Plant optimal-operation-planning device

Abstract

The purpose of the present disclosure is to provide a plant optimal-operation-planning device for creating an optimal operation plan for a plant on the basis of an optimal cooling water temperature. The plant optimal-operation-planning device according to the present disclosure creates an optimal operation plan for a target plant (200) having plant constituent equipment arranged in a hierarchical configuration, and is provided with: a demand prediction unit (114) for predicting power demand and heat demand on the basis of plant operation data of the target plant (200) and weather data; a temperature search unit (116) for searching for an optimal cooling water temperature for the plant constituent equipment for the purpose of minimizing or maximizing the evaluation value of an evaluation function; and a planning unit (117) for creating an optimal operation plan which includes a start / stop state and an input / output energy schedule for each plant constituent equipment and which minimizes or maximizes the evaluation value of the evaluation function on the basis of the predicted power demand and heat demand, a device characteristic coefficient depending on the cooling water temperature for the plant constituent equipment, and the optimal cooling water temperature.

Description

Plant optimal operation planning system

[0001] The present disclosure relates to calculation of an optimal operation plan for a plant having hierarchically configured plant component equipment.

[0002] It is important to operate a plant in a way that reduces its energy costs. Therefore, research is being conducted on plant operation planning problems, which involve formulating plans for the start / stop states of plant components and input / output energy, with the aim of minimizing energy costs.

[0003] In plant components such as absorption chillers or turbo chillers that produce chilled water, the chilled water production efficiency changes depending on the cooling water temperature. Generally, lower cooling water temperatures tend to increase chilled water production efficiency. In the case of cooling tower systems, the cooling water temperature changes depending on the power consumption of the fan. Generally, increasing the fan's power consumption tends to decrease the cooling water temperature. In this way, changing the cooling water temperature changes the chilled water production efficiency and the fan's power consumption, so by setting the cooling water temperature appropriately, it is possible to expect to reduce energy costs.

[0004] Patent Literature 1 discloses an optimal operation system for an energy plant, which includes a cooling water temperature input means for inputting the cooling water temperature of the condenser of each turbine as a measured quantity or estimating it from the temperature of the cooling source, a correction amount calculation means for calculating a power output correction amount due to changes in condenser performance based on various process quantities of the energy plant and the condenser cooling water temperature, a model construction / update means for modeling the characteristics of each device constituting the energy plant based on the various process quantities of the energy plant and the power output correction amount to construct an equipment characteristic model, and an optimal operation solution calculation means for calculating an optimal operation solution for the boiler steam generation rate, steam allocation rate and extraction steam rate of each turbine of the energy plant based on the various process quantities of the energy plant, the power output correction amount and the equipment characteristic model. This optimal operation system for an energy plant explicitly incorporates the cooling water temperature, which affects turbine condenser performance, making it possible to construct a highly accurate equipment characteristic model and calculate a stable optimal operation solution.

[0005] Japanese Patent Application Laid-Open No. 2007-255198

[0006] Patent Document 1 describes a method that takes into account cooling water temperature characteristics by calculating a correction amount for energy output due to changes in equipment performance based on cooling water temperature using a measured or estimated value of cooling water temperature, which affects equipment performance. However, this method treats the cooling water temperature as a fixed value, and does not describe the creation of an operation plan based on an optimal cooling water temperature obtained by searching for a solution with the aim of maximizing or minimizing the evaluation value of an evaluation function. In other words, the method of Patent Document 1 cannot improve the production efficiency of chilled water and reduce energy costs by changing the cooling water temperature itself.

[0007] The technology disclosed herein has been made in consideration of the above circumstances, and aims to provide a plant optimal operation planning device that creates an optimal plant operation plan based on an optimal cooling water temperature.

[0008] The plant optimal operation planning device disclosed herein is a plant optimal operation planning device that creates an optimal operation plan for a target plant having hierarchically configured plant component equipment, and includes: a demand prediction unit that predicts power demand and heat demand based on plant operation data and weather data of the target plant; a temperature search unit that searches for an optimal cooling water temperature for the plant component equipment with the aim of minimizing or maximizing the evaluation value of an evaluation function; and a planning unit that creates an optimal operation plan including plans for start-up and shutdown states and input / output energy for each plant component equipment, based on the predicted power demand and heat demand, equipment characteristic coefficients that depend on the cooling water temperature of the plant component equipment, and the optimal cooling water temperature, so that the evaluation value of the evaluation function is minimized or maximized.

[0009] The present disclosure provides an optimal plant operation planning system that can generate an optimal operation plan for a target plant based on an optimal cooling water temperature. Objects, features, aspects, and advantages of the present disclosure will become more apparent from the following detailed description and the accompanying drawings.

[0010] Fig. 1 is a functional configuration diagram of a plant optimal operation planning device according to embodiment 1. Fig. 2 is a diagram showing an example of a target plant according to embodiment 1. Fig. 3 is a hardware configuration diagram of a plant optimal operation planning device according to embodiment 1. Fig. 4 is a flowchart showing the operation of the plant optimal operation planning device according to embodiment 1. Fig. 5 is a functional configuration diagram of a plant optimal operation planning device according to embodiment 2. Fig. 6 is a flowchart showing the operation of the plant optimal operation planning device according to embodiment 2.

[0011] Hereinafter, embodiments will be described with reference to the accompanying drawings. In the following embodiments, detailed features will be shown for the purpose of explaining the technology, but these are merely examples and are not necessarily essential features for enabling the embodiments to be implemented.

[0012] The drawings are schematic, and for the sake of convenience, components may be omitted or simplified as appropriate. Furthermore, the relative sizes and positions of components shown in different drawings are not necessarily accurately depicted and may be changed as appropriate.

[0013] In the following description, the same components are denoted by the same reference numerals, and their names and functions are also the same. Therefore, detailed descriptions of them may be omitted to avoid duplication.

[0014] Furthermore, in the description given in this specification, when a certain component is described as "comprising," "including," or "having," unless otherwise specified, this is not an exclusive expression that excludes the presence of other components.

[0015] <A. First Embodiment> <A-1. Target Plant> Fig. 2 shows an example of a target plant 200 that is a target of the optimal plant operation planning system according to the first embodiment. The target plant 200 will be described below with reference to Fig. 2.

[0016] The target plant 200 is configured to include, as plant constituent equipment, two boilers 241A and 241B, three absorption chillers 242A, 242B, and 242C, and two cooling towers 243A and 243B. In the following description, when there is no need to distinguish between the boiler 241A and the boiler 241B, they may be simply referred to as the boiler 241. The same applies to the absorption chillers 242A, 242B, and 242C and the cooling towers 243A and 243B. Note that there may be only one boiler 241, one absorption chiller 242, and one cooling tower 243. Furthermore, a boiler group in which multiple boilers 241 are regarded as one boiler, and a cooling tower group in which multiple cooling towers 243 are regarded as one cooling tower, are also plant constituent equipment.

[0017] The boiler 241 is a plant component that consumes fuel 221 to produce steam. The fuel 221 generates energy, such as city gas. The absorption chiller 242 is a plant component that consumes steam to produce chilled water. The cooling tower 243 is a plant component that releases heat from the cooling water into the atmosphere.

[0018] The target plant 200 supplies fuel 221 purchased from a gas utility to boilers 241A and 241B through a gas pipeline network. Steam produced by boilers 241A and 241B is supplied to a steam header 211. The steam header 211 supplies steam to a building or factory with steam demand 231 through a steam pipeline network. Steam is also supplied from the steam header 211 to absorption chillers 242A, 242B, and 242C. Chilled water produced by absorption chillers 242A, 242B, and 242C is supplied to a building or factory with chilled water demand 232 through a chilled water pipeline network. The steam demand 231 and chilled water demand 232 are referred to as heat demand. Heat generated when chilled water is produced by absorption chillers 242A, 242B, and 242C is discarded as cooling water. The cooling towers 243A and 243B rotate their fans to release heat from the cooling water into the atmosphere. To rotate the fans, electricity 222 purchased from a retail electricity supplier using the power network of a general electricity transmission and distribution company is required. Furthermore, the target plant 200 supplies the electricity 222 purchased from the retail electricity supplier to the power demand 233 of the building where the plant is located using the power network of the general electricity transmission and distribution company.

[0019] The target plant 200 hierarchically combines two types of plant constituent equipment, a boiler 241 and an absorption chiller 242, to produce energy, i.e., chilled water, from fuel 221. A plant that hierarchically combines two or more types of plant constituent equipment to produce one or more types of energy from fuel 221 in this way is referred to as a plant having hierarchically configured plant constituent equipment.

[0020] The operator of the target plant 200 (hereinafter referred to as the plant operator), who is a user of the plant optimal operation planning apparatus 101, is required to efficiently produce energy while maintaining the pressure or temperature specified in the supply specification. In order to maintain the pressure or temperature specified in the supply specification, it is necessary to control the start / stop states of the plant constituent devices, input / output energy, etc., in order to supply the steam heat quantity, chilled water heat quantity, and power that match the steam demand 231, chilled water demand 232, and power demand 233 from the target plant 200.

[0021] <A-2. Functional Configuration of the Plant Optimal Operation Planning Apparatus> Fig. 1 is a functional configuration diagram of a plant optimal operation planning apparatus 101 according to embodiment 1. An example of the functional configuration of the plant optimal operation planning apparatus 101 will be described below with reference to Fig. 1.

[0022] The plant optimal operation planning device 101 is configured to include an operation data input unit 111, an operation data storage unit 112, a weather data input unit 113, a demand forecasting unit 114, a coefficient storage unit 115, a temperature search unit 116, a planning unit 117, a plan output unit 118, and a data input / output unit 119.

[0023] The operation data input unit 111 acquires operation data (hereinafter referred to as "plant operation data") of the target plant 200. The plant operation data includes operation data for each plant component device, operation data measured on the sending side to a consumer with steam demand 231, operation data measured on the sending side to a consumer with chilled water demand 232, and operation data on the amount of power measured at a distribution board of a consumer with power demand 233. The operation data for each plant component device includes operation data on the fuel input amount, steam temperature, steam pressure, and steam flow rate for each plant component device of the boiler 241, operation data on the steam temperature, steam pressure, steam flow rate, chilled water temperature, chilled water flow rate, cooling water temperature, and cooling water flow rate for each plant component device of the absorption chiller 242, and operation data on the cooling water temperature, cooling water flow rate, and power consumption for each plant component device of the cooling tower 243. The operation data measured on the sending side to a consumer with steam demand 231 includes operation data on the steam temperature, steam pressure, and steam flow rate. The operational data measured on the sending side to the consumer having chilled water demand 232 includes operational data on chilled water temperature and chilled water flow rate.

[0024] The operation data input unit 111 calculates the steam calorific value, the chilled water calorific value, and the cooling water calorific value using the acquired plant operation data. The calculated steam calorific value, the chilled water calorific value, and the cooling water calorific value are part of the plant operation data.

[0025] The operation data storage unit 112 stores the plant operation data acquired or calculated by the operation data input unit 111 .

[0026] The weather data input unit 113 acquires weather data for the point closest to the building in which the target plant 200 is located. The weather data includes a predicted air temperature value or a predicted outside air wet-bulb temperature value.

[0027] The demand forecasting unit 114 uses the plant operation data stored in the operation data storage unit 112 and the weather data acquired by the weather data input unit 113 to forecast steam demand 231, chilled water demand 232, or electricity demand 233 for the planning period and calculates it as a demand forecast value.

[0028] The coefficient storage unit 115 stores the equipment characteristic coefficients of the plant constituent equipment. The equipment characteristic coefficients of the plant constituent equipment include an equipment characteristic coefficient of a boiler group in which the boiler 241A and the boiler 241B are regarded as one boiler, an equipment characteristic coefficient for each plant constituent equipment of the absorption chiller 242 that depends on the cooling water temperature, and an equipment characteristic coefficient of a cooling tower group in which the cooling tower 243A and the cooling tower 243B are regarded as one cooling tower that depends on the cooling water temperature and the outside air wet-bulb temperature.

[0029] When the equipment characteristics of the boiler group are expressed by a linear function, the equipment characteristic coefficients of the boiler group are the slope and intercept of the linear function.

[0030] The equipment characteristic coefficients for each plant component equipment of the absorption chiller 242 that depends on the cooling water temperature are equipment characteristic coefficients expressed by transient equipment characteristics and steady-state equipment characteristics that depend on the cooling water temperature. When the transient equipment characteristics are expressed by a first-order lag system, the time constant is the equipment characteristic coefficient. When the steady-state equipment characteristics that depend on the cooling water temperature are expressed by a linear function and a cooling water temperature characteristic gain based on the cooling water reference temperature, the slope and intercept, the cooling water reference temperature, and the cooling water temperature characteristic are the equipment characteristic coefficients. When the steady-state equipment characteristics that depend on the cooling water temperature are expressed by a convex piecewise linear function and a cooling water temperature characteristic gain based on the cooling water reference temperature, the slope and intercept of each section, the cooling water reference temperature, and the cooling water temperature characteristic are the equipment characteristic coefficients.

[0031] The equipment characteristic coefficients that depend on the cooling water temperature and outside air wet-bulb temperature of a cooling tower group are, when the equipment characteristics are expressed by a linear function and a cooling water temperature characteristic gain based on the cooling water reference temperature and an outside air wet-bulb temperature characteristic gain based on the outside air wet-bulb reference temperature, the slope and intercept, the cooling water reference temperature, the cooling water temperature characteristic, the outside air wet-bulb reference temperature, and the outside air wet-bulb temperature characteristic are the equipment characteristic coefficients.

[0032] The temperature search unit 116 acquires operational constraints related to the cooling water temperature and searches for an optimal cooling water temperature that minimizes the evaluation value of an evaluation function, such as energy cost. The operational constraints related to the cooling water temperature include a limit on the rate of change of the cooling water temperature, upper and lower limits of the cooling water temperature from the perspective of protecting plant component equipment, or the number of significant digits of the cooling water temperature. The cooling water temperature is the cooling water temperature in units of time used by the plant operator to manage the operation of the target plant 200. The unit of time used to manage the operation of the target plant 200 is, for example, 30 minutes. The temperature search unit 116 searches for an optimal cooling water temperature that satisfies the operational constraints related to the cooling water temperature and is within a range of a lower limit of the cooling water temperature that depends on the outside air wet-bulb temperature. The temperature search unit 116 uses metaheuristics such as a local search method or Tabu search, or an expert system constructed based on the knowledge of the target plant operator, to search for the optimal cooling water temperature that minimizes the evaluation value of the evaluation function.

[0033] The planning unit 117 creates an operation plan for the target plant 200 based on the demand forecast values ​​for the planning period predicted by the demand forecasting unit 114, the equipment characteristic coefficients of the plant constituent equipment read from the coefficient storage unit 115, the optimal cooling water temperature read from the temperature search unit 116, and the set values ​​of the operational constraints of the plant constituent equipment. The demand forecast values ​​for the planning period include steam demand 231, chilled water demand 232, and electricity demand 233. The set values ​​of the operational constraints of the plant constituent equipment are set to take into account operational constraints such as equipment capacity constraints, minimum operation time constraints, or minimum shutdown time constraints of the plant constituent equipment, and include upper and lower limit values ​​of the heat quantity, upper and lower limit values ​​of the flow rate, and minimum operation time or minimum shutdown time of the plant constituent equipment. The planning unit 117 creates an operation plan for the target plant 200 that minimizes the evaluation value of a predetermined evaluation function such as energy cost while satisfying the operational constraints of the plant constituent equipment. This operation plan includes the start / stop status of each plant component of the absorption chiller 242, the fuel input amount and steam heat quantity of the boiler group, the steam heat quantity, chilled water heat quantity, chilled water flow rate and cooling water heat quantity of each plant component of the absorption chiller 242, and input / output energy such as cooling water heat quantity and power consumption of the cooling tower group.

[0034] The plan output unit 118 creates a stacked graph or a line graph that represents the operation plan based on the operation plan for the target plant 200 created by the planning unit 117.

[0035] The data input / output unit 119 receives equipment characteristic coefficients of the plant constituent equipment stored in the coefficient storage unit 115. These equipment characteristic coefficients are set by the plant operator. The data input / output unit 119 also receives set values ​​of operational constraint conditions related to cooling water temperature. These set values ​​are taken into consideration by the temperature search unit 116. The data input / output unit 119 also receives set values ​​of operational constraint conditions of the plant constituent equipment. These set values ​​are set by the plant operator and taken into consideration by the planner 117. The data input / output unit 119 also displays a stacked graph or a line graph representing the operation plan created by the plan output unit 118 to the operator of the target plant.

[0036] One optimal plant operation planning device 101 is installed for one target plant 200. The optimal plant operation planning device 101 is installed in a room where a plant operator is present, for example, an operation room in the building where the target plant 200 is located.

[0037] The above is a description of an example of the functional configuration of the optimal plant operation planning device 101.

[0038] <A-3. Hardware Configuration of the Plant Optimal Operation Planning Apparatus> Fig. 3 is a hardware configuration diagram of the plant optimal operation planning apparatus 101. An example of the hardware configuration of the plant optimal operation planning apparatus 101 will be described below with reference to Fig. 3.

[0039] The plant optimal operation planning apparatus 101 includes an input device 301, an output device 302, a CPU (Central Processing Unit) 303, a main storage device 304, a secondary storage device 305, and a communication device 306. The communication device 306 is used to connect the plant optimal operation planning apparatus 101 to a communication network 307. The CPU 303, the main storage device 304, and the secondary storage device 305 are examples of processing circuits.

[0040] The data input / output unit 119 in Fig. 1 is realized by the input device 301 and the output device 302. The operation data storage unit 112 and the coefficient storage unit 115 in Fig. 1 are realized by the main storage unit 304 or the secondary storage unit 305. The demand forecasting unit 114, the temperature search unit 116, the planner 117, and the plan output unit 118 in Fig. 1 are realized by the CPU 303 executing software programs stored in the main storage unit 304 or the secondary storage unit 305. In Fig. 1, the operation data input unit 111 that acquires information from the target plant 200 and the weather data input unit 113 that acquires weather data necessary for demand forecasting are realized by the communication device 306.

[0041] The above is an example of the hardware configuration of the optimal plant operation planning device 101.

[0042] <A-4. Operation of the optimal plant operation planning device> Fig. 4 is a flowchart showing the calculation process of the optimal plant operation planning device 101. The calculation process of the optimal plant operation planning device 101 will be described below with reference to Fig. 4.

[0043] The plant optimal operation planning device 101 is started up at a certain fixed time, such as 6:00 every day, and starts executing the calculation process shown in FIG. 4 at that timing. The plant optimal operation planning device 101 predicts power demand and heat demand in step S101. Next, the plant optimal operation planning device 101 acquires plant component equipment characteristic coefficients in step S102. Thereafter, the plant optimal operation planning device 101 searches for the cooling water temperature in step S103. Next, the plant optimal operation planning device 101 formulates an optimal operation plan in step S104. Thereafter, the plant optimal operation planning device 101 displays the calculation results in step S105.

[0044] (Step S101 in FIG. 4: Prediction of power demand and heat demand) The operation data input unit 111 calculates the steam calorific value, chilled water calorific value, and cooling water calorific value using the acquired operation data of the target plant 200. The operation data input unit 111 calculates the effective heat drop from the steam temperature and steam pressure, and further calculates the steam calorific value from the effective heat drop and steam flow rate. The operation data input unit 111 calculates the chilled water calorific value using the chilled water temperature, chilled water flow rate, and specific heat. The operation data input unit 111 calculates the cooling water calorific value using the cooling water temperature, cooling water flow rate, and specific heat. The operation data of the target plant 200 acquired by the operation data input unit 111 and the steam calorific value, chilled water calorific value, and cooling water calorific value calculated by the operation data input unit 111 are stored as plant operation data in the operation data storage unit 112.

[0045] The demand forecasting unit 114 uses the date and day of the week of the target schedule to search the plant operation data stored in the operation data storage unit 112 for a similar date that is close to the target schedule date and that matches the day of the week. The demand forecasting unit 114 then constructs regression models for steam demand 231, chilled water demand 232, and electricity demand 233 using the plant operation data for the similar date and actual values ​​of meteorological data, such as actual air temperature or actual outdoor wet-bulb temperature. The demand forecasting unit 114 then obtains a predicted value for steam demand 231 using the constructed regression model for steam demand 231 and meteorological data acquired by the meteorological data input unit 113. The demand forecasting unit 114 also obtains a predicted value for chilled water demand 232 using the constructed regression model for chilled water demand 232 and meteorological data acquired by the meteorological data input unit 113. The demand forecasting unit 114 also obtains a predicted value for electricity demand 233 using the constructed regression model for electricity demand 233 and meteorological data acquired by the meteorological data input unit 113.

[0046] (Step S102 in FIG. 4: Acquisition of Plant Constituent Equipment Characteristic Coefficients) The planner 117 acquires the equipment characteristic coefficients of the plant constituent equipment stored in the coefficient storage unit 115.

[0047] [Obtaining Equipment Characteristic Coefficients of Boiler Group] Equation (1) is an equation expressing the equipment characteristics of a boiler group in which the boiler 241A and the boiler 241B are regarded as one boiler.

[0048]

[0049] Note that t∈Tm. Tm is a set of times obtained by dividing the planning period into 30-minute intervals, which are time units used by the plant operator to manage the operation of the target plant 200, and numbering the times consecutively, starting with 1 as the initial time of the planning period. ｔ represents the amount of steam heat [GJ / h] produced by the boiler group. ｔ is the fuel input of the boiler group [m ３ / h]. ｔ is a binary value representing the activation / deactivation state of the boiler group, with 1 representing the activation state and 0 representing the deactivation state. HA_B is the slope of the equipment characteristic of the boiler group, and HB_B is the intercept of the equipment characteristic of the boiler group.

[0050] The equipment characteristic coefficients of the boiler group stored in the coefficient storage unit 115 are the slope HA_B of the equipment characteristic of the boiler group and the intercept HB_B of the equipment characteristic of the boiler group. Acquiring the equipment characteristic coefficients of the boiler group stored in the coefficient storage unit 115 means acquiring the slope HA_B of the equipment characteristic of the boiler group and the intercept HB_B of the equipment characteristic of the boiler group.

[0051] [Obtaining Equipment Characteristic Coefficients of Absorption Chiller 242] Equations (2) to (6) are equations expressing equipment characteristics that depend on the cooling water temperature for each of the plant constituent equipment of the absorption chiller 242. Equation (2) is an equation expressing steady-state equipment characteristics that depend on the cooling water temperature.

[0052]

[0053] Note that a∈AR, and AR is a set of absorption refrigerators 242. ａ，ｔ represents the steady-state component [GJ / h] of the heat amount of chilled water produced by the absorption chiller 242. ａ，ｔ represents the amount of steam heat [GJ / h] consumed by the absorption refrigerator 242. ａ，ｔ is a binary value representing the activation / deactivation state of the absorption chiller 242, where 1 represents the activation state and 0 represents the deactivation state. ａ，ｔ is the cooling water temperature characteristic gain, G ａ () is a piecewise linear function.

[0054] Equation (3) is an equation that expresses the transient device characteristics as a first-order lag system.

[0055]

[0056] In addition, cw_ar ａ，ｔ represents the amount of heat [GJ / h] of chilled water produced by the absorption chiller 242, and T_AR ａ represents the time constant [s].

[0057] Equation (4) is a calculation formula for the coolant temperature characteristic gain.

[0058]

[0059] In addition, T_CDW ｔ represents the cooling water temperature [°C], and T_CDWZ_AR ａ represents the cooling water reference temperature [°C], and C_CDW_AR ａ represents the cooling water temperature characteristic [% / °C].

[0060] Equations (5) and (6) are equations that express a convex piecewise linear function with N intervals.

[0061]

[0062]

[0063] In addition, s_ar ａ，ｔ，ｋ represents the steam heat quantity [GJ / h] consumed by the absorption chiller 242 in section k, and GA_AR ａ，ｋ represents the slope of the equipment characteristic of the absorption chiller 242 in section k, and GB_AR ａ represents the intercept of the equipment characteristic of the absorption refrigerator 242.

[0064] The equipment characteristic coefficient for each plant component equipment of the absorption chiller 242 that depends on the cooling water temperature and is stored in the coefficient storage unit 115 is the gradient GA_AR of the equipment characteristic of the absorption chiller 242 in the section k. ａ，ｋ , the intercept GB_AR of the equipment characteristic of the absorption refrigerator 242 ａ , time constant T_AR ａ , cooling water reference temperature T_CDWZ_AR ａ , and the coolant temperature characteristic C_CDW_AR ａThe acquisition of the equipment characteristic coefficient for each plant component of the absorption chiller 242 that depends on the cooling water temperature and is stored in the coefficient storage unit 115 is performed by calculating the slope GA_AR of the equipment characteristic of the absorption chiller 242 in the section k. ａ，ｋ and the intercept GB_AR of the equipment characteristic of the absorption refrigerator 242 ａ , time constant T_AR ａ , cooling water reference temperature T_CDWZ_AR ａ , and the coolant temperature characteristic C_CDW_AR ａ The goal is to obtain

[0065] [Obtaining Equipment Characteristic Coefficients for Cooling Tower Group] Equations (7) to (10) are equations that express the equipment characteristics of the cooling tower group when cooling tower 243A and cooling tower 243B are considered as one cooling tower. The equipment characteristics of the cooling tower group are expressed by a linear function, a cooling water temperature characteristic gain based on the cooling water reference temperature, and an outside air wet-bulb temperature characteristic gain based on the outside air wet-bulb reference temperature.

[0066] Equation (7) expresses the equipment characteristics that depend on the cooling water temperature and the outside air wet-bulb temperature of the cooling tower group.

[0067]

[0068] In addition, e_ct ｔ is the fan power consumption [kW] of the cooling tower group. ｔ is the amount of cooling water heat released to the atmosphere [GJ / h]. FA_CT is the slope of the equipment characteristics of the cooling tower group. FB_CT is the intercept of the equipment characteristics of the cooling tower group. K_CDW_CT ｔ is the coolant temperature characteristic gain. ｔ is the outside air wet-bulb temperature characteristic gain.

[0069] Equation (8) is a calculation formula for the coolant temperature characteristic gain.

[0070]

[0071] Note that T_CDWZ_CT is the reference coolant temperature [°C], and C_CDW_CT is the coolant temperature characteristic [% / °C].

[0072] Equation (9) is a calculation formula for the outside air wet-bulb temperature characteristic gain.

[0073]

[0074] In addition, T_WB ｔ is the outside air wet-bulb temperature [°C]. T_WBZ_CT is the outside air wet-bulb reference temperature [°C]. C_WB_CT is the outside air wet-bulb temperature characteristic [% / °C].

[0075] Equation (10) is a formula for calculating the amount of heat of the cooling water released into the atmosphere.

[0076]

[0077] The equipment characteristic coefficients dependent on the cooling water temperature and the outside air wet-bulb temperature of the cooling tower group stored in the coefficient storage unit 115 are the slope of the equipment characteristic of the cooling tower group FA_CT, the intercept of the equipment characteristic of the cooling tower group FB_CT, the cooling water reference temperature T_CDWZ_CT, the cooling water temperature characteristic C_CDW_CT, the outside air wet-bulb reference temperature T_WBZ_CT, and the outside air wet-bulb temperature characteristic C_WB_CT. Acquiring the equipment characteristic coefficients dependent on the cooling water temperature and the outside air wet-bulb temperature of the cooling tower group stored in the coefficient storage unit 115 means acquiring the slope of the equipment characteristic of the cooling tower group FA_CT, the intercept of the equipment characteristic of the cooling tower group FB_CT, the cooling water reference temperature T_CDWZ_CT, the cooling water temperature characteristic C_CDW_CT, the outside air wet-bulb reference temperature T_WBZ_CT, and the outside air wet-bulb temperature characteristic C_WB_CT.

[0078] (S103 in FIG. 4: Search for Cooling Water Temperature) The temperature search unit 116 acquires operational constraints related to the cooling water temperature. The operational constraints related to the cooling water temperature include a limit on the rate of change of the cooling water temperature as shown in Equation (11), an upper and lower limit range of the cooling water temperature from the viewpoint of protecting the plant component equipment, such as 24° C. to 32° C., or the number of significant digits of the cooling water temperature, such as two digits.

[0079]

[0080] In addition, RR_T_CDW ｔ is the limit of the rate of change of the cooling water temperature.

[0081] The temperature search unit 116 uses a local search method, which is one of metaheuristics, to search for an optimal cooling water temperature that minimizes the evaluation value of an evaluation function such as energy cost.

[0082] An example of searching for the optimal cooling water temperature using the local search method is shown below.

[0083] In step 1, the temperature search unit 116 calculates the lower limit of the cooling water temperature, which depends on the outside air wet-bulb temperature. The calculation formula for the lower limit of the cooling water temperature is shown in Equation (12).

[0084]

[0085] In addition, T_CDW_LB ｔ is the lower limit of the cooling water temperature [°C]. T_AP is the lower limit of the approach temperature [°C]. The approach temperature is the difference between the outside air wet-bulb temperature and the cooling water temperature, and its lower limit is determined by the cooling tower capacity.

[0086] In step 2, the temperature search unit 116 sets k=0 and finds an initial solution T_CDW of the cooling water temperature that satisfies the operational constraints on the cooling water temperature and the range of the cooling water temperature lower limit that depends on the outside air wet-bulb temperature. ｔ （ｋ） is generated and the evaluation value Z(T_CDW ｔ （ｋ） ) is calculated.

[0087] In step 3, the temperature search unit 116 generates a set N(T_CDW) of neighborhood solutions that satisfy the operational constraints on the cooling water temperature and the range of the cooling water temperature lower limit that depends on the outside air wet-bulb temperature, according to a predefined neighborhood generation rule. ｔ （ｋ） The temperature search unit 116 generates a neighborhood solution T_CDW ｔ （ｋ） ∈N(T_CDW ｔ （ｋ） ) evaluation value Z(T_CDW ｔ ) and calculate {T_CDW ｔ ∈N(T_CDW ｔ （ｋ） ) | Z (T_CDW ｔ ) ∈ Z(T_CDW ｔ （ｋ） ) ≠ {}, then T_CDW ｔ（ｋ） The optimum coolant temperature T_CDW ｔ ＊ The search is terminated as follows. ｔ ∈N(T_CDW ｔ （ｋ） ) | Z (T_CDW ｔ ) ∈ Z(T_CDW ｔ （ｋ） )}≠{}, the temperature search unit 116 finds an improved solution T_CDW ｔ （ｋ＋１） ∈{T_CDW ｔ ∈N(T_CDW ｔ （ｋ） ) | Z (T_CDW ｔ ) ∈ Z(T_CDW ｔ （ｋ） )}. Then, the temperature search unit 116 sets k=k+1, returns to step 3, and continues the search.

[0088] In the above, the temperature search unit 116 uses a local search method, which is a metaheuristic, to search for the optimal cooling water temperature, but the optimal cooling water temperature may also be searched for using an expert system constructed based on the knowledge of the plant operator.

[0089] An example of searching for the optimum cooling water temperature using an expert system is shown below.

[0090] In step 1, the temperature search unit 116 calculates the average value T_CDW_AVE of the outside air wet-bulb temperature [° C.] for the planning period.

[0091] In step 2, the temperature search unit 116 calculates a set of candidate solutions for the cooling water temperature T_CDW based on the calculated average value of the outside air wet-bulb temperature T_CDW_AVE. ｔ ∈N(T_CDW_AVE). The candidate solutions for the cooling water temperature generated at this time are generated according to a rule based on the knowledge of the plant operator, such as "if the average value of the outside air wet-bulb temperature is low, it is better to set the cooling water temperature lower."

[0092] In step 3, the temperature search unit 116 calculates the candidate solution T_CDW of the coolant temperature. ｔ ∈N(T_CDW_AVE) evaluation value Z(T_CDW ｔ) is calculated, and the candidate solution for the coolant temperature with the smallest evaluation value is the optimal coolant temperature T_CDW ｔ ＊ Let's say.

[0093] The planning unit 117 calculates the demand forecast value predicted by the demand forecasting unit 114, the equipment characteristic coefficients of the plant constituent equipment read from the coefficient storage unit 115, and the neighborhood solution T_CDW read from the temperature search unit 116. ｔ ∈N(T_CDW ｔ （ｋ） ) or a set of candidate solutions for the coolant temperature T_CDW ｔ ∈N(T_CDW_AVE) and the set values ​​of the operational constraints of the plant constituent equipment, an operation plan for the target plant 200 is created that minimizes the evaluation value of a predetermined evaluation function such as energy cost while satisfying the operational constraints, and the evaluation value of the evaluation function obtained at this time is designated as evaluation value Z(T_CDW ｔ )

[0094] (S104 in FIG. 4: Formulation of optimal operation plan) The planner 117 forms an operation plan for the target plant 200 that minimizes the evaluation value of a predetermined evaluation function such as energy cost while satisfying the operational constraints, based on the demand forecast value for the planning period predicted by the demand forecaster 114, the equipment characteristic coefficients of the plant constituent equipment read from the coefficient memory unit 115, the optimal cooling water temperature read from the temperature search unit 116, and the setting values ​​of the operational constraints of the plant constituent equipment. Note that the planner 117 is not limited to the operation plan that minimizes the evaluation value of the evaluation function, and may form an operation plan that maximizes the evaluation value of an evaluation function in which the evaluation value increases as the evaluation value increases.

[0095] (S105 in FIG. 4: Display of plan results) The plan output unit 118 creates a stacked graph or a line graph representing the operation plan formulated by the planner 117. The data input / output unit 119 displays the stacked graph or the line graph representing the operation plan created by the plan output unit 118 to the plant operator.

[0096] The plant operator checks the stacked graph or line graph representing the operation plan, and increases or decreases the power consumption of the fan to change the cooling water temperature, or controls the start / stop status and input / output energy of the plant component equipment, in order to supply the steam heat quantity, chilled water heat quantity, or electricity that matches the steam demand 231, chilled water demand 232, or electricity demand 233 from the target plant 200.

[0097] <A-5. Effects> The plant optimal operation planning device 101 according to the first embodiment creates an optimal operation plan for a target plant 200 having hierarchically configured plant constituent equipment. The plant optimal operation planning device 101 includes a demand forecasting unit 114 that forecasts power demand and heat demand based on plant operation data and weather data for the target plant 200, a temperature search unit 116 that searches for optimal cooling water temperatures for the plant constituent equipment so as to minimize or maximize the evaluation value of an evaluation function, and a planning unit 117 that creates an optimal operation plan including plans for start / stop states and input / output energy for each plant constituent equipment, so as to minimize or maximize the evaluation value of the evaluation function, based on the predicted power demand and heat demand, equipment characteristic coefficients that depend on the cooling water temperatures of the plant constituent equipment, and the optimal cooling water temperature. With the above configuration, the plant optimal operation planning device 101 enables the creation of an operation plan based on the optimal cooling water temperature, and by increasing or decreasing the power consumption of the fan to change the cooling water temperature to the optimal value, it is possible to improve the efficiency of chilled water production and reduce energy costs.

[0098] <B. Second Embodiment> <B-1. Functional Configuration of a Plant Optimal Operation Planning Apparatus> Fig. 5 is a diagram showing an example of the functional configuration of a plant optimal operation planning apparatus 102 according to a second embodiment. The functional configuration of the plant optimal operation planning apparatus 102 will be described below with reference to Fig. 5. In the following description, components similar to those described in the first embodiment are denoted by the same reference numerals, and detailed description thereof will be omitted as appropriate.

[0099] The optimal plant operation planning device 102 has a configuration in which a temperature storage unit 121 is added to the functional components of the optimal plant operation planning device 101 according to the first embodiment.

[0100] The temperature storage unit 121 stores candidates for the cooling water temperature input by the plant operator.

[0101] The temperature search unit 116 acquires operational constraints on the coolant temperature and candidate coolant temperatures stored in the temperature storage unit 121, and searches for an optimal coolant temperature that minimizes the evaluation value of an evaluation function such as energy cost. This optimal coolant temperature is searched for from among the candidates for coolant temperature stored in the temperature storage unit 121, within a range of coolant temperature lower limit values ​​that satisfy the operational constraints on the coolant temperature and that depend on the outside air wet-bulb temperature.

[0102] The data input / output unit 119 receives candidates for the cooling water temperature input by the plant operator in addition to the processing described in the first embodiment. The candidates for the cooling water temperature are stored in the temperature storage unit 121.

[0103] The above is a description of an example of the functional configuration of the optimal plant operation planning device 102.

[0104] <B-2. Hardware Configuration of the Plant Optimal Operation Planning Apparatus> The hardware configuration of the plant optimal operation planning apparatus 102 is as shown in Fig. 3. The temperature storage unit 121 in Fig. 5 is realized by the main storage device 304 or the secondary storage device 305. The hardware configuration of the other functional components of the plant optimal operation planning apparatus 102 is as described in the first embodiment.

[0105] <B-3. Operation> Fig. 6 is a flowchart showing the calculation process of the optimal plant operation planning system 102. The flow in Fig. 6 is obtained by adding step S201 between step S102 and step S103 in the flow in Fig. 4 described in the first embodiment.

[0106] Steps S101 and S102 are the same as those described in the first embodiment.

[0107] After step S102, in step S201, the temperature search unit 116 acquires candidates for the coolant temperature stored in the temperature storage unit 121.

[0108] After step S201, in step S103, the temperature search unit 116 searches for an optimal coolant temperature that minimizes the evaluation value of an evaluation function such as energy cost, based on operational constraints related to the coolant temperature and candidate coolant temperatures. An example of searching for an optimal coolant temperature that minimizes the evaluation value of an evaluation function such as energy cost is shown below.

[0109] As a procedure, the temperature search unit 116 searches for a candidate coolant temperature T_CDW ｔ ∈CAND_T_CDW evaluation value Z(T_CDW ｔ ) is calculated, and the candidate coolant temperature with the smallest evaluation value is selected as the optimal coolant temperature T_CDW ｔ ＊ It should be noted that CAND_T_CDW is a set of candidates for the coolant temperature.

[0110] The planning unit 117 calculates the demand forecast value for the planning period predicted by the demand forecasting unit 114, the equipment characteristic coefficients of the plant constituent equipment read from the coefficient storage unit 115, and the candidate cooling water temperature T_CDW read from the temperature storage unit 121. ｔ ∈CAND_T_CDW and the set values ​​of the operational constraints of the plant constituent equipment, an operation plan for the target plant 200 is created that minimizes the evaluation value of a predetermined evaluation function such as energy cost while satisfying the operational constraints, and the evaluation value of the evaluation function obtained at this time is called the evaluation value Z(T_CDW ｔ The planner 117 is not limited to an operation plan that minimizes the evaluation value of the evaluation function, but may also create an operation plan that maximizes the evaluation value of the evaluation function, where the evaluation function has a higher evaluation as the evaluation value increases.

[0111] Steps S104 and S105 are the same as those described in the first embodiment.

[0112] <B-4. Effects> In the plant optimal operation planning device 102 according to the second embodiment, the temperature search unit searches for the optimal cooling water temperature from among candidate cooling water temperatures input by the user. Therefore, the plant optimal operation planning device 102 makes it possible to formulate an operation plan based on the optimal cooling water temperature searched from among candidate cooling water temperatures set by the plant operator, and by increasing or decreasing the power consumption of the fan to change the cooling water temperature to the optimal value, it is possible to improve the efficiency of chilled water production and reduce energy costs.

[0113] It should be noted that the embodiments can be freely combined, and each embodiment can be modified or omitted as appropriate. The above description is an example in all respects. It is understood that countless variations not illustrated can be envisioned.

[0114] 101, 102 Plant optimal operation planning device, 111 Operation data input unit, 112 Operation data storage unit, 113 Weather data input unit, 114 Demand forecasting unit, 115 Coefficient storage unit, 116 Temperature search unit, 117 Planning unit, 118 Plan output unit, 119 Data input / output unit, 121 Temperature storage unit, 200 Target plant, 211 Steam header, 221 Fuel, 222 Electric power, 231 Steam demand, 232 Chilled water demand, 233 Electric power demand, 241, 241A, 241B Boiler, 242, 242A, 242B, 242C Absorption chiller, 243, 243A, 243B Cooling tower, 301 Input device, 302 Output device, 303 CPU, 304 Main storage device, 305 Secondary storage device, 306 Communication equipment, 307 Communications network.

Claims

1. A plant optimal operation planning device that creates an optimal operation plan for a target plant having hierarchically configured plant component equipment, comprising: a demand forecasting unit that predicts power demand and heat demand based on plant operation data and weather data of the target plant; a temperature search unit that searches for an optimal cooling water temperature for the plant component equipment with the objective of minimizing or maximizing an evaluation value of an evaluation function; and a planning unit that creates the optimal operation plan, including a plan for start / stop states and input / output energy for each of the plant component equipment, based on the predicted power demand and heat demand, equipment characteristic coefficients that depend on the cooling water temperature of the plant component equipment, and the optimal cooling water temperature, so that the evaluation value of the evaluation function is minimized or maximized.

2. A plant optimal operation planning device according to claim 1, wherein the temperature search unit searches for the optimal cooling water temperature from among candidate cooling water temperatures input by a user.

3. The plant optimal operation planning device according to claim 1, wherein the temperature search unit searches for the optimal cooling water temperature using metaheuristics or an expert system.

4. A plant optimal operation planning device according to any one of claims 1 to 3, wherein the temperature search unit searches for the optimal cooling water temperature for each time unit during which a user manages the operation of the target plant.

5. A plant optimal operation planning device according to any one of claims 1 to 4, wherein the temperature search unit searches for the optimal cooling water temperature within a range whose lower limit is a cooling water temperature lower limit value that depends on the outside air wet-bulb temperature.

6. A plant optimal operation planning system according to any one of claims 1 to 5, wherein the equipment characteristic coefficients that depend on the cooling water temperature of the plant constituent equipment are expressed by transient equipment characteristics and steady-state equipment characteristics that depend on the cooling water temperature.

Images