**2. Methodology**

There were four steps used. First, ultimate analysis data and calorific value of the organic fraction of MSW (OFMSW) were collected based on literature data [12, 13]. Second, the hypothetical chemical formula was calculated from their ultimate analysis data as a basis for estimating the energy released when thermal conversion and bioconversion processes were applied. Third, correlations between higher heating value (HHV) and ultimate analysis data were developed. Fourth, comparing the

*Estimating the Calorific Value and Potential of Electrical Energy Recovery of Organic… DOI: http://dx.doi.org/10.5772/intechopen.108232*

potential energy recovered from experimental, stoichiometric manner, and empirical models developed.

#### **2.1 Characteristics of waste**

The characteristics of OFMSW data such as ultimate analysis included carbon (C), hydrogen (H), nitrogen (N), oxygen (O), sulfur (S) (mass percentages on a dry basis), and water content (H2O, mass percentages as discarded), calorific value, volatile solid (VS), and lignin content were used. As reported in [12], the organic fraction of MSW was collected from a landfill site in Indonesia. The content of carbon (C) was determined by the standard American Standard for Testing Materials ASTM) D 5373, hydrogen (H) by the standard ASTM D 5373, nitrogen (N) by the standard ASTM D 5373, oxygen (O) by standard ASTM D 3176, and sulfur (S) by standard ASTM D 4239. These elemental analysis data were performed using CHNS-O Analyzers (Perkin-Elmer 2400 Series) at the mineral and coal technology laboratory, Bandung Indonesia [12]. The higher heating value (HHV) of the sample was determined based on the standard ASTM D 5865 by using Bomb Calorimeter [12]. The lignin content was analyzed at Food and Nutrient Laboratory Gadjah Mada of University Yogyakarta [13].

#### **2.2 Hypothetical development chemical formula**

The molecular formula is the actual whole number ratio between the elements. The quantity of each element was divided by its molar mass to give the number of hypothetical moles of each element. Furthermore, these mole ratios were used to determine the molecular formula. The molecular formula was used too in determining the principal reactions that occur during combustion and bioconversion.

#### **2.3 Empirical correlations**

Correlations between calorific value with percent carbon (C), hydrogen (H), oxygen (O), nitrogen (N), and sulfur (S) were used to estimate calorific value. In this case, correlations equations were developed from previously available empirical equations (**Table 1**).

The fulfillment of model performances was assessed by four statistical criteria, namely: sample paired test, coefficient of correlation, average absolute error (AAE), and average bias error (ABE). Sample paired test and coefficient of correlation were determined by SPSS 17 version. The symmetrical relationships were used to determine the correlation between the calorific value of the calculation results of the model with the measurement. The coefficient correlations were used to determine strong or weak relationships by the following criteria: 0.00–0.199 very weak, 0.20–0.399 weak, 0.40– 0.599 sufficient, 0.60–0.799 strong, and very strong 0.80–1.00.

The average absolute error can be expressed as follow:

$$AAE = \frac{1}{n} \sum\_{i=1}^{n} \left| \frac{Ya - Yp}{Ya} \right| \times 100\text{\%} \tag{11}$$

Where AAE is the mean percentage of absolute error, Ya and Yp are the actual and expected values. n represents the number of data points. The sum of squared errors can be given by the following equation:



*Correlation models from any research.*

*Estimating the Calorific Value and Potential of Electrical Energy Recovery of Organic… DOI: http://dx.doi.org/10.5772/intechopen.108232*

$$ABE = \frac{1}{n} \sum\_{i=1}^{n} \frac{Ya - Yp}{Ya} \times 100\% \tag{12}$$

Where ABE is the mean percentage of bias error.
