Heating season peak capacity improving method and system based on power grid and heat supply network cooperative complementation

Abstract

The invention belongs to the technical field of power grids, and provides a heating season peak capacity improving method and system based on power grid and heat supply network collaborative complementing.The method comprises the steps that S1, whether a thermoelectric unit in an area has peak requirements or not is determined, and if yes, S2 is executed; if not, continuously operating according to the current state; s2, judging peak demand types of the thermoelectric units in the region, and entering different subsequent step flows according to different peak demand types; s3, calculating a first parameter of the tracking thermoelectric unit; s4, the unit is adjusted to the maximum power generation working condition under the current heat supply amount, and a second parameter of the tracking thermoelectric unit is calculated; s5, according to the first parameter and the second parameter, determining the cooperative operation condition of the power grid and the heat supply network, and based on the cooperative operation condition of the power grid and the heat supply network, calculating the revenue of the power grid peak capacity and the heat supply network investment cost; and S6, calculating a critical electricity price, and forming a long-term cooperative operation mechanism of the power grid and the heat supply network. According to the invention, heat supply network cooperation is taken as load side response, and power grid load adjustment flexibility and capacity improvement are realized.

Description

Technical Field

[0001] The present disclosure relates to the field of power grid technology, and in particular to a method and system for improving peak capacity during the heating season based on the coordinated complementarity of power grid and heat network. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] With economic development, the proportion of wind, solar and other renewable energy power generation connected to the grid has increased significantly, which has put forward higher requirements for the flexibility and adjustable capacity of the load adjustment of the power system. At the same time, small-capacity coal-fired power units and self-contained units have been gradually shut down, and large-scale cogeneration units have assumed comprehensive energy services such as heat, electricity and steam. The flexibility of coal-fired power units in load adjustment has been squeezed, and the flexibility of load adjustment on the power supply side needs to be further explored. As the load side, the demand for heating in winter continues to increase, and the structure of the heat network is becoming increasingly large and complex. On the one hand, it is reflected in the substantial increase in the area of ​​heating buildings and the diversity of types, and on the other hand, it is reflected in the diversity of heat sources in the heat network, including both regional power grid-controlled heat and power units, self-contained heat and power units, heat storage devices, various types of waste heat resources, and peak boilers in the heat network.

[0004] For the power grid-controlled thermal power units, traditional thermal-electric decoupling methods, such as electric boilers, heat pumps and other technologies, can reduce the load of coal-fired power units to a certain extent, but it is difficult to increase the peak capacity. In the case that large-scale energy storage resources (compressed air energy storage, pumped storage) are limited by natural resources and investment costs, starting from the operating mechanism and strategy level, it can release a certain amount of flexibility and space for load adjustment for coal-fired power units.

[0005] The regional power grid and heat network belong to different dispatching and operation systems, each with distinct characteristics and obvious complementary characteristics. Specifically, the electric load is instantaneously balanced, easy to transmit, and difficult to store; the heat load is easy to store, and there is thermal inertia in the supply and demand balance process. The two networks are connected through cogeneration units, which makes it possible for the two networks to work together. Summary of the invention

[0006] In response to the above-mentioned defects, the present disclosure proposes a method and system for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heating network, using the coordination of the heating network as the load-side response to achieve improved flexibility and capacity of power grid load adjustment.

[0007] In order to achieve the above objectives, the present disclosure adopts the following technical solutions:

[0008] The first aspect of the present disclosure provides a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heating network, comprising the following steps:

[0009] S1 determines whether there is a peak demand for thermal power units in the area. If so, it goes to S2; if not, each thermal power unit continues to operate according to the current state;

[0010] S2 determines the peak demand type of thermal power units in the area. If it is the first type of peak demand, it enters S3 and skips S4 and directly enters S5. If it is the second type of peak demand, it skips S3 and enters S4.

[0011] S3 calculates the first parameter of the centralized thermal power unit according to the thermal characteristics of the centralized thermal power unit;

[0012] S4 adjusts the unit to the maximum power generation condition under the current heat supply, and then calculates the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit;

[0013] S5 determines the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculates the benefits of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network;

[0014] S6 calculates the critical electricity price and forms a long-term coordinated operation mechanism between the power grid and the heat network.

[0015] As a further implementation method, the first type of peak demand is a small-capacity or short-duration peak demand, and the second type of peak demand is a large-capacity and long-duration peak demand.

[0016] As a further implementation method, the basis for judging the peak demand type of thermal power units in the region is: if the peak demand is greater than or equal to the set value of the peak demand for power system load adjustment, and the peak time is greater than or equal to the set value of the peak duration for power system load adjustment, then it is the second type of peak demand, otherwise it is the first type of peak demand.

[0017] As a further implementation, the set value of the peak demand of the power system load adjustment is affected by the ability of the heating network to respond to the peak demand of the power grid;

[0018] The set value of the peak duration of the power system load adjustment is jointly affected by the renewable energy power generation forecast and the user load forecast.

[0019] As a further implementation, the first parameter is the throttling amount of the heating extraction steam of the centralized thermal power unit and the heat released by the heat storage device of the heat network;

[0020] The second parameter is the heating extraction steam throttling amount of the centralized thermal power unit, the heat release of the heat storage device of the heat network, the heating supply of waste heat resources and the heating supply of the self-provided peak boiler.

[0021] As a further implementation method, the basis for determining whether there is a peak demand for thermal power units in the region is: if the peak demand is greater than zero, there is a peak demand, otherwise there is no peak demand.

[0022] As a further implementation method, the critical electricity price is the electricity price at which the peak revenue of the power grid just offsets the investment cost of the heating network.

[0023] The second aspect of the present disclosure provides a system for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network, comprising:

[0024] The peak demand determination module is configured to: determine whether there is a peak demand for the thermal power units in the area, if so, enter S2; if not, each thermal power unit continues to operate according to the current state;

[0025] The type judgment module is configured to: judge the peak demand type of the thermal power unit in the area, if it is the first type of peak demand, then skip S4 after entering S3 and directly enter S5, if it is the second type of peak demand, then skip S3 and enter S4;

[0026] The first parameter calculation module is configured to calculate a first parameter of the centralized thermal power unit according to the thermal characteristics of the centralized thermal power unit;

[0027] The second parameter calculation module is configured to: adjust the unit to the maximum power generation condition under the current heat supply, and then calculate the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit;

[0028] The benefit and cost calculation module is configured to: determine the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculate the benefit of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network;

[0029] The collaborative operation module is configured to calculate the critical electricity price and form a long-term collaborative operation mechanism between the power grid and the heat network.

[0030] The third aspect of the present disclosure provides a medium on which a program is stored. When the program is executed by a processor, the steps of a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network described in the first aspect of the present disclosure are implemented.

[0031] The fourth aspect of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network as described in the first aspect of the present disclosure are implemented.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The present disclosure proposes a method for improving the peak capacity of the heating season based on the synergy and complementarity of the power grid and the heat network. It makes full use of the complementary characteristics of the heat network and the power grid. The electric load is instantly balanced, easy to transmit, and difficult to store; while the heat load is easy to store, and there is thermal inertia in the supply and demand balance regulation. The two networks are connected through thermal power units, which makes it possible for the two networks to work together. The coordinated operation of the two networks embodies the load-side response mechanism, which can effectively release the flexibility of load adjustment on the power supply side, and respond to the peak demand of the power system through the thermoelectric coupling characteristics of the thermal power units. Relying on the heat network's adjustment of the thermal load, its own thermal inertia, and the reserve heat source adjustment, it is realized to meet the peak power and adjustment time requirements. Using the heat network synergy as the load-side response, the flexibility and capacity of the power grid load adjustment can be improved.

[0034] The present disclosure proposes a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network. Different power grid-heat network coordinated operation strategies are proposed according to the different peak demand times. When the peak demand time is short or the capacity is small, more peak capacity is provided to the power grid through the throttling of the heating extraction steam of the unified dispatching unit and the coordinated heat storage device; when the peak demand time is long and the capacity is large, in addition to the throttling of the heating extraction steam of the unified dispatching unit and the coordinated heat storage device, the heat network calls on the peak boiler and its own waste heat resources, including environmental waste heat resources and industrial waste heat sources.

[0035] The present invention discloses a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heating network. By configuring the heating network with energy storage of corresponding capacity and fully tapping various active and passive heat sources available in the heating network, the self-balancing ability of the heating network's heating load is improved, which helps to achieve the load-side response of the heating network, improve the coordination of the two networks, and tap the peak capacity.

[0036] The method for improving the peak capacity of the heating season based on the synergy and complementarity of the power grid and the heat network proposed in the present disclosure has strong scalability. According to the characteristics of the heat network and the power grid in different regions, the operation of the heat network and the power grid can be coordinated according to local conditions, and methods and strategies for improving the peak capacity of the heating season suitable for the local area can be proposed. For example, in a power grid with pumped storage or compressed gas energy storage, the above-mentioned units can all be used as the unified dispatching resources of the power grid. Different heat networks have different types of waste heat resources, such as industrial waste heat, data center waste heat or solar energy waste heat, which can all be used as unified dispatching resources for the heat network. By calculating the income and investment costs of the peak process of the heat network coordinating with the power grid, and realizing paid services with the help of the capacity compensation mechanism, it is helpful to combine the power auxiliary service market to achieve an effective long-term coordination mechanism.

[0037] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure.

[0039] Figure 1 It is a flow chart of the method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network disclosed in the present invention;

[0040] Figure 2 is the operation of the power grid and heat network of the present disclosure when there is no peak demand;

[0041] Figure 3 It is the coordinated operation of the power grid and the heat network in the small capacity or short-time peak demand scenario disclosed in the present invention;

[0042] Figure 4 This is the coordinated operation of the power grid and heat network in the large-capacity and long-term peak demand scenario disclosed in the present invention.

[0043] Among them, 1. Centrally controlled thermal power plant; 2. Wind power; 3. Photovoltaic; 4. Heat storage device; 5. Waste heat source of heating network; 6. Self-contained boiler of heating network; 7. Electricity demand; 8. Heat demand. DETAILED DESCRIPTION

[0044] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0045] It should be noted that the following detailed descriptions are all illustrative and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

[0046] In the absence of conflict, the embodiments in the present disclosure and the features in the embodiments may be combined with each other.

[0047] Embodiment 1

[0048] like Figure 1 As shown, the first embodiment of the present disclosure provides a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heating network, which mainly includes the following steps:

[0049] S1 determines whether there is a peak demand for thermal power units in the area. If so, it goes to S2; if not, each thermal power unit continues to operate according to the current state;

[0050] S2 determines the peak demand type of thermal power units in the area. If it is the first type of peak demand, it enters S3 and skips S4 and directly enters S5. If it is the second type of peak demand, it skips S3 and enters S4.

[0051] S3 calculates the first parameter of the centralized thermal power unit according to the thermal characteristics of the centralized thermal power unit;

[0052] S4 adjusts the unit to the maximum power generation condition under the current heat supply, and then calculates the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit;

[0053] S5 determines the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculates the benefits of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network;

[0054] S6 calculates the critical electricity price and forms a long-term coordinated operation mechanism between the power grid and the heat network.

[0055] First, S1 determines the Figure 2 Whether there is a peak demand for thermal power units in the area shown is based on: if the peak demand P peak >0, there is peak demand, otherwise there is no peak demand.

[0056] Attached Figure 2-4 In the figure, 1 is the centrally dispatched thermal power plant, 1-1...1-n are the 1st to nth cogeneration centrally dispatched units respectively; 2 is wind power; 3 is photovoltaic power; 4 is heat storage device; 5 is the waste heat source of the heating network, 5-1 and 5-2 represent different types of waste heat sources respectively; 6 is the self-provided boiler of the heating network; 7 is the power demand; 8 is the heat demand. Among them, the power flow is represented by a solid line; the heat flow is represented by a dotted line; the unit outline belonging to the power grid dispatch is represented by a solid line; the unit outline belonging to the heating network dispatch is represented by a dotted line.

[0057] P peak =P Demand -∑P SP -∑P WP -∑P CHP

[0058] Among them, P Demand P is the electricity demand in MW. SP , P WP , and P CHP They are the current power generation of photovoltaic, wind power and thermal power units, in MW. Among them, the real-time power generation data of wind power and photovoltaic, or the forecast data of wind power and photovoltaic power generation based on historical operation data and weather conditions.

[0059] If there is a peak demand, enter S2; if there is no peak demand, each thermal power unit continues to operate according to the current state.

[0060] S2 determines the peak demand type of thermal power units in the area. If it is the first type of peak demand, it enters S3 and skips S4 to directly enter S5. If it is the second type of peak demand, it skips S3 and enters S4.

[0061] The first type of peak demand is a small-capacity or short-duration peak demand, and the second type of peak demand is a large-capacity and long-duration peak demand.

[0062] The basis for judging the peak demand type of thermal power units in the region is: Peak demand P peak ≥P E , and the peak time T peak ≥T E , it is the second type of peak demand, otherwise it is the first type of peak demand.

[0063] Among them, P E The set value for adjusting the peak demand of the power system load is affected by the ability of the heating network to respond to the peak demand of the power grid. E The set value for adjusting the peak duration of the power system load is jointly affected by the renewable energy generation forecast and the user load forecast.

[0064] S3 calculates the first parameter of the coordinated thermal power unit according to the thermoelectric characteristics of the coordinated thermal power unit.

[0065] The first parameter is the heating extraction steam throttling amount Δm of the centralized thermal power unit. H And the heat storage device of the heat network releases heat Q H The coordinated operation status of the heat network and the power grid is shown in the attached Figure 3 shown.

[0066] S3.1 Calculate the heating extraction steam throttling amount Δm H :

[0067]

[0068] Among them, h H With h W are the heat extraction steam enthalpy and the return water enthalpy, in kJ / kg, and η is the heat-to-electricity conversion coefficient, which means the unit heat extraction steam throttling (Δm H ) caused by the power increase (ΔP).

[0069] S3.2 Calculate the heat release Q of the heat storage device in the heat network H :

[0070] Q H =ΔAm H ·(h H -h W )

[0071] S4 adjusts the unit to the maximum power generation condition under the current heat supply, and then calculates the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit.

[0072] The second parameter is the heating extraction steam throttling amount Δm of the centralized thermal power unit. H, the heat storage device of the heat network releases heat Q H 、Waste heat resource heating capacity Q YH And the self-provided peak boiler heating capacity Q Boiler The coordinated operation status of the heat network and the power grid is shown in the attached Figure 4 shown.

[0073] S4.1 The maximum power generation under the current heat supply of the computer group can be obtained through the thermal and electric load operation domain of the unit:

[0074] P MAX =f(m H )

[0075] Among them, P MAX is the maximum power generation of the thermal power unit under the current heat supply, in MW; f() is the constraint function of the upper boundary of the thermal power load operation domain of the unit; m H is the amount of steam extraction for heating, unit: t·h -1 .

[0076] S4.2 The heating extraction steam throttling amount required by the computer group:

[0077]

[0078] Among them, P CHP is the current power generation of the thermal power unit, P MAX It is the maximum power generation of the thermal power unit under the current heating supply, and the unit is MW.

[0079] S4.3 Calculate the heat release Q of the heat storage device in the heat network H 、Waste heat resource heating capacity Q YH And the self-provided peak boiler heating capacity Q Boiler The total amount of heat required to be provided by the heat network is Q all =Δm H ·(h H -h W The maximum heating capacity of the heat storage device, waste heat resources, and peak boiler is represented by Q H，MAX , Q YH，MAX , Q Boiler,MAX express.

[0080] If Q H，MAX +Q YH，MAX ≥Q all , then the waste heat resources are fully utilized, and the heat from the waste heat resources Q YH For: Q YH =Q YH，MAX , the heat storage device of the heat network releases heat Q H For: Q H =Q all -Q YH .

[0081] If Q H，MAX +Q YH，MAX <Q all , then the heat from the waste heat resources and the heat storage device is fully utilized, and the peak boiler is required to provide additional heat. At this time, the heat from the waste heat resources Q YH =Q YH，MAX ; Heat released by heat storage device in heat network Q H =Q H，MAX ; Peak boiler heat release Q Boiler =Q all -Q YH -Q H .

[0082] S5 determines the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculates the benefit of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network.

[0083] The peak revenue of the power grid is:

[0084] Profit=Y power ·P peak ·T peak

[0085] The investment cost of heating network is:

[0086] Cost = Y Heat Q all ·T peak +Y Boiler ·T peak

[0087] Among them, Y power With Y Heat are the electricity selling price and the heat selling price respectively, Boiler For peak boiler operating costs.

[0088] S6 calculates the critical electricity price and forms a long-term coordinated operation mechanism between the power grid and the heat network.

[0089] The critical electricity price is the electricity price at which the peak revenue of the power grid just offsets the investment cost of the heating network.

[0090] The critical electricity price is:

[0091]

[0092] The technical solution of the present disclosure is described below with two specific examples.

[0093] In a typical embodiment of the present disclosure, there is a centralized thermal power plant with two thermal power units, a wind farm, and a photovoltaic power plant; the heat network includes a heat storage device, an environmental waste heat resource, an industrial waste heat source, and two heat network peak boilers. In order to meet the peak demand of small capacity or short time of the power grid, a method and strategy for improving the peak capacity of the heating season based on the synergy and complementarity of the power grid and the heat network is proposed, which takes the synergy of the heat network as the load side response to achieve the improvement of the flexibility of the load adjustment and the peak capacity of the power grid.

[0094] Among them, the parameters of the two coordinated thermal power units are exactly the same. Both are 330MW subcritical units with single reheating. The main steam flow is 1002.4t / h, the pressure is 16.7MPa, and the temperature is 537℃; the reheat steam pressure is 3.2MPa, the temperature is 537℃; the exhaust pressure is 5.4kPa. The heat recovery system includes 3 high-pressure heaters, 1 deaerator and 4 low-pressure heaters. The heat extraction position is the 4th stage heat recovery extraction, the extraction temperature is 343℃, the extraction enthalpy is 3146.8kJ / kg, the return water temperature is 146.3℃, and the return water enthalpy is 617.8kJ / kg.

[0095] The two centrally controlled thermal power units have a power generation capacity of 250MW each and a heating capacity of 345MW each.

[0096] S1 is confirmed as attached Figure 2 Whether there is a peak demand for the thermal power units in the area shown, if yes, enter S2; if not, each thermal power unit continues to operate according to the current state.

[0097] The judgment basis is: if the peak demand P peak >0, there is peak demand; otherwise, there is no peak demand.

[0098] P peak =P Demand -∑P SP -∑P WP -∑P CHP

[0099] Where P Demand The power demand is 700MW. SP , P WP , and P CHP These are the current power generation of photovoltaic, wind power and thermal power units, which are 60MW, 108MW and 250MW respectively.

[0100] It is calculated that P peak =32>0, there is a peak demand and enter S2.

[0101] S2 determines the peak demand type of thermal power units in the area. If it is a small capacity or short-term peak demand, it enters S3 and skips S4 to directly enter S5; if it is a large capacity and long-term peak demand, it skips S3 and enters S4 and S5 in sequence.

[0102] The judgment basis is: Peak demand P peak ≥P E , and the peak time T peak ≥T E , it is a large capacity and long-term peak demand, otherwise it is a small capacity or short-term peak demand.

[0103] Among them, P E is the set value of the peak demand of the power system load adjustment, which is affected by the ability of the heating network to respond to the peak demand of the power grid. E 10% of the total rated power of all thermal power units, that is, P E =10%×(330+330)=66MW.

[0104] T E is the set value of the peak duration of the power system load adjustment, which is affected by the forecast of renewable energy generation and user load forecast. E For 6 hours.

[0105] After calculation, the P peak =32MW, and the peak time is T peak =0.5h, which belongs to the scenario of small capacity or short-time peak demand.

[0106] S3 calculates the heating extraction steam throttling amount Δm of the unified thermal power unit according to the thermal and electric characteristics of the unified thermal power unit H1 , and the heat storage device of the heat network releases heat Q H The coordinated operation status of the heat network and the power grid is shown in the attached Figure 3 shown.

[0107]

[0108] In the formula, h H With h W are the heat extraction steam enthalpy and the return water enthalpy, which are 3146.8 kJ / kg and 617.8 kJ / kg respectively. η is the heat-to-electricity conversion coefficient. After calculation, η=9.1359×10 -5 , and we get

[0109]

[0110] Calculate the heat release Q of the heat storage device in the heat network H for:

[0111]

[0112] S5 realizes paid services based on the results of coordinated optimization of power grid and heat network and the corresponding mechanism of power spot market, and calculates the benefits of peak capacity of power grid and investment cost of heat network.

[0113] The income comes from the compensation obtained by the coordinated thermal power units for meeting the peak demand of the power grid. The specific compensation price is determined by the power market in view of the scarcity of peak capacity. In this example, it is calculated at 1 yuan / kWh. The heat price is calculated at 50 yuan / GJ.

[0114] The peak revenue of the power grid is 1000×32×0.5=16,000 yuan.

[0115] The investment cost of the heating network is 50×97×0.5×3.6=8730 yuan.

[0116] The net profit is 16,000-8,730=7,270 yuan. These net profits can be distributed between the power grid and the heat network to mobilize the heat network's response enthusiasm for participating in power auxiliary services. In addition, in actual operation, given the scarcity of peak capacity and the different ways of obtaining peak capacity, the compensation price for the peak of the power grid may be higher than 1 yuan / kWh. At this time, the benefits and feasibility of the method provided by this patent will be higher.

[0117] Based on the results of the coordinated operation of the power grid and the heat network, S6 calculates the critical electricity price at which the peak revenue of the power grid just offsets the investment cost of the heat network, so as to guide the mechanism of long-term coordinated operation of the two networks.

[0118] The critical electricity price is 8730 / (32×0.5×1000)=0.545 yuan / kWh. Therefore, as long as the peak electricity price is higher than 0.545 yuan / kWh, the power grid and the heat network have the feasibility of coordinated operation and can obtain benefits, thus forming a mechanism that is conducive to guiding the long-term coordinated operation of the two networks.

[0119] In the second typical embodiment of the present disclosure, there is a coordinated thermal power plant with two thermal power units, a wind farm, and a photovoltaic power plant. The heat network includes a heat storage device, an environmental waste heat resource and an industrial waste heat source, and two heat network peak boilers. Considering the large-capacity and long-term peak demand of the power grid, a method and strategy for improving the peak capacity of the heating season based on the synergy and complementarity of the power grid and the heat network is proposed, with the heat network and the power grid as the load side response, to achieve the improvement of the flexibility and capacity of the load adjustment of the power grid.

[0120] Among them, the parameters of the two coordinated thermal power units are exactly the same. Both are 330MW subcritical units with single reheating. The main steam flow is 1002.4t / h, the pressure is 16.7MPa, and the temperature is 537℃; the reheat steam pressure is 3.2MPa, the temperature is 537℃; the exhaust pressure is 5.4kPa. The heat recovery system includes 3 high-pressure heaters, 1 deaerator and 4 low-pressure heaters. The heat extraction position is the 4th stage heat recovery extraction, the extraction temperature is 343℃, the extraction enthalpy is 3146.8kJ / kg, the return water temperature is 146.3℃, and the return water enthalpy is 617.8kJ / kg.

[0121] Before the coordinated operation of the power grid and the heat network, the operating conditions of the two centralized thermal power units are shown in Table 1.

[0122] Table 1 Operating conditions of two coordinated thermal power units before the coordinated operation of the power grid and heat network

[0123]

[0124] The real-time power generation data of wind power and photovoltaic power are shown in Table 2.

[0125] Table 2 Power generation of wind power and photovoltaic power

[0126]

[0127] S1 is confirmed as attached Figure 2 Whether there is a peak demand for thermal power units in the area shown, if so, enter S2; if not, each thermal power unit continues to operate according to the current state. During the period of 10:00-15:00, the power demand of the power grid is shown in Table 3.

[0128] Table 3 Grid power demand

[0129]

[0130]

[0131] The peak demand for each time period is calculated according to the following formula. The results are shown in Table 4.

[0132] P peak =P Demand -ΣP SP -ΣP WP -ΣP CHP

[0133] S2 determines the peak demand type of thermal power units in the area. The peak demand during the period of 10:00 to 15:00 is shown in Table 4. The peak demand P peak All of them are greater than 66MW, and the peak time is T = 6h, which belongs to the scenario of large capacity and long-term peak demand. Therefore, it directly enters S4.

[0134] Table 4 Peak demand P value

[0135]

[0136] S4 adjusts the unit to the maximum power generation condition under the current heat supply, and then calculates the heating extraction steam throttling amount Δm of the unified heat and power unit according to the thermoelectric characteristics of the unified heat and power unit. H , the heat storage device of the heat network releases heat Q H 、Waste heat resource heating capacity Q YH And the self-provided peak boiler heating capacity Q Boiler The coordinated operation status of the heat network and the power grid is shown in the attached Figure 4 shown.

[0137] S4.1 calculates the maximum power generation of the computer group under the current heating supply. The results are shown in Table 5.

[0138] P MAX =f(m H )

[0139] Table 5 Maximum power generation under the current heating supply of the unit

[0140]

[0141] The heating extraction steam throttling amount required by the S4.2 computer group is shown in Table 6.

[0142]

[0143] Table 62 throttling amount of steam extraction for heating of 2 thermal power units

[0144]

[0145] S4.3 Calculate the heat release Q of the heat storage device in the heat network H 、Waste heat resource heating capacity Q YH And the self-provided peak boiler heating capacity Q Boiler The total amount of heat required to be provided by the heat network is Q all =Δm H ·(h H -h W The maximum heating capacity of the heat storage device, waste heat resources, and peak boiler is represented by Q H,MAX , Q YH,MAX , Q Boiler,MAX express.

[0146] If Q H,MAX +Q YH,MAX ≥Q all , then the waste heat resources are fully utilized, and the heat from the waste heat resources Q YH For: Q YH =QYH,MAX ; Heat released by heat storage device in heat network Q H For: Q H =Q all -Q YH .

[0147] If Q H,MAX +Q YH,MAX <Q all , then the heat from the waste heat resources and the heat storage device is fully utilized, and the peak boiler is required to provide additional heat. At this time, the heat from the waste heat resources Q YH =Q YH,MAX ; Heat released by heat storage device in heat network Q H =Q H,MAX ; Peak boiler heat release Q Boiler =Q all -Q YH -Q H .

[0148] Maximum heat release of heat storage device Q H,MAX =50MW, the heat network includes 1 environmental waste heat resource and 1 industrial waste heat source. Within 6 hours of peak demand, the maximum heat available is shown in Table 7. The maximum heat release of the peak boiler Q Boiler =200MW.

[0149] Table 7 Utilizable heat from waste heat source

[0150]

[0151] After calculation, the heat supply of each heat source in the heat network is shown in Table 8:

[0152] Table 8 Heating network operation status

[0153]

[0154]

[0155] At this time, the operating conditions of each unit in the power grid are shown in Table 9.

[0156] Table 9 Operation status of power grid units

[0157]

[0158] It can be seen from the results in Tables 8 and 9 that after the coordinated operation of the power grid and the heat network, both the electricity demand and the heat demand are met.

[0159] S5 calculates the benefits of the peak capacity of the power grid and the investment cost of the heat network based on the results of the coordinated operation of the power grid and the heat network.

[0160] The peak revenue of the power grid is:

[0161] Profit=Y power ·P peak ·T peak

[0162] The investment cost of heating network is:

[0163] Cost = Y Heat Q all ·T peak +Y Boiler ·T peak

[0164] The calculation results are shown in Table 10. Among them, the electricity price is calculated at 1 yuan / kWh, and the heating price of the heat network is calculated at 50 yuan / GJ. The heat production and operation cost of the peak boiler is calculated at 32 yuan / GJ. The benefits, costs and net profits of the coordinated operation of the power grid and the heat network in this example are shown in Table 10.

[0165] Table 10 Benefits, costs and net profits of coordinated operation of power grid and heat network

[0166]

[0167] As shown in Table 10, after the coordinated operation of the power grid and the heat network, the accumulated net profit for 6 hours is 187,644 yuan. These net profits can be distributed between the power grid and the heat network, forming a mechanism that is conducive to guiding the long-term coordinated operation of the two networks. In addition, in actual operation, given the scarcity of peak capacity and the different ways of obtaining peak capacity, the compensation price of the peak of the power grid may be higher than 1 yuan / kWh. At this time, the benefits and feasibility of the method provided by this patent will be higher.

[0168] Based on the results of the coordinated operation of the power grid and the heat network, S6 calculates the critical electricity price at which the peak revenue of the power grid just offsets the investment cost of the heat network, so as to guide the mechanism of long-term coordinated operation of the two networks.

[0169] The critical electricity price is: 281356 / (469×1000)=0.6 yuan / kWh. Therefore, as long as the peak electricity price is higher than 0.6 yuan / kWh, the power grid and the heat network have the feasibility of coordinated operation and can obtain benefits, thus forming a mechanism that is conducive to guiding the long-term coordinated operation of the two networks.

[0170] Embodiment 2

[0171] The second embodiment of the present disclosure provides a system for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heating network, including:

[0172] The peak demand determination module is configured to: determine whether there is a peak demand for the thermal power units in the area, if so, enter S2; if not, each thermal power unit continues to operate according to the current state;

[0173] The type judgment module is configured to: judge the peak demand type of the thermal power unit in the area, if it is the first type of peak demand, then skip S4 after entering S3 and directly enter S5, if it is the second type of peak demand, then skip S3 and enter S4;

[0174] The first parameter calculation module is configured to calculate a first parameter of the centralized thermal power unit according to the thermal characteristics of the centralized thermal power unit;

[0175] The second parameter calculation module is configured to: adjust the unit to the maximum power generation condition under the current heat supply, and then calculate the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit;

[0176] The benefit and cost calculation module is configured to: determine the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculate the benefit of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network;

[0177] The collaborative operation module is configured to calculate the critical electricity price and form a long-term collaborative operation mechanism between the power grid and the heat network.

[0178] The more detailed steps are the same as those in the first embodiment and will not be repeated here.

[0179] Embodiment 3

[0180] Embodiment 3 of the present disclosure provides a medium on which a program is stored. When the program is executed by a processor, the steps of a method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network as described in Embodiment 1 of the present disclosure are implemented.

[0181] The more detailed steps are the same as those in the first embodiment and will not be repeated here.

[0182] Embodiment 4

[0183] Embodiment 4 of the present disclosure provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps of a method for improving peak capacity during the heating season based on coordinated complementarity between the power grid and the heat network as described in Embodiment 1 of the present disclosure are implemented.

[0184] The more detailed steps are the same as those in the first embodiment and will not be repeated here.

[0185] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for improving peak capacity during the heating season based on the synergy and complementarity between the power grid and the heating network, characterized in that: The following steps are involved: S1 determines whether there is a peak demand for thermal power units in the area. If so, it goes to S2; if not, each thermal power unit continues to operate according to the current state; S2 determines the peak demand type of thermal power units in the area. If it is the first type of peak demand, it enters S3 and skips S4 and directly enters S5. If it is the second type of peak demand, it skips S3 and enters S4. S3 calculates the first parameter of the centralized thermal power unit according to the thermal characteristics of the centralized thermal power unit; S4 adjusts the unit to the maximum power generation condition under the current heat supply, and then calculates the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit; S5 determines the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculates the benefits of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network; S6 calculates the critical electricity price and forms a long-term coordinated operation mechanism between the power grid and the heat network.

2. The method for improving peak capacity during the heating season based on the synergy and complementarity between the power grid and the heating network as claimed in claim 1, characterized in that: The first type of peak demand is a small-capacity or short-duration peak demand, and the second type of peak demand is a large-capacity and long-duration peak demand.

3. The method for improving peak capacity in the heating season based on the synergy and complementarity of the power grid and the heating network as claimed in claim 1, characterized in that: The basis for judging the peak demand type of thermal power units in the region is: if the peak demand is greater than or equal to the set value of the peak demand for power system load adjustment, and the peak time is greater than or equal to the set value of the peak duration for power system load adjustment, then it is the second type of peak demand, otherwise it is the first type of peak demand.

4. The method for improving peak capacity in the heating season based on the synergy and complementarity of the power grid and the heating network as described in claim 3, characterized in that: The set value of the peak demand for load adjustment of the power system is affected by the ability of the heating network to respond to the peak demand of the power grid; The set value of the peak duration of the power system load adjustment is jointly affected by the renewable energy power generation forecast and the user load forecast.

5. The method for improving peak capacity in the heating season based on the synergy and complementarity of the power grid and the heating network as claimed in claim 1, characterized in that: The first parameter is the throttling amount of the heating extraction steam of the centralized thermal power unit and the heat released by the heat storage device of the heat network; The second parameter is the heating extraction steam throttling amount of the centralized thermal power unit, the heat release of the heat storage device of the heat network, the heating supply of waste heat resources and the heating supply of the self-provided peak boiler.

6. The method for improving peak capacity in the heating season based on the synergy and complementarity of the power grid and the heating network as claimed in claim 1, characterized in that: The basis for determining whether there is a peak demand for thermal power units in the region is: if the peak demand is greater than zero, there is a peak demand, otherwise there is no peak demand.

7. The method for improving peak capacity in the heating season based on the synergy and complementarity of the power grid and the heating network as claimed in claim 1, characterized in that: The critical electricity price is the electricity price at which the peak revenue of the power grid just offsets the investment cost of the heating network.

8. A heating season peak capacity enhancement system based on the synergy and complementarity of the power grid and the heating network, characterized in that: include: The peak demand determination module is configured to: determine whether there is a peak demand for the thermal power units in the area, if so, enter S2; if not, each thermal power unit continues to operate according to the current state; The type judgment module is configured to: judge the peak demand type of the thermal power unit in the area, if it is the first type of peak demand, then skip S4 after entering S3 and directly enter S5, if it is the second type of peak demand, then skip S3 and enter S4; The first parameter calculation module is configured to calculate a first parameter of the centralized thermal power unit according to the thermal characteristics of the centralized thermal power unit; The second parameter calculation module is configured to: adjust the unit to the maximum power generation condition under the current heat supply, and then calculate the second parameter of the centralized thermal power unit according to the thermoelectric characteristics of the centralized thermal power unit; The benefit and cost calculation module is configured to: determine the coordinated operation of the power grid and the heat network according to the first parameter and the second parameter, and calculate the benefit of the peak capacity of the power grid and the investment cost of the heat network based on the coordinated operation of the power grid and the heat network; The collaborative operation module is configured to calculate the critical electricity price and form a long-term collaborative operation mechanism between the power grid and the heat network.

9. A storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heat network as described in any one of claims 1 to 7 are implemented.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for improving the peak capacity of the heating season based on the coordinated complementarity of the power grid and the heating network as described in any one of claims 1 to 7 are implemented.

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