Fresh and stored crops - a new way to organize all-year substrate supply for a biogas plant

Last changed: 29 March 2018

For crop-based biogas plants, the cost for buying the crops is a predominant production cost and efficient systems for production, harvesting, transportation and storage are therefore of major importance. Furthermore, there is a discussion going on about competition on land between food and energy production. EU has decided to strongly limit the production of transportation fuel based on crops grown on arable land. For crop-based biogas production it is therefore very interesting to ex- amine ways to reduce substrate costs for crops as well as to find alternative crops that are not competing with food production.

This project was carried out as a case study for two crop based biogas plants in Jordberga and Örebro, both of them owned by Gasum AB, former Swedish Biogas International (SBI). The over- all aim of the project was to reduce substrate costs by at least 10%, by organizing the supply of crops in a new way, combining fresh and ensiled crops. The underlying assumption was that substrate costs could be reduced by feeding fresh crops into the biogas digester during the harvest period and thereby reduce costs for storage and avoid losses of dry matter during storage.

The goal of this project was to improve cost calculations and develop an optimization model for substrate supply to analyze how different fresh and ensiled substrates should be best combined to minimize substrate costs during various times of the year. In the previous f3 financed project ”Optimized logistics for biogas production” a model based on linear programming was developed for optimization and strategic planning of the logistics for biogas plants. In the present project, the model was further developed to optimize the supply for the year divided into different periods, instead of on annual basis as in the previous project.

In the first part of the project, an inventory of crops to include in the case studies and crop proper- ties such as harvest times, dry matter yield and biomethane yield was carried out. Using GIS a geo- graphical inventory for the case study sites was carried out based on the national database of agricultural land receiving subsidies from the EU. The agricultural fields were classified as small fields (1-5 ha) and large fields (>5 ha). For each field the real-world transport distance to the biogas plant was calculated. The fields were then divided into 7 zones with different transport distance from 0- 100 km and for each zone the field area for small and large fields were summarized. The average transport distance for all fields in each zone was calculated.

Based on the inventory cultivation costs were calculated. Reflecting the production potential of crops otherwise grown on the field, a land use cost was also calculated. The harvest systems were adapted for small and large fields. Costs for transport with tractor or truck were calculated and the cheapest alternative for each crop and zone was used in the optimization model. For crops harvested with a precision chop forage wagon an additional pre-treatment cost (bio-extrusion) was added to sufficiently reduce particle size. For the ensiled crops, a storage cost was added based on storage in bunker silos. Dry matter losses during storage were accounted for.

An optimization model was developed to minimize the cost of substrate supply with fresh and stored crops during different periods of the year when producing 80% of the annual biomethane production of the biogas plants. The period from May to November, when fresh crops were available, was divided into one-week periods, while the rest of the year was divided in two periods when only ensiled crops were available, reflecting different storage need of different crops. Based on the selected crops, a list of substrates was prepared, where the properties for every harvest opportunity for a fresh crop, and every period when an ensiled crop was available, was represented by unique list entries. It was assumed that the ensiled crops were harvested at the time resulting in the lowest cost per biomethane production. For the Jordberga case, 19 crops were selected, and since many were available during several periods, this resulted in a list of 255 potential substrates. For the Örebro case, 15 crops were selected, resulting in 237 potential substrates. Transport costs were calculated for 14 zones, where zones A1-A7 represented agricultural land in large fields and B1-B7 represented agricultural land in small fields.

Scenarios with different land use and crop combination constraints were tested and compared with a reference scenario (1) without optimization including the crops used currently which is ensiled whole-crop cereal and maize in Jordberga and ensiled whole-crop cereal and grass-clover in Örebro. In scenario 2 an optimization was done using only ensiled crops enabling comparison of optimized results with and without fresh crops. In scenario 3 both fresh and ensiled crops were included with (3a) and without (3b) the restriction that maximum 1/3 of the crops supplied could be fresh to avoid any negative effects on the biogas process of supplying only fresh crops. In scenario 4a the effect of using only so called 2nd generation biofuel crops was studied. Scenario 4b analysed if grass-clover is more competitive as a biogas substrate if its positive effect on other crops in a cereal based crop rotation was considered. The results of the optimizations are summarized in the table below.

Scenarios

1, reference

2, ensiled

3a, mixed

3b, mixed unrestricted

4a, advanced biofuel

4b, advanced biofuel with crop rotation values

Jordberga

 

 

 

 

 

 

Total annual cost, MSEK

46.9

46.1

44.3

42.0

59.2

56.5

Average cost, SEK/Nm3

4.94

4.86

4.67

4.43

6.24

5.95

Average cost, SEK/t DM

1 349

1 287

1 274

1 256

1 594

1 475

Savings, % (reference)

-

2

5

10

-26

-20

Örebro

 

 

 

 

 

 

Total annual cost (MSEK)

14.7

12.3

12.2

12.1

17.2

15.7

Average cost (SEK/Nm3)

4.38

3.67

3.64

3.61

5.11

4.67

Average cost (SEK/t DM)

1 101

974

969

965

1 225

1 119

Savings, % (reference)

-

16

17

17

-17

-7

For Jordberga the optimized solution allowing only ensiled crops (Scenario 2) included whole-crop cereal as the only crop grown on 2754 ha. This can be compared with 1000 ha maize and 1500 ha whole-crop cereal in the reference scenario. If both fresh and ensiled substrates were included in the optimization without restrictions (Scenario 3b), fresh whole-crop cereal and sugarbeet tops were added to the solution. Annual costs were reduced to 10% lower than the reference scenario.

This means that the goal of the project to decrease cost costs with 10% was reached with this scenario. When restricting the amount of fresh crops to maximum 1/3 of the crops used each week (Scenario 3a), annual substrate costs were 5.5% lower compared with the reference scenario. Maximum transport distance was 15 km.

Örebro biogas plant today uses ensiled whole-crop cereal and grass-clover (Scenario 1). The optimized solution based on only ensiled substrates (Scenario 2) included only whole-crop cereal grown on 1219 ha in zone 1-3 up to 15 km transport distance. When allowing fresh substrates in the optimization (Scenario 3a), whole-crop cereal was complemented by fresh whole-crop cereal in the optimal solution and the costs were reduced by 17% compared to the reference scenario (1).

The suggested update of the EU renewable energy directive (RED) will require biogas plants producing vehicle fuel from crops to find alternative crops suitable as advanced biofuel crops. Scenario 4a and 4b therefore only included grass-clover, landscape conservation grass, green rye, cover crops and sugarbeet tops (only in Jordberga) following the definition of food-based biofuel from the Swedish Energy Agency (maize, whole-crop cereal and sugarbeets excluded). For Jordberga the optimization resulted in ensiled green rye being the main crop followed by grass-clover from large fields. Also fresh sugarbeet tops, landscape conservation grass and green rye (as a winter cover crop) were included in the solution. To supply Jordberga biogas plant with crops the maximum transport distance increased to 100 km. When considering the crop rotation value (Scenario 4b), grass-clover from large fields became the main ensiled crop in the optimized solution. For Örebro biogas plant the optimization in scenario 4a resulted in whole-crop cereal being replaced with grass-clover from large fields, green rye and cover crops.

Advanced biofuels crops such as sugarbeet tops, green rye and landscape conservation grass and grass-clover are interesting alternatives for biogas production but will increase substrate costs. In our analysis substrate costs increased with 26% compared to the current crops used at Jordberga biogas plant. Corresponding value for Örebro biogas plant was 17%.

Grass-clover was more competitive as a biogas crop in Örebro compared to in Jordberga. In Örebro, grass-clover was the main ensiled crop both in the advanced biofuel scenario (Scenario 4a) and when crop rotation values of grass-clover was considered (Scenario 4b). In Jordberga, the main ensiled crops in the advanced biofuel scenarios were green rye and grass-clover. Fresh grass-clover harvested with an adapted system with low capacity could not compete with costs with ensiled grass-clover harvested with a high capacity system, neither in Jordberga nor in Örebro.

Compared to the current crop based biogas production using only a few crops, the analysis of the advanced biofuel scenarios showed that the number of crops increased and both fresh and ensiled crops were included. This will increased complexity of the harvest-, transport- and storage system and the possible advantages and drawbacks of this need to be studied further.

The presented results are examples of the possibilities in using an optimization model as a tool for strategic planning and examining the trade-offs between cost savings and process and management related constraints for crop supply. Further work and site-specific tests are needed to study effects on the stability of the biogas process by feeding fresh substrates.

Facts:

The project was funded by The Swedish Knowledge Centre for Renewable Transportation Fuels (f3)

Duration of the project: 2014-2017
Project Leader: Carina Gunnarsson
Other contributors: Thomas Prade, Sven-Erik Svensson, David Ljungberg, Lars Sjösvärd

Page editor: andrus.kangro@slu.se