11.1. Production structure of the farm
11.2. Energy balance in alcohol fuel production and the utilization system
11.3. Heat and electricity balance in an IES
11.4. Dimensioning of energy producing plants
The planting, animal husbandry, food processing and energy conversion make up the main production structure. In the yard of the farm, there are 300 m2 of plastic green house, 60 m2 of glass house for vegetable production and raising seedlings, and yearly there are 200 pigs and 20 cows for sale. The processing division is responsible for food and forage processes. The energy conversion parts include various renewable energy conversion equipment for producing oil, heat and electricity.
Farm production today is heavily dependent upon a reliable liquid fuel to power tractors and self-propelled equipment. A shortage at the wrong time could cost the farmer a substantial part of his annual income. Energy conservation measures and alternative fuels are being promoted to help reduce the farmer's dependence on petroleum fuel.
11.2.1 Fuel Consumption and Production
Conventional fuel consumption demand can be calculated by using the following formula. The parameter list of mechanical field operations for this farm was omitted here.
Diesel:
or Gasoline:
where:
DD, GD - diesel or gasoline demand for field working, Kg;
Ai - field operation area, mu;
Ki - standard mu coefficient;
N - the number of the field operation;
Fdi, Fgi - diesel or gasoline demand per standard mu, kg/mu;
Consumption of ethanol in converted tractors was calculated for both sparking ignition and diesel conversions. It was found that ethanol consumption in a sparking-ignition tractor was proportional to the gasoline consumption in a unconverted tractor across the full load range of the tractor. This proportionality constant was a function of the water content of the fuel and the modification used. For a minor carburettor modification with 90 percent ethanol, the constant was 1.44. With increased compression and 90 percent ethanol, the constant was 1.28.
For dual-fueled diesel engines, it was found that the consumption of ethanol varied with the load on the tractor as well as with the water content. When ethanol was sprayed into the intake air, the diesel displacement was 0.25. With a carburettor approach the diesel displacement was 0.45 on a energy basis.
In the 600 mu demonstration base of the integrated energy system in Shenyang, for different engine conversions, the ethanol demand and the necessary ethanol production capacity are listed in Tab. 11.1.
Tab.11.1 The Data for Ethanol Production System (600 mu)
|
Type |
Ethanol demand (Kg) |
Self-sufficient ratio (%) |
Sweet sorghum Area (mu, %) |
Ethanol prod.scale (Kg/d) |
|
Gasoline |
|
|
|
|
|
minor modi |
4945.53 |
100 |
49.65 (8.4%) |
91 |
|
major modi. |
5461.34 |
100 |
49.33 (8.3) |
82 |
|
Diesel |
|
|
|
|
|
spry inject. |
1027.16 |
25 |
9.33 (1.5) |
17 |
|
carburetted |
1991.14 |
45 |
18.10 (3.0) |
33 |
11.2.2 Energy Balance in the Ethanol Production System
Based on the mass balance in the ethanol production system, the energy flow in this system can be illustrated as in Fig. 11.1
Fig. 11.1 Energy Input/Output in Ethanol Production
11.3.1 Methodology of Stationary Energy Balance Analysis in an IES
An analysis of energy supply and demand in rural and agricultural sectors, with special reference to renewable energy, has produced the concept of an Integrated Energy System (IES). This is defined as a combination of renewable and conventional energy sources designed to meet the energy requirements (heat and electricity) of the stationary user points in a farm. This concept is based on the following principle factors, which should be taken into consideration when designing an IES. The heat and electricity demand pattern of the site is extremely variable over time as well as in terms of end use; daily, weekly and monthly peaks may be four to eight times the corresponding average. Because of the nature of the source and type of technology, most renewable energy sources have a low degree of operating elasticity. Consequently, the use of individual technologies to meet demand peaks requires oversized facilities and/or large storage systems. However, an integrated energy system offers an alternative which has been demonstrated to be more economic than the solutions mentioned above and hence more likely to be competitive with conventional systems.
Therefore, the use of renewable energies in agriculture requires the integration between end-use points and energy sources. Because of the unique characteristics of both farm user points (discontinuous function, variable energy demand etc.) and available source (uncertainty, low energy intensity, etc.). Consequently, integrated energy systems are needed for the optimization of the balance between energy demand and supply. The aim here is not to install a series of independent plants using non-conventional energies, but rather to design the entire system on basis of the optimization mentioned above. Correct design requires consideration of the simultaneous behavior of various plants in relation to each other and to the various users. Given the availability in the quantities of energy involved, special models are necessary to simulate the behavior of the energy system of the farm. Hence, the objective of the study is to develop a software of systematic analysis on an integrated energy system of energy sufficient farms (FIESM) which can be applied to determine the best combination of energy technologies and sources which may be introduced in a given farm by taking into account the special socioeconomic situation under investigation. It can also be used to come up with a preliminary plan for the energy system of the farm.
The renewable energy sources analyzed by the model include:
- R.E. sources for agricultural systems: these consist of solar energy and energy originating from a solar based system.- R.E. sources from agricultural systems: these concern the various types of biomass used for energy and produced on farms and in forests. The only biomass examined by the model are those involving biochemical (biogas, ethanol) and thermochemical conversion (straw and wood residues)
The computer software is made up of four submodels and their functions are as follows:
- UPED simulates the electric and the thermal energy requirements of each stationary user point installed on the farm on the basis of the input data obtained; it can also create a cumulative load curve by adding two or more files of different user points with similar energy behavior.
- ARES processes and quantifies the local availability of renewable energy sources (RES) obtained in the form of input that is subject to random variations beyond the user's control (e.g climate and process complexity); this submodel considers only RES with no or limited operating elasticity.
- PTEE includes INPUT, ENPROD, ENUTIL, ANECON and OUTPUT sections, calculates the technical and economic performance of possible useful system configurations on the basis of the economic input data defined above.
- ANET calculates the behavior of the complete, integrated system when the analysis carries out by PTEE submodel is divided into several subsystem configurations. It can also consider other benefits (or costs) produced.
All the programs have been written in Turbo-Pascal and ase-III language.
The FIESM models identify several alternative system configurations in order to determine which is the best suited to the specific technical and economic situation. A system configuration can be defined as a set of renewable and conventional energy technologies which are combined to meet the energy requirements of a specific group of selected end-users of a farm.
Within a given system configuration, each technology is considered at different size. These represent the real or marginal costs of the technologies involved. Since technologies are lumpy or expensive from an investment point of view, relatively large marginal values may be included without changing the quality of the result. Thus, each calculation involves marginal costs.
The advantages offered by the system are represented by the costs of reference solutions, that is, the value of the conventional energy which is replaced by the project solution. This value is the product of the quantity of energy saved and its unit cost top user. As stated above, useful economic evaluation should also consider the real economic cost of the energy, since market prices or policy are not reliable measures, especially in rural areas.
FIESM is based on a " day-by-day" comparison between the energy demands of the farm's stationary user points and the energy available from renewable and conventional sources. The economic results obtainable from each system configuration are determined by extending this comparison to include every day of the year. Correct application of FIESM must include following steps:
- Identification of the R.E. sources available on the farm and selection of R.E. technologies.- Identification of all the stationary user points present at the farm and analysis of their technical performance or requirements.
- Identification of all the possible connections between technologies and user points.
- Preparation of requirement data file by running UPED submodel.
- Preparation of renewable source available data files by running ARES.
- Preparation of data files relating to the main technical and economic parameters of the technologies considered by running INPUT.
- Calculation of the energy produced by each technology by running ENPROD.
- Identification of all the possible subsystems present in each system configuration of the general LIES and calculation of each of these for each group of users, by running the ENUTIL for each subsystem.
- Evaluation of the economic performance of the subsystems under examination by running the ANECON section each time the ENUTIL section is run; a printout of the result can be obtained by running the OUTPUT section.
- Comprehensive analysis comparing the results obtained from each simulation process and selection of the most favorable plant solution.
- Possible comprehensive analysis of the entire integrated energy system using the PTEE submodel.
11.3.2 Farm Heat and Electricity Demand
The demand of noble energy for stationary user points and of low temperature heat was recorded and monitored monthly at the site. The different patterns of electricity and heat demand are apparent from the monthly load. The electricity load fluctuated but around 2038 Kwh/month.
The total demand (23898 Kwh/year) breakdown by main user points yields the following values: ethanol production 34%, pig house and biogas digester 7.4 %, solar house and greenhouse 9.4%, lighting 28.5%, forage processing 6.4%, and others 14.3%.
Heat demand (540899 Kwh/year) instead is widely variable from 36761 kwh in January to 2041 kwh in summer. The winter heating and ethanol production heating demand accounts for more than 70 % of the total heat consumption. Tab.10.2 gives the summary of all heat and electricity requirements.
Tab.10.2 Farm's Heat and Electricity Requirements
|
|
J |
F |
M |
A |
M |
J |
J |
A |
S |
O |
N |
D |
Total |
|
Total elect. requirements |
1520 |
1520 |
1520 |
|
795 |
|
795 |
|
4441 |
|
1390 |
540899 |
|
|
|
1520 |
1520 |
|
795 |
|
795 |
|
4441 |
|
5072 |
|
|
|
|
Total heat requirements |
36761 |
|
30623 |
|
2041 |
|
2041 |
|
2041 |
|
150019 |
|
23898 |
|
36761 |
|
2041 |
|
2041 |
|
2041 |
|
121437 |
|
33658 |
|
||
11.3.3 Possibilities for Using Renewable Energies
The use of a given type of renewable energy depends on the geographical position of the farm and on its crop pattern; the equipment should be dimensioned on the basis of the load curve and the heat content.
A. Solar energy
Since the development of simplified air and water solar collectors, this energy source has become technically applicable and economically advantageous. From May to October, the solar water collector is chiefly required for bath and shower. The air collector is used for heating assistance to the solar house. However in this farm, the heat from the solar collector is low since the collector areas are so limited.
B. Energy from Anaerobic Digestion of Animal Waste
Since pigs and sheep are raised on the farm, the possibility for producing biogas through animal waste anaerobic digestion becomes especially interesting using a batch type digester.
Sizewise, the batch digester could handle 60% of the swine manure. Mean retention time is assumed as 30 days; net production per Kg of volatile solid matter is given in Tab. 11.3. The feedstock has a mean dry matter content of 15 %. These elements are sufficient for a first dimensioning of the digester. Biogas can be used to feed a cogeneration system, delivering heat and electricity.
Tab.11.3 Monthly Net Energy Output from Digester (kwh/v.s* 0.1)
|
Plant |
J |
F |
M |
A |
M |
J |
J |
A |
S |
O |
N |
D |
|
Batch |
- |
- |
- |
- |
4.6 |
4.8 |
6.0 |
5.7 |
4.6 |
3.8 |
- |
- |
C. Energy by Biomass Pyrolysis System
Biomass thermochemical conversion offers wide scope for the generation of mechanical and electrical energy and heat. At present, of the various processes under this heading, the most interesting for agricultural waste appears to be that of biomass pyrolysis.
After plotting the load curve and selecting the most suitable energy source for the farm, the energy producing facilities were dimensioned. This problem can be approached from different angles. The most immediate approach is to settle for the solution which has the absolute minimum cost on the basis of current prices for conventional energy sources. Another approach is based on the maximum utilization of farm energy sources by proved technologies. A third avenue, is that of aiming for full farm energy self-sufficiency. However, with the limitations of the current farm's conditions, here are the present case conducted.
This solution covers only the present applied technologies in the farm: Solar water collector, solar air collector, biogas digester biomass pyrolysis, conventional boiler and electricity grid. Apparently the unfavorable load curve pattern completely eliminates the possibility of using solar energy; the capacity of the biogas digester and pyrolysis plant are too low. Yearly only 65.5 % required heat and 8.2% required electricity can be supplied by the system, others are met by conventional energy as shown in Table 11.4.
This solution therefore is not perfect since it does not provide significant conventional energy saving. Based on the above analysis, the optimum solution recommended is: 1) Increasing the capacity of biomass pyrolysis up to 100 Kg/h; 2) Installing a 10 Kw wind mill on site; 3) Scaling the biogas digester up to 60 M3; 4) Utilizing the biomass combustion technology for ethanol distillation.
Table 11.4 Plant Size, Utilization Factors and Load Covered
|
|
|
Heat (KWh/year) |
|
Electra (KWh/year) |
| ||||
|
Plant |
Size |
Generated |
Used |
Factor |
Load cover |
Generated (%) |
Used (%) |
Factor |
Load cover (%) |
|
Solar Air |
4m2 |
2304 |
2304 |
100 |
0.4 |
|
|
|
|
|
Solar water |
4m2 |
959 |
959 |
100 |
0.2 |
|
|
|
|
|
Biogas |
30m3 |
5872 |
5872 |
100 |
1.1 |
1958 |
1958 |
100 |
8.2 |
|
Pyrolysis |
50 kg/h |
344947 |
344947 |
100 |
63.8 |
|
|
|
|
|
Total renewable energy |
65.5 |
|
|
|
8.2 | ||||
Conclusion
A software for the systematic analysis of an integrated energy system for energy- sufficient farms (FIESM) was developed. Using FIESM, farm managers are able to come up with a preliminary plan with regard to the determination of the best combination of energy technologies and energy sources and an optimal energy system configuration by taking into account the specific farm situation, such as geographic position, weather conditions and resource availability, and the agricultural production structure. Although FIESM was devised through the UNDP/FAO Project "The Establishment of An Integrated Energy System for China's Northeast Cold Region" as a decision-making tool, FIESM can be widely applied by administrators of farms to analyze and evaluate both the energy related and economic benefits of the system configuration of any farm's integrated energy system. The models have been verified and applied to this project from which the practical and feasible scenarios were obtained.
Reference
1. Bernard Biet. Manual on Design and Assessment of Integrated Energy System. FAO, 1989.
2. Wang Shuwen. The summary and assessment of European integrated energy system research, 3rd Northeast New Energy Symposium, 1988.
