Container terminal energy consumption prediction system, and container terminal energy consumption prediction method

Abstract

To provide an energy consumption prediction system and an energy consumption prediction method that predict energy consumption in a container terminal on the basis of information used in the current container terminal operation.SOLUTION: An energy consumption prediction system acquires actual results of energy consumption, and past actual results data related to the amount of containers handled in container loading and unloading operations and the amount of containers stored in a container terminal, in a first acquisition step, calculates unit energy consumption per container or per container loading and unloading operations on the basis of the actual results of energy consumption and the past actual results data, in a calculation step, acquires plan information related to container loading and unloading operations and a schedule for carrying in or carrying out containers, in a second acquisition step, and predicts energy consumption per unit time on the basis of the unit energy consumption and the plan information, in a prediction step.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a container terminal energy consumption forecasting system and a container terminal energy consumption forecasting method. [Background technology]

[0002] Container terminals, which use large cranes to handle heavy containers, are one of the business establishments that consume a lot of energy when loading and unloading containers. However, due to the recent rise in global crude oil prices and the resulting rise in electricity costs, utility expenses related to container loading and unloading have increased significantly.

[0003] The electricity bill, which is one of the utilities, is the sum of a basic charge and an energy charge. The basic charge is generally calculated based on the maximum 30-minute demand throughout the year, so in order to reduce the basic charge, it is necessary to predict and understand the 30-minute demand in advance.

[0004] Patent Document 1 discloses a method and device for predicting energy consumption in a building, and Patent Document 2 discloses a demand monitoring device. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent Publication No. 2003-281223 [Patent Document 2] Patent Publication No. 8-63132 Summary of the Invention [Problem to be solved by the invention]

[0006] However, at container terminals, multiple operations may be carried out simultaneously, such as transporting containers in and out of the container terminal by truck, and unloading and loading containers onto ships using large cranes, making it difficult to predict detailed loading and unloading schedules for each container.It is also difficult to set patterns in advance for combinations of container loading volumes, which are related to energy consumption, the sizes and weights of those containers, and loading and unloading schedules.

[0007] Furthermore, even if demand is monitored for 30 minutes using the contracted power as a threshold, the determination of whether the contracted power will be exceeded is made every 30 minutes, making it difficult to take measures to prevent the contracted power from being exceeded the day before or several hours in advance.

[0008] Furthermore, if the 30-minute demand exceeds the contracted power, one possible countermeasure would be to shut down the operation of equipment within the container terminal. However, because container terminals are core facilities for logistics, stopping operations requires considerable advance preparation, and operations cannot be easily shut down.

[0009] In view of the above circumstances, an object of the present invention is to provide an energy consumption prediction system and an energy consumption prediction method for predicting energy consumption in a container terminal based on information used in current container terminal operations. [Means for solving the problem]

[0010] A first aspect of the present invention is a system for predicting energy consumption in a container terminal, configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data related to the handling volume of containers in container handling operations and the storage volume of containers in a container terminal are acquired; In the calculation step, a unit energy consumption amount per container or per container handling operation is calculated based on the actual power consumption data and the past actual data; In a second acquisition step, plan information regarding container handling operations and container loading or unloading schedules is acquired; In the prediction step, the energy consumption prediction system predicts an amount of energy consumption per unit time based on the unit amount of energy consumption and the plan information.

[0011] A second aspect of the present invention is a method for predicting energy consumption in a container terminal, comprising: configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data related to the handling volume of containers in container handling operations and the storage volume of containers in a container terminal are acquired; In the calculation step, a unit energy consumption amount per container or per container handling operation is calculated based on the actual power consumption data and the past actual data; In a second acquisition step, plan information regarding container handling operations and container loading or unloading schedules is acquired; In the prediction step, an amount of energy consumed per unit time is predicted based on the unit amount of energy consumed and the plan information, which is an energy consumption prediction method. [Brief description of the drawings]

[0012] [Figure 1] Overview of Energy Consumption Prediction System 1 [Diagram 2] Flowchart diagram according to the first embodiment [Diagram 3] Overall view of power supply system 2 [Figure 4] Flowchart diagram according to the second embodiment [Diagram 5] Overall view of power supply system 3 [Figure 6] Flowchart diagram according to the third embodiment [Figure 7] Flowchart diagram according to another embodiment DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Various features shown in the embodiments described below can be combined with each other.

[0014] <First embodiment> 1 is a diagram showing an overall view of an energy consumption prediction system 1. The energy consumption prediction system 1 mainly comprises a server 8, a power monitoring system 6, and a cargo handling management system 7, which are connected via a network. Note that the network referred to here is not limited to a private network, and may be a public network or a virtual network.

[0015] The server 8 has a communication unit 81, a recording unit 82, a control unit 83, and a calculation unit 84, and these components are electrically connected inside the server 8 via a communication bus 91. Note that the server 8 can be a locally existing server device, but may also be a cloud server. In this embodiment, the communication unit 81, the recording unit 82, the control unit 83, and the calculation unit 84 are configured to be included in one server, but each unit may be present in multiple servers.

[0016] The power monitoring system 6 is a system provided in a high-voltage substation facility, which monitors and controls the devices in the facility and records information on operation, measurement results, and the like.

[0017] The cargo handling management system 7 is a system installed in the container terminal, and manages container handling plans and performance data, as well as equipment such as cranes.

[0018] The communication unit 81 may employ wired communication means such as USB, IEEE1394, Thunderbolt, wired LAN network communication, etc., as well as wireless LAN network communication, mobile communication such as 5G, LTE, 3G, Bluetooth (registered trademark) communication, etc., but is not limited to these. The server 8 transmits and receives data related to actual power consumption, and data related to actual loading and unloading work or container loading and unloading work plans to and from the power monitoring system 6 and the loading and unloading management system 7 via the network via the communication unit 81. Details will be described later.

[0019] The recording unit 82 records information received from the power monitoring system 6 and the cargo handling management system 7 described above, as well as values ​​calculated by a calculation unit 84 described below, and details will be described later. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs related to the server 8 executed by a control unit 83 described below, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the calculation of the programs. Alternatively, it may be a combination of these.

[0020] The control unit 83 processes and controls the overall operation related to the server 8. The control unit 83 is, for example, a central processing unit (CPU) not shown. The control unit 83 transmits and receives data related to power consumption results, data related to loading and unloading work results or loading and unloading work plans, and predicts the amount of energy consumed per unit time by reading out a predetermined program recorded in the storage unit 22. That is, information processing by the software recorded in the storage unit 22 can be specifically realized by the control unit 83, which is an example of hardware, and executed as a functional unit (not shown) included in the control unit 83. These will be described in detail later. The control unit 83 is not limited to being single, and may be implemented to have multiple control units 83 for each function, or a combination thereof.

[0021] The calculation unit 84 calculates the power consumption per container per unit time (hereinafter referred to as the "first unit of consumption") and the power consumption per loading and unloading operation (hereinafter referred to as the "second unit of consumption") based on the data related to the actual power consumption and the loading and unloading operation recorded in the recording unit 82, and also calculates a predicted value of the power consumption based on the first unit of consumption and the second unit of consumption and the data related to the container loading and unloading operation plan. Note that in this embodiment, the first unit of consumption and the second unit of consumption are calculated based on the actual power consumption, but they may also be calculated based on, for example, the actual consumption of fossil fuels, etc., which will be described later.

[0022] 2 is a flowchart showing the flow of information processing executed by the energy consumption prediction system 1. Each step in this flowchart will be described below.

[0023] First, the power monitoring system 6 acquires past power consumption data for each facility and the cargo handling operation data for each facility held by the cargo handling management system 7 via a network (S101). The facilities referred to here are, for example, gantry cranes, portal cranes, outdoor lighting, a management building, and reefer containers, but are not limited thereto. In this embodiment, the power monitoring system 6 and the cargo handling management system 7 are connected to other systems via a network, but if they are not connected, the power consumption data and the cargo handling operation data may be manually input to the recording unit 82. The cargo handling operation data may be, for example, the number of containers loaded and unloaded by each crane operating at the container terminal, the number of containers stored in the container terminal at a certain time, or the type of the container. Furthermore, in this embodiment, only actual electricity consumption data obtained from the electricity monitoring system 6 is considered as the actual energy consumption data, but the actual consumption of fossil fuels such as diesel and carbon-neutral fuels such as hydrogen and ammonia (hereinafter referred to as "fossil fuels, etc.") used in port loading and unloading equipment such as tractor heads and top lifters may also be considered.

[0024] The first and second basic units are calculated from the acquired electricity consumption record data and cargo handling work record data (S102). Here, the container in the first basic unit refers to a container that consumes electricity, fossil fuels, etc., such as a reefer container, and the unit time is, for example, one hour, but is selected according to the data collection interval of the electricity consumption record data and the cargo handling work record data. Moreover, the cargo handling work in the second basic unit refers to, for example, one cargo handling work by a gantry crane or a portal crane, and also includes transportation work by other port cargo handling equipment such as a tractor head or a top lifter.

[0025] For example, the first unit of consumption is calculated from the amount of electricity consumed by a reefer container on a specific date and time and the number of reefer containers stored in a container terminal on the same date and time, and the second unit of consumption is calculated from the amount of electricity consumed by a gantry crane on a specific date and time and the number of containers handled by the gantry crane on the same date and time.

[0026] Next, data related to the container handling operation plan at the date and time for predicting the power consumption is obtained from the cargo handling management system 7 (S103). The data includes, for example, the time when the ship will dock, the number of containers to be unloaded or loaded (hereinafter referred to as "unloading, etc."), the number of gantry cranes and other cargo handling equipment used for the operation, the time period when the unloading, etc. will be performed, the number and time of containers to be brought in from outside the premises or taken out from the premises (hereinafter referred to as "carrying in, etc."), the number and time of container storage location changes within the container terminal, etc., but is not limited to these. Note that in this embodiment, data related to the container handling operation plan is obtained from the cargo handling management system 7, but values ​​estimated from past cargo handling operation performance data obtained in S101 may be used.

[0027] Based on the acquired plan data related to the container handling work and the first and second basic units calculated in S102, the predicted power consumption per unit time of each facility at the time scheduled in the plan data is calculated (S104). That is, it is calculated by multiplying the number of containers stored in the container terminal, which is calculated from the number of containers to be unloaded or carried in, by the first basic unit, and by multiplying the number of containers to be unloaded or carried in per unit time by the second basic unit, for example.

[0028] This makes it possible to accurately predict energy consumption using a simple calculation formula based on the information currently used in container terminal operations.

[0029] <Second embodiment> The second embodiment of the present invention will be described, focusing on the differences from the first embodiment. The power supply system 2 of this embodiment differs from the first embodiment in that it has a power generation device 5 and that the server 8 has a determination unit 85. In the following description, the same components as those in the first embodiment are denoted by the same reference numerals, and description thereof will be omitted.

[0030] 3 is a diagram showing an overall view of the power supply system 2. The power supply system 2 mainly includes a server 8, a power monitoring system 6, a cargo handling management system 7, and a power generation device 5, which are connected via a network.

[0031] The power generation device 5 is, for example, a diesel engine generator, but is not limited to this and may be a fuel cell power generation system, a gas turbine cogeneration system, or a storage battery.

[0032] The server 8 further includes a determination unit 85, which determines whether the predicted power consumption exceeds a preset threshold. Details will be described later. The threshold set here is, for example, a contract power value, but is not limited to this and may be any value that provides economic benefits.

[0033] 4 is a flowchart showing the flow of information processing executed by the power supply system 2. Each step in this flowchart will be described below.

[0034] First, past actual power consumption data for each facility held by the power monitoring system 6 and past actual loading and unloading work data held by the loading and unloading management system 7 are acquired via the network (S201), and the first and second basic units are calculated from the acquired actual power consumption data and actual loading and unloading work data (S202).

[0035] Next, data related to a container handling operation plan at the date and time for predicting the power consumption is acquired from the cargo handling management system 7 (S203). Next, based on the acquired plan data related to the container handling operation and the first and second basic units calculated in S202, the predicted power consumption per unit time in each facility at the scheduled time in the plan data is calculated (S204).

[0036] Then, it is determined whether the power consumption calculated in S204 exceeds a preset threshold value (S205), and if it is determined that the power consumption exceeds the threshold value, the power generation device 5 is operated at the time when the power consumption exceeds the threshold value, and power is supplied to the container terminal (S206). Note that the power supply is supplied from the power generation device 5 by cutting off the grid power connected to some of the facilities, but the power generation device 5 may be connected to the grid power without cutting off the grid power, and is not limited to this. Also, the power generation device 5 is operated manually, but may be controlled to operate automatically at the time when the threshold value is exceeded.

[0037] This makes it possible to curb consumption of grid power that exceeds the contracted power, thereby reducing electricity bills.

[0038] <Third embodiment> The third embodiment of the present invention will be described, focusing on the differences from the second embodiment. In the following description, the same components as those in the second embodiment will be denoted by the same reference numerals, and the description thereof will be omitted.

[0039] Fig. 5 is an overall diagram of the power supply system 3, and Fig. 6 is a flowchart showing the flow of information processing executed by the power supply system 3. Each step in this flowchart will be described below.

[0040] First, past actual power consumption data for each facility held by the power monitoring system 6 and past actual loading and unloading work data held by the loading and unloading management system 7 are acquired via the network (S301), and the first and second basic units are calculated from the acquired actual power consumption data and actual loading and unloading work data (S302).

[0041] Next, data related to a container handling operation plan at the date and time for predicting the power consumption is acquired from the cargo handling management system 7 (S303). Next, based on the acquired plan data related to the container handling operation and the first and second basic units calculated in S302, the predicted power consumption per unit time in each facility at the scheduled time in the plan data is calculated (S304).

[0042] Then, it is determined whether the power consumption calculated in S304 exceeds a preset threshold value (S305), and if it is determined that the power consumption exceeds the threshold value, the storage battery 9 of the power supply system 3 is charged by at least the excess power amount before the time arrives at which the threshold value will be exceeded (S306). At this time, if the power consumption exceeds the threshold value due to charging the storage battery 9, it is more preferable to stop charging the storage battery 9 during that time period.

[0043] Then, at the time when the threshold is exceeded, power is supplied from the storage battery 9 to the container terminal (S307). At this time, the power supply is performed from the storage battery 9 by cutting off the grid power connected to some of the equipment, but the power supply is not limited to this and may be connected to the grid power without cutting off the grid power. Also, the storage battery 9 is operated manually, but may be controlled to operate automatically at the time when the threshold is exceeded.

[0044] This will not only curb consumption of grid power that exceeds the contracted power, but also contribute to reducing CO2 emissions from energy consumption within the container terminal.

[0045] <Other aspects> In another embodiment of the present invention, the server 8 may further acquire weather information for the date and time to be predicted. The weather information includes, but is not limited to, the outside temperature, the weather, the amount of precipitation, and the humidity.

[0046] Reefer containers are controlled to keep their cargo at a constant temperature, and so power consumption increases on days when the temperature is high. Therefore, predictions can be made more sophisticated by correcting power consumption based on a correction coefficient calculated from the difference between the temperature at which the reefer container is kept and the outside air temperature. [Explanation of symbols]

[0047] 1 Energy consumption prediction system 1 2 Power Supply System 2 3 Power Supply System3 5. Power generation equipment 6. Power Monitoring System 7 Cargo Handling Management System 8 Server 9. Storage battery 81 Communications Department 82 Recording Section 83 Control Unit 84 Arithmetic section 85 Judgment section 91 Communication Bus

Claims

1. A system for predicting energy consumption in a container terminal, comprising: configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data related to the handling volume of containers in container handling operations and the storage volume of containers in a container terminal are acquired; In the calculation step, a unit energy consumption amount per container or per container handling operation is calculated based on the actual power consumption data and the past actual data; In the second acquisition step, plan information regarding container handling operations and container loading or unloading schedules is acquired; In the prediction step, an amount of energy consumption per unit time is predicted based on the unit amount of energy consumption and the plan information. Energy consumption prediction system.

2. In the second acquisition step, weather information is further acquired; The energy consumption prediction system according to claim 1 , wherein in the prediction step, an amount of energy consumption per unit time is predicted based on the unit amount of energy consumption, the plan information, and the weather information.

3. A method for predicting energy consumption in a container terminal, comprising: configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data related to the handling volume of containers in container handling operations and the storage volume of containers in a container terminal are acquired; In the calculation step, a unit energy consumption amount per container or per container handling operation is calculated based on the actual power consumption data and the past actual data; In the second acquisition step, plan information regarding container handling operations and container loading or unloading schedules is acquired; In the prediction step, an amount of energy consumption per unit time is predicted based on the unit amount of energy consumption and the plan information. Energy consumption prediction method.

4. A power supply system in a container terminal having a power generation device, comprising: configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data related to the handling volume of containers in container handling operations and the storage volume of containers in a container terminal are acquired; In the calculation step, a unit energy consumption amount per container or per container handling operation is calculated based on the actual power consumption data and the past actual data; In the second acquisition step, plan information regarding container handling operations and container loading or unloading schedules is acquired; In the prediction step, an amount of energy consumed per unit time is calculated based on the unit amount of energy consumed and the plan information; In the power generation step, when the predicted energy consumption value calculated in the prediction step exceeds a threshold value, the power generation device is operated for a time period during which the predicted energy consumption value exceeds the threshold value. Power supply system.

5. A power supply system in a container terminal having a storage battery, comprising: configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data related to the handling volume of containers in container handling operations and the storage volume of containers in a container terminal are acquired; In the calculation step, a unit energy consumption amount per container or per container handling operation is calculated based on the actual power consumption data and the past actual data; In the second acquisition step, plan information regarding container handling operations and container loading or unloading schedules is acquired; In the prediction step, an amount of energy consumed per unit time is calculated based on the unit amount of energy consumed and the plan information; In the power generation step, when the predicted energy consumption value calculated in the prediction step exceeds a threshold, power is supplied from the storage battery during a time period during which the predicted energy consumption value exceeds the threshold. Power supply system.

6. It also has a charging step. The power supply system according to claim 5 , wherein in the charging step, the storage battery is charged before a time when the predicted energy consumption value exceeds a threshold value.

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