microgrid" *Applied Sciences* 10, no. 3: 1071.
https://doi.org/10.3390/app10031071