Simulation of integrated rural energy system for farming in Bangladesh

Pergamon

SIMULATION

Plh S0360-5442(96)00155-7

Energy Vol. 22, No. 6, pp. 59t-599, 1997 © 1997 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0360-5442197 $ t7.00 + 0.00

OF INTEGRATED RURAL ENERGY FARMING IN BANGLADESH

SYSTEM FOR

M. S. ALAM,** B. K. BALA ~ and A. M. Z. HUQ ~ ~Department of Electrical & Electronic Engineering, Bangladesh Institute of Technology, Rajshahi, Bangladesh, ~Department of Farm Power & Machinery, Bangladesh Agricultural University, Mymensingh, Bangladesh and Bangladesh ¶Depaxtment of Electrical & Electronic Engineering, Bangladesh University of Engineering & Technology, Dhaka, Bangladesh

(Received 8 June 1996)

Abstract--Previous efforts in rural energy modelling have been reviewed and critically examined. A system-dynamics model of an integrated energy system for farming in Bangladesh has been developed based on Huq's revised model. The model considers energy use in various forms, including food production and consumption. The physical quality of life is also discussed. The model incorporates existing feedback loops, non-linearity, and time-lag characteristics inherent in real world systems. The model has been used to simulate different energetic variables for farming systems in Bangladesh. Implications of policy changes are discussed. © 1997 Elsevier Science Ltd. All rights reserved.

INTRODUCTION

Bangladesh is a densely populated, largely rural, food-deficient country with rapidly diminishing bioenergy resources. Self-reliant development must consider not only food production but also populationcontrol measures and increased production policies and planned use of energy for improving the quality of life with self-sufficiency in energy production. The integrated energy system for farm production involves biological, technological, economic, and social elements. A modelling endeavour for such a system is a formidable challenge. Edelman [1] and Baughman and Hnyilicza [2] have presented an overview of energy modelling, examined various methodological approaches available and discussed alternative ways in which the model can be used. Pellizi [3] simulated an integrated energy system for a Kenyan village to assess energy requirements for food self-sufficiency. Adams et al [4] developed an optimization model for the production and distribution of liquid biomass fuel and its economic relation to the production of other agricultural products. Lewis et al [5] developed a system-dynamic model for a South Indian village to demonstate how economical biogas plants could be developed. Jordanides and Meditch [6] critically reviewed previous efforts on modelling petroleum utilization in the U.S. and formulated a system-dynamic model for policy analysis. Huq [7] proposed a more complete and realistic qualitative model for integrated rural energy utilization in Bangladesh. Bala and Sattar [8] developed a simulated model that considers integrated energy use for food production. Parikh [9,10] developed a general linear programming model for energy and agricultural interaction in rural areas of developing countries; this model was applied to Bangladesh. Alam et al [11] developed a systemdynamic model for the integrated rural energy system of a Bangladeshi village. Nail [12] described the conceptual development of a model for U.S. energy supply and demand which has been used for projections in energy-policy analysis. Nail's model represents one of the real success stories of system dynamics. Here, we present a model of an integrated rural energy system for farming in Bangladesh and evaluate system performance in terms of the physical quality of life (PQL) index. MODELLING

Successful integration of energy systems requires detailed information on dynamic behaviour. By substituting models for real systems, designers of integrated energy systems can perform tests to find

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7

Integrated rural energy system

593

Table I. Energy use pattern in Bangladesh fanning activities, 1980-1986; from Ref. 8. Operation

1980-81

1981-82

1982-83

1983-84

1984-85

1985-86

21.44

21.16

20.90

20.64

21.38

21.98

Draft cattle ( 106 heads)

11.43

11.28

11.14

11.00

11.40

11.72

Draft power (kW/ha)

0.22

0.21

0.21

0.20

0.20

0.21

20.91

21.78

22.12

22.12

22.06

22.36

1033

1130

1340

1536

1739

1721

Ploughing Total cattle 106, heads

Energy input (GJ × 106)

Irrigated area (ha) Modern × 103 Traditional x 103 Energy input Diesel (GJ × 106)

643

643

549

463

376

377

2.94

3.17

3.17

4.32

3.87

4.84

242.5

249.4

325.7

382.6

365.7

Fertilizer Application Nutrient Urea 262 (Mt × 103) TSP ( M t × 103)

100.5

97.4

94.4

119.9

159.0

136.8

MP (Mt x 103)

27.6

27.6

30.6

37.5

41.5

35.9

Average (kg/ha)

31.38

30.26

34.74

40.35

44.35

39.76

Energy input (GJ x 106)

21.93

20.38

24.00

27.22

32.21

30.54

alternative courses of actions and trade-offs with models that are accurate representations of the real systems. System-dynamic methodology appears to be the most appropriate technique for handling complex systems. The rural energy system for farming consists of several closed loops. Feedback for these loops simulates the dynamic behaviour of the system. The quality of life, food per capita and population density link the population non-linearly. These factors act as the mechanism for population control. The system-dynamic block diagram of the population sub-model is shown in Fig. 1. Cattle supplies the entire draft energy for land preparation in Bangladesh. The cattle population is determined by birth, importation and consumption rates. Price links the cattle population non-linearly through deficit in draft power, production and consumption. Cattle raisers adjust their expected price in response to price received in the past. Accordingly, their expectation to raise cattle is continuously adjusted in response to price and availability of fodder. The cattle-production rate is either increased or decreased continuously to adjust the gap between actual and desired capacity over a period of 2.25 years. It is also greatly influenced by the availability of straw, which is the principal source of staple feed supply for Bangladesh cattle. The projected quantity of power tillers is proportional to the difference of optimum draft power required for tillage operation and the draft power available from the cattle population. The system-dynamic block diagram for this cattle population sub-model was given in Ref. 8. The crop-production system deals mainly with the production of food grain and straw. The straw is primarily used for cattle feed. Major inputs to crop production are seed, irrigation, fertilizer, and human and cattle power. Since land is limited, crop production must be increased by using high-yielding varieties in conjunction with irrigation and fertilizers. The yield is influenced by draft power from the cattle population. The cattle-population system, in turn, is influenced by crop production. The systemdynamic block diagram for the crop-production sub-model was also given in Ref. 8. The cattle-production system provides not only draft power but also cow dung, which is supplied to the biogas system. The biogas system has essentially a biogas digester for the production of biogas. Thus, crop, cattle and biogas production form a closed loop. The proposed biogas production system shown in Fig. 2 supplies

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biogas as a fuel for cooking and therefore reduces the pressure on rural forests and also diminishes pollution. Treated slurry replaces the use of commercial fertilizer in crop production. This process, in turn, reduces the ecological imbalance. The energy-use pattern in the rural farming sector of Bangladesh is presented in Table 1. The quality of life is used here as a measure of performance for integrated rural energy systems. It is computed by using multipliers obtained from food, crowding, and biogas as cooking fuel [13]. The multipliers are chosen to be 1 for 1980. Figure 3 represents the system-dynamic block diagram for the PQL sub-model. SIMULATED RESULTS

To illustrate the use of the model as a tool for policy planning, it was evaluated in both the basic and policy-planning modes during the period 1980-2010. The basic mode corresponds to existing conditions, whereas the policy-planning mode corresponds to a policy option that is being tested• Model results for both modes are shown in Figs. 4-10. The policy mode involves biogas production at a rate equal 4.4

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Fig. 4. Irrigated area, total food, and food per capita during the period 1980-2010 (-- policy mode).

basic mode, - - -

Integrated rural energy system

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policy mode).

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to 15% of the difference between the biogas potential and the actual level of biogas production, while the draft-power constraint remains constant throughout the simulation period and a 5% increment is implemented in the importation rate of cattle as a ramp input to the cattle-production system. The energy coefficient for different energetic variables are presented in Table 2. The total food production in the basic mode (see Fig. 4) is seen to rise from 19.76x 109 to 23.04 x 109 k g from 1980 to 2010 and to 24.76 x 109 kg in the policy mode. The per capita available food varies from 186 to 144 kg in the basic mode and is 157 kg in the policy mode, which is below the subsistence requirement. The irrigated area is increased to 4.24 x 106 hectares by 2010. Cattle population and draft-power level are shown (see Fig. 5) to change and oscillate with time. The amplitude ranges of oscillation in the basic mode fall from 21.8 to 19:23 x 106 for the cattle population and from 0.238 to 0.210 kW/hectare for draft power. In the policy mode, the amplitude range of the oscillation is within 21.80 x l06 heads for the cattle population. The range for draft power lies in the range 0.238-0.220 kW/hectare, whereas the optimum requirement of draft power/hectare is 0.373 kW. The simulated level of the draft-power shortage and power tillers required to compensate the draft-power shortage change and oscillate with time (see Fig. 6). The amplitude range is 972.81109 x 103 kW for draft-power shortage and 107-122 units for power-fillers requirements. The draft power-output rating of a power tiller is 9.8 kW [14]. Adaptation of a policy for installation of biogas digesters will save at most 24.79% of the optimal

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Fig. 7. Biogas potential, biogas production and percentage of cooking energy saved during the period 19802010 ( basic mode, - - - policy mode). 15°1 1401¢_

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Fig. 8. N2, P205 and K20 (organics) available during the period 1980-2010 ( mode).

2010 basic mode, - - -

policy

cooking energy of 4.2 GJ (see Fig. 7). The biogas potential and actual level of biogas production are illustrated in Fig. 7. Model results for organic manure availability as a fertilizer to supplement N2, P205 and K20 requirements are shown in Fig. 8. Percentages of commercial fertilizers (N2, P205 and K20) saved are shown in Fig. 9. Figure 10 indicates population increases from 89.93 to 159.8 x 106 in the basic mode and to 159.00 x 106 in the policy mode by 2010. The quality of life is assumed to be a product function of food, crowding and biogas. In the basic mode, the quality of life is reduced to 0.77 in 2010 from 1 in 1980 while it is always greater than 0.97 in the policy mode. DISCUSSION AND CONCLUSIONS

Validation of a model verifies its utility [15]. Table 3 shows both model results and data obtained by others ,on human and animal populations, irrigated area, and food production for the farming sector [16-18]. The agreement is seen to be good. There is increased food production with increased irrigation. Pulsations in food production are caused by limit-cycle oscillations in cattle production for the non-

Integrated rural energy system

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0.6 1980

I 1985

I 1990

I 1995 Year

I 2000

Fig. 10. Population and quality of life during the period 1980-2010 (

I 2005

2010

basic mode, - - -

policy mode).

linear system. Since cattle supplies draft power for tillage, this relation is obvious for a deficit of draft power. The pulsating behaviour of food production may possibly be suppressed by the removal of deficit of draft power. The simulated cattle population is not far removed from the prediction of Dickey and Hoque [ 19]. The model shows that the total yearly average draft-power shortage is 1.047× 1 0 6 k W (0.1415 kW/ha). If power tillers are used only to meet the estimated shortage of draft power, 1.15 x 103 power tillers will be required on average, which is close to the estimated figure (1.32 x 103) of BEPP [14]. Animal draft power and manures are an integral part of food production in Bangladesh and may be utilized with considerable benefits [20,21]. Utilizing biogas technology, almost 25% of the rural cooking energy and 15% of commercial fertilizers may be saved. Thus, an integrated energy system for food production should not only consider animal draft power but also the full potential of animal dung and biogas production. The model results show that the population-growth rate is much higher than the growth rate of food production. For the proposed policy, the model shows that the PQL of the rural sector of Bangladesh improves significantly. The model also indicates that self-reliance in food and energy is essential to raise the PQL.

M. S. Alam et al

598

Table 2. Energy coefficients of the different elements of energy sources in farming activities. Source: Alam [22]. Description

Coefficient

Human muscle power/capita Draft animal power/animal Nitrogen in dung Phosphorus in dung Potassium in dung Energy required for irrigation equipment Energy for pesticide Energy in seed Energy in cow dung Energy in commercial fertilizer, Nitrogen Energy in commercial fertilizer, Phosphorus Energy in commercial fertilizer, Potassium Energy in tree biomass Energy in kerosine Energy in rice Energy in rice husk Energy in ricestraw Power tiller output power Average solar energy incident

628 × 10-~ GJ/hr 1674 × 10--6 GJ/hr 0.5% 0,2% 0,47% 86.7 x 10--6 GJ/kg 101.3 × 10-3 GJ/kg 15.49 × 10-3 GJ/kg 13.46 x 10-3 GJ/kg 77.4 × 10-3 GJ/kg 13.8 x 10-3 GJ/kg 09.6 x 10-3 GJ/kg 15.16 x 10-3 GJ/kg 46.05 x 10-3 GJ/kg 14.53 × 10-3 GJ/kg 15.57 × 10-3 GJ/kg 15.17 × 10-3 GJ/kg 9.8 kW/unit 65.15 × 103 GJ/ha

Table 3. Comparison between model results and data obtained by others; from Ref. 8. Population (106 )

Cattle (106)

Irrigated Area (106)

Food (106)

Year

A

B

C

A

B

A

B

D

A

B

E

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2005

89.9 91.7 93.5 95.5 97.5 99.5 101.6 103.7 105.8 108.0 110.2 112.4 114.7 117.0 119.4 121.7 124.1 126.5 128.9 131.0 133.4 146.6

87.4 89.2 81.1 83.0 95.0 97.0 99.0 101.1 103.2 105.1 108.0 109.9 112.2 114.6 116.9 119.4 121.8 124.4 127.1 129.7 -

89.7 95.2 99.6 113.0 129.4 147.3 166.2

21.8 21.2 20.8 20.6 20.6 20.9 21.3 21.6 21.9 22.1 22.2 22.2 22.0 21.8 21.4 21.2 21.0 20.7 20.5 20.4 20.4 .

21.4 21.2 20.9 20.7 21.4 22.0 22.9 23.4 23.5 23.6 23.4 23.3 22.9 22.3 21.9 21.4 21.1 20.8 20.7 20.9 .

1.22 1.30 1.37 1.45 1.53 1.61 1.70 1.77 1.87 1.96 2.05 2.14 2.24 2.33 2.43 2.53 2.63 2.73 2.83 2.94 3.05 .

1.25 1,29 1.32 1,34 1.37 1.39 1.47 1.44 1.46 1.47 1.49 1.51 1.52 1.54 1.55 1.56 1.57 1.58 1.59 1.60 .

1.10 1.19 1.28 1.47 1.49 1.80 -

16.8 16.7 16.7 16.8 16.1 17.4 17.8 18.2 18.5 18.9 19.1 19.4 19.5 19.6 19.8 19.9 20.0 20.1 20.3 20.5 20.7

14.6 14.5 14.4 14.4 14.4 14.7 14.9 15.3 15.5 15.6 15.6 15.6 15.6 15.5 15.3 15.1 14.9 14.9 14.8 14.8

15.0 14.6 15.3 15.7 16.1 16.1 16.2 16.4 -

.

.

.

.

Source: A, present study; B, Bala [8]; C, Mustaq [22]; D Statistical Year Book [17]; E, UNDP [18]; F, BEPP [12]; (approximately 85% of which may be assumed to be rural domestic consumption).

Implementation

of the model

requires continuing

surveys and updating

initial values, and data. Sensitivity analysis of the parameters

of parameters,

constants,

is also required to determine policy-

entry points.

REFERENCES 1. D a v i d E d e l m a n , J., Environmental Systems, 1977, 7, 279. 2. B a u g h m a n , L. M., Martin, M. and H n y i l i c z a , E., IEEE. 1975, 63, 475.

Integrated rural energy system

599

3. Pellizi, G., Agriculture Mechanization in Asia, Africa and Latin America, 1984, 15, 21. 4. Adams, R. I., Stulp, V. J. and Konzen, O. G., National model of production, distribution and consumption of biomass energy. In Energy from Biomass, 2nd E.C. Conference, eds. A. Strub, P. Chartier and Schleser, Applied Science Publ. Ltd., London, 1982, pp. 771-774. 5. Lewis, C. W., Slesser, M. and Hounam, I., Biomass use for self-reliant development of third world rural countries, pp. 766--770 in [4]. 6. Jordanides, T. and Meditch, J. M., IEEE SMC-7 1977, 247. 7. Huq, A. M. Z., Energy modelling for agricultural units in Bangladesh, paper presented at the National Seminar on Integrated Rural Development, Dhaka, 1975. 8. Bala, B. K. and Sattar, M. A., Modelling of integrated energy systems for food production in developing countries, Proceedings of the 2nd International Conference on Energia and Agricultura, 1986, 3, 306, Sirmione/Brescia. 9. Parikh, J., Energy--The International Journal, 1985, 10, 793. 10. Parikh, J. K. and Kronmer G., Energy--The International Journal, 1985, 10, 805. 11. Alam, M. S., Huq, A. M. Z. and Bala, B. K., Energy--The International Journal, 1990, 15, 131. 12. Nail, R. F., System Dynamics Review, 1992, 8, 1. 13. Forrester, J. W., Worm Dynamics. Wright Allen Press, Boston, MA, 1971. 14. BEPP, Bangladesh energy planning project: interim report. Planning Commission, Govt of Bangladesh, Dhaka, 1984. 15. Forrester, J. W. and Senge, P. M., Test of Building Confidence in a System Dynamics Model. North Holland, Amsterdam, 1980. 16. Ahmand, M., Bangladesh agriculture towards self sufficiency. Ministry of Information, Govt of Bangladesh, Dhaka, 1988. 17. Bangladesh Bureau of Statistics, Statistical year book of Bangladesh, Dhaka, 1986. 18. UNDP, Bangladesh agriculture sector review--II, Bangladesh, March 1989. 19. Dickey, R. J. and Emdadul Huque, Q. M., Status of the Bangladesh livestock industry in relation to fodder supply and consumption of annual products. Bangladesh Agricultural Research Council/Winrock International Institute for Agricultural Development, Dhaka, 1986. 20. Hoque, M. S., Present availability of nitrogen from organic wastes and biological sources, Proceedings of the National Seminar on Nitrogen in Crop Production, Mymensingh, 1977. 21. O'Callaghan, J. R. O., Dodd, V. A. and Pollock, K. A., Agriculture Engineering Research, 1973, 18, 1. 22. Alam, M. S., Integrated modeling of a rural energy system: a system dynamics approach, Ph.D. thesis, Department of Electrical & Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1991.