**4.1 Smart grid deployment reference model for a rural distribution grid**

**Table 7** presents the KPIs for a rural distribution grid project. It uses the reference model based on roles, which has 5 layers that are associated with the interoperability layers of the SGAM model.

**Figure 5.** *Distribution grid in rural area. \* Increased local economic development.*

*Smart Grid Project Planning and Cost/Benefit Evaluation DOI: http://dx.doi.org/10.5772/intechopen.96315*


*n: number of busses; Nb: number of time intervals; Ndes: number of Des, Ne: number of network elements; EG: Total energy generated by PVs [kWh]; EFG: Emissions Factor by Generation.*

#### **Table 7.**

*Evaluation criteria for a rural distribution grid.*

The A3 sub-criterion is properly a qualitative KPI, because it is an aspect associated with the increase of the local economy, the other KPIs can be calculated from the operation records and projections of the five alternatives to be considered.

#### **Figure 6.**

*AHP methodology. Goal, criteria, subcriteria and alternatives for rural distribution grid projects.*


#### **Table 8.**

*Corresponding weights for each layer and KPIs.*


#### **Table 9.**

*Performance matrix for increase local economic development.*


*Smart Grid Project Planning and Cost/Benefit Evaluation DOI: http://dx.doi.org/10.5772/intechopen.96315*

> **Table 10.** *Decisionmatrix.*

**Figure 7.** *Sensitivity analysis: a) NPV criterion; b) CO2 reduction criterion.*

#### **4.2 Multicriteria analysis for rural distribution grid projects**

The multi-criteria analysis for rural distribution grid used is AHP where qualitative and quantitative data can combine. In the case of quantitative data is required to maximize or minimize the KPI and calculate the corresponding weighting. For qualitative data is need a paired comparison using the Saaty's scale. **Figure 6** shows AHP's structure for rural distribution grid planning.

**Table 8** presents the performance matrix of each KPI in relation to the alternatives.

#### *4.2.1 Increased local economic development*

The A3 is the sub-criteria associated to Local development that significantly contributes to national economic performance and has become more critical with increased global competition, population mobility, technological advances, and consequential spatial differences and imbalances. Effective local development can reduce disparities between poor and rich places, add to the stock of locally generated jobs and firms, increase overall private sector investment, improve the information flows with investors and developers, and increase the coherence and confidence with which local economic strategy is pursued [33]. This can also give rise to better diagnostic assessment of local economic assets and distinctive advantages, and lead to more robust strategy assessment. This indicator is evaluated using Saaty's scale through pairwise comparison as shown in **Table 9**.

The AHP requires that the weightings of the criteria, sub-criteria and alternatives be calculated. After making these assessments, the decision matrix is obtained, providing the result of prioritization among the alternatives, as shown in **Table 10**.

**Figure 7** shows the sensitivity for A1(41%) and A2(3%) subcriteria, these are investment and reactive power exchange net value and CO2 reduction, the sensitivity analysis is calculated with decision matrix.

#### **5. Conclusions**

The proposed tool aims to simplify decision making processes, so a pilot project into SGAM reference model is represented. This tool adds one more step for identifying weaknesses and opportunities, realizing for sensitivity analysis to decisionmaking stability assessment. This implementation includes the tangibles and intangibles impacts and data collection and allows planning smart grid based on applications of an assessment framework.

*Smart Grid Project Planning and Cost/Benefit Evaluation DOI: http://dx.doi.org/10.5772/intechopen.96315*
