Plant optimal operation planning system

Abstract

The present disclosure provides a plant optimal operation planning device that creates an optimal operation plan for a plant based on 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 hierarchically configured plant component devices, and includes: a demand forecasting unit (114) that predicts 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 component devices with the objective of minimizing or maximizing an 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 component device, based on the predicted power demand and heat demand, equipment characteristic coefficients that depend on the cooling water temperatures of the plant component devices, and the optimal cooling water temperature, so that the evaluation value of the evaluation function is minimized or maximized.

Description

[Technical Field]

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

[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 Document 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 and 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. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2007-255198 Summary of the Invention [Problem to be solved by the invention]

[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 in Patent Document 1 cannot improve the efficiency of chilled water production 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. [Means for solving the problem]

[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 constituent 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 constituent equipment with the objective of minimizing or maximizing an evaluation value of an evaluation function, and a temperature search unit that searches for an optimal cooling water temperature for the plant constituent equipment based on the predicted power demand and heat demand, equipment characteristic coefficients that depend on the cooling water temperature of the plant constituent equipment, and the optimal cooling water temperature. To ensure that the cooling water temperature of the plant components is at the optimum temperature and a planning unit that creates an optimal operation plan that minimizes or maximizes the evaluation value of the evaluation function and includes plans for start / stop states and input / output energy for each piece of plant constituent equipment. [Effects of the Invention]

[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. [Brief explanation of the drawings]

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

Mode for Carrying Out the Invention

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

[0012] The drawings are shown schematically, and for the convenience of explanation, omissions or simplifications of the configuration are made in the drawings as appropriate. Also, the mutual relationships of the sizes and positions of the configurations shown in different drawings are not necessarily accurately described and can be changed as appropriate.

[0013] Also, in the explanations shown below, the same reference numerals are given to the same components in the drawings, and their names and functions are also considered the same. Therefore, detailed explanations thereof may be omitted to avoid duplication.

[0014] Also, in the descriptions described in this specification of the present application, when a component is described as "including", "comprising" or "having", etc., it is not an exclusive expression excluding the existence of other components unless otherwise specified.

[0015] <A. Embodiment 1> [[ID=3[]]<A-1. Target Plant> FIG. 2 shows an example of a target plant 200 targeted by the plant optimal operation planning device according to Embodiment 1. Hereinafter, the target plant 200 will be described along with FIG. 2. [[ID=[]]

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

[0018] Target plant 200 supplies fuel 221 purchased from a gas utility to boiler 241A and boiler 241B through a gas pipeline network. Steam produced by boiler 241A and boiler 241B is supplied to steam header 211. Steam header 211 supplies steam to a building or factory with steam demand 231 through a steam pipeline network. Steam is also supplied from steam header 211 to absorption chiller 242A, absorption chiller 242B, and absorption chiller 242C. Chilled water produced by absorption chiller 242A, absorption chiller 242B, and absorption chiller 242C is supplied to a building or factory with chilled water demand 232 through a chilled water pipeline network. Steam demand 231 and chilled water demand 232 are referred to as heat demand. Heat generated when chilled water is produced by absorption chiller 242A, absorption chiller 242B, and absorption chiller 242C is discarded as cooling water. Cooling tower 243A and cooling tower 243B rotate fans to release heat from the cooling water into the atmosphere. In order 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, target plant 200 supplies electricity 222 purchased from a retail electricity supplier to electricity 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 component equipment, a boiler 241 and an absorption chiller 242, to produce energy, namely, chilled water, from fuel 221. In this way, a plant that hierarchically combines two or more types of plant component equipment to produce one or more types of energy from fuel 221 is referred to as a plant having hierarchically configured plant component equipment.

[0020] The operator of the target plant 200, who is a user of the plant optimal operation planning device 101 (hereinafter referred to as the plant operator), is required to efficiently produce energy while maintaining the pressure or temperature specified in the supply regulations. In order to maintain the pressure or temperature specified in the supply regulations, it is necessary to control the startup and shutdown states of the plant component devices and the input and output energy, etc., in order to supply the target plant 200 with the amount of steam heat, the amount of chilled water heat, and the electric power that match the steam demand 231, the chilled water demand 232, and the electric power demand 233.

[0021] <A-2. Functional Configuration of Plant Optimal Operation Planning Device> FIG. 1 is a functional configuration diagram of the plant optimal operation planning device 101 according to Embodiment 1. Hereinafter, an example of the functional configuration of the plant optimal operation planning device 101 will be described along with FIG. 1.

[0022] The plant optimal operation planning device 101 includes an operation data input unit 111, an operation data storage unit 112, a weather data input unit 113, a demand prediction 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 of the target plant 200 (hereinafter referred to as "plant operation data"). 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 steam calorific value, the chilled water calorific value, and the cooling water calorific value calculated here 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 closest point 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, which 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 characteristics 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 characteristics 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, and the number of significant digits of the cooling water temperature. The cooling water temperature is the cooling water temperature in the time unit by which the plant operator manages the operation of the target plant 200. The time unit for managing 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 the range of the cooling water temperature lower limit, which 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 planner 117 creates an operation plan for the target plant 200 based on the demand forecast values ​​for the planning period predicted by the demand forecaster 114, the equipment characteristic coefficients of the plant constituent equipment read from the coefficient memory 115, the optimal cooling water temperature read from the temperature searcher 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 the equipment capacity constraint, minimum operation time constraint, or minimum shutdown time constraint of the plant constituent equipment, and include upper and lower limits of the heat quantity, upper and lower limits of the flow rate, and minimum operation time or minimum shutdown time of the plant constituent equipment. The planner 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 device 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 device of the absorption chiller 242, and input / output energy such as cooling water heat quantity and power consumption of the cooling tower group.

[0034] Based on the operation plan of the target plant 200 formulated by the planning unit 117, the planning output unit 118 creates a stacked graph or a line graph representing the operation plan.

[0035] The data input / output unit 119 receives the equipment characteristic coefficients of the plant component equipment stored in the coefficient storage unit 115. These equipment characteristic coefficients are set by the plant operator. Also, the data input / output unit 119 receives the set value of the operation constraint condition regarding the cooling water temperature. This set value is considered in the temperature search unit 116. Further, the data input / output unit 119 receives the set value of the operation constraint condition of the plant component equipment. This set value is set by the plant operator and considered in the planning unit 117. Additionally, the data input / output unit 119 displays the stacked graph or the line graph representing the operation plan created by the planning output unit 118 to the target plant operator.

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

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

[0038] <A-3. Hardware Configuration of Plant Optimal Operation Planning Device> Figure 3 is a hardware configuration diagram of the plant optimal operation planning device 101. Hereinafter, an example of the hardware configuration of the plant optimal operation planning device 101 will be described along with Figure 3.

[0039] The plant optimal operation planning device 101 includes an input device 301, an output device 302, a CPU (Central Processing Unit) 303, a main memory device 304, a secondary memory device 305, and a communication device 306. The communication device 306 is for connecting the plant optimal operation planning device 101 to a communication network 307. The CPU 303, the main memory device 304, and the secondary memory device 305 are an example of a processing circuit.

[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 memory device 304 or the secondary memory device 305. The demand prediction unit 114, the temperature search unit 116, the planning unit 117, and the plan output unit 118 in FIG. 1 are realized by the CPU 303 executing a software program stored in the main memory device 304 or the secondary memory device 305. 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 prediction in FIG. 1 are realized by the communication device 306.

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

[0042] <A-4. Operation of the Plant Optimal Operation Planning Device> FIG. 4 is a flowchart showing the calculation process of the plant optimal operation planning device 101. Hereinafter, the calculation process of the plant optimal operation planning device 101 will be described 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, the chilled water calorific value, and the 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 of the target plant 200 acquired by the operation data input unit 111 and the steam calorific value, the chilled water calorific value, and the 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 for a similar date that is close to the target schedule date and that matches the day of the week from the plant operation data stored in the operation data storage unit 112. The demand forecasting unit 114 then uses the plant operation data for the similar date and actual values ​​of meteorological data, such as actual air temperature or actual outdoor air wet-bulb temperature, to construct regression models for steam demand 231, chilled water demand 232, and electricity demand 233. 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 component equipment characteristic coefficients) The planning unit 117 acquires the equipment characteristic coefficients of the plant constituent equipment stored in the coefficient storage unit 115 .

[0047] [Obtaining boiler group equipment characteristic coefficients] Equation (1) is an equation that expresses the equipment characteristics of a boiler group in which the boiler 241A and the boiler 241B are regarded as one boiler.

[0048]

number

[0049] Note that t∈Tm. Tm is a set of times that are obtained by dividing the planning period into 30-minute intervals, which are the time units used by the plant operator to manage the operation of the target plant 200, and numbering the intervals consecutively, starting with 1 as the initial time of the planning period. t represents the steam heat [GJ / h] produced by the boiler group. t is the fuel input of the boiler group [m 3 / h]. tis a binary value that indicates the start / stop state of the boiler group, with 1 indicating the start state and 0 indicating the stop state. HA_B is the slope of the equipment characteristics of the boiler group, and HB_B is the intercept of the equipment characteristics 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 the equipment characteristic coefficients of absorption chiller 242] Equations (2) to (6) express the equipment characteristics of each plant component device of the absorption chiller 242, which depend on the cooling water temperature. Equation (2) expresses the steady-state equipment characteristics that depend on the cooling water temperature.

[0052]

number

[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 quantity of chilled water produced by the absorption chiller 242. a,t represents the steam heat amount [GJ / h] consumed by the absorption refrigerator 242. a,t is a binary value that indicates the activation / deactivation state of the absorption chiller 242, where 1 indicates the activation state and 0 indicates the deactivation state. a,t is the coolant temperature characteristic gain, and G a () is a piecewise linear function.

[0054] Equation (3) expresses the transient characteristics of the equipment as a first-order lag system.

[0055]

number

[0056] In addition, cw_ar a,t represents the amount of cold water heat [GJ / h] 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]

number

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

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

[0061]

number

[0062]

number

[0063] In addition, s_ar a,t,k represents the steam heat amount [GJ / h] consumed by the absorption chiller 242 in section k, and GA_AR a,k represents the slope of the equipment characteristics 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 of the absorption chiller 242 that depends on the cooling water temperature and is stored in the coefficient storage unit 115 is the slope GA_AR of the equipment characteristic of the absorption chiller 242 in the section k. a,k, Intercept of the equipment characteristics of absorption refrigerator 242 GB_AR a , time constant T_AR a , cooling water reference temperature T_CDWZ_AR a , and coolant temperature characteristics C_CDW_AR a The acquisition of the equipment characteristic coefficient for each plant component equipment of the absorption chiller 242 that depends on the cooling water temperature and that is stored in the coefficient storage unit 115 is carried out by calculating the slope GA_AR a,k and the intercept of the equipment characteristics of absorption chiller 242 GB_AR a , time constant T_AR a , cooling water reference temperature T_CDWZ_AR a , and coolant temperature characteristics C_CDW_AR a The goal is to obtain

[0065] [Getting the cooling tower group equipment characteristic coefficients] Equations (7) to (10) express the equipment characteristics of the cooling tower group, where 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 outdoor air wet-bulb temperature characteristic gain based on the outdoor air wet-bulb reference temperature.

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

[0067]

number

[0068] In addition, e_ct t is the fan power consumption of the cooling tower group [kW]. q_cdw t is the cooling water heat quantity 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. K_WB_CT t is the outside air wet-bulb temperature characteristic gain.

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

[0070]

number

[0071] Note that T_CDWZ_CT is the cooling water reference temperature [℃]. C_CDW_CT is the cooling water temperature characteristic [% / ℃].

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

[0073]

number

[0074] In addition, T_WB t is the outdoor wet-bulb temperature [℃]. T_WBZ_CT is the outdoor wet-bulb reference temperature [℃]. C_WB_CT is the outdoor wet-bulb temperature characteristic [% / ℃].

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

[0076]

number

[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 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. Obtaining the equipment characteristic coefficients dependent on the cooling water temperature and the outside air wet-bulb temperature of the cooling tower group stored in coefficient storage unit 115 means obtaining 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 Figure 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]

number

[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]

number

[0085] In addition, T_CDW_LB t is the lower limit of the cooling water temperature [℃]. T_AP is the lower limit of the approach temperature [℃]. 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 equipment 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) Generate 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 ends with {T_CDW 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 built 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 cooling water temperature generated at this time are generated according to a rule based on the knowledge of plant operators, such as "if the average 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 searches for a candidate solution T_CDW of the coolant temperature. t ∈N(T_CDW_AVE) evaluation value Z(T_CDW t ) 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 the set of candidate solutions for the cooling water 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 called the evaluation value Z(T_CDW t )

[0094] (S104 in Figure 4: Optimal operation plan creation) The planning unit 117 formulates 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 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 setting values ​​of the operational constraints of the plant constituent equipment. Note that the planning unit 117 is not limited to an operation plan that minimizes the evaluation value of the evaluation function, and may formulate 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 Figure 4: Display of planning results) The plan output unit 118 creates a stacked graph or a line graph that represents the operation plan created by the planner 117. The data input / output unit 119 displays the stacked graph or the line graph that represents 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 in order to supply the steam heat quantity, chilled water heat quantity, or electric power that matches the steam demand 231, chilled water demand 232, or electric power demand 233 from the target plant 200, the plant operator changes the cooling water temperature by increasing or decreasing the power consumption of the fan, or controls the startup and shutdown states of the plant component devices and the input and output energy, etc.

[0097] <A-5. Effect> The plant optimal operation planning device 101 according to Embodiment 1 creates an optimal operation plan for the target plant 200 having plant component devices with a hierarchical structure. The plant optimal operation planning device 101 includes a demand prediction unit 114 that predicts the power demand and heat demand based on the plant operation data and meteorological data of the target plant 200, a temperature search unit 116 that searches for the optimal cooling water temperature of the plant component devices for the purpose of minimizing or maximizing the evaluation value of the evaluation function, and based on the predicted power demand and heat demand, the device characteristic coefficient that depends on the cooling water temperature of the plant component devices, and the optimal cooling water temperature, a planning unit 117 that creates an optimal operation plan including the startup and shutdown states and input and output energy plans for each plant component device for which the evaluation value of the evaluation function is minimized or maximized. With the above configuration, according to the plant optimal operation planning device 101, it becomes possible to formulate an operation plan based on the optimal cooling water temperature, and by changing the cooling water temperature to an optimal value by increasing or decreasing the power consumption of the fan, it is possible to improve the production efficiency of chilled water and reduce the energy cost.

[0098] <B. Embodiment 2> <B- . Functional Configuration of Plant Optimal Operation Planning Device> FIG. 5 is a diagram showing an example of the functional configuration of the plant optimal operation planning device 102 according to Embodiment 2. Hereinafter, the functional configuration of the plant optimal operation planning device 102 will be described along with FIG. 5. In the following description, the same reference numerals are given to the components similar to those described in Embodiment 1, and the detailed description thereof will be omitted as appropriate.

[0099] The plant optimal operation planning device 102 has a configuration in which a temperature storage unit 121 is added to the functional components of the plant optimal operation planning device 101 according to Embodiment 1.

[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 the operation constraints related to the cooling water temperature and the candidates for the cooling water temperature stored in the temperature storage unit 121, and searches for the optimal cooling water temperature at which the evaluation value of an evaluation function such as the energy cost is minimized. This optimal cooling water temperature is searched from among the candidates for the cooling water temperature stored in the temperature storage unit 121 that satisfy the operation constraints related to the cooling water temperature and are within the range of the lower limit value of the cooling water temperature that depends on the outside air wet-bulb temperature.

[0102] In addition to the processing described in Embodiment 1, the data input / output unit 119 accepts candidates for the cooling water temperature input by the plant operator. These candidates for the cooling water temperature are stored in the temperature storage unit 121.

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

[0104] <B-2. Hardware Configuration of Plant Optimal Operation Planning Device> The hardware configuration of the plant optimal operation planning device 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 configurations of the other functional components of the plant optimal operation planning device 102 are as described in Embodiment 1.

[0105] <B-3. Operation> FIG. 6 is a flowchart showing the calculation processing of the plant optimal operation planning device 102. The flow in FIG. 6 is obtained by adding step S2o1 between steps Sio2 and Sio3 in the flow of FIG. 4 described in Embodiment 1.

[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 ) and the candidate coolant temperature with the smallest evaluation value is the optimal coolant temperature T_CDW t * Note 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. Effect> In the plant optimal operation planning device 102 according to Embodiment 2, the temperature search unit searches for the optimal cooling water temperature from among the candidates for the cooling water temperature input by the user. Therefore, according to the plant optimal operation planning device 102, it is possible to formulate an operation plan based on the optimal cooling water temperature searched from among the candidates for the cooling water temperature set by the plant operator, and by increasing or decreasing the power consumption of the fan to change the cooling water temperature to an optimal value, it is possible to improve the production efficiency of chilled water and reduce the energy cost.

[0113] It should be noted that it is possible to freely combine the respective embodiments, or to appropriately modify or omit the respective embodiments. The above description is illustrative in all aspects. It is understood that innumerable variations not illustrated can be envisioned.

Description of Reference Numerals

[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 prediction 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 memory device, 305 Secondary storage device, 306 Communication device, 307 Communication network.

Claims

1. A plant optimal operation planning device that creates an optimal operation plan for a target plant having a hierarchical configuration of plant components, A demand forecasting unit that predicts electricity demand and heat demand based on plant operation data and weather data of the aforementioned target plant, A temperature search unit that searches for the optimal cooling water temperature of the plant components with the aim of minimizing or maximizing the evaluation value of the evaluation function, The system includes a planning unit that creates an optimal operation plan, which includes a plan for the start-up / stop state and input / output energy for each plant component, based on the predicted power demand and heat demand, equipment characteristic coefficients that depend on the cooling water temperature of the plant components, and the optimal cooling water temperature, so that the evaluation value of the evaluation function is minimized or maximized so that the cooling water temperature of the plant components becomes the optimal cooling water temperature. Plant optimization operation planning device.

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

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

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

5. A plant optimal operation planning device according to claim 1, The temperature search unit searches for the optimal cooling water temperature within a range where the lower limit of the cooling water temperature depends on the ambient wet-bulb temperature. Plant optimization operation planning device.

6. A plant optimal operation planning device according to claim 1, The equipment characteristic coefficients of the aforementioned plant components, which depend on the cooling water temperature, are expressed in terms of transient equipment characteristics and steady-state equipment characteristics that depend on the cooling water temperature. Plant optimization operation planning device.

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