3.1

Carbon trading cost

3.1.1

Carbon trading

Carbon emission rights be referred as economically schedulable resources by introducing carbon trading mechanism ¹⁰. Therefore, the actual amount of emissions participating in the market is:

In the equations: E_{IES, t} is IES’s carbon emissions trading volume; E_{IES, a} is the actual carbon emissions; E_IES is the quota of system.

Ladder carbon trading model:

3.1.2

Mode of carbon emission quota

Emission sources mainly come from CHP, GB (gas boiler) and electricity and gas energy. The carbon emission quota model is:

In the equations: E_IES、E_e,buy、E_CHP、E_GB is the emission quota of IES、Purchased electricity、CHP and GB.

3.1.3

Mode of actual carbon emission

In the equations: E_IES,a、E_e,buy,a are actual carbon emissions for electricity purchased and IES; E_total,a is the actual amount of CO₂ for GHP and GB; E_MR,a is actual CO₂ absorbed by MR.

3.2

Objective Function

The economic maximization of the IES is realized in the condition of satisfying the constraints. The optimization of IES scheduling model is constructed by the objective function of the cost of wind abandonment、energy purchased and carbon trading.

Energy purchase cost:

Cost of wind abandonment:

Carbon trading cost:

see Figure 2 above.

Figure 2.

Price of carbon trading.

3.3

Constraint condition

CHP constraint:

In the equations: P_g,CHP (t) is the gas power into CHP; 、 are the range boundary of natural gas inputting CHP; 、 are limits of climbing power.

Wind power output constraints:

In the equations: P_DG (t) is the wind power; is maximum that wind power can output power.

Power balance constraints:

In the equations: P_h,Load(t)、P_e,Load(t) indicates heat and electrical load; 、 indicate the thermal and electrical power which inputs storage device; P_e,P2G(t) Indicates the power input to P2G device; P_e,buy(t) indicates the power purchased from power grid.

4.1

Operation results

Take 24 hours in a day as a cycle. The electricity 、natural gas price as Fig. 3. Fig.3 also shows the prediction results of various load demands and wind power output in one day. Four scenarios were set up as Table 3. Set up L = 2t; a = 25%; λ = 50 yuan / t on trading. Using cplex solver in MATLAB operate the model.

Figure 3.

Load curve, wind power forecast and time-of use electricity 、gas price

Table 1.

Set up scenarios

Table 2.

Cost comparison under different scenarios

On ordinary carbon trading, the carbon emissions in Scenario 2 are significantly reduced by 16.86 % compared with Scenario 1. Because P2G contains the MR, the device is capable of absorbing CO2 and synthesizing natural gas supply gas loads. It can be seen that the P2G devices in Scenario 2 can reduce CO2 emissions, and the cost of Scenario 2 is significantly lower than the cost of Scenario 1 on the condition of satisfying the gas load.

In addition, P2G devices can convert electrical energy to avoid waste. Therefore, the cost of wind abandonment in scenario 2 with P2G equipment is zero with the ordinary carbon trading, reducing wind abandonment and improving environmental protection. And compared to Scenario 1, the cost in Scenario 2 with P2G devices is also decrease 12.38 %.

P2G is not included in the comparison scenario: Compared with Scenario 1, Scenario 3 reduces emissions by 445Kg and increases the total cost by 1038.9 yuan; P2G is included in the comparison scenario: Compared with Scenario 2, Scenario 4 has reduced carbon emissions by 837.8kg and only increased total cost by 1038.9 yuan.

4.2

Electric power balance

Analyze Scenarios 1 and Scenarios 3. In the morning, there are mainly storage devices, wind power and CHP to meet demand; When wind power is insufficient at noon, system will purchase power to achieve demand; at night, wind power is sufficient, IES purchase electricity from the grid no longer. wind power, CHP power generation and storage device discharge can achieve power balance.

Analyze Scenario 2 and Scenario 4. When the system contains P2G equipment, the wind power consumption rate is 100 %. Analyze the operation of P2G, the IES system first transmits the surplus wind power to the EL equipment for hydrogen production, and consumes all wind power. It can be known that part of the hydrogen is stored inside the hydrogen storage and others are transported to the MR to synthesize natural gas. So when IES contains P2G, wind power which costs 0 can be fully utilized.

Optimal electrical load balancing as Figure 4.

Figure 4.

Optimal electrical load balancing

4.3

Economic and environment comparison

By analyzing, the economy and environmental protection in different scenarios are reflected respectively. Figure 5.can see that scenario 4 has the least carbon emissions, which indicates that scenario 4 has the best environmental protection; the total cost is the lowest in scenario 2, which indicates that the economy of scenario 2 is the best.

Figure 5.

Total cost and emissions

Environmental protection is inversely proportional to carbon emissions, and the economy is inversely proportional to the total cost.

Environmental protection coefficient ‘a’ and Economic coefficient ‘b’ is:

In the equations: COST represents the total cost of the system; C_CO₂ represents CO₂ emissions.

Figure 6. can be more intuitive and clear comparison of different scenarios of economic and environmental protection. From the data of scenarios, it can be seen that scenario 4 can achieve the optimization of economy and environmental protection and balance in ‘a’ and ‘b’.

Figure 6.

The comparison of economic and environment