A multi-type unit maintenance plan configuration method and system based on a polymerization unit combination

Abstract

The application discloses a kind of based on the multi-type unit maintenance plan configuration method and system of polymeric unit combination, the method first collects the comprehensive data of target power system, including regional load, traditional unit, hydroelectric unit, pumped storage unit, battery energy storage system and wind power photovoltaic unit data, then combined with the optimization model based on clustering unit combination of pre-set, to formulate the maintenance plan of multi-type unit.This optimization model comprehensively the operation model of thermal power unit, hydroelectric unit, pumped storage unit and battery energy storage, and the maintenance model of unit to be maintained, aims at balancing operation cost, maintenance cost and the penalty cost caused by unit unavailability.By this method, the application can ensure the reliable operation of power system within the optimization period, while considering the maintenance needs of multiple unit types, improve the comprehensiveness and accuracy of maintenance plan configuration, effectively solve the problem of single unit type and low solving efficiency in traditional method.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power maintenance, and relates to a multi-type unit maintenance plan configuration method and system based on an aggregated unit combination. BACKGROUND

[0002] The increasing demand for electric power energy poses challenges to the efficient and reliable operation of the power system. With the rapid development of the power system, its scale is expanding, the power network is becoming more complex, and the power equipment is also increasing. Once the generator set, as the backbone of the power system, fails, it will affect the efficiency and reliability of the power system, and even may cause system failure or paralysis. Reasonably arranging the maintenance of the power equipment is an important part of the operation planning of the power system. The unit maintenance plan arrangement not only affects the operation reliability of the unit itself, but also affects the generation capacity adequacy of the power system at each period, the generation scheduling sequence of the unit, and further affects the safe and reliable operation of the power system. However, the maintenance plan of the generator set in the medium and long term operation of the power system involves a long time span, a large problem scale, and high calculation difficulty. Therefore, how to design an efficient generator maintenance scheduling model is an important problem in the medium and long term reliable operation of the power system.

[0003] At present, the power system still mainly adopts planned maintenance as the main body, that is, the maintenance plan is manually prepared. Such a scheme is based on simple rules and arranges maintenance according to fixed time intervals or predetermined operation plans, and is only a feasible plan. Therefore, the reliability and economy of the power system operation cannot be maximally guaranteed. The maintenance model of the generator set generally includes two categories of mathematical optimization algorithm and heuristic algorithm. The heuristic method of unit maintenance mainly includes equal reserve method and equal risk degree method, especially the equal reserve method, which is widely used because it can obtain a satisfactory solution with less calculation amount due to its simplicity and intuition. These methods arrange and combine the maintenance sequence of the generator set by using certain heuristic rules, so that the reserve rate and other reliability targets of the system during the overall operation period are minimized. Although these methods have fast operation speed, they cannot simulate the actual operation process of the power system, and the operability and economy of the results are difficult to guarantee. The mathematical optimization method simulates the operation and maintenance process of the generator set by establishing a mixed integer programming model, but it is often only for solving a single type of unit, and generally, the mathematical optimization algorithm has large calculation amount, and the final solution is greatly related to the accuracy of the model. By establishing an aggregated unit combination model, the solving efficiency of the maintenance model can be significantly improved, and it is suitable for large-scale power systems.

[0004] In summary, in the power system maintenance plan configuration, the maintenance arrangement of multiple different types of units needs to be considered, and the overall operation efficiency can be ensured to be as fast as possible under the target of meeting the system economic optimization, and an efficient multi-type generator maintenance scheduling model is urgently needed to ensure the long-term reliable operation of the power system. SUMMARY

[0005] In view of the problems in the prior art, the application provides a multi-type unit maintenance plan configuration method and system based on an aggregated unit combination, thereby solving the technical problems of single unit type and low solving efficiency in the prior art.

[0006] The application is implemented by the following technical solutions:

[0007] A multi-type unit maintenance plan configuration method based on an aggregated unit combination comprises the following steps:

[0008] Obtain input information; wherein the input information comprises regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data, and wind and photovoltaic unit data of a target power system;

[0009] According to the obtained regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data, and wind and photovoltaic unit data, and in combination with a multi-type unit maintenance plan configuration optimization model constructed based on a clustered unit combination, wherein the objective function of the multi-type unit maintenance plan configuration optimization model constructed based on the clustered unit combination aims to minimize the operation cost of each type of unit, the maintenance cost of the unit to be maintained, and the penalty cost of load loss, wind abandonment, light abandonment, and water abandonment, the maintenance plan of multiple types of units such as traditional thermal power units, hydropower units, and pumped storage units is obtained, and the multi-type unit maintenance plan configuration is completed.

[0010] Preferably, the construction process of the multi-type unit maintenance plan configuration model based on the clustered unit combination is as follows:

[0011] A multi-type unit operation model is established, specifically: based on the actual operation of each unit of the power system, a clustered unit combination operation model of traditional thermal power units, a hydropower unit operation model, a pumped storage unit operation model, and a battery energy storage operation model are established;

[0012] A maintenance model of the unit to be maintained is established, specifically: based on the maintenance requirements of different types of units to be maintained, a thermal power unit maintenance model, a hydropower unit maintenance model, and a pumped storage unit maintenance model are established;

[0013] An economic optimization objective function is established, specifically, a target function of minimizing the operation cost of each type of unit, the maintenance cost of the unit to be maintained, and the penalty cost of loss of load, abandoned wind, abandoned light, and abandoned water is constructed based on the overall economic optimization objective of the power system.

[0014] A power system unit maintenance plan configuration model is established according to the multi-type unit operation model, the unit to be maintained maintenance model, and the economic optimization objective function.

[0015] Preferably, a traditional thermal power unit clustering unit combined operation model is established based on the actual operation of the thermal power unit of the power system, and the traditional thermal power unit clustering unit combined operation model is specifically:

[0016]

[0017] Wherein, t is the time number of the operation time; is the minimum technical output of the aggregated thermal power unit i at t time; is the output of the aggregated thermal power unit i at t time; is the online installed capacity of the aggregated thermal power unit i at t time; is the maximum output of the aggregated thermal power unit i at t time; is the ratio of the maximum start-up capacity to the installed capacity of the aggregated thermal power unit; is the ratio of the maximum upward ramping capacity to the installed capacity of the aggregated thermal power unit; is the ratio of the maximum shutdown capacity to the installed capacity of the aggregated thermal power unit; is the ratio of the maximum downward ramping capacity to the installed capacity of the aggregated thermal power unit;SU i,t is the installed capacity of the aggregated thermal power unit i started at t time;SD i,t is the installed capacity of the aggregated thermal power unit i shut down at t time;T i,on , T i,off are the minimum start-up and shutdown times of the aggregated thermal power unit i, respectively;

[0018] A hydroelectric unit operation model is established based on the actual operation of the hydroelectric unit of the power system, and the hydroelectric operation model is specifically:

[0019]

[0020] Wherein, are the minimum technical output and the maximum power upper limit of the hydroelectric unit i, respectively; is the real-time output of the hydroelectric unit i at t time; is the abandoned water power of the hydroelectric unit i at t time; is a state variable of the hydropower unit i at time t, and has a value of 1 indicating that the unit is in a start state, and has a value of 0 indicating that the unit is in a stop state; is the total power distribution of the hydropower unit i in the wth week; is the annual power of the hydropower unit i;

[0021] Preferably, based on the actual operation of the pumped storage unit of the power system, a pumped storage unit operation model is established, and the pumped storage unit operation model is specifically:

[0022]

[0023] wherein, is the actual pumping power of the pumped storage unit i at time t; is the actual pumping power of the pumped storage unit i at time t; is the maximum pumping power of the pumped storage unit i; is the maximum pumping power of the pumped storage unit i; is a pumping state variable of the pumped storage unit i at time t, and has a value of 1 indicating that the unit is in a pumping state, and has a value of 0 indicating that the unit is in a non-pumping state; is a power generation state variable of the pumped storage unit i at time t, and has a value of 1 indicating that the unit is in a power generation state, and has a value of 0 indicating that the unit is in a non-power generation state; is the upstream reservoir capacity of the pumped storage unit i at time t; is the lower limit of the upstream reservoir capacity of the pumped storage unit i; is the upper limit of the upstream reservoir capacity of the pumped storage unit i; is the downstream reservoir capacity of the pumped storage unit i at time t; is the lower limit of the downstream reservoir capacity of the pumped storage unit i; is the upper limit of the downstream reservoir capacity of the pumped storage unit i; PS,pump is the pumping efficiency of the pumped storage unit i; PS,dch is the power generation efficiency of the pumped storage unit i;

[0024] Preferably, based on the actual operation of the battery energy storage of the power system, a battery energy storage operation model is established, and the battery energy storage operation model is specifically:

[0025]

[0026] wherein, is the actual charging power of the battery energy storage i at time t; is the actual discharging power of the battery energy storage i at time t; is the maximum charging power of the battery energy storage i; is the maximum discharging power of the battery energy storage i; is a charging state variable of the battery energy storage i at time t, and a value of 1 indicates that the unit is in a charging state, and a value of 0 indicates that the unit is in a non-charging state; is a discharging state variable of the battery energy storage i at time t, and a value of 1 indicates that the unit is in a discharging state, and a value of 0 indicates that the unit is in a non-discharging state; is a battery capacity of the battery energy storage i at time t; is a minimum state of charge of the battery energy storage i; is a maximum state of charge of the battery energy storage i; η ES,cha is a charging efficiency of the battery energy storage i; η ES,dch is a discharging efficiency of the battery energy storage i;

[0027] Preferably, the maintenance requirements of different types of units to be maintained are established, and a thermal power unit, a hydropower unit and a pumped storage unit maintenance model is established, and the thermal power unit, the hydropower unit and the pumped storage unit maintenance model is:

[0028]

[0029] wherein w is a time number of a maintenance time, in units of weeks; z i,w is an action state variable of whether the maintenance of the power generating unit i at time w starts, a value of 1 indicates that the unit has an action of entering a maintenance state at time w, and a value of 0 indicates that the unit has no action of entering a maintenance state at time w; x i,w is a maintenance state variable of the power generating unit i at time w, a value of 1 indicates that the unit is in a maintenance state at time w, and a value of 0 indicates that the unit is in a normal operation state at time w; MN i is the number of times of maintenance of the power generating unit i in a year; MT i is the time required for each maintenance of the power generating unit i; MC TG is the number of conventional thermal power units in a maintenance state at each time; MC HS is the number of hydropower units in a maintenance state at each time; MC PS is the number of pumped storage units in a maintenance state at each time

[0030] Preferably, based on the overall economic optimization target of the power system, a target function of the lowest operation cost of each type of unit, the maintenance cost of the unit to be maintained and the penalty cost of loss of load, abandoned wind, abandoned light and abandoned water is constructed, and the economic target function is:

[0031] min C = C TG + C ES + C PS + C MA + C PEN

[0032]

[0033] wherein C is the total system economic cost in the given research period; C TG is the operation cost of traditional thermal power units in the given research period; CE S is the operation cost of battery energy storage in the given research period; C PS is the operation cost of pumped storage units in the given research period; C MA is the unit maintenance cost of traditional thermal power units; C PEN is the penalty cost of loss of load, curtailment of wind, curtailment of light, and curtailment of water in the given research period; is the unit operation cost of traditional thermal power units; is the start-up cost of traditional thermal power units; is the shut-down cost of traditional thermal power units; is the unit charging cost of battery energy storage; is the unit discharging cost of battery energy storage; is the unit pumping cost of pumped storage units; c L is the unit penalty cost of loss of load; c CW is the unit penalty cost of curtailment of wind; c CPV is the unit penalty cost of curtailment of light; c CH is the unit penalty cost of curtailment of water; ΔD i,t is the actual loss of load power of region i at time t; is the actual curtailment of wind power of wind turbine i at time t; is the actual curtailment of light power of photovoltaic turbine i at time t; is the actual curtailment of water power of hydropower turbine i at time t; c TG,main is the unit maintenance cost of traditional thermal power units; c PS,main is the unit maintenance cost of pumped storage units; c H,main is the unit maintenance cost of hydropower units;

[0034] A multi-type unit maintenance plan configuration system based on clustering unit combination, comprising:

[0035] A data acquisition unit, configured to acquire regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data, and wind and photovoltaic unit data of a target power system;

[0036] A data processing unit is configured to obtain a maintenance plan of multiple types of units according to the obtained regional load data, traditional unit data, hydroelectric unit data, pumped storage unit data, battery energy storage system data and wind and photovoltaic unit data, and in combination with a preset optimization model of multiple types of unit maintenance plan configuration based on a clustering unit combination, wherein an objective function of the optimization model aims to minimize operation cost of each type of unit, maintenance cost of a unit to be maintained and penalty cost of load loss, wind abandonment, light abandonment and water abandonment, to obtain a maintenance plan of multiple types of units such as traditional thermal power units, hydroelectric units and pumped storage units, and to complete configuration of the maintenance plan of the multiple types of units.

[0037] A terminal device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0038] A computer readable storage medium stores a computer program, wherein the computer program is executable by a processor to implement the steps of the above method.

[0039] Compared with the prior art, the present application has the following beneficial technical effects:

[0040] The application discloses a multi-type unit maintenance plan configuration method based on a polymerization unit combination, which first realizes comprehensive consideration of multiple types of units of a power system by acquiring comprehensive data including traditional units, hydroelectric units, pumped storage units, battery energy storage systems and wind and photovoltaic units, wherein the comprehensive consideration of the multi-type unit data helps to more accurately reflect the actual operation state of the power system, so that a more reasonable and comprehensive maintenance plan is formulated; in addition, the method can more effectively process a large amount of unit data and improve solving efficiency by constructing a multi-type unit maintenance plan configuration optimization model based on a clustering unit combination, meanwhile, the clustering unit combination helps to capture the similarity and difference between units, providing more valuable information for optimizing the maintenance plan; meanwhile, in the processing process, the objective function of the method aims to minimize the operation cost of each type of unit, the maintenance cost of the unit to be maintained and the penalty cost of loss of load, abandoned wind, abandoned light, abandoned water, which not only considers the economy of the unit, but also fully considers the reliability and environmental protection of the power system, and by minimizing these costs, the maintenance cost can be reduced while ensuring the stable operation of the power system, and the power loss and renewable energy waste caused by unit maintenance can be reduced, in combination with the comprehensive data and the optimization model, the method can comprehensively solve the maintenance plan of multiple types of units such as traditional thermal power units, hydroelectric units and pumped storage units, and the comprehensive solving method avoids the one-sidedness caused by the single type of unit in the traditional method, and by comprehensively considering the maintenance requirements of multiple types of units, the method can formulate a more coordinated and efficient maintenance plan, and improve the overall operation efficiency and reliability of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments, and it should be understood that the following drawings only show some embodiments of the present application, and should not be regarded as a limitation to the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0042] Figure 1 A flowchart of a multi-type unit maintenance plan configuration method based on a polymerization unit combination in the present application;

[0043] Figure 2 A distribution of annual hydroelectric power to each week in the present application;

[0044] Figure 3 The curve is configured for the maintenance plan of different types of units in the application;

[0045] Figure 4 The structural schematic diagram of the method for configuring the maintenance plan of multiple types of units based on the combination of aggregated units in the application is shown in the figure.

[0046] Figure 5 The structural schematic diagram of the method for configuring the maintenance plan of multiple types of units based on the combination of aggregated units in the application is shown in the figure. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the embodiments of the application clearer, the technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, rather than all the embodiments. The components of the embodiments of the application described and shown in the drawings can be arranged and designed in various different configurations.

[0048] Therefore, the following detailed description of the embodiments of the application provided in the drawings is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the application without creative labor are within the scope of protection of the application.

[0049] It should be noted that: similar reference numbers and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0050] In the description of the embodiments of the application, it should be noted that if the terms "upper", "lower", "horizontal", "inner" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship when the product of the application is usually placed, which is only for the convenience of describing the application and simplifying the description, and does not indicate or imply that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, therefore, it cannot be understood as a limitation on the application. In addition, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0051] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly inclined. For example, "horizontal" only means that its direction is relatively more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly inclined.

[0052] In the description of the embodiments of the present application, it also needs to be explained that, unless explicitly specified and limited, if the terms "set", "install", "connect", "connect" appear, they should be understood in a broad sense, for example, can be fixedly connected, can also be detachably connected, or integrally connected; can be mechanically connected, can also be electrically connected; can be directly connected, can also be indirectly connected through an intermediate medium, can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0053] The present application will be further described in detail below in combination with the drawings:

[0054] Embodiment 1

[0055] As Figure 1 shown, the multi-type unit maintenance plan configuration method framework based on the combination of the polymerization unit group of the present application is based on the input load, wind power photovoltaic, conventional thermal power unit, hydropower unit, pumped storage unit, battery energy storage data, considering the boundary conditions of the operation of each unit, taking the minimum total cost of the whole system operation and maintenance as the target, comprehensively considering the operation constraints of thermal power units, operation constraints of hydropower units, battery energy storage constraints, pumped storage unit constraints, power balance constraints, establishing a maintenance configuration optimization model, and finally obtaining the maintenance arrangement of thermal power, hydropower and pumped storage three types of units.

[0056] Specifically, first, the regional load data, conventional thermal power unit data, hydropower unit data, pumped storage unit data, battery energy storage system data and wind power photovoltaic unit data of the target power system are obtained;

[0057] The regional load data includes the partition situation of the target power system, the load data of each partition for 8760 hours in a year, the traditional thermal power unit data includes the installed capacity of the thermal power unit, the region to which each unit belongs, the upper and lower limits of the output of each unit, the minimum start-up and shut-down time of each unit, the maximum up and down ramping power of each unit, the start-up and shut-down cost of each unit, the cluster number to which each unit belongs, and the maintenance number, time and maximum simultaneous maintenance number of each unit; the hydropower unit data includes the installed capacity of the hydropower unit, the upper and lower limits of the output of each unit, the total annual power of each unit, and the maintenance number, time and maximum simultaneous maintenance number of each unit; the pumped storage unit data includes the installed capacity of the pumped storage unit, the upper and lower limits of the pumping and power generation output of each unit, the pumping and power generation efficiency of each unit, the upper and lower limits of the reservoir capacity of the upstream and downstream of each unit, and the maintenance number, time and maximum simultaneous maintenance number of each unit; the battery energy storage data includes the maximum and minimum charging power of each unit, the maximum and minimum discharging power of each unit, the charging and discharging efficiency of each unit, and the maximum and minimum state of charge of each unit; the wind and photovoltaic unit data, i.e. new energy data, includes the installed capacity of wind power and photovoltaic power, and the output standard value of the wind and photovoltaic unit for 8760 hours in a year.

[0058] Then, according to the obtained regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data and wind and photovoltaic unit data, and in combination with a preset multi-type unit maintenance plan configuration optimization model based on cluster unit combination, the target function of the optimization model aims to minimize the operation cost of each type of unit, the maintenance cost of the unit to be maintained, and the penalty cost of load loss, wind abandonment, light abandonment and water abandonment, to obtain the maintenance plan of the multi-type units such as traditional thermal power units, hydropower units and pumped storage units, and complete the configuration of the multi-type unit maintenance plan.

[0059] The construction process of the power system flexible resource planning model is as follows:

[0060] I. Based on the actual operation of each unit of the power system, a traditional thermal power unit cluster unit combination operation model, a hydropower unit operation model, a pumped storage unit operation model and a battery energy storage operation model are established.

[0061] The power output of the aggregated thermal power unit at each time is subject to the minimum technical output and the online installed capacity thereof; the state of the aggregated thermal power unit at each time is subject to the minimum start-up and shut-down time thereof, and a unit cannot be started up and shut down at the same time; the change in the output of the aggregated thermal power unit over time is subject to the climbing ability thereof; therefore, based on the actual operation of the thermal power unit of the power system, a traditional thermal power unit clustering unit commitment operation model is established, and the traditional thermal power unit clustering unit commitment operation model is specifically:

[0062]

[0063] wherein t is the time number of the operation time; is the minimum technical output of the aggregated thermal power unit i at the t time; is the output of the aggregated thermal power unit i at the t time; is the online installed capacity of the aggregated thermal power unit i at the t time; is the maximum output of the aggregated thermal power unit i at the t time; is the ratio of the maximum start-up capacity to the installed capacity of the aggregated thermal power unit; is the ratio of the maximum upward climbing capacity to the installed capacity of the aggregated thermal power unit; is the ratio of the maximum shut-down capacity to the installed capacity of the aggregated thermal power unit; is the ratio of the maximum downward climbing capacity to the installed capacity of the aggregated thermal power unit;SU i,t is the installed capacity of the aggregated thermal power unit i started at the t time;SD i,t is the installed capacity of the aggregated thermal power unit i shut down at the t time;T i,on , T i,off are the minimum start-up and shut-down times of the aggregated thermal power unit i, respectively;

[0064] The power output of the hydropower unit at each time is subject to the minimum technical output and the start-up state thereof, and the power generation of a unit per week is subject to the weekly electricity amount; the annual power generation of the hydropower unit is subject to the total power generation; the water abandonment amount per time needs to be positive; therefore, based on the actual operation of the hydropower unit of the power system, a hydropower unit operation model is established, and the hydropower operation model is specifically:

[0065]

[0066] wherein P i H,min , P i H,max are the minimum technical output and the maximum power upper limit of the hydropower unit i, respectively; is the real-time output of the hydropower unit i at the t time; is the abandoned water power of the hydropower unit i at time t; is the state variable of the hydropower unit i at time t, and the value of 1 indicates that the unit is in the start state, and the value of 0 indicates that the unit is in the stop state; is the total power distribution of the hydropower unit i in the wth week; W i H is the annual power of the hydropower unit i;

[0067] The pumping power of the pumped storage unit at each moment is limited by the maximum pumping power of the unit and the state thereof; the power generation of the pumped storage unit at each moment is limited by the maximum pumping power of the unit and the state thereof; the upstream and downstream reservoir capacities of the pumped storage unit at each moment are related to the upstream and downstream reservoir capacities of the previous moment and the pumping and power generation of the unit at each moment, and are limited by the maximum and minimum reservoir capacities; therefore, based on the actual operation of the pumped storage unit of the power system, a pumped storage unit operation model is established, and the pumped storage unit operation model is specifically:

[0068]

[0069] wherein, is the actual pumping power of the pumped storage unit i at time t; is the actual pumping power of the pumped storage unit i at time t; P i PS,pump,max is the maximum pumping power of the pumped storage unit i; P i PS,dch,max is the maximum pumping power of the pumped storage unit i; is the pumping state variable of the pumped storage unit i at time t, and the value of 1 indicates that the unit is in the pumping state, and the value of 0 indicates that the unit is in the non-pumping state; is the power generation state variable of the pumped storage unit i at time t, and the value of 1 indicates that the unit is in the power generation state, and the value of 0 indicates that the unit is in the non-power generation state; is the upstream reservoir capacity of the pumped storage unit i at time t; is the lower limit of the upstream reservoir capacity of the pumped storage unit i; is the upper limit of the upstream reservoir capacity of the pumped storage unit i; is the downstream reservoir capacity of the pumped storage unit i at time t; is the lower limit of the downstream reservoir capacity of the pumped storage unit i; is the upper limit of the downstream reservoir capacity of the pumped storage unit i; η PS,pump is the pumping efficiency of the pumped storage unit i; η PS,dch is the power generation efficiency of the pumped storage unit i;

[0070] A battery energy storage operation model is established based on actual operation of a battery energy storage system in a power system, and the battery energy storage operation model is specifically:

[0071]

[0072] wherein, is an actual charging power of the battery energy storage i at time t; is an actual discharging power of the battery energy storage i at time t; i ES,cha,max is a maximum charging power of the battery energy storage i; i ES,dch,max is a maximum discharging power of the battery energy storage i; is a charging state variable of the battery energy storage i at time t, and a value of 1 indicates that the unit is in a charging state, and a value of 0 indicates that the unit is in a non-charging state; is a discharging state variable of the battery energy storage i at time t, and a value of 1 indicates that the unit is in a discharging state, and a value of 0 indicates that the unit is in a non-discharging state; is a battery capacity of the battery energy storage i at time t; is a minimum state of charge of the battery energy storage i; is a maximum state of charge of the battery energy storage i; η ES,cha is a charging efficiency of the battery energy storage i; η ES,dch is a discharging efficiency of the battery energy storage i;

[0073] II. Based on the maintenance requirements of different types of units to be maintained, a thermal power unit, a hydroelectric unit and a pumped storage unit maintenance model is established;

[0074] Generally, the time scale of the maintenance plan (such as every day or every week) is usually different from the time scale of the unit operation scheduling (usually every hour). The established maintenance model is for the annual maintenance plan problem, and the maintenance time scale is usually set to every week. In addition, the model considers the annual maintenance of three different types of units, i.e., thermal power, hydroelectric and pumped storage. The maintenance configuration of each type of unit is limited by the number of maintenance times and the length of each maintenance; each type of unit is subject to the continuity constraint of maintenance, i.e., once the maintenance starts at a certain time, it needs to be continuously carried out until the required maintenance length is reached to stop, and the development of the maintenance work is limited by the maintenance resources, and generally multiple units cannot be maintained at the same time.

[0075]

[0076] wherein, w is the time number of the maintenance time, in weeks; z i,w is an action state variable of whether the power generating unit i is started at time w, a value of 1 indicates that the unit has an action of entering the maintenance state at time w, and a value of 0 indicates that the unit has no action of entering the maintenance state at time w; xi,w is the maintenance state variable of generator set i at time w, taking value 1 to indicate that the unit is in maintenance state at time w, and taking value 0 to indicate that the unit is in normal operation state at time w; MN i is the number of times of maintenance needed for generator set i in a year; MT i is the time needed for each maintenance of generator set i; MC TG is the number of conventional thermal power units in maintenance state at each time; MC HS is the number of hydropower units in maintenance state at each time; MC PS is the number of pumped storage units in maintenance state at each time;

[0077] III. Based on the overall economic optimality of the power system, a target function is constructed to minimize the operation cost of each type of unit, the maintenance cost of units to be maintained, and the penalty cost of loss of load, curtailment of wind, curtailment of light, and curtailment of water;

[0078] min C = C TG + C ES + C PS + C MA + C PEN

[0079]

[0080] wherein C is the overall economic cost of the system in the given research period; C TG is the operation cost of conventional thermal power units in the given research period; C ES is the operation cost of battery energy storage in the given research period; C PS is the operation cost of pumped storage units in the given research period; C MA is the unit maintenance cost in the given research period; C PEN is the penalty cost of loss of load, curtailment of wind, curtailment of light, and curtailment of water in the given research period; is the unit operation cost of conventional thermal power units; is the start-up cost of conventional thermal power units; is the shut-down cost of conventional thermal power units; is the unit charging cost of battery energy storage; is the unit discharging cost of battery energy storage; is the unit pumping cost of pumped storage units; c L is the unit penalty cost of loss of load; c CW is the unit penalty cost of curtailment of wind; c CPV is the unit penalty cost of curtailment of light; c CH is the unit penalty cost of curtailment of water; ΔD i,t is the actual loss of load power of region i at time t; is the actual wind power abandoned by the wind turbine i at time t; is the actual light power abandoned by the photovoltaic turbine i at time t; is the actual water power abandoned by the water turbine i at time t;c TG,main is the unit maintenance cost of the traditional thermal power unit;c PS,main is the unit maintenance cost of the pumped storage unit;c H,main is the unit maintenance cost of the water turbine;

[0081] Four, according to the traditional thermal power unit clustering unit combined operation model, the water turbine operation model, the pumped storage unit operation model, the battery energy storage operation model, the thermal power unit, the water turbine, the pumped storage unit maintenance model, and the operation cost of each type of unit, the maintenance cost of the unit to be maintained, and the penalty cost of the loss of load, the abandoned wind, the abandoned light, and the abandoned water, a multi-type unit maintenance plan configuration optimization model is established, and finally the annual maintenance arrangement of different types of units is obtained, and the multi-type unit maintenance plan configuration is completed. That is, based on the minimization of the total cost of the whole system operation, maintenance and penalty, considering the operation, maintenance and other constraints of each unit, a multi-type unit maintenance plan configuration optimization model is established, and finally the annual maintenance arrangement of different types of units is obtained.

[0082] The model constraints of the multi-type unit maintenance plan configuration also include:

[0083] Supply and demand balance constraints:

[0084]

[0085] Wherein, is the output of the i th thermal power unit, the output of the i th water turbine, the output of the i th wind turbine and the output of the i th photovoltaic turbine at time t respectively; is the abandoned water amount of the i th water turbine, the abandoned wind amount of the i th wind turbine and the abandoned light amount of the i th photovoltaic turbine at time t respectively; is the discharge power and charging power of the i th battery energy storage unit at time t respectively; is the power generation and pumping power of the i th pumped storage unit at time t respectively;D i,t is the load size of the i th region at time t;ΔD i,t is the load shedding size of the i th region at time t;

[0086] Wind power and photovoltaic related constraints:

[0087]

[0088] Further, the effectiveness of the model is verified by comparing the maintenance configuration model based on the traditional unit combination

[0089] On the basis of the current boundary conditions, the same load scale is maintained, and the basic unit combination model (BUC) and the aggregated unit combination model (CUC) are used for solving respectively. For the two models, the solving time and variable parameters in the solving process are obtained, as shown in Table 1. It can be found that compared with BUC, the number of binary variables in CUC is significantly reduced, the solving gap is reduced, and the solving speed is greatly accelerated

[0090] Table 1 Comparison of solving parameters of two models

[0091]

[0092] The distribution of the weekly power of the hydropower unit adopting the basic unit combination (BUC) model and the aggregated unit combination model (CUC) is shown in Figure 2 Obviously, the weekly distribution of the power of the annual regulation hydropower under different maintenance models is basically consistent, and is positively correlated with the maximum weekly load (see Figure 3 When the maximum weekly load is high, the hydropower will distribute more power in the week to achieve system power balance, and vice versa.

[0093] The configuration of the multi-type unit annual maintenance plan adopting the aggregated unit combination model (CUC) is shown in Figure 3 When the maximum weekly load is low, more maintenance capacity is usually arranged. On the contrary, in the weeks with high load peaks (when the system needs more units to be normally put into operation), the maintenance plan distributes less maintenance capacity.

[0094] Through the above description, the multi-type unit maintenance plan configuration method based on the aggregated unit combination proposed by the application can greatly accelerate the solving speed compared with the basic unit combination model under the premise of ensuring the solving accuracy, and can make reasonable maintenance arrangement strategy of the multi-type unit, and the effectiveness of the model is verified.

[0095] The application discloses a multi-type generator unit maintenance plan configuration method based on a cluster generator unit combination, and the method comprises the following steps: acquiring regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data and wind power photovoltaic unit data of a target power system; acquiring maintenance plans of traditional thermal power units, hydropower units, pumped storage units and other multi-type units according to the acquired regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data and wind power photovoltaic unit data, and combining a multi-type unit maintenance plan configuration optimization model based on a cluster unit combination, and completing the multi-type unit maintenance plan configuration. The unit maintenance plan configuration optimization model comprises a traditional thermal power unit, a hydropower unit, a pumped storage unit, a battery energy storage operation model and a maintenance model of a unit to be maintained. The multi-type unit maintenance configuration method considers the comprehensive of operation cost, maintenance cost and penalty cost, so as to ensure the reliable operation of the power system in the optimization period.

[0096] Embodiment 2

[0097] Reference Figure 4 , Figure 4 is a schematic diagram of a computer device in the embodiments of the application. In an embodiment, a computer device is provided, which can be a server, and the internal structure diagram of the computer device can be as shown in Figure 4 The computer device comprises a processor, a memory, a network interface and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The computer program is executed by the processor to implement the multi-type unit maintenance plan configuration method based on the cluster generator unit combination.

[0098] Embodiment 3

[0099] In addition, as shown in Figure 5 , the application further provides a multi-type unit maintenance plan configuration system based on a cluster generator unit combination, which comprises:

[0100] A data acquisition unit is configured to acquire regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data and wind power photovoltaic unit data of a target power system.

[0101] The data processing unit is used for obtaining the maintenance plan of the multiple types of units according to the obtained regional load data, traditional unit data, hydroelectric unit data, pumped storage unit data, battery energy storage system data and wind and photovoltaic unit data, and combining a preset multiple type unit maintenance plan configuration optimization model based on a cluster unit combination, wherein the objective function of the optimization model aims to minimize the operation cost of each type of unit, the maintenance cost of the unit to be maintained and the penalty cost of lost load, abandoned wind, abandoned light and abandoned water, obtains the maintenance plan of the multiple types of units such as traditional thermal power units, hydroelectric units and pumped storage units, and completes the configuration of the multiple type unit maintenance plan.

[0102] Further, an embodiment of the terminal device provided by the present application provides a schematic diagram of the terminal device. The terminal device of the embodiment comprises a processor, a memory and a computer program stored in the memory and executable on the processor. The processor implements the steps in each of the above method embodiments when executing the computer program. Alternatively, the processor implements the functions of each module / unit in each of the above device embodiments when executing the computer program.

[0103] The computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application.

[0104] The terminal device can be a desktop computer, a notebook computer, a palm computer and a cloud server, etc. The terminal device can include, but is not limited to, a processor and a memory.

[0105] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0106] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the terminal device by running or executing the computer program and / or modules stored in the memory, and calling the data stored in the memory.

[0107] The modules / units integrated in the terminal device, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0108] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for configuring maintenance plans for multiple types of units based on aggregated unit combinations, characterized in that: The following steps are involved: Obtaining input information; wherein the input information includes regional load data of the target power system, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data, and wind power and photovoltaic unit data; According to the acquired regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data, and wind power and photovoltaic unit data, and in combination with a preset multi-type unit maintenance plan configuration optimization model constructed based on clustering unit combination, wherein the objective function of the multi-type unit maintenance plan configuration optimization model constructed based on clustering unit combination takes the operating cost of each type of unit, the maintenance cost of the unit to be repaired, and the penalty cost of load loss, wind abandonment, solar abandonment, and water abandonment as the minimum, maintenance plans of multiple types of units such as traditional thermal power units, hydropower units, and pumped storage units are obtained, and the maintenance plan configuration of the multiple types of units is completed; The construction process of the multi-type unit maintenance plan configuration model based on clustering unit combination is as follows: Establish multi-type unit operation models. Specifically, based on the actual operation of each unit in the power system, establish a clustered unit combination operation model for traditional thermal power units, a hydropower unit operation model, a pumped storage unit operation model, and a battery energy storage operation model. Establish maintenance models for units to be overhauled. Specifically, based on the maintenance requirements of different types of units to be overhauled, establish maintenance models for thermal power units, hydropower units, and pumped storage units. Establish an economic optimization objective function. Specifically, based on the overall economic optimization goal of the power system, construct an objective function to minimize the operating costs of each type of unit, the maintenance costs of units awaiting maintenance, and the penalty costs for load loss, wind power curtailment, solar power curtailment, and hydropower curtailment. Establishing a power system unit maintenance plan configuration model based on the multi-type unit operation model, the maintenance model of the unit to be maintained, and the economic optimal objective function; According to the maintenance requirements of different types of units to be overhauled, the maintenance models of thermal power units, hydropower units and pumped storage units are established. The maintenance models of thermal power units, hydropower units and pumped storage units are as follows: in, w It is the time number of the maintenance time, in weeks; for w Time generator set i The action state variable of whether the maintenance has started, a value of 1 indicates that the unit is w There is an action of entering the maintenance state at any time. A value of 0 means the unit is in w There is no action to enter the maintenance state at any time; for w Time generator set i The maintenance status variable, a value of 1 indicates that the unit is w It is always in maintenance state. A value of 0 means the unit is w Always in normal operation; For generator sets i The number of times maintenance is required in a year; For generator sets i The time required for each maintenance; is the number of traditional thermal power units under maintenance at each moment; The number of hydropower units under maintenance at each moment; The number of pumped storage units under maintenance at each moment.

2. The method for configuring maintenance plans for multiple types of units based on aggregated unit combinations according to claim 1, characterized in that: Based on the actual operation of thermal power units in the power system, a clustered unit combination operation model of traditional thermal power units is established. The clustered unit combination operation model of traditional thermal power units is specifically as follows: in, t Number the moments of the run time; For aggregated thermal power units i exist t Minimum technical output of installed capacity online at all times; For aggregated thermal power units i exist t The effort of every moment; For aggregated thermal power units i exist t Always-on installed capacity; For aggregated thermal power units i exist t Maximum output at any moment; is the ratio of the maximum starting capacity to the installed capacity of the aggregated thermal power units; is the ratio of the maximum ramp-up capacity of the aggregated thermal power units to the installed capacity; is the ratio of the maximum shutdown capacity of the aggregated thermal power units to the installed capacity; is the ratio of the maximum downward ramping capacity of the aggregated thermal power units to the installed capacity; For aggregated thermal power units i exist t Installed capacity activated at any given time; For aggregated thermal power units i exist t The installed capacity that is shut down at all times; 、 Aggregate thermal power units i Minimum startup and shutdown times; Based on the actual operation of the hydropower units in the power system, a hydropower unit operation model is established. The hydropower operation model is specifically as follows: in, 、 Hydropower units i The minimum technical output and maximum power limit; for t Moment hydropower unit i Real-time output; for t Moment hydropower unit i of abandoned hydropower; for t Moment hydropower unit i The state variable of , a value of 1 indicates that the unit is in the on state, and a value of 0 indicates that the unit is in the off state; For the w Zhoushui power unit i Total electricity distribution; For hydropower units i of annual electricity consumption.

3. The method for configuring maintenance plans for multiple types of units based on aggregated unit combinations according to claim 1, characterized in that: Based on the actual operation of the pumped storage unit in the power system, a pumped storage unit operation model is established. The pumped storage unit operation model is specifically as follows: in, for t Pumped storage unit i The actual pumping power; for t Pumped storage unit i The actual pumping power; For pumped storage units i Maximum pumping power; For pumped storage units i Maximum pumping power; for t Pumped storage unit i The pumping state variable, a value of 1 indicates that the unit is in the pumping state, and a value of 0 indicates that the unit is in the non-pumping state; for t Pumped storage unit i The power generation state variable, a value of 1 indicates that the unit is in the power generation state, and a value of 0 indicates that the unit is in the non-power generation state; for t Pumped storage unit i upstream reservoir capacity; For pumped storage units i the lower limit of upstream reservoir capacity; For pumped storage units i the upper limit of upstream reservoir capacity; for t Pumped storage unit i downstream reservoir capacity; For pumped storage units i the lower limit of downstream reservoir capacity; For pumped storage units i the upper limit of downstream reservoir capacity; For pumped storage units i Pumping efficiency; For pumped storage units i power generation efficiency.

4. The method for configuring maintenance plans for multiple types of units based on aggregated unit combinations according to claim 1, characterized in that: Based on the actual operation of battery energy storage in the power system, a battery energy storage operation model is established. The battery energy storage operation model is specifically as follows: in, for t Battery energy storage at all times i The actual charging power; for t Battery energy storage at all times i The actual discharge power; Storing energy in batteries i Maximum charging power; Storing energy in batteries i Maximum discharge power; for t Battery energy storage at all times i The charging state variable, a value of 1 indicates that the unit is in a charging state, and a value of 0 indicates that the unit is in a non-charging state; for t Battery energy storage at all times i The discharge state variable, a value of 1 indicates that the unit is in the discharge state, and a value of 0 indicates that the unit is in the non-discharge state; for t Battery energy storage at all times i Battery capacity; Storing energy in batteries i The minimum state of charge; Storing energy in batteries i Maximum state of charge; Storing energy in batteries i Charging efficiency; Storing energy in batteries i discharge efficiency.

5. The method for configuring maintenance plans for multiple types of units based on aggregated unit combinations according to claim 1, characterized in that: Based on the overall economic optimization goal of the power system, an objective function is constructed to minimize the operating costs of various types of units, the maintenance costs of units to be repaired, and the penalty costs of load loss, wind power abandonment, solar power abandonment, and hydropower abandonment. The economic objective function is: in, C is the economic cost of the entire system during the given study period; is the operating cost of traditional thermal power units during the given study period; is the operating cost of battery energy storage during the given study period; is the operating cost of the pumped storage unit during the given study period; is the unit maintenance cost during the given study period; is the penalty cost for load loss, wind power curtailment, solar power curtailment, and water power curtailment during the given study period; is the unit operating cost of traditional thermal power units; The startup cost of traditional thermal power units; The shutdown cost of traditional thermal power units; Unit charging cost for battery energy storage; is the unit discharge cost of battery energy storage; is the unit pumping cost of the pumped storage unit; is the penalty cost per unit load loss; Penalty cost for unit wind curtailment; The penalty cost for unit abandonment of light; Penalty cost for unit water abandonment; for t Time zone i The actual load loss power; for t Moment wind turbines i The actual wind power curtailment for t Moment photovoltaic unit i The actual abandoned optical power; for t Moment hydropower unit i The actual water abandonment power; is the unit maintenance cost of traditional thermal power units; is the unit maintenance cost of the pumped storage unit; is the unit maintenance cost of the hydropower unit.

6. A multi-type unit maintenance plan configuration system based on clustering unit combination, characterized in that: A method for configuring a maintenance plan for multiple types of units based on an aggregated unit combination, for implementing any one of claims 1 to 5, comprising: A data acquisition unit, configured to acquire regional load data, conventional generator set data, hydropower generator set data, pumped storage generator set data, battery energy storage system data, and wind and photovoltaic generator set data of a target power system; A data processing unit is used to obtain maintenance plans for multiple types of units, such as traditional thermal power units, hydropower units, pumped storage units, battery energy storage system data, and wind power and photovoltaic unit data, based on the acquired regional load data, traditional unit data, hydropower unit data, pumped storage unit data, battery energy storage system data, and wind power and photovoltaic unit data, in combination with a preset multi-type unit maintenance plan configuration optimization model constructed based on clustering unit combinations, wherein the objective function of the optimization model is to minimize the operating cost of each type of unit, the maintenance cost of the unit to be repaired, and the penalty cost of load loss, wind abandonment, solar abandonment, and water abandonment, and complete the maintenance plan configuration of the multiple types of units.

7. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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