Container terminal energy consumption forecasting system and container terminal energy consumption forecasting 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 businesses 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] Electricity charges, which are one of the utility charges, are the sum of a basic charge and a power consumption 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 into or out of the container terminal by truck, and unloading or loading containers onto ships using large cranes. This makes it difficult to predict detailed loading and unloading schedules for each container, and it is also difficult to set patterns in advance for combinations of the amount of containers being handled, which are related to energy consumption, the size and weight of the containers, or the 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 stop the operation of the equipment within the container terminal. However, because container terminals are core logistics facilities, stopping the equipment requires considerable advance preparation, and it is not easy to stop operations.

[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 relating to the amount of containers handled in container handling operations and the amount of containers stored in the container terminal are acquired; In the calculation step, EnergyCalculate the unit energy consumption per container or per container handling operation based on the actual consumption data and the past performance data. In the 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 the amount of energy consumed 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, There was, configured to perform at least the following steps: In the first acquisition step, energy consumption results and past performance data relating to the amount of containers handled in container handling operations and the amount of containers stored in the container terminal are acquired; In the calculation step, Energy Calculate the unit energy consumption per container or per container handling operation based on the actual consumption data and the past performance data. In the 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 method predicts the amount of energy consumption per unit time based on the unit amount of energy consumption and the plan information. [Brief explanation of the drawings]

[0012] [Figure 1] Overall view of the Energy Consumption Prediction System 1 [Figure 2] Flowchart according to the first embodiment [Figure 3] Overall view of power supply system 2 [Figure 4] Flowchart diagram according to the second embodiment [Figure 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 INVENTION

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

[0014] First Embodiment Figure 1 shows 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 here is not limited to a private network, but may also 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 utilize a locally existing server device, but it may also be a cloud server. Also, 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 also be present in multiple servers.

[0016] The power monitoring system 6 is a system installed in a high-voltage power receiving and transforming facility, which monitors and controls the devices of the power receiving and transforming facility, and records information such as operation and measurement results.

[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, data related to actual cargo handling work, or container cargo handling work plans via the communication unit 81 to the power monitoring system 6 and the cargo handling management system 7 over the network. Details will be described later.

[0019] The recording unit 82 records information received from the power monitoring system 6 and cargo handling management system 7, as well as values ​​calculated by the calculation unit 84, which will be described later in detail. This may 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 the control unit 83, which will be described later, or as a memory such as a random access memory (RAM) that stores temporarily required information related to program calculations (arguments, arrays, etc.). Alternatively, a combination of these may be used.

[0020] The control unit 83 processes and controls the overall operations related to the server 8. The control unit 83 is, for example, a central processing unit (CPU) not shown. The control unit 83 reads out a predetermined program recorded in the memory unit 22 to transmit and receive data related to actual power consumption, data related to actual cargo handling work, or cargo handling work plans, and predict the amount of energy consumed per unit time. In other words, information processing by the software recorded in the memory unit 22 is specifically realized by the control unit 83, which is an example of hardware, and can be 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 a single unit, and may be implemented with multiple control units 83 for each function, or a combination thereof.

[0021] The calculation unit 84 calculates the amount of power consumption per container per unit time (hereinafter referred to as the "first unit of consumption") and the amount of power consumption per cargo handling operation (hereinafter referred to as the "second unit of consumption") based on data relating to actual power consumption and cargo handling operation results recorded in the recording unit 82, and also calculates a predicted value of the amount of power consumption based on the first unit of consumption and the second unit of consumption and data relating to the container cargo handling operation plan. Note that in this embodiment, the first unit of consumption and the second unit of consumption are calculated based on actual power consumption, but they may also be calculated based on 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 flow of this flowchart will be explained below.

[0023] First, past power consumption data for each piece of equipment held by the power monitoring system 6 and past cargo handling work performance data held by the cargo handling management system 7 are acquired via a network (S101). The various pieces of equipment referred to here include, but are not limited to, gantry cranes, portal cranes, outdoor lighting, a management building, and reefer containers. In this embodiment, the power monitoring system 6 and the cargo handling management system 7 are connected to other systems via a network. However, if they are not connected, the power consumption performance data and cargo handling work performance data may be manually input into the recording unit 82. The cargo handling work performance data may include, 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 container. Furthermore, in this embodiment, only actual electricity consumption data obtained from the electricity monitoring system 6 is considered as actual energy consumption data, but actual consumption data 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 actual electricity consumption data and actual cargo handling work data (S102). Here, the container in the first basic unit refers to a container that itself consumes electricity, fossil fuels, etc., such as a reefer container, and the unit time is, for example, one hour, but is selected depending on the data collection interval for the actual electricity consumption data and the actual cargo handling work data. Furthermore, the cargo handling work in the second basic unit refers to, for example, a single cargo handling operation using a gantry crane or portal crane, and also includes transportation work using other port cargo handling equipment such as a tractor head or top lifter.

[0025] For example, the first basic unit is calculated from the amount of power 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 basic unit is calculated from the amount of power 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 for the date and time for which the power consumption is predicted is obtained from the cargo handling management system 7 (S103). This 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 during which unloading, etc. will be performed, the number and times 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 times of container changes within the container terminal storage location, etc., but is not limited to these. 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 also 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, for example, the second basic unit.

[0028] This makes it possible to accurately predict energy consumption using a simple calculation formula based on 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 includes a power generation device 5 and that the server 8 includes a determination unit 85. In the following description, the same components as those in the first embodiment will be 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 comprises 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, selected to be the contracted 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 flow of this flowchart will be explained 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 the container handling work plan for 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 work and the first and second basic units calculated in S202, the predicted power consumption per unit time for each facility at the time scheduled in the plan data is calculated (S204).

[0036] Then, it is determined whether the power consumption calculated in S204 exceeds a preset threshold (S205), and if it is determined that the power consumption exceeds the threshold, the power generation device 5 is operated at the time when the power consumption exceeds the threshold, 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 equipment, but this is not limiting and the power generation device 5 may be connected to the grid power without cutting off the grid power. Furthermore, the power generation device 5 is operated manually, but may be controlled to operate automatically at the time when the threshold is exceeded.

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

[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 flow in this flowchart will be explained below.

[0040] First, past actual power consumption data for each piece of equipment 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 the container handling work plan for 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 work and the first and second basic units calculated in S302, the predicted power consumption per unit time for each piece of equipment at the time scheduled in the plan data is calculated (S304).

[0042] Then, it is determined whether the power consumption calculated in S304 exceeds a preset threshold (S305), and if it is determined that the power consumption exceeds the threshold, 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 will be exceeded (S306). At this time, if the power consumption exceeds the threshold due to charging the storage battery 9, it is more preferable that charging the storage battery 9 be stopped 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 grid connected to some of the equipment is cut off and power is supplied from the storage battery 9, but the power may be connected to the grid without being cut off, and this is not limiting. Furthermore, 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 contribute to reducing CO2 emissions from energy consumption within the container terminal, as well as curbing grid power consumption that exceeds the contracted power.

[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. Weather information includes, but is not limited to, outside temperature, weather, precipitation, and humidity.

[0046] Reefer containers are controlled to maintain cargo at a constant temperature, and power consumption increases on days and days when the temperature is high. Therefore, predictions can be further improved by correcting power consumption based on a correction coefficient calculated from the difference between the temperature at which the reefer container is maintained and the outside temperature. [Explanation of symbols]

[0047] 1 Energy Consumption Prediction System 1 2 Power Supply System 2 3 Power Supply System 3 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. An energy consumption prediction system for a container terminal, comprising: configured to perform at least the following steps: In the first acquisition step, actual energy consumption data and past performance data relating to the amount of containers handled in container handling operations and the amount of containers stored in the 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 energy consumption data and the past actual data; In the second acquisition step, plan information regarding the container handling operation and the container loading or unloading schedule 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, the 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: the server is configured to perform at least each of the following steps: In the first acquisition step, actual energy consumption data and past performance data relating to the amount of containers handled in container handling operations and the amount of containers stored in the 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 energy consumption data and the past actual data; In the second acquisition step, plan information regarding the container handling operation and the container loading or unloading schedule 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, configured to perform at least the following steps: In the first acquisition step, actual energy consumption data and past performance data relating to the amount of containers handled in container handling operations and the amount of containers stored in the 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 energy consumption data and the past actual data; In the second acquisition step, plan information regarding the container handling operation and the container loading or unloading schedule 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, the power generation device is operated for a time period during which the predicted energy consumption value exceeds the threshold. Power supply system.

5. A power supply system in a container terminal having a storage battery, configured to perform at least the following steps: In the first acquisition step, actual energy consumption data and past performance data relating to the amount of containers handled in container handling operations and the amount of containers stored in the 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 energy consumption data and the past actual data; In the second acquisition step, plan information regarding the container handling operation and the container loading or unloading schedule 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 the charging step charges the storage battery before a time when the predicted energy consumption value exceeds a threshold value.

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