Multi-unit and multi-heat-supply-mode thermal power plant heat supply load distribution optimization method

Abstract

The invention relates to the technical field of thermal power plant heat supply load distribution, and discloses a multi-unit and multi-heat supply mode thermal power plant heat supply load distribution optimization method, which comprises the following steps: collecting operation data of a thermal power plant, and recording the model, power, displacement, heat supply mode, operation state, heat supply composite requirement and fuel consumption requirement of a heat supply unit; and summarizing the data of the power supply unit into a table. According to the multi-unit and multi-heat-supply-mode thermal power plant heat supply load distribution optimization method, detailed data of actual power supply units of a thermal power plant are summarized, operation data of a single heat supply machine are summarized and calculated as data of the heat supply units of a region, the data are calculated to become calculation models, the models are compared, and after an optimal scheme is selected, the optimal scheme is obtained. The method is applied to actual heat supply, the actual heat supply load is monitored, the heat supply load is continuously adjusted, the optimal heat supply load distribution optimization method of the multiple heat supply units is obtained, the heat supply efficiency is improved, and the energy loss is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of heat supply load distribution in thermal power plants, and in particular to a heat supply load distribution optimization method for a thermal power plant with multiple units and multiple heating modes. Background Art

[0002] A thermal power plant is a coal-fired power plant. Waste heat is generated during the power generation process, and this waste heat is used for heating. In order to tap the peak-shaving capacity of the thermal power plant, it is necessary to reasonably allocate the heat loads of multiple heating units and improve the flexibility of the heating units under thermal load conditions. This will enable the multiple heating units in the thermal power plant to give full play to their potential and reduce the production costs of the enterprise. Therefore, it is necessary to study the optimization method of heating load distribution in thermal power plants.

[0003] In the prior art, when optimizing the heating load distribution of a thermal power plant, the focus of the optimization is usually on optimizing a single heating machine and analyzing and improving the energy consumption of the single heating machine. However, in actual production, the method of analyzing, studying and adjusting a single heating machine will be limited by the power of a single machine, resulting in a limited adjustment range of the heating load. In addition, due to the complex losses of multiple heating units, the method of studying a single unit cannot be normally applied to multiple heating units, resulting in the inability to distribute the heating load according to the comprehensive energy consumption of the thermal power plant. Therefore, it is necessary to invent a method for optimizing the heating load distribution of a thermal power plant with multiple units and multiple heating modes to solve the above problems. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a method for optimizing the distribution of heating loads in a thermal power plant with multiple units and multiple heating modes. The method summarizes the detailed data of the actual power supply units of the thermal power plant, summarizes the operating data of a single heating machine and extrapolates it into the data of the heating units in the region, and calculates it into a calculation model. The models are compared, and after the best solution is selected, it is applied to the actual heating, and the actual heating load is monitored. The heating load is continuously adjusted to obtain an optimization method for the best heating load distribution of multiple heating units, thereby improving the efficiency of heating and reducing energy loss. At the same time, by constraining the power, heat balance and average heat supply value during the heating load distribution process, multiple heating units can ensure heat balance during the heating process, reduce heat loss in the heating load, and reduce the consumption cost of the thermal power plant during heating.

[0006] (II) Technical solution

[0007] In order to realize the above-mentioned heat supply load distribution of the thermal power plant, the present invention provides the following technical solution: a heat supply load distribution optimization method for a thermal power plant with multiple units and multiple heating modes, comprising the following steps:

[0008] S1. Data Collection

[0009] According to the number of heating units in the thermal power plant, collect the operating data of the thermal power plant, record the model, power, displacement, heating method, operating status, heating composite requirements and fuel consumption requirements of the heating units, and summarize the data of the power supply units into a table.

[0010] S2. Data Modeling

[0011] By analyzing the operating data of a single heating machine, a mathematical model of the heating unit and the heating load is established, and the calculation model of the heating unit in the thermal power plant area is deduced based on the operating data of the single heating machine.

[0012] The formula for calculating the heat supply of the power supply units in thermal power plants is:

[0013] Q=m h (h h -h d ) / 3600.

[0014] S3. Operation strategy optimization

[0015] Using the optimization algorithm, the heating load distribution of the thermal power plant is optimized according to the operating capacity and heating mode of different heating units. The operating energy consumption comparison is constructed into a tree diagram, and the best distribution optimization plan is selected from it.

[0016] Taking the coal consumption as the standard for optimizing the operation strategy, the calculation formula of coal consumption is:

[0017]

[0018] S4. Constraints Consideration

[0019] According to the actual operating conditions and constraints of the thermal power plant, the constraints are added to the calculation model, and a new round of calculations is carried out to obtain the actual optimization data after the heating load distribution under the constraints of the existing productivity.

[0020] S5. Monitoring and Adjustment

[0021] The optimal heating load distribution plan is adopted and applied in the actual operation of the thermal power plant to make the actual operation data as close as possible to the optimized data.

[0022] The heating load is monitored in real time. If a heating unit failure is detected during monitoring, a new round of allocation plan optimization is carried out.

[0023] The recalculation of the optimization of the heating load distribution of the heating unit is based on the original optimization data, and the calculation formula is:

[0024]

[0025] S6. Model evaluation improvements

[0026] By comparing with the actual operation data, the optimization model is evaluated and improved according to the defects of the optimization model. By continuously improving the optimization model, the best method for heating load distribution of the heating module of the thermal power plant is obtained.

[0027] Preferably, the calculation formula of the fuel consumption in step S1 is:

[0028] B i =f(P i ,Q i ).

[0029] Preferably, in step S2, the calculation model needs to calculate the energy utilization rate of the heating unit, and the calculation formula of the energy utilization rate is:

[0030] .

[0031] The calculation formula for the energy consumption of the heating units in the thermal power plant area is:

[0032]

[0033] Preferably, in step S3, the calculation of the operating capacity requires integrating different heating units into one system, using a particle swarm algorithm to calculate the heating load, and performing a comparison through a tree diagram of energy consumption in the entire thermal power plant area.

[0034] Preferably, in step S4, the heating load constraint of the heating unit is:

[0035]

[0036] Preferably, in step S4, multiple power supply units need to be subject to heat balance constraints, and the constraint formula is:

[0037]

[0038] The total amount of electricity generated by multiple heating units is equal to the external electrical load, and the constraint formula is:

[0039]

[0040] The average heat output of multiple heating units cannot exceed the heat output of a single unit, and the power generation must be less than the heat output of the unit.

[0041] Preferably, in step S5, a new round of allocation scheme optimization continues to use the ion swarm algorithm, calculates based on the initial optimization scheme, determines whether the heating constraints and power generation constraints can be met, and calculates energy consumption, and subsequent optimization schemes are based on the previous round of schemes.

[0042] Preferably, in step S6, the optimized calculation scheme needs to be evaluated for model fitness, and the evaluation formula is:

[0043] B=f1(P1,Q1)+f2(P2,Q2)+P ca W.

[0044] Preferably, in step S6, when evaluating the model, it is necessary to consider the impact of the peak value of the heating season of the thermal power plant on the basis of the particle swarm algorithm, and to distribute and compare the heating loads of the heating units before and after optimization, so as to serve as the basis for the best allocation method.

[0045] Preferably, in the multi-unit heating mode, the heating unit with the largest heat-to-electricity ratio is given priority to carry out the maximum heating load, and the remaining heating load is allocated to the remaining heating units.

[0046] (III) Beneficial effects

[0047] Compared with the prior art, the present invention provides a method for optimizing the distribution of heating loads in a thermal power plant with multiple units and multiple heating modes, which has the following beneficial effects:

[0048] 1. The method for optimizing the distribution of heating loads in a thermal power plant with multiple units and multiple heating modes summarizes the detailed data of the actual power supply units of the thermal power plant, summarizes the operating data of a single heating machine and extrapolates it into the data of the heating units in the region, and calculates it to make it into a calculation model. After comparing the models and selecting the best solution, it is applied to the actual heating, and the actual heating load is monitored. The heating load is continuously adjusted to obtain the optimization method for the best heating load distribution of multiple heating units, thereby improving the efficiency of heating and reducing energy loss.

[0049] 2. The method for optimizing the distribution of heating loads in a thermal power plant with multiple units and multiple heating modes, by constraining the power, heat balance and average heating value in the process of heating load distribution, enables multiple heating units to ensure heat balance in the heating process, reduces heat loss in the heating load, and reduces the consumption cost of heating in the thermal power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 The present invention is an optimization step flow chart. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1 The present invention provides a technical solution: a method for optimizing the distribution of heating loads in a thermal power plant with multiple units and multiple heating modes, comprising the following steps:

[0053] S1. Data Collection

[0054] According to the number of heating units in the thermal power plant, collect the operating data of the thermal power plant, record the model, power, displacement, heating method, operating status, heating composite requirements and fuel consumption requirements of the heating units, and summarize the data of the power supply units into a table.

[0055] S2. Data Modeling

[0056] By analyzing the operating data of a single heating machine, a mathematical model of the heating unit and the heating load is established, and the calculation model of the heating unit in the thermal power plant area is deduced based on the operating data of the single heating machine.

[0057] The formula for calculating the heat supply of the power supply units in thermal power plants is:

[0058] Q=m h (h h -h d ) / 3600.

[0059] S3. Operation strategy optimization

[0060] Using the optimization algorithm, the heating load distribution of the thermal power plant is optimized according to the operating capacity and heating mode of different heating units. The operating energy consumption comparison is constructed into a tree diagram, and the best distribution optimization plan is selected from it.

[0061] Taking the coal consumption as the standard for optimizing the operation strategy, the calculation formula of coal consumption is:

[0062] .

[0063] S4. Constraints Consideration

[0064] According to the actual operating conditions and constraints of the thermal power plant, the constraints are added to the calculation model, and a new round of calculations is carried out to obtain the actual optimization data after the heating load distribution under the constraints of the existing productivity.

[0065] S5. Monitoring and Adjustment

[0066] The optimal heating load distribution plan is adopted and applied in the actual operation of the thermal power plant to make the actual operation data as close as possible to the optimized data.

[0067] The heating load is monitored in real time. If a heating unit failure is detected during monitoring, a new round of allocation plan optimization is carried out.

[0068] The recalculation of the optimization of the heating load distribution of the heating unit is based on the original optimization data, and the calculation formula is:

[0069]

[0070] S6. Model evaluation improvements

[0071] By comparing with the actual operation data, the optimization model is evaluated and improved according to the defects of the optimization model. By continuously improving the optimization model, the best method for heating load distribution of the heating module of the thermal power plant is obtained.

[0072] Furthermore, the calculation formula of the fuel consumption in step S1 is:

[0073] B i =f(P i ,Q i ).

[0074] Furthermore, in step S2, the calculation model needs to calculate the energy utilization rate of the heating unit, and the calculation formula of the energy utilization rate is:

[0075]

[0076] The calculation formula for the energy consumption of the heating units in the thermal power plant area is:

[0077]

[0078] Furthermore, in step S3, the calculation of the operating capacity requires integrating different heating units into one system, using a particle swarm algorithm to calculate the heating load, and comparing it through a tree diagram of the energy consumption of the entire thermal power plant area.

[0079] Furthermore, in step S4, the heating load constraint of the heating unit is:

[0080]

[0081] Furthermore, in step S4, multiple power supply units need to be constrained for heat balance, and the constraint formula is:

[0082]

[0083] The total amount of electricity generated by multiple heating units is equal to the external electrical load, and the constraint formula is:

[0084]

[0085] The average heat output of multiple heating units cannot exceed the heat output of a single unit, and the power generation must be less than the heat output of the unit.

[0086] Furthermore, in step S5, a new round of allocation scheme optimization continues to use the ion swarm algorithm, and is calculated based on the initial optimization scheme to determine whether the heating constraints and power generation constraints can be met, and the energy consumption is calculated. Subsequent optimization schemes are based on the previous round of schemes.

[0087] Furthermore, in step S6, the optimized calculation scheme needs to be evaluated for model fitness, and the evaluation formula is:

[0088] B=f1(P1,Q1)+f2(P2,Q2)+P ca W.

[0089] Furthermore, in step S6, when evaluating the model, it is necessary to consider the impact of the peak heating season of the thermal power plant on the basis of the particle swarm algorithm, and to distribute and compare the heating loads of the heating units before and after optimization, so as to serve as the basis for the optimal allocation method.

[0090] Furthermore, in the multi-unit heating mode, the heating unit with the largest heat-to-electricity ratio is given priority to carry out the maximum heating load, and the remaining heating load is allocated to the remaining heating units.

[0091] The method for optimizing the distribution of heating loads in a thermal power plant with multiple units and multiple heating modes summarizes the detailed data of the actual power supply units of the thermal power plant, summarizes the operating data of a single heating machine and extrapolates it into the data of the heating units in the region, and calculates it to make it into a calculation model. The models are compared, and after the best solution is selected, it is applied to the actual heating, and the actual heating load is monitored. The heating load is continuously adjusted to obtain an optimization method for the best heating load distribution of multiple heating units, thereby improving the efficiency of heating and reducing energy loss. At the same time, by constraining the power, heat balance and average heat supply value in the process of heating load distribution, multiple heating units can ensure heat balance in the heating process, reduce heat loss in the heating load, and reduce the consumption cost of the thermal power plant when supplying heat.

[0092] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes, characterized in that: The following steps are involved: S1. Data Collection According to the number of heating units in the thermal power plant, collect the operating data of the thermal power plant, record the model, power, displacement, heating mode, operating status, heating composite requirements and fuel consumption requirements of the heating units, and summarize the data of the power supply units into a table; S2. Data Modeling By analyzing the operating data of a single heating machine, a mathematical model of the heating unit and the heating load is established, and the calculation model of the heating unit in the thermal power plant area is deduced based on the operating data of the single heating machine; The formula for calculating the heat supply of the power supply units in thermal power plants is: Q=m h (h h -h d ) / 3600; S3. Operation strategy optimization Using the optimization algorithm, the heating load distribution of the thermal power plant is optimized according to the operating capacity and heating mode of different heating units, the energy consumption comparison of the working conditions is constructed into a tree diagram, and the best distribution optimization plan is selected from it; Taking the coal consumption as the standard for optimizing the operation strategy, the calculation formula of coal consumption is: S4. Constraints Consideration According to the actual operation status and constraints of the thermal power plant, the constraints are added to the calculation model, and a new round of calculations is carried out to obtain the actual optimization data after the heating load distribution under the constraints of the existing productivity; S5. Monitoring and Adjustment The best heating load distribution scheme is adopted and applied in the actual operation of the thermal power plant to make the actual operation data as close to the optimized data as possible; Real-time monitoring of heating loads. When a heating unit failure occurs during monitoring, a new round of allocation plan optimization is performed; The recalculation of the optimization of the heating load distribution of the heating unit is based on the original optimization data, and the calculation formula is: S6. Model evaluation improvements By comparing with the actual operation data, the optimization model is evaluated and improved according to the defects of the optimization model. By continuously improving the optimization model, the best method for heating load distribution of the heating module of the thermal power plant is obtained.

2. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1 is characterized in that: The calculation formula of the fuel consumption in step S1 is: B i =f(P i ,Q i )。 3. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1 is characterized in that: In step S2, the calculation model needs to calculate the energy utilization rate of the heating unit. The calculation formula of the energy utilization rate is: The calculation formula for the energy consumption of the heating units in the thermal power plant area is:

4. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1 is characterized in that: In step S3, the calculation of the operating capacity requires integrating different heating units into one system, using a particle swarm algorithm to calculate the heating load, and performing a comparison through a tree diagram of the energy consumption of the entire thermal power plant area.

5. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1 is characterized in that: In step S4, the heating load constraint of the heating unit is:

6. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1 is characterized in that: In step S4, multiple power supply units need to be constrained for heat balance, and the constraint formula is: The total amount of electricity generated by multiple heating units is equal to the external electrical load, and the constraint formula is: The average heat output of multiple heating units cannot exceed the heat output of a single unit, and the power generation must be less than the heat output of the unit.

7. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1 is characterized in that: In step S5, the new round of allocation scheme optimization continues to use the ion swarm algorithm, calculates based on the initial optimization scheme, determines whether the heating constraints and power generation constraints can be met, and calculates the energy consumption. The subsequent optimization scheme is based on the previous round of schemes.

8. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1, characterized in that: In step S6, the optimized calculation scheme needs to be evaluated for model fitness, and the evaluation formula is: B=f1(P1,Q1)+f2(P2,Q2)+P ca W。 9. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1, characterized in that: In step S6, when evaluating the model, it is necessary to consider the impact of the peak heating season of the thermal power plant on the basis of the particle swarm algorithm, and to distribute and compare the heating loads of the heating units before and after optimization, so as to form the basis for the best allocation method.

10. The method for optimizing heating load distribution in a thermal power plant with multiple units and multiple heating modes according to claim 1, characterized in that: In the multi-unit heating mode, the heating unit with the largest heat-to-electricity ratio is preferentially used to carry out the maximum heating load, and the remaining heating load is distributed to the remaining heating units.

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