The Diffusion Rule of Demand-Oriented Biogas Supply in Distributed Renewable Energy System: An Evolutionary Game-Based Approach
Abstract
:1. Introduction
2. Research Methods
2.1. Establishment of the Evolutionary Game Model
2.1.1. Model Hypothesis
- The two players choose their strategies by maximizing their own interests, while being influenced by government incentives, etc. The influence of other stakeholders is set as exogenous variables in the game.
- Behavioral strategy: The dispatching center may or may not choose the electricity supplied by the biogas plant. When using the electricity from biogas, the biogas plant is responsible for supplying biogas on demand to meet the electricity load curve of the service area; if the biogas plant is not able to supply biogas on demand, the dispatching center has to temporary deployment of other energy sources to cover the demand gap. For biogas plants, they have also the two choices, on-demand supply or not; if the biogas plant implements the DO while the dispatching center does not use the biogas, the produced biogas can only be used for satisfying the plant’s internal varying power demand at a low-capacity level. The players may have different response options and strategies selection in each scenario, but they are not taken into consideration in this study.
- Probability of players’ behavioral strategy: Assuming that the probability of the dispatching center using the biogas plant’s electricity is X (the probability of not using is 1 − X); the probability of the biogas plant implementing DO mechanism is Y (the probability of biogas plant not implementing is 1 − Y);
- Parameter assumptions and basic explanations: C1: cost of collection and transportation of substrates when the biogas plant does not implement DO; C2: cost of operation and maintenance when the biogas plant does not implement DO; h1: saved fees of purchased electricity when the biogas plant dies not implement DO; Q1: government subsidy for biogas plants when the biogas plant does not implement DO; u1: revenue from electricity sales when the biogas plant does not implement DO; M1: cost of collection and transportation of substrates when the biogas plant implements DO; M2: cost of operation and maintenance when the biogas plant implements DO; h2: saved fees of purchased electricity when the biogas plant implements DO; Q2: government subsidy for biogas plants when the biogas plant implements DO; a: additional revenue from on-demand electricity sales when the biogas plant implements DO; b1: cost for purchased electricity when the biogas plant implements DO and the dispatching center use biogas; b2: cost of using emergency back-up energy; m1: revenue from electricity sales of the dispatching center when they use biogas and the biogas plant implements DO; r1: social-environmental benefits of the region brought by the implementation of DO; b3: cost for purchased electricity when the dispatching center use biogas while the biogas plant does not implement DO; m2: revenue from electricity sales of the dispatching center when they use biogas but the biogas plant does not implement DO; r2: social-environmental benefits of the region when the dispatching center use biogas but the biogas plant does not implement DO; b4: cost for purchased electricity when the dispatching center does not use biogas; m3: revenue from electricity sales of the dispatching center when they do not use biogas.
2.1.2. The Payoff Matrix and Replicator Dynamic Equations of the Evolutionary Game
2.1.3. Stability Analysis of the Game
2.2. Simulation of the Evolutionary Game Based on System Dynamics
2.2.1. Construction of the SD Model
2.2.2. SD Simulation Parameters and Data Acquisition
3. Results and Discussion
3.1. Simulation Results of the Evolutionary Game and the Model’s Verifications
3.2. Sensitivity Analysis of Model Parameters
3.3. Implications for the Optimal Policy Instrument Selection
3.4. Discussion
4. Conclusions
- According to the deduction results of the ESS and the SD, the biogas plant and the dispatching center in DES will converge to an undesirable set of ESS (not implement the DO, not use the power from biogas) when the carbon trading mechanism are not introduced into the case region. However, when the DES is able to obtain monetized returns of socio-environmental benefits, through participating in the carbon trading with other regions, it can converge to the ideal ESS (implement the DO, use the power from biogas), at which point the dispatching center can reach a stable equilibrium around the fifth year, and the biogas plant will reach equilibrium around the thirtieth year, driven by the demands for power from biogas.
- The results of the sensitivity analysis show that the revenue from electricity sales of the dispatching center when they do not use biogas, as well as the revenue from electricity sales of the dispatching center when they use biogas but the biogas plant does not implement DO, are the most critical parameters influencing the evolutionary game process between the biogas plant and dispatching center. The parameters of cost for purchased electricity when the dispatching center does not use biogas, as well as the cost for purchased electricity when the dispatching center use biogas while the biogas plant does not implement DO, also have significant impact on the results. The acceptance of DO by both the dispatching center and biogas plant occurs only when the m3 increase remains within a threshold to 1.484 Yuan/KWh in unit revenue. Other factors, such as the substrates collection and transportation cost, the governmental subsidies to the biogas plant and the social-environmental benefits, do not have significant impacts on the final results of the game.
- Based on the results of sensitivity analysis, it is recommended that more regions and enterprises should be included in the national unified carbon market, and the market-based industrial policies such as green electricity quota trading can be used to restrict the users’ acceptance for non-renewable sources and the willingness to pay, while suitable targeted polices are needed to extend the industrial chain of original biogas production, so that the potential revenues of biogas plants can be enhanced and, finally, the ESS for better promotion of DO can be rated and successfully implemented.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
DO | demand oriented biogas supply | DES | distributed renewable energy system |
ESS | evolutionarily stable strategy | PV | photovoltaic |
C1 | cost of collection and transportation of substrates when biogas plant not implement DO | C2 | cost of operation and maintenance when biogas plant not implement DO |
h1 | saved fees of purchased electricity when biogas plant not implement DO | Q1 | government subsidy for biogas plants when biogas plant not implement DO |
u1 | revenue from electricity sales when biogas plant not implement DO | M1 | cost of collection and transportation of substrates when biogas plant implement DO |
M2 | cost of operation and maintenance when biogas plant implement DO | h2 | saved fees of purchased electricity when biogas plant implement DO |
Q2 | government subsidy for biogas plants when biogas plant implement DO | a | additional revenue from on-demand electricity sales when biogas plant implement DO |
b1 | cost for purchased electricity when biogas plant implement DO and the dispatching center use biogas | b2 | cost of using emergency back-up energy |
m1 | revenue from electricity sales of dispatching center when they use biogas and biogas plant implement DO | r1 | social-environmental benefits of the region brought by the implementation of DO |
b3 | cost for purchased electricity when the dispatching center use biogas while biogas plant do not implement DO | m2 | revenue from electricity sales of dispatching center when they use biogas but biogas plant do not implement DO |
r2 | social-environmental benefits of the region when dispatching center use biogas but biogas plant do not implement DO | b4 | cost for purchased electricity when dispatching center do not use biogas |
m3 | revenue from electricity sales of dispatching center when they do not use biogas | SD | system dynamics |
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Game Players | Dispatching Center | ||
---|---|---|---|
Use the Biogas (X) | Do not Use the Biogas (1 − X) | ||
Biogas plant | Implement DO (Y) | u1 + a + Q2 + h2 − M1 − M2; | Q2 + h2 − M1 − M2; |
m1 + r1 − b1 − b2 | m3 − b4 | ||
Not implement DO (1 − Y) | u1 + Q1 + h1 − C1 − C2; | Q1 + h1 − C1 − C2; | |
m2 + r2 − b2 − b3 | m3 − b4 |
(x, y) | F11 | F22 |
---|---|---|
(0, 0) | m2 − b2 − b3 + r2 − m3 + b4 | Q2 + h2 − Q1 − h1 − M1 − M2 + C1 + C2 |
(0, 1) | m1 + r1 + b4 − b1 − b2 − m3 | Q1 + h1 + M1 + M2 − Q2 − h2 − C1 − C2 |
(1, 0) | b2 + b3 + m3 − m2 − r2 − b4 | a + Q2 + h2 − Q1 − h1 − M1 − M2 + C1 + C2 |
(1, 1) | b1 + b2 + m3 − m1 − r1 − b4 | Q1 + h1 + M1 + M2 − a − Q2 − h2 − C1 − C2 |
Input Parameters | Numerical Values | Sources and Measurement Methods |
---|---|---|
C1 | 0.12 million Yuan/a | The substrates used can be calculated by the biogas demand when the DO has not been implemented, in which the 1 m3 of biogas can generate 1.8 KWh electricity, and 1 ton of substrates (here we have taken the livestock manure and wheat straw as the substrates) can produce about 250 m3 of biogas [31]; the concentrative collection and transportation cost of straw is about 80 Yuan/ton. |
C2 | 26.32 thousand Yuan/a | The Operating and maintenance costs of biogas production are 1% of the initial investment based on the study by Lauer et al. [32]. |
h1 | 59.79 thousand Yuan/a | When the DO is not implemented, 13% of the hourly generated electricity should be used for self-use [33], from which the saved fees for industrial electricity use can be calculated. |
Q1 | 0.16 million Yuan/a | We calculated the subsidy for the biogas plant based on the subsidy standard for renewable source 0.25 Yuan/KWh in China. |
u1 | 0.38 million Yuan/a | Under this scenario, electricity from biogas is directly composing into the power grid, and the local industrial electricity price is 0.657 Yuan/KWh |
M1 | 0.23 million Yuan/a | The substrates used can be calculated by the biogas demand when DO has been implemented. |
M2 | 0.18 million Yuan/a | When DO is implemented, the operating and maintenance costs must consider the increment of biogas storage capacity, the equipped automatic control system and the electricity monitoring system, which account for 2% of the initial investments of biogas plants according to Lauer et al. [32]. |
h2 | 0.14 million Yuan/a | It can be calculated by the hourly electricity demand at this scenario, similar to h1. |
Q2 | 0.33 million Yuan/a | The biogas plant can receive the subsidy based on the power output, which can be calculated referred to Q1. |
a | 0.38 million Yuan/a | The extraneous income from DO can be calculated by excess power supply through peak-regulating. |
b1 | 0.75 million Yuan/a | Calculated as the electricity consumption under the DO multiplied by the price of electricity. |
b2 | 0.15 million Yuan/a | When the dispatching center decides to use the electricity from biogas, it needs to purchase additional 20% of the total energy demand as the reserves to cope with the risk of supply outages. |
m1 | 0.94 million Yuan/a | The revenue of dispatching center when DO is implemented can be calculated by the time-of-use power price. |
r1 | 0/0.56 million Yuan/a | As there is no mechanism to transform the social-environmental benefits of distributed renewable energy system into economic returns in the current case region, r1 is assigned to 0. Considering that the carbon trading has been implemented in some regions of China, this study assumes that if the carbon trading is introduced in this region, 1 KWh of electricity can achieve 0.006 t CO2 emission reduction [34], and the surplus carbon emission permit can be sold in the carbon trading market; the price is about 71.1 Yuan/ton. |
b3 | 0.70 million Yuan/a | When DO is not implemented, the peak-regulating and complementary to renewable energy will be undertaken by thermal power. |
b4 | 0.65 million Yuan/a | It is assumed that the gap in electricity demand will be supplied by thermal power in this scenario. |
m3 | 0.92 million Yuan/a | Users in this region are charged according to the traditional electricity price. |
m2 | 0.86 million Yuan/a | Part of the power will be sold by the price of electricity from biogas. |
r2 | 0/0.28 million Yuan/a | Calculated method can be referred to r1. |
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Liu, Y.; Wu, J.; Li, J.; Huang, J. The Diffusion Rule of Demand-Oriented Biogas Supply in Distributed Renewable Energy System: An Evolutionary Game-Based Approach. Sustainability 2023, 15, 14297. https://doi.org/10.3390/su151914297
Liu Y, Wu J, Li J, Huang J. The Diffusion Rule of Demand-Oriented Biogas Supply in Distributed Renewable Energy System: An Evolutionary Game-Based Approach. Sustainability. 2023; 15(19):14297. https://doi.org/10.3390/su151914297
Chicago/Turabian StyleLiu, Yiyun, Jun Wu, Jianjun Li, and Jingjing Huang. 2023. "The Diffusion Rule of Demand-Oriented Biogas Supply in Distributed Renewable Energy System: An Evolutionary Game-Based Approach" Sustainability 15, no. 19: 14297. https://doi.org/10.3390/su151914297