# Design and Optimization of a Grid-Connected Solar Energy System: Study in Iraq

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## Abstract

**:**

_{2}emission (3913 kg/year). Finally, the sensitivity analysis was performed on various critical parameters, which are found to affect the optimum results on different scales. Taking into consideration the recent advocacy efforts aimed at achieving the sustainable development targets, the models proposed in this paper can be used for a similar system design and operation planning that allow a shift to more efficient dispatch strategies of HESs.

## 1. Introduction

_{2}) in the atmosphere and, hence, mitigating the global warming issue [2]. In the 21st century, the transition to renewable energy is a global and unprecedented development. Renewable energy sources (RESs), such as solar photovoltaic (PV), solar thermal, hydropower, geothermal, wind, and biomass, could offer competitive cost options, clean and sustainable energy to everyone, regardless of their geographical location [3]. Electricity production from RESs increased by about 8% in 2021, reaching 8300 TWh, the largest yearly increase in more than 40 years. Due to the increased power generation from all RESs, the share of renewables in the electricity generation mix is expected to reach 30% in 2021. Figure 1 shows the increase in renewable energy production by region, country, and technology from 2020 to 2021 [4].

## 2. Methodology

#### 2.1. Assessment of Electricity Consumption

#### 2.2. Solar Energy Availability

^{2}/day in December to 7.560 kWh/m

^{2}/day in June, with a yearly mean solar irradiation of 5.06 kWh/m

^{2}/day. The clearness index is a measure of atmospheric attenuation. It is a dimensionless quantity between 0 and 1 and calculated as the ratio of the measured global solar radiation on the surface of the earth to the extraterrestrial solar radiation at the top of the atmosphere. The clearness index is low on cloudy days and high on clear/clean sky days. For the selected site, the clearness index varies between 0.521 in December and 0.657 in June.

#### 2.3. Schematic of the Proposed HES

#### 2.4. Mathematical Modeling

#### 2.4.1. PV Modeling

_{PV},

_{STC}: PV array rated power (kW);

_{PV}: derating factor (%);

_{S}: amount of solar radiation striking the PV array (kW/m

^{2});

_{S,STC}: standard radiation (1 kW/m

^{2});

_{T}: temperature coefficient of power (%/°C);

_{C}: PV cell temperature (°C);

_{STC}: PV cell temperature under standard test condition (25 °C).

#### 2.4.2. Battery

_{inv}: inverter efficiency (%);

_{rect}: rectifier efficiency (%);

_{rt}: battery round-trip efficiency (%).

#### 2.4.3. Converter

_{out}: output power of converter (kW);

_{in}: input power of converter (kW).

#### 2.4.4. Load Prediction

_{t}: level components;

_{t}: trend component;

_{t}: seasonal component;

_{t}: actual observed value;

_{t+τ}: forecast for τ periods ahead.

#### 2.4.5. Economic Mathematical Models

_{ann,total}: total yearly cost (USD/year);

_{p}: project lifetime (year);

_{served}: yearly electrical energy that is used to supply the load (kWh/year).

#### 2.5. Control Algorithm

#### 2.5.1. LF Strategy

- ➢
- Case 1: If the national grid is available, the following possible subcases take place:
- If the PV production exceeds the load, the PV power covers the load and the batteries store the excess power for later use.
- If the electricity consumption is higher than the PV production, the cost of buying power from the grid to meet the net load is compared with the batteries’ discharge cost. Two possibilities exist:
- ▪
- The batteries meet the net load if the cost of buying power from the grid to meet the net load is higher than the batteries’ discharging cost. Note that the net load is equal to the electricity consumption minus the electricity production from PV.
- ▪
- The national grid feeds the net load if its cost is lower than the batteries’ discharge cost.

- ➢
- Case 2: If the national grid is not available, there are two possibilities:
- If the electrical load requires lower power than the output of PV panels, the PV power covers the load and the excess electricity charges the batteries.
- If the electricity consumption is higher than the PV production, the net load is covered by discharging the batteries.

_{batt,w}: cost of battery wear (USD/kWh), and it is calculated using [24]:

_{life}: throughput of a single battery (kWh);

_{batt}: number of batteries in the storage bank.

#### 2.5.2. CC Strategy

- ➢
- Case 1: If the national grid is available, the following possible subcases take place:
- If the PV production exceeds the load, the PV power covers the load and the batteries store the excess power for later use.
- If the electricity consumption is higher than the PV production, the cost of buying power from the grid for the purpose of satisfying the remaining required load and charging the batteries is compared with the batteries’ discharge cost. Two possibilities exist:
- ▪
- The net load is satisfied by the battery if the cost of buying power from the grid for the purpose of satisfying the remaining required load and charging the batteries is higher than the batteries’ discharge cost.
- ▪
- Otherwise, the national grid meets the net load and allows the batteries to charge.

- ➢
- Case 2: If the national grid is not available, there are two possibilities:
- If the electrical load requires lower power than what the PV panels are generating, the PV power covers the load and the surplus power is used to charge the batteries.
- If the electricity consumption is higher than the PV production, the net load is satisfied by discharging the batteries.

_{batt,energy}: battery energy cost (USD/kWh) in time step n. It is calculated using [24]:

_{cc,i}: cycle charging cost in time step i (USD);

_{cc,i}: value of stored energy in the battery in time step i (kWh).

#### 2.5.3. The Modified Dispatch Strategy

- ➢
- Case 1: If the forecasted surplus electricity from the PV is higher than the upper limit, the following possibilities take place:
- If the national grid is available, the following possible subcases take place:
- ▪
- If the power produced by the PV in the current hour is greater than the load, the PV power covers the load and the batteries store the excess power for later use.
- ▪
- If the electricity consumption is higher than the PV production in the current hour, the cost of buying power from the grid for the purpose of satisfying the remaining required load is compared with the cost of discharging the batteries. Two possibilities exist as follows:
- ○
- The batteries meet the net load if the cost of buying power from the grid to meet the net load is higher than the batteries’ discharging cost.
- ○
- Otherwise, the national grid feeds the net load without charging the batteries. The grid does not charge the batteries in this case since in the upcoming hour, there is a lot of excess electricity, which can charge the batteries for free instead of buying power from the grid.

- If the national grid is not available, there are two possible subcases:
- ▪
- If the PV production in the current hour exceeds the load, the PV power covers the load and the batteries store the excess power for later use.
- ▪
- If the electricity consumption is higher than the PV production in the current hour, the net load is satisfied by the batteries.

- ➢
- Case 2: If the forecasted surplus electricity from the PV is higher than the upper limit, the following possibilities take place:
- If the national grid is available, the following possible subcases take place:
- ▪
- If the power produced by the PV in the current hour is greater than the load, the PV power covers the load and the excess electricity goes to charge the batteries.
- ▪
- If the PV does not provide enough power to cover the load alone, the national grid feeds the net load and charges the battery. The grid charges the battery in this case since in the upcoming hour, there is not enough excess electricity to charge the battery. This avoids capacity shortage when the national grid is not available in the upcoming hours, besides insufficient output power of PV to satisfy the load.

- If the national grid is not available, there are two possible subcases:
- ▪
- If the power produced by the PV in the current hour is greater than the load, the PV power covers the load and the surplus power is used to charge the battery.
- ▪
- If the electricity consumption is higher than the PV production, the remaining required load is met by the batteries.

## 3. Results and Discussion

#### 3.1. Prediction Model Validation

#### 3.2. Optimal Configurations

#### 3.3. Technical Analysis

#### 3.4. Environmental Analysis

_{2}removal technology, which directly targets the original reason of climate change by sequestering CO

_{2}from the air [57]. In comparison with the single conventional generation system, the HES has positive effects on the environment. In this study, the national grid is the only source of released emissions. In this section, the different dispatch strategies are compared with each other from the environmental perspective, and the results are provided in Table 6. For the LF strategy, the amounts of CO

_{2}, sulfur dioxide (SO

_{2}), and nitrogen oxide (NO

_{x}) emissions are calculated as 4550, 19.7, and 9.65 kg/year, respectively. In the case of the CC strategy, these values are evaluated as 7845, 34, and 16.6 kg/year, respectively. On the other hand, for the modified strategy, these emissions are estimated to be 3913, 16.94, and 8.3 kg/year, respectively. It is obvious that the HES configuration using the modified strategy provides greater savings in the released emissions compared with other strategies. This is mainly due to the low power purchase from the national grid in this strategy, which leads to reducing the amount of fuel consumption in comparison with other strategies.

#### 3.5. Sensitivity Analysis

^{2}/day increases the renewable fraction by 23.6% and decreases the NPC by 5.1%.

## 4. Conclusions

- The HES using the modified strategy offers the best economic performance with an NPC of USD 33,747, which is 16.3% and 3.1% lower than the system using the LF and CC strategies, respectively.
- The modified strategy results in the best reliable performance by having the lowest unmet load (87 kWh/year) in comparison with that of the LF and CC strategies, which are estimated at 143 and 118 kWh/year, respectively.
- From an environmental perspective, the modified strategy shows about 14% and 50.1% reduction in CO
_{2}in comparison with the two default strategies, LF and CC, respectively. - With respect to the sensitivity results, it is found that the grid power price, PV capital cost, solar radiation, mean grid outage frequency, annual average ambient temperature, and project lifetime affect the performance of the optimum HES on different scales.
- The validation of the load prediction model in Python ensures the accuracy of the proposed method in forecasting the load demand.
- The findings of this work show that the proposed strategy can be a realistic and cost-effective option to control the grid-connected HESs in Iraq. The obtained results can be further generalized to other countries that suffer from a severe shortage of electricity.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## Abbreviation

CC | cycle charging |

COE | cost of energy |

CO_{2} | carbon dioxide |

CRF | capital recovery factor |

HES | hybrid energy system |

HOMER | Hybrid Optimization of Multiple Energy Resources |

LF | load following |

NASA | National Aeronautics and Space Administration |

NOx | nitrogen oxide |

NPC | net present cost |

O and M | operation and maintenance |

PV | photovoltaic |

RES | renewable energy source |

SO_{2} | sulfur dioxide |

a, β, and γ | smoothing constants |

C_{ann,total} | total yearly cost |

C_{batt,energy} | battery energy cost |

C_{batt,w} | battery wear cost |

C_{cc,i} | cycle charging cost in time step i |

C_{disch} | battery discharging cost |

C_{T} | temperature coefficient of power |

D_{PV} | derating factor |

E_{cc,i} | value of stored energy in the battery in time step i |

E_{served} | yearly electrical energy that is used to supply the load |

F_{t+τ} | forecast for τ periods ahead |

i | yearly real interest rate |

L_{t} | level components |

m_{t} | trend component |

N_{batt} | number of batteries in the storage bank |

s | length of seasonality |

S_{t} | seasonal component |

P_{in} | input power of converter |

P_{L} | load demand |

P_{out} | output power of converter |

P_{PV} | PV output power |

P_{PV},_{STC} | PV array rated power |

Q_{life} | throughput of a single battery |

R_{S} | amount of solar radiation striking the PV array |

R_{S,STC} | standard radiation |

T_{C} | PV cell temperature |

T_{p} | project lifetime |

T_{STC} | PV cell temperature under standard test condition |

Y_{t} | actual observed value |

η_{inv} | inverter efficiency |

η_{rect} | rectifier efficiency |

η_{rt} | battery round-trip efficiency |

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**Figure 1.**Increase in electricity production from RESs by region, country, and technology, 2020–2021.

**Figure 14.**Comparative cost analyses of HES components for the (

**a**) LF, (

**b**) CC, and (

**c**) modified strategies.

**Figure 16.**One-year time series of power source outputs and ambient temperature for the (

**a**) LF, (

**b**) CC, and (

**c**) modified strategies.

**Figure 19.**Sensitivity analysis of the modified strategy by considering: (

**a**) grid power price, (

**b**) PV capital cost, (

**c**) annual solar radiation, (

**d**) grid outage frequency, (

**e**) annual ambient temperature, and (

**f**) project lifetime.

Component | Capital Investment | Operation and Maintenance (O and M) Cost | Replacement Cost | Reference |
---|---|---|---|---|

PV | USD 659/kW | USD 10/year/kW | USD 659/kW | [40] |

Battery | USD 538/battery | USD 8/year/battery | USD 538/battery | [36] |

Converter | USD 648/kW | USD 5.5/year/kW | USD 598/kW | [40] |

Reference | Parameter | Value |
---|---|---|

[40] | 1. PV | |

Panel type | Flat plate | |

Lifetime | 25 years | |

Tracking system | No | |

Nominal operating cell temperature | 47 °C | |

Nominal efficiency | 18% | |

Ground reflectance | 20% | |

[36] | 2. Batteries | |

Model | Trojan SAGM 12 20 | |

Nominal capacity | 2.63 kWh | |

Nominal voltage | 12 V | |

Round trip efficiency | 85% | |

Maximum Capacity | 219 Ah | |

[40] | 3. Converter | |

Lifetime | 15 years | |

Efficiency | 95% | |

Rectifier capacity | 100% |

**Table 3.**National grid power prices of the housing sector in Iraq [36].

Monthly Consumed Power (kWh) | Price (USD per kWh) | Price (IQD per kWh) |
---|---|---|

1–1500 | 0.0069 | 10 |

1501–3000 | 0.0240 | 35 |

3001–4000 | 0.0550 | 80 |

>4000 | 0.0827 | 120 |

Strategy | PV (kW) | No. of Batteries | Converter (kW) | COE (USD/kWh) | NPC (USD) |
---|---|---|---|---|---|

LF strategy | 12 | 28 | 5 | 0.147 | 40,336 |

CC strategy | 5 | 16 | 5 | 0.145 | 34,826 |

Modified strategy | 8 | 21 | 5 | 0.142 | 33,747 |

Parameter | LF Strategy | CC Strategy | Modified Strategy | Unit |
---|---|---|---|---|

Grid purchases | 7200 | 12,412 | 6188 | kWh/year |

PV production | 18,022 | 7509 | 12,014 | kWh/year |

Renewable fraction | 64.3 | 29.9 | 54.2 | % |

Excess electricity | 3485 | 703 | 1021 | kWh/year |

Unmet load | 143 | 118 | 87 | kWh/year |

Battery throughput | 199 | 379 | 224 | kWh/year |

Battery life | 11.5 | 6.3 | 10.2 | Year |

Emissions | Unit | LF Strategy | CC Strategy | Modified Strategy |
---|---|---|---|---|

CO_{2} | kg/year | 4550 | 7845 | 3913 |

SO_{2} | kg/year | 19.7 | 34 | 16.94 |

NO_{X} | kg/year | 9.65 | 16.6 | 8.3 |

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## Share and Cite

**MDPI and ACS Style**

Aziz, A.S.; Tajuddin, M.F.N.; Zidane, T.E.K.; Su, C.-L.; Mas’ud, A.A.; Alwazzan, M.J.; Alrubaie, A.J.K.
Design and Optimization of a Grid-Connected Solar Energy System: Study in Iraq. *Sustainability* **2022**, *14*, 8121.
https://doi.org/10.3390/su14138121

**AMA Style**

Aziz AS, Tajuddin MFN, Zidane TEK, Su C-L, Mas’ud AA, Alwazzan MJ, Alrubaie AJK.
Design and Optimization of a Grid-Connected Solar Energy System: Study in Iraq. *Sustainability*. 2022; 14(13):8121.
https://doi.org/10.3390/su14138121

**Chicago/Turabian Style**

Aziz, Ali Saleh, Mohammad Faridun Naim Tajuddin, Tekai Eddine Khalil Zidane, Chun-Lien Su, Abdullahi Abubakar Mas’ud, Mohammed J. Alwazzan, and Ali Jawad Kadhim Alrubaie.
2022. "Design and Optimization of a Grid-Connected Solar Energy System: Study in Iraq" *Sustainability* 14, no. 13: 8121.
https://doi.org/10.3390/su14138121