# A Techno-Economic Analysis of Energy Storage Components of Microgrids for Improving Energy Management Strategies

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## Abstract

**:**

## 1. Introduction

## 2. Energy Management Strategies in Microgrids

#### 2.1. Presentation of the Microgrid

#### 2.1.1. Definition of the Hybrid Energy Storage System

^{−1}), $R$ is the gas constant (J.mol

^{−1}.K

^{−1}), I is the battery charging current expressed in C-rate, ${T}_{Bat}$ is the battery temperature (K), ${B}_{i}$ is the $SOC$ influence coefficient, and ${C}_{i}$ is the current influence coefficient expressed in (h. p.u

^{−1}). ${T}_{r}$ is the reference temperature where the “$i$” aging mechanism influence is assumed to be zero (typically ${T}_{r}=0\mathrm{K}$ for calendar and hot cycling aging). $b$ and $c$ are unitless model parameters. C-rate is a measure of charging or discharging current, expressed as a ratio of the rated capacity to the time required to fully charge an energy storage system.

#### 2.1.2. Photovoltaic Panel System

#### 2.1.3. Connection to the Utility Grid

#### 2.2. Development of Control Strategies

#### 2.2.1. Strategy 1: Classical Microgrid Energy Management

#### 2.2.2. Control Strategy Considering Battery Aging

- During peak hours, the price per kWh from the grid is higher than the battery’s one. The load is supplied from the battery;
- During off-peak hours, the grid kWh cost is cheaper than the battery’s one. Extra power is purchased from the grid. Table 1 shows the prices per kWh for the grid and battery.

## 3. Simulation Results

#### 3.1. Comparison of Strategies 1 and 2 Regarding Battery Aging

#### 3.2. Techno-Economic Study

#### 3.3. Simulation Results of the HESS

#### 3.4. Simulation Results under Extreme Temperature Conditions

## 4. Conclusions and Perspectives

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 6.**Photovoltaic installation of the Centre Pierre Guillaumat of UTC [17].

Grid | Battery | |
---|---|---|

Peak hours | 0.7 | 0.3 |

Off-peak hours | 0.1 | 0.3 |

**Table 2.**Total cost of strategies 1 and 2 for a 20-year microgrid project with $SO{C}_{max}$ = 100 and $T$ = 25 °C.

Strategy 1 | Strategy 2 | |
---|---|---|

qloss (p.u. × 10^{−4}) | 10 | 7.84 |

Battery life (years) | 5.5 | 7 |

Total cost of energy purchased for 20 years (EUR) | 720 | 2380 |

Number of battery replacements over 20 years | 4 | 3 |

Battery cost over 10 years (EUR) | 18,201 | 14,308 |

Total project cost over 10 years (EUR) | 18,921 | 16,688 |

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**MDPI and ACS Style**

Ndiaye, A.; Locment, F.; De Bernardinis, A.; Sechilariu, M.; Redondo-Iglesias, E.
A Techno-Economic Analysis of Energy Storage Components of Microgrids for Improving Energy Management Strategies. *Energies* **2022**, *15*, 1556.
https://doi.org/10.3390/en15041556

**AMA Style**

Ndiaye A, Locment F, De Bernardinis A, Sechilariu M, Redondo-Iglesias E.
A Techno-Economic Analysis of Energy Storage Components of Microgrids for Improving Energy Management Strategies. *Energies*. 2022; 15(4):1556.
https://doi.org/10.3390/en15041556

**Chicago/Turabian Style**

Ndiaye, Alla, Fabrice Locment, Alexandre De Bernardinis, Manuela Sechilariu, and Eduardo Redondo-Iglesias.
2022. "A Techno-Economic Analysis of Energy Storage Components of Microgrids for Improving Energy Management Strategies" *Energies* 15, no. 4: 1556.
https://doi.org/10.3390/en15041556