Resource management system, integrated resource management device, and resource management method

Abstract

This resource management system solves an optimization problem having, for each subsystem, an amount of change in a KPI as a constraint condition and an additional allocation amount of a resource as an objective function, to thereby calculate additional allocation amounts for the subsystems such that, when the resource is redistributed on the basis of the additional allocation amounts, the KPIs improve in comparison with an initial resource allocation plan. The resource management system determines acceptance / non-acceptance of the resource reallocation for each subsystem by accepting reallocation if the calculated value of the KPI actually achieved by each of a plurality of subsystems when the resource is reallocated does not deteriorate, and determines whether to adopt the resource reallocation plan on the basis of the acceptance / non-acceptance for each of the plurality of subsystems.

Description

Resource management system, integrated resource management device, and resource management method

[0001] The present invention relates to a resource management system, an integrated resource management device, and a resource management method.

[0002] For example, Patent Document 1 discloses a power transmission control method, a power transmission management system, and a program that aim to "control the amount of electricity generated by private power generation facilities according to the demand of consumers who use the power interchange service, and transmit the generated electricity to the corresponding consumers via the power grid."

[0003] Specifically, the prior art disclosed in Patent Document 1 is configured as "a power transmission control method executed on a terminal connected to a communication network, which includes a process of individually predicting the amount of electricity that each consumer using a power interchange service will receive from the power grid, and a process of controlling the amount of electricity generated by each consumer's private power generation facility and transmitted to the power grid in accordance with the predicted amount of electricity, and when the private power generation facility is shared by multiple consumers using the power interchange service, the amount of electricity generated by the private power generation facility is controlled within a range that satisfies a distribution ratio for each consumer predetermined among the multiple consumers, and the distribution ratio is changed in a predetermined time unit."

[0004] Patent No. 7202928

[0005] Here, consider a case where a consumer is a fleet operator that operates multiple vehicles, including electric vehicles (EVs). Each base of the fleet operator is equipped with facilities capable of charging the EVs, and surplus electricity at each base can be shared among the bases as a shared resource according to a wheeling allocation plan.

[0006] In this case, there is a need to create vehicle operation plans and consignment allocation plans at multiple bases of a fleet operator while optimizing an overall KPI (Key Performance Indicator), which is the sum of the KPIs of each base.

[0007] However, in the above-mentioned conventional technology, the distribution ratio is determined based on the power demand of each consumer as a given condition, and therefore there is a problem in that it is not possible to take into consideration the optimization of the overall KPI, which changes depending on the increase or decrease in the power demand of each consumer. This problem is not limited to vehicle operation plans that allocate surplus power at each base as a shared resource, but also applies to cases where a utilization plan for shared resources at multiple bases is planned while taking into consideration the overall KPI.

[0008] The present invention has been made in consideration of the above circumstances, and aims to enable the creation of a utilization plan for shared resources at multiple bases while optimizing overall KPIs.

[0009] As one aspect for solving the above problem, there is provided a resource management system that includes a plurality of subsystems and calculates a resource allocation plan for allocating resources to the plurality of subsystems, the resource management system having a processor and a memory, the processor of the resource management system calculates an initial resource allocation plan for implementing initial allocation of resources to the plurality of subsystems, and calculates a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is implemented based on the initial resource allocation plan. and calculating an additional allocation amount for the subsystem that will improve the KPI compared to the initial resource allocation plan when the resources are reallocated based on the additional allocation amount by solving an optimization problem for each subsystem in which the amount of change in the KPI is a constraint and the amount of additional allocation of the resources is an objective function; calculating a resource reallocation plan for reallocating the resources to the plurality of subsystems based on the additional allocation amount and an expected value of the KPI that is expected to be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; calculating an estimated value of the KPI that will actually be achieved by each of the plurality of subsystems when the resources are reallocated based on the resource reallocation plan; comparing the estimated value with the expected value of the KPI, and deciding whether to accept the resource reallocation plan for each of the subsystems in which the calculated value of the KPI deteriorates and whether to accept the plan when the calculated value of the KPI does not deteriorate; and deciding whether to adopt the resource reallocation plan based on the acceptance decision for each of the plurality of subsystems.

[0010] According to the present invention, it is possible to formulate a utilization plan for shared resources at a plurality of bases while optimizing the overall KPI.

[0011] 1 is an explanatory diagram of an overview of a resource management system according to a first embodiment. A diagram showing an example of the configuration of a resource management system according to the first embodiment. A flowchart showing an example of resource management processing according to the first embodiment. A flowchart showing an example of resource management processing according to the first embodiment. A flowchart showing an example of resource management processing according to the first embodiment. A diagram showing an example of the configuration of consignment allocation time series data according to the first embodiment. A diagram showing an example of the configuration of resource addition proposal data according to the first embodiment. A diagram showing an example of the configuration of an estimated ΔKPI value, a calculated ΔKPI value, and acceptance / rejection data (successful case) according to the first embodiment. A diagram showing an example of the configuration of an estimated ΔKPI value, a calculated ΔKPI value, and acceptance / rejection data (failed case) according to the first embodiment. A diagram showing an example of the display of a resource allocation negotiation process according to the first embodiment. A diagram showing an example of calculation (subsystem 1 (proposal side)) of a resource allocation negotiation process according to the first embodiment. A diagram showing an example of calculation (subsystem 2 (decision side)) of a resource allocation negotiation process according to the first embodiment. A flowchart showing a detailed example of Δ resource calculation processing by interchanging an objective function and a constraint condition according to the first embodiment. An explanatory diagram of a modified example of the first embodiment. 1 is a flowchart showing an example of a resource management process (planning phase: resource allocation negotiation process) according to a second embodiment. FIG. 2 is a diagram showing an example of the configuration of ΣΔKPI (success case) according to the second embodiment. FIG. 3 is a diagram showing an example of the configuration of ΣΔKPI (failure case) according to the second embodiment. FIG. 4 is a diagram showing an example of a ΔKPI / Δresource map according to a third embodiment. FIG. 5 is a diagram showing an example of a Δresource / ΔKPI dataset according to the third embodiment. FIG. 6 is a flowchart showing an example of an energy management process (planning phase: initial planning process) according to the third embodiment.

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that the embodiments described below do not limit the invention according to the claims, and not all of the elements and combinations thereof described in the embodiments are necessarily essential to the solution of the invention.

[0013] In the following description, a program that realizes each processing function unit is executed by a processor to perform a predetermined process while appropriately using storage resources (e.g., memory) and / or communication interface devices (e.g., ports). The processor is, for example, a CPU (Central Processing Unit). Therefore, the process executed by each processing function unit may be a process performed by the processor or a computer having that processor.

[0014] In the following description, identical or similar components are given the same reference numerals, and in the following embodiments and examples, the description may be omitted or only the differences may be described. Furthermore, when there are multiple identical or similar components, they may be described with the same reference numerals but with different subscripts. Furthermore, when it is not necessary to distinguish between these multiple components, the subscripts may be omitted. The number of each component may be singular or plural unless otherwise specified.

[0015] In the following explanation, various information is represented in table format, but the information is not limited to table format and may be in CSV (Comma Separated Values) or other formats. Since various information does not depend on the data format, for example, an "XXX table" can be called "XXX information."

[0016] Furthermore, among the items in the various information, the names of items that include information to distinguish the record in question from other records, such as "# (number)", "identification information", "ID", and "name", may be interchangeable.

[0017] 1 is a diagram illustrating an overview of a resource management system S according to a first embodiment. In this embodiment, the resource management system S is described as a multi-site fleet energy management system having one power transmission site that transmits surplus power from its own site and two power receiving sites that receive surplus power from other sites. The power transmission site is equipped with a large-capacity distributed power source, and transmits excess power, which is a shared resource, to the power receiving site in excess of the power demand for buildings and EV charging at the own site.

[0018] Each of the power transmission bases and power receiving bases is a charging base (vehicle depot, logistics center, bus terminal, etc.) for multiple electric vehicles (EVs) of a fleet operator (bus operator, truck operator, etc.) that operates multiple vehicles. The fleet operator may be a single operator or multiple operators in a cooperative relationship.

[0019] Each base is equipped with distributed power sources (PV (PhotoVoltaic, solar power generation equipment), fuel cells, engine generators including hydrogen co-fuel combustion, etc.), and surplus electricity (power generation exceeding demand) at each base is shared as a shared resource (sometimes simply called a resource). For example, in Japan, under the self-dispatch system, surplus electricity can be shared by using the transmission and distribution lines of the electricity transmission and distribution company.

[0020] In this embodiment, the vehicle operation mode is assumed to be route delivery and route bus (trucks and buses are dispatched along fixed circular routes), but the operation mode and vehicle type are not limited. The vehicles may be EVs only, or a mixture of EVs and internal combustion engine vehicles (ICEs). The difference in performance (cruising range and transport capacity) between EVs and ICEs or between EVs determines the degree of freedom in vehicle dispatch. Key performance indicators (KPIs) such as CO2 emissions and energy costs change depending on the frequency of charging opportunities and the power supply configuration of the power supply.

[0021] The EMS (Energy Management System) at each base is a set of independent subsystems (loosely coupled systems) that individually create power supply and demand plans (power generation, charging and discharging of stationary batteries, and EV charging). The EMS at each base may be a system that includes the FMS (tightly coupled system), or a system independent of the FMS. In this embodiment, the EMS and FMS are tightly coupled systems that simultaneously create power supply and demand plans and vehicle operation plans for each base.

[0022] The base EMS2, which is a subsystem loosely coupled via a network, is provided for each of the power transmission and receiving bases and has the function of a Fleet Management System (FMS).The base EMS2 simultaneously creates a power supply and demand plan for its own base (plans for power generation, charging and discharging of stationary batteries, and EV charging) and a vehicle operation plan (dispatch of vehicles to specified routes).

[0023] In this embodiment, the resource management system S is configured to include a multi-site integrated EMS (integrated resource management device) 1 and multiple base EMSs 2. However, the distribution of the functions of the multi-site integrated EMS 1 and the multiple base EMSs 2 is not limited to this embodiment, as described below. That is, the processing performed by the multi-site integrated EMS 1 may be performed by one or multiple base EMSs 2, and the processing performed by one or multiple base EMSs 2 may be performed by the multi-site integrated EMS 1.

[0024] The multi-site integrated EMS1, which has the distribution function, manages the resource allocation negotiation process between the base EMS2 of multiple power receiving sites based on resource sharing information (time series data of surplus power) from the base EMS2 of the power transmission site, and develops a transmission allocation plan (resource allocation plan).

[0025] First, in step S1, the base EMS 2 of the power transmission base transmits information about surplus power at its own base as resource sharing information to the multi-base integration EMS 1. Next, in step S2, the multi-base integration EMS 1 calculates a resource allocation plan based on the resource sharing information received from the base EMS 2 of the power transmission base (initial calculation).

[0026] Next, in step S3, the multi-site integrated EMS 1 transmits the resource allocation plan calculated in step S2 to the site EMSs 2 of the power receiving sites 1 and 2.

[0027] Next, in step S4, the base EMSs 2 of the power receiving bases 1 and 2 initially calculate resource usage plans based on the resource allocation plan transmitted in step S3. If the base EMS 2 of the power receiving base 1 is expected to improve its own base's individual KPI by adding resources based on the resource allocation plan, it calculates resource addition proposal data D102 (described below) including Δresources (amount of resource addition) and ΔKPI (amount of KPI improvement). Δresources (amount of resource addition) and ΔKPI (amount of KPI improvement) are called negotiation parameters. ΔKPI is a value obtained by subtracting the KPI after the resource addition from the KPI before the resource addition.

[0028] In step S5, the base EMS 2 of the power receiving base 1 transmits the negotiation parameters calculated in step S4 to the multi-base integrated EMS 1. Note that the base EMS 2 of the power receiving base 2 does not calculate negotiation parameters or transmit them to the multi-base integrated EMS 1 because it has determined that adding resources based on the resource allocation plan transmitted in step S3 is not likely to improve the individual KPI of its own base.

[0029] Next, in step S6, the multi-site integrated EMS 1 recalculates the resource allocation plan based on the resource addition proposal (negotiation index) received from the site EMS 2 of the power receiving site 1. Next, in step S7, the multi-site integrated EMS 1 transmits the resource allocation plan together with a response request to the site EMS 2 of the power receiving sites 1 and 2.

[0030] Next, in step S8, the base EMSs 2 of the power receiving bases 1 and 2 recalculate the resource utilization plan based on the resource allocation plan transmitted in step S7 and determine whether to accept or reject the resource allocation plan. Next, in step S9, the base EMSs 2 of the power receiving bases 1 and 2 respond to the multi-base integrated EMS 1 with the acceptance or rejection determined in step S8.

[0031] The multi-site integrated EMS 1 aggregates the responses from the site EMS 2 of the power receiving sites 1 and 2, evaluates the overall KPI, and if improvement is expected, adopts the resource allocation plan calculated in step S6. The multi-site integrated EMS 1 notifies the site EMS 2 of the power receiving sites 1 and 2 that the resource allocation plan has been adopted.

[0032] 2 is a diagram showing an example of the configuration of the resource management system S according to the first embodiment. The resource management system S includes a multi-site integrated EMS 1 and a plurality of site EMSs 2.

[0033] The multi-site integrated EMS 1 includes a communication device 11, a computing device 12, a storage device 13, and an input / output device 14. The communication device 11 is a communication interface that enables the multi-site integrated EMS 1 to communicate with the site EMS 2 via a public network or a closed network, whether wired or wireless. The computing device 12 is a processor represented by a CPU (Central Processing Unit). The storage device 13 includes memory and storage. The input / output device 14 includes input devices such as a keyboard and a mouse and output devices such as a display.

[0034] The arithmetic device 12 executes a program in cooperation with the memory to realize a resource allocation planning unit 121 and a response aggregation unit 122. The arithmetic device 12 also executes a program in cooperation with the memory to realize a ΔKPI / Δresource map display function unit 141 as an output function on the input / output device 14.

[0035] The storage device 13 stores the surplus power time-series data 131 as well as various programs and various data.

[0036] The base EMS 2 has a communication device 21, a calculation device 22, a storage device 23, and an input / output device 24. The communication device 21 is a communication interface that enables the base EMS 2 to communicate with the multi-base integrated EMS 1 via a public network or a closed network, whether wired or wireless. The calculation device 22 is a processor such as a CPU. The storage device 23 includes memory and storage. The input / output device 24 includes input devices such as a keyboard and a mouse and output devices such as a display.

[0037] The arithmetic device 22 executes the program in cooperation with the memory to realize a resource usage planning unit 221, a Δ resource calculation unit 222, and a ΔKPI evaluation and response unit 223. The arithmetic device 22 also executes the program in cooperation with the memory to realize a vehicle operation and power supply and demand plan display function unit 241 on the input / output device 24.

[0038] The storage device 23 stores plan condition data 231, vehicle operation data 232, and power supply and demand data 233, as well as various programs and various data.

[0039] The plan condition data 231 includes facility information, operation conditions, and supply and demand conditions. The facility information includes EV vehicle specifications, distributed power source specifications, and stationary battery (BESS (Battery Energy Storage System)) specifications. The operation conditions include the route configuration on which vehicles including EVs operate, EV electricity consumption and fuel efficiency, and electricity and fuel unit prices. The supply and demand conditions include a building electricity demand forecast and a solar power generation output forecast.

[0040] The vehicle operation data 232 is a vehicle operation plan (vehicle allocation to a route) calculated by the resource utilization planning unit 221 .

[0041] The power supply and demand data 233 is a power supply and demand plan (including EV charging, charging and discharging of stationary batteries, power generation, and photovoltaic power generation output suppression) calculated by the resource utilization planning unit 221 .

[0042] The multi-site integrated EMS 1 and the site EMS 2 transmit and receive information by performing network communication using the communication devices 11 and 21. The multi-site integrated EMS 1 may be either an on-premise system or a cloud system.

[0043] The base EMS 2 may be an add-in system for a fleet management system that creates vehicle operation plans for each fleet operator. Alternatively, the base EMS 2 may be a system that includes or is included in the fleet management system of each fleet operator. Alternatively, the base EMS 2 may be a cloud system that links with the fleet management system of each fleet operator.

[0044] (Resource Management Processing According to First Embodiment) FIGS. 3A, 3B, and 3C are flowcharts showing an example of resource management processing according to the first embodiment.

[0045] In Figures 3A to 3C, the functions of the base EMS (subsystem 1) 2-1 and the base EMS (subsystem 1) 2-2 are equivalent. The base EMS (subsystem 1) 2-1 is the proposer, and the base EMS (subsystem 1) 2-2 is the decision maker. The wheeling allocation time series data D101 is data obtained by increasing or decreasing the surplus power time series data (not shown) by multiplying it by a predetermined coefficient. In other words, the negotiation parameter is a scalar value. The surplus power time series data could be increased or decreased for each time frame of the time series, but this would result in the negotiation parameter being vectorized and becoming enormous. Furthermore, changes in self-wheeling over time are absorbed by a stationary battery installed at the base. For this reason, the wheeling allocation time series data D101 is increased or decreased by a predetermined coefficient calculated for each predetermined unit of time, such as a day, and multiplied by the surplus power time series data.

[0046] Steps S11 to S15 in FIG. 3A show the resource management process (planning phase: initial planning process).

[0047] First, in step S11, the multi-site integrated EMS 1 receives surplus power time-series data from the base EMS 2 of the power transmission base and updates the resource sharing information. Next, in step S12, the resource allocation planning unit 121 of the multi-site integrated EMS 1 calculates an initial resource allocation plan, i.e., an initial wheeling allocation plan. In the initial calculation of the wheeling allocation plan, the multi-site integrated EMS 1 equally allocates the surplus power time-series data to the target bases for each date and time. The initial wheeling allocation plan is as exemplified in the wheeling allocation time-series data D101 (before negotiation (the table on the left in Figure 4)).

[0048] In the resource allocation plan shown in Fig. 4, solar power generation is assumed as the surplus power source, so surplus power occurs during the daytime. Therefore, before resource allocation negotiations shown in the table on the left of Fig. 4, resources are equally allocated between the base EMSs 2-1 and 2-2.

[0049] Next, in step S13, the resource allocation planning unit 121 of the multi-site integrated EMS 1 transmits the pre-negotiation consignment allocation time series data D101 corresponding to the initial consignment allocation plan (initial resource allocation plan) initially calculated in step S12 to the site EMSs 2-1 and 2-2.

[0050] Next, in step S14, the resource utilization planning unit 221 of the base EMS 2-1, 2-2 calculates a utilization plan for the shared resources at the base and an individual KPI for the base based on the consignment allocation time-series data D101 transmitted in step S13 from the multi-base integrated EMS 1. The resource utilization planning unit 221 of the base EMS 2-1, 2-2 calculates, for example, a vehicle operation and electricity supply and demand plan as the utilization plan for the shared resources, and calculates CO2 emissions as the individual KPI for the base.

[0051] Next, in step S15, the resource usage planning unit 221 of the base EMS 2-1, 2-2 determines whether the individual KPI of the base calculated in step S14 will improve by using the shared resource. If the individual KPI of the base will improve, the resource usage planning unit 221 adopts the shared resource usage plan calculated in step S14. In step S15, if the individual KPI of the base will not improve, the base EMS 2-1, 2-2 rejects the shared resource usage plan calculated in step S14.

[0052] Steps S16 to S28 in Fig. 3B show the resource management process (planning phase: resource allocation negotiation process). In the resource allocation negotiation process shown in Fig. 3B, the base EMS 2-1, believing that additional shared resources will further improve its own base's individual KPI, sends a request for adding shared resources to the multi-base integrated EMS 1. Note that only the base EMS 2-1 may send a request for adding shared resources to the multi-base integrated EMS 1, or both the base EMSs 2-1 and 2-2 may send a request for adding shared resources to the multi-base integrated EMS 1.

[0053] Next, in step S16, the Δ resource calculation unit 222 of the base EMS 2-1 calculates Δ resources if the individual KPI of the base calculated in step S14 does not improve by using shared resources. Δ resources can be calculated by solving an optimization problem with the change amount ΔKPI (CO2 reduction amount) as a constraint and Δ resources (additional amount of consignment allocation or additional allocation amount) as an objective function. ΔKPI represents an improvement in the KPI when it is positive, and a negative value represents a deterioration in the KPI when it is negative. Δ resources represent an addition to consignment allocation when it is positive, and a reduction in consignment allocation when it is negative.

[0054] Next, in step S17, the Δ resource calculation unit 222 of the base EMS 2-1 determines whether the ΔKPI calculated in step S16 has improved (is a positive value). If the ΔKPI has improved, the Δ resource calculation unit 222 generates resource addition proposal data D102 ( FIG. 5 ) including the Δ resource corresponding to this ΔKPI. The resource addition proposal data D102 corresponds to each row identified by an ID in FIG. 5 .

[0055] The resource addition proposal data D102 shown in Figure 5 is data for each of the proposing base EMS 2-1. The resource addition proposal data D102 is described as a surcharge rate for the consignment allocation time-series data D101. For example, if Δresource is "+0.5", a resource allocation of 1.5 times (1 + 0.5) the consignment allocation time-series data D101 in the resource allocation plan is proposed.

[0056] Next, in step S18, the Δ resource calculation unit 222 of the base EMS 2-1 transmits the resource addition proposal data D102 generated in step S17 to the multi-base integrated EMS 1.

[0057] Next, in step S19, the resource allocation planning unit 121 of the multi-site integrated EMS 1 recalculates the resource allocation plan (resource reallocation plan) and the estimated value of ΔKPI (i.e., the consignment allocation plan and the estimated value of CO2 increase). The resource allocation planning unit 121 of the multi-site integrated EMS 1 recalculates the resource allocation plan (resource reallocation plan) and the estimated value of ΔKPI based on the resource addition proposal data D102 transmitted from the base EMS 2-1 in step S18. The recalculated resource allocation plan inherits the ID of the resource addition proposal data D102 received from the base EMS 2-1. The resource allocation plan recalculated in step S20 is as shown in the consignment allocation time-series data D101 (after negotiation (the table on the right side of Figure 4)).

[0058] After the resource allocation negotiation shown in the table on the right side of FIG. 4, the resource allocation between base EMS 2-1 and base EMS 2-2 has changed to 1.5:0.5 compared to when the resource allocation before the negotiation was equal.

[0059] Next, in step S20, the multi-site integrated EMS 1 transmits to the site EMSs 2-1 and 2-2 an acceptance / rejection inquiry that includes the resource allocation plan and estimated ΔKPI value recalculated in step S19. Here, in the case where there are two subsystems, as in this embodiment, the negative value of the Δ resource of the proposing subsystem is set as the positive Δ resource of the determining subsystem. Furthermore, in the case where there are three or more subsystems, the negative value of the Δ resource of the proposing subsystem is prorated by the number of sites in the determining subsystem, and set as the positive Δ resource of the determining subsystem. Similarly, the negative value of the ΔKPI of the proposing subsystem is prorated by the number of sites in the determining subsystem, and set as the estimated ΔKPI of the determining subsystem.

[0060] Next, in step S21, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 recalculates the shared resource utilization plan at the base based on the resource allocation plan transmitted from the multi-base integrated EMS 1 in step S20.

[0061] Next, in step S22, the ΔKPI evaluation and response unit 223 of the base EMS2-2 recalculates the variation ΔKPI of the individual KPI of the base that was initially calculated in step S14, based on the shared resource utilization plan recalculated in step S21.

[0062] Next, in step S23, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 compares the ΔKPI (ΔKPI calculated value) calculated in step S22 with the expected ΔKPI value transmitted from the multi-base integrated EMS 1 in step S20. If the ΔKPI calculated value is equal to or less than the expected ΔKPI value, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 accepts the resource allocation plan transmitted from the multi-base integrated EMS 1 in step S20. On the other hand, if the ΔKPI calculated value is greater than the expected ΔKPI value, the ΔKPI evaluation and response unit 223 rejects the resource allocation plan transmitted from the multi-base integrated EMS 1 in step S20 and determines whether to accept the resource allocation plan.

[0063] On the other hand, in step S24, the ΔKPI evaluation and response unit 223 of the base EMS 2-1 decides to accept the resource allocation plan because the resource allocation plan sent from the multi-base integrated EMS 1 in step S20 is based on the shared resource addition proposal made by its own device.

[0064] Next, in step S25, the resource utilization planning unit 221 of the base EMS 2-2 transmits to the multi-base integrated EMS 1 a response indicating whether or not the resource allocation plan determined in step S23 or S24 is accepted or rejected.

[0065] Next, in step S26, if the resource allocation planning unit 121 of the multi-site integrated EMS 1 receives responses accepting the resource allocation plan from all of the base EMSs 2 that are subsystems, the resource allocation planning unit 121 determines whether to adopt the resource allocation plan recalculated in step S19. If there is even one base EMS 2 that has sent a rejection response, the resource allocation planning unit 121 of the multi-site integrated EMS 1 determines whether to reject the recalculated resource allocation plan in step S19.

[0066] 3B (planning phase: resource allocation negotiation process) may be repeatedly executed until the resource allocation plan is minimized in step S26. Alternatively, if the number of times the resource management process (planning phase: resource allocation negotiation process) is repeatedly executed reaches an upper limit, the resource allocation plan initially calculated in step S12 (FIG. 3A) may be adopted.

[0067] 6A and 6B show examples of the determination results of the multi-site integrated EMS 1 in step S26 based on the responses sent from both the site EMSs 2-1 and 2-2 to the multi-site integrated EMS 1 in step S25.

[0068] 6A, the acceptance / rejection of the resource allocation plan with "ID" "Plan0001" at all base EMSs 2-1 and 2-2 is "accepted," and the total of the ΔKPI calculated values ​​(CO2 emissions) across base EMSs 2-1 and 2-2 is "-20." Because the ΔKPI calculated value of "-20" is a better value than the assumed ΔKPI value of "0," the adoption of the resource allocation plan with "ID" "Plan0001" is "established."

[0069] 6B, the acceptance / rejection of the resource allocation plan with "ID" "Plan0001" by base EMS 2-1 is "accepted." Meanwhile, the acceptance / rejection of base EMS 2-2 is "rejected," and the sum of the ΔKPI calculated values ​​(CO2 emissions) for base EMS 2-1 and 2-2 is "+20." The ΔKPI calculated value of "+20" is a worse value than the ΔKPI assumed value of "0," so the adoption of the resource allocation plan with "ID" "Plan0001" is "not established."

[0070] Next, in step S27, the resource allocation planning unit 121 of the multi-site integrated EMS 1 sends an adoption notice that the resource allocation plan adopted in step S26 has been adopted to all of the base EMSs 2-1 and 2-2. Next, in step S28, the resource usage planning units 221 of the base EMSs 2-1 and 2-2 adopt the resource usage plans for the shared resources that were decided to be adopted in step S28. The resource usage plans adopted in step S28 are resource usage plans after resource allocation negotiation.

[0071] Step S29 in FIG. 3C shows the resource management process (execution phase).

[0072] In step S29, the base EMSs 2-1 and 2-2 implement the resource usage plan adopted in step S15 (FIG. 3A) or step S28 (FIG. 3B). Specifically, the base EMSs 2-1 and 2-2 operate vehicles at their own bases, charge EVs, charge and discharge stationary batteries, etc., in accordance with the resource usage plan. The resource usage plan adopted in step S15 is the resource usage plan before the resource allocation negotiation.

[0073] (Display of Resource Allocation Negotiation Process According to Embodiment 1) Fig. 7 is a diagram showing an example of a display 141D of the resource allocation negotiation process according to embodiment 1. The ΔKPI / Δresource map display function unit 141 of the multi-site integrated EMS 1 can visualize the resource allocation negotiation process to the user on a display screen via a display 141D as shown in Fig. 7 .

[0074] Referring to display 141D, after two rounds of resource allocation negotiations, the total CO2 emissions at base 1 corresponding to base EMS 2-1 and base 2 corresponding to base EMS 2-2 have clearly decreased, as can be seen from the graph on the left side of Figure 7.

[0075] On the other hand, as can be seen from the graph on the right of Figure 7, CO2 emissions at base 1 clearly decrease as self-dispatch increases, while CO2 emissions at base 2 increase as self-dispatch decreases. Self-dispatch refers to transmitting electricity generated by a company to its own facilities via the power transmission and distribution network. Arrows 141D1 and 141D2 in the graph on the right of Figure 7 indicate the progress of resource allocation negotiations, such as the initial resource allocation, the resource allocation after the first negotiation, and the resource allocation after the second negotiation.

[0076] 7, it can be seen that for base 1, the increase in the slope of arrow 141D1 (ΔKPI / Δresources) is large, the amount of CO2 reduction is large relative to the increase in the consignment allocation amount, and the utilization value of the shared resources is high. For base 2, the decrease in the slope of arrow 141D2 (ΔKPI / Δresources) is small, the amount of CO2 increase is small relative to the decrease in the consignment allocation amount, and the utilization value of the shared resources is low. It is suggested that base 1, which has high utilization value, will use more of the shared resources, and it can be seen that this will improve the overall KPI, and that this will be achieved through the resource allocation negotiation process.

[0077] By referring to display 141D, the user can understand how CO2 emissions change as the self-consignment volume of each base increases or decreases, and can recognize whether reallocation of shared resources is appropriate.

[0078] 8 and 9 are diagrams illustrating an example of calculation of the resource allocation negotiation process according to embodiment 1. Fig. 8 illustrates calculation of the resource allocation negotiation process in the base EMS 2 of subsystem 1 (proposal side). Fig. 9 illustrates calculation of the resource allocation negotiation process in the base EMS 2 of subsystem 2 (decision side).

[0079] 8 and 9, at power receiving points 1 and 2, solar power is used to charge the BESS during the daytime, from approximately 8:00 to 16:00, and to charge the EV during the nighttime, from 16:00 to 8:00 the next day. In graphs (b11), (b12), (b21), and (b22) in Fig. 8, the positive portion of the vertical axis represents power demand, and the negative portion represents power supply.

[0080] At power receiving point 1 of subsystem 1 (proposal side) shown in FIG. 8 , before resource allocation negotiations, as shown in graph (b11), there are restrictions on contracted power, and the amount of power that can be charged by BESS during the day is also small due to the small amount of self-consignment during the day. Therefore, the amount of charge for EV1, EV2, and EV3 due to BESS discharge at night is limited. For this reason, as shown in graph (a11), EV1, EV2, and EV3 are assigned to deliveries on shorter routes than internal combustion engine vehicles ICE1, ICE2, and ICE3. ICE stands for Internal Combustion Engine.

[0081] On the other hand, after resource allocation negotiations at the power receiving point 1 of the subsystem 1 (proposal side) shown in FIG. 8 , as shown in graph (b12), the amount of power charged by the BESS during the day increases because self-consignment during the day is added (see arrow "1" in graph (b12)). This increases BESS discharge at night (see arrow "2" in graph (b12)), which in turn increases the amount of power charged to EV1, EV2, and EV3 (see arrow "3" in graph (b12)). Therefore, as shown in graph (a12), EV1, EV2, and EV3 are assigned to deliveries over longer distances compared to the internal combustion engine vehicles ICE1, ICE2, and ICE3.

[0082] On the other hand, at power receiving point 2 of subsystem 2 (decision side) shown in Figure 9, before resource allocation negotiation, as shown in graph (b21), there is sufficient self-consignment during the day and sufficient power for BESS charging during the day. Therefore, there is sufficient power for charging EV1, EV2, and EV3 through BESS discharge at night. Therefore, as shown in graph (a21), EV1, EV2, and EV3 are assigned to deliveries on long-distance routes compared to internal combustion engine vehicles ICE1, ICE2, and ICE3.

[0083] On the other hand, after resource allocation negotiations at the power receiving point 2 of the subsystem 2 (decision-making side) shown in FIG. 9 , although the self-dispatch during the daytime decreases, the amount of power for BESS charging during the daytime is still sufficiently secured (see arrow "1" in graph (b22)). Therefore, the BESS discharge at night is still sufficiently secured (see arrow "2" in graph (b22)), and thus the amount of power for charging EV1, EV2, and EV3 is still sufficiently secured (see arrow "3" in graph (b22)). Therefore, as shown in graph (a22), even though the self-dispatch at the power receiving point 2 decreases, there is no change in the dispatch of EV1, EV2, and EV3, so that they are still assigned to deliveries on long-distance routes compared to the internal combustion engine vehicles ICE1, ICE2, and ICE3. However, because the amount of retail electricity consumed at night increases, CO2 emissions increase.

[0084] (Details of Δ resource calculation process (steps S16 to S18 (FIG. 3B))) FIG. 10 is a flowchart showing a detailed example of the Δ resource calculation process by interchanging the objective function and constraint conditions according to the first embodiment. FIG. 10 is a flowchart detailing steps S16 to S18 shown in FIG. 3B. In this embodiment, the detailed processing of the Δ resource calculation process is executed by the base EMS 2-1, which is the proposing subsystem 1.

[0085] Before explaining the flowchart, we will explain the constraints and objective functions of the vehicle operation plan and the power supply and demand plan. The constraints and objective functions of the vehicle operation plan and the power supply and demand plan can be written and calculated in the same way as the method described in Reference 1, for example. Reference 1: "Vehicle dispatch / charging plan to expand electrification coverage in route delivery using a mix of EV and diesel vehicles" (Kumagaya Masatoshi et al., 2022 Electrical Engineering Institute of Japan Power and Energy Division Conference)

[0086] In this embodiment, the application of the technology of Document 1 is expanded to include power generation by on-site PV (photovoltaic power generation equipment within a base), charging and discharging of stationary batteries, and self-consignment.

[0087] In the following formulas, capital letters represent constants (given conditions) and lowercase letters represent variables (planned objects). In this embodiment, vehicles are not shared between multiple bases, and vehicle operation plans are created for each base.

[0088] 1. Constraints (Vehicle Allocation) Let x(v,d,r) be the allocation variable that represents the association between vehicle v and route r on date d (1: allocation, 0: non-allocation), and the constraint to allocate vehicle v to any route r on date d is expressed by formula (1). Σ_r in formula (1) represents the sum over all routes r. Σ_r x(v,d,r) = 1... (1)

[0089] The constraint that one vehicle is assigned to route r on date d is expressed by equation (2). Σ_v x(v,d,r) = 1 ... (2)

[0090] Here, if A_travel(k,r) is a parameter matrix representing the travel distance on route r at time k, the constraint representing the travel distance z(v,t) of vehicle v at time t based on the dispatch variables is expressed by equation (3): z(v,t) = z(v,d,k) = Σ_r (x(v,d,r) A_travel(k,r)) ... (3)

[0091] Furthermore, assuming that A_site(k,r) is a parameter matrix (1: stay, 0: absence) representing the stay at a site on route r at time k, and C is the charger output, the constraint (always 0 for ICE) representing the charge amount y(v,t) of vehicle v at time t based on vehicle dispatch is expressed by equation (4): y(v,t) = y(v,d,k) ≦ C Σ_r (x(v,d,r) A_site(k,r)) ... (4)

[0092] 2. Constraints (changes in vehicle energy storage) If the EV's electricity consumption is M_ev(v) [km / kWh], the constraint that represents the change in the energy storage amount b(v,t) of vehicle v is expressed by equation (5). Equation (5) indicates that the energy storage amount at time t is the value obtained by adding the charge amount y(v,t) at time t to the energy storage amount at time t-1 and subtracting the traveling power consumption amount z(v,t) / M_ev(v) at time t. b(v,t) = b(v,t-1) + y(v,t) - z(v,t) / M_ev(v) ... (5)

[0093] The constraint that limits the change in the amount of stored electricity due to charging and running to between the lower limit value Bmin(v) and the upper limit value Bmax(v) of the amount of stored electricity of vehicle v is expressed by equation (6): Bmin(v) ≦ b(v,t) ≦ Bmax(v) (6)

[0094] 3. Constraints (base supply and demand balance) The constraints (base supply and demand balance) are expressed by equation (7). W_bld(t) + w_bs,charge(t) + Σ_v y(v,t) = W_pv(t) + w_rt(t) + w_sc(t) + w_bs,discharge(t) ... (7) where, W_bld(t): Building electricity demand (given time series data) W_pv(t): On-site PV power generation (given time series data) w_bs,charge(t): Stationary battery charge amount (subject to exclusion constraints with discharge amount and stationary battery capacity constraints) w_bs,discharge(t): Stationary battery discharge amount w_rt(t): Retail supply amount (upper limit constrained by contracted power) w_sc(t): Self-dispatched electricity reception amount.

[0095] 4. Regarding the amount of power received by self-dispatch The amount of power received by self-dispatch is expressed by formula (8): w_sc(t) = s W_pl(t) ... (8) Where, W_pl(t): Dispatch allocation time series data...the surplus power allocated to this base in the dispatch allocation plan drawn up by the allocation function s: Dispatch allocation gain (if s is fixed at 1, the surplus power is received and used according to the dispatch allocation plan).

[0096] 5. Objective function (minimization of CO2 emissions) The objective function (minimization of CO2 emissions) is expressed by equation (9). G_rt Σ_t w_rt(t) + G_sc Σ_t w_sc(t) + G_ice Σ_v,v ∈V_ice (Σ_t z(v,t) / M_ice(v)) ... (9) Here, G_rt is the CO2 emission coefficient of retail supply electricity [kg-CO2 / kWh], G_sc is the CO2 emission coefficient of surplus electricity [kg-CO2 / kWh], G_ice is the CO2 emission coefficient of ICE fuel [kg-CO2 / L], and M_ice(v) is the fuel efficiency of ICE [km / L]. The first term is the CO2 emissions from retail supply of buildings and EVs combined, the second term is the CO2 emissions from self-consignment, and the third term is the CO2 emissions from ICE.

[0097] Minimizing equation (9) minimizes the CO2 emissions from buildings and vehicles (EVs and ICEs), and also minimizes the CO2 emissions from vehicles.

[0098] Furthermore, by setting an upper limit to the objective function of equation (9) and minimizing the wheeling distribution gain, i.e., by exchanging the objective function and the constraints, the wheeling distribution amount required to keep the CO2 emissions below a predetermined level can be calculated. The CO2 emissions and wheeling distribution amount are expressed as differences, respectively, resulting in ΔKPI (CO2 reduction amount) and Δresources (wheeling distribution additional amount).

[0099] Although the objective function is set to CO2 emissions here, OPEX can also be minimized by describing it in terms of retail supply charges, self-transportation charges, or fuel unit prices instead of CO2 emissions.

[0100] First, in step S16a, the Δ resource calculation unit 222 of the base EMS 2-1 sets the wheeling allocation gain to a fixed value of 1 as a constraint condition, and calculates the vehicle operation plan, power supply and demand plan, and reference KPI (CO2 emissions) with the objective function being minimization of CO2 emissions (forward calculation).

[0101] Next, in step S16b, the Δ resource calculation unit 222 replaces the objective function and constraint conditions of step S16a. That is, an upper limit of the improvement reference KPI is set as a constraint condition, and the objective function is set to minimize the wheeling allocation gain. The upper limit of the improvement reference KPI is a value better than the reference KPI, and if the reference KPI is CO2 emissions, it is a value smaller than the reference KPI.

[0102] Next, in step S16c, the Δ resource calculation unit 222 calculates the vehicle operation plan, the power supply and demand plan, the improvement standard KPI, and the wheeling allocation gain using the constraints and objective function set in step S16b (inverse calculation). Here, if the improvement standard KPI does not match the upper limit, the calculation is repeated.

[0103] Next, in step S16d, the Δ resource calculation unit 222 determines whether the improved KPI can be calculated in step S16c (whether there is a solution for the inverse calculation). If the improved KPI can be calculated in step S16c, the Δ resource calculation unit 222 proceeds to step S16e, and if the improved KPI cannot be calculated, the Δ resource calculation unit 222 proceeds to step S16g.

[0104] In step S16e, the Δ resource calculation unit 222 calculates the difference value ΔKPI (CO2 reduction amount) between the standard KPI calculated in step S16a and the improved KPI calculated in step S16c, and the wheeling distribution gain at that time. The Δ resource calculation unit 222 also calculates the Δ resource (wheeling distribution additional amount) by adding the calculated value of the wheeling distribution gain calculated in step S16c to the fixed value 1 of the wheeling distribution gain set in step S16a. However, the Δ resource (wheeling distribution additional amount) calculated here is the ratio of the resource after negotiation to the resource before negotiation.

[0105] Next, in step S16f, the Δ resource calculation unit 222 makes a resource addition proposal (transmits the Δ resource and ΔKPI to the multi-site integrated EMS 1, which is the allocation function).

[0106] On the other hand, in step S16g, the Δ resource calculation unit 222 postpones the resource addition proposal and does not execute it.

[0107] In the first embodiment described above, as long as the overall KPI is improved, the additional allocation of shared resources is prioritized for a base that has declared that its KPI will be improved if additional shared resources are allocated to that base. This allows for the optimization of the overall KPI, while quickly creating a usage plan for shared resources at multiple bases on a first-come, first-served basis.

[0108] (Variation of First Embodiment) Fig. 11 is an explanatory diagram of a variation of the first embodiment. In the first embodiment, in a "multi-site fleet energy management" system, a "shared resource" is "surplus power" at a certain site, an "allocation function (integrated system)" is a multi-site integrated EMS 1, "subsystems" are a plurality of site EMSs 2, and a "KPI" is CO2 emissions. The "allocation function" allocates the "shared resource" to one of the "subsystems" so as to improve an overall KPI, which is the total value of "KPIs" across all the "subsystems."

[0109] In multi-site fleet energy management, the shared resource is the surplus power shared between sites through self-dispatch. The allocation function is the multi-site integrated EMS, which creates a dispatch allocation plan. The subsystem is the site EMS (including the FMS), which creates a power supply-demand plan and vehicle operation plan for each site. The KPI is CO2 emissions or OPEX. The expansion of charging opportunities due to the addition of surplus power through self-dispatch (Δresources) leads to an expansion of electrification coverage, and if the surplus power is from renewable energy sources, CO2 emissions will be significantly reduced (ΔKPI). Even if the total power consumption across all sites increases (including an increase in retail supply), if the CO2 emissions per EV mileage (kg-CO2 / km) derived from retail supply are lower than the CO2 emissions per ICE mileage, the CO2 reduction effect will be significant.

[0110] However, the present invention is not limited to the above and can also be applied to "multi-modal urban transportation" in which multiple types of transportation are linked together. In this case, in multi-modal urban transportation, the shared resource is the allowable waiting time for each transportation mode. The allocation function is a system of a public transportation manager that is independent of each transportation operator and is responsible for ensuring convenience throughout the city. The subsystem is a system of operators of buses, trains, etc. The KPI is the travel time of users. For example, if a main line train is delayed and many users have to wait for the departure of a bus to which they are connecting, the convenience of users who only take the bus will decrease, but the convenience of users who are transferring will improve.

[0111] In other words, the "shared resource" is the "departure waiting time" of a certain transportation service, the "allocation function" is the system of the higher-level "public transportation manager," the "subsystem" is the system of multiple bus and railway operators, and the "KPI" is "passenger travel time." The "allocation function" then allocates the "shared resource" to one of the "subsystems" in order to improve the overall KPI, which is the sum of the "KPIs" across all "subsystems."

[0112] The present invention can also be applied to "mixed cargo and passenger transport" in transportation systems that transport both freight and passengers. In this case, the shared resource is the transport capacity of transportation systems such as buses and trains. The allocation function is the transportation system. The subsystems are systems for passenger service providers (Mobility as a Service (MaaS) operators) that handle the movement of people and transportation service providers (logistics operators) that handle the movement of goods. The KPI is the combined transportation volume of people and goods. For example, if a transportation service provider requests additional resources during peak train hours, the passenger space will decrease, significantly impairing the passenger service KPI.

[0113] On the other hand, during non-congested hours, even if the transportation service provider requests additional resources, the passenger service KPI is not impaired, and therefore the overall KPI improves in proportion to the improvement in the transportation service KPI.

[0114] In other words, the "shared resource" is the transportation capacity of the transportation facility, the "allocation function" is the "transportation operation system," the "subsystems" are the systems of passenger service providers and logistics service providers, and the "KPI" is the "transport volume of people and goods." The "allocation function" then allocates the "shared resource" to one of the "subsystems" in order to improve the overall KPI, which is the sum of the "KPIs" across all "subsystems."

[0115] [Embodiment 2] In embodiment 1, in response to a proposal for shared resource allocation from the allocation function, a subsystem at a certain base quickly submits a revised allocation proposal and has it approved by the subsystems at other bases, resulting in shared resource allocation on a first-come, first-served basis.

[0116] In contrast, in the second embodiment, the allocation function calculates ΔKPIs in each subsystem in response to a proposal for shared resource allocation, and if the ΣΔKPIs satisfy the conditions in the allocation function, the allocation function itself approves the proposal. Hereinafter, the second embodiment will be described, focusing on the differences from the first embodiment.

[0117] (Multi-resource management processing (planning phase: resource allocation negotiation process) according to embodiment 2) FIG. 12 is a flowchart showing an example of resource management processing (planning phase: resource allocation negotiation process) according to embodiment 2. In comparison with embodiment 1, embodiment 2 differs in that steps S19B, S20B, S23B, S24B, S25B, and S26B are executed instead of steps S19, S20, S23, S24, S25, and S26 of the resource management processing (FIG. 3B), respectively.

[0118] In step S19B, the resource allocation planning unit 121 of the multi-site integrated EMS 1 recalculates the resource allocation plan, that is, the consignment allocation plan, based on the resource addition proposal data D102 transmitted from the site EMS 2-1 in step S18.

[0119] In step S20B, the multi-site integrated EMS 1 transmits an approval / disapproval inquiry including the resource allocation plan recalculated in step S19B to the site EMSs 2-1 and 2-2.

[0120] In step S23B, the ΔKPI evaluation and response unit 223 of the base EMS 2-2 determines the ΔKPI (ΔKPI calculated value) calculated in step S22 as the response to be sent to the multi-base integrated EMS 1. In step S24B, the ΔKPI evaluation and response unit 223 of the base EMS 2-1 determines the ΔKPI resource allocation plan that has already been calculated for its own device as the response to be sent to the multi-base integrated EMS 1. This is because the resource allocation plan sent from the multi-base integrated EMS 1 in step S20B is based on the shared resource addition proposal proposed by its own device.

[0121] In step S25B, the resource utilization planning unit 221 of the base EMS 2-2 transmits the response determined in step S23B or S24B to the multi-base integrated EMS 1.

[0122] In step S26B, if the total ΣΔKPI of the ΔKPIs received from all the subsystems, that is, the base EMSs 2, is negative, the resource allocation planning unit 121 of the multi-base integrated EMS 1 adopts the resource allocation plan recalculated in step S19B. A negative ΣΔKPI means that the KPIs of the entire resource management system S have improved as a result of resource allocation.

[0123] (Aggregation of KPI Responses According to Embodiment 2) Fig. 13A is a diagram showing an example of the configuration of ΣΔKPI (successful case) according to embodiment 2. Fig. 13B is a diagram showing an example of the configuration of ΣΔKPI (failure case) according to embodiment 2.

[0124] In Figure 13A, for the resource allocation plan with "ID" "Plan0001", the ΔKPI for base 1 (proposal side, base EMS2-1) is "-100", and the ΔKPI for base 2 (decision side, base EMS2-2) is "+80". In addition, the sum of the ΣΔKPI (CO2 emissions) across base EMS2-1 and 2-2 is "-20". Since ΣΔKPI = "-20" is a negative value and the overall KPI has improved (total CO2 emissions have decreased), the adoption of the resource allocation plan with "ID" "Plan0001" is "successful".

[0125] On the other hand, in Figure 13B, for the resource allocation plan with "ID" "Plan0001", the ΔKPI of base 1 (proposal side, base EMS2-1) is "-100", and the ΔKPI of base 2 (decision side, base EMS2-2) is "+120". In addition, the sum of the ΣΔKPI (CO2 emissions) across base EMS2-1 and 2-2 is "+20". Since ΣΔKPI = "+20" is a positive value and the overall KPI has worsened (total CO2 emissions have increased), the adoption of the resource allocation plan with "ID" "Plan0001" is "not established".

[0126] In the second embodiment, the multi-site integrated EMS has the base EMSs, which are subsystems, calculate the KPIs that are the basis for deciding whether to allocate additional shared resources, and determines whether to allocate additional shared resources based on the results of the calculations of the KPIs by each base EMS. Thus, the multi-site integrated EMS can fairly formulate an additional allocation plan for shared resources that optimizes the overall KPI.

[0127] [Embodiment 3] In embodiment 3, the allocation function performs allocation by having each subsystem calculate a predetermined number of ΔKPIs in response to a proposal for shared resource allocation from the allocation function, searching for the combination of ΔKPIs that is the smallest in the allocation function, and having each location approve it.

[0128] (ΔKPI / ΔResource Map According to Embodiment 3) FIG. 14 is a diagram showing an example of a ΔKPI / ΔResource map according to embodiment 3. In this embodiment, it is assumed that there are three subsystems (three power receiving bases). A plurality of patterns of combinations of wheeling allocation amount and CO2 emissions (ΔKPI / ΔResource) at each base are calculated in advance. Then, as shown in FIG. 14, ΔKPI / ΔResource, which is the result of dividing ΔKPI by ΔResource, is plotted on a graph with wheeling allocation amount on the horizontal axis and CO2 emissions on the vertical axis.

[0129] When the initial planning process receives the wheeling allocation time series data, each subsystem calculates multiple combinations of ΔKPI and Δresources and sends them to the allocation function. The allocation function selects the combination that minimizes CO2 emissions. In Figure 14, "●" indicates the initial allocation, and the "●" and "○" connected by a solid line are combinations that minimize CO2 emissions without changing the total wheeling allocation amount (total Δresources is 0, ΔKPI is negative).

[0130] 15 is a diagram illustrating an example of a dataset of Δ resources and Δ KPIs according to embodiment 3. The base EMS 2 of each base calculates a combination of a consignment allocation amount (Δ resources) and a CO2 emission amount (Δ KPI) in advance for each base EMS 2 using a plurality of patterns, and compiles the combination into the dataset shown in FIG. 15 and transmits it to the multi-base integrated EMS 1.

[0131] (Energy Management Processing (Planning Phase: Initial Planning Process) According to Embodiment 3) Fig. 16 is a flowchart showing an example of energy management processing (planning phase: initial planning process) according to embodiment 3. Embodiment 3 differs from embodiment 1 in that steps S141CB, S142C, S143C, and S144C are executed instead of step S14 between steps S13 to S15 of the energy management processing (Fig. 3B).

[0132] In step S141C, the base EMSs 2-1 and 2-2 each create a ΔKPI / Δresource map. Next, in step S142C, the base EMSs 2-1 and 2-2 create a Δresource / ΔKPI data set (FIG. 15) related to the ΔKPI / Δresource created in step S141C and transmit it to the multi-base integrated EMS 1.

[0133] Next, in step S143C, the multi-site integrated EMS 1 determines a combination of Δ resources that minimizes the ΣKPI (CO2 emissions). Next, in step S143C, the multi-site integrated EMS 1 notifies each site EMS 2 of the Δ resources to be allocated to each site related to the combination determined in step S143C.

[0134] Effect of Embodiment 3 In the above-described embodiment 3, the multi-site integrated EMS causes each base EMS to calculate the KPIs and additional resources that are the basis for adopting additional allocation of shared resources, and calculates multiple combinations of ΔKPIs and Δ resources for each base EMS.The multi-site integrated EMS then selects, for each base EMS, a combination that optimizes the overall KPI from the combinations of ΔKPIs and Δ resources for each base EMS.This makes it possible to create an additional allocation plan that fairly allocates additional shared resources to each base while optimizing the overall KPI.

[0135] Although the embodiments of the present disclosure have been described in detail above, the present disclosure is not limited to the above-described embodiments and can be modified in various ways without departing from the spirit of the present disclosure. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present disclosure is not necessarily limited to those including all of the described configurations. Furthermore, some of the configurations of the above-described embodiments can be added to, deleted from, or replaced with other configurations.

[0136] Furthermore, the above-described configurations, functional units, processing units, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software by a processor interpreting and executing a program that implements each function. Information such as the programs, tables, and files that implement each function can be stored in a memory, a storage device such as an HDD or SSD, or a recording medium such as an IC card, an SD card, or a DVD.

[0137] In addition, in the above-mentioned drawings, the control lines and information lines shown are those that are considered necessary for explanation, and do not necessarily show all the control lines and information lines that are actually implemented. For example, it may be considered that almost all components are actually connected to each other.

[0138] The above-described arrangement of functions and data of the multi-site integrated EMS 1 and the site EMSs 2, 2-1, and 2-2 is merely an example. The arrangement, integration, and distribution of functions and data can be changed to an optimal form from the viewpoint of hardware and software performance, processing efficiency, communication efficiency, etc.

[0139] S: resource management system, 1: multi-site integrated EMS, 2, 2-1, 2-2: site EMS, 12, 22: computing device, 13, 23: storage device.

Claims

1. A resource management system including a plurality of subsystems, the resource management system having a processor and a memory, the processor of the resource management system: calculates an initial resource allocation plan for implementing an initial allocation of resources to the plurality of subsystems; calculates a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is implemented based on the initial resource allocation plan; calculates an additional allocation amount for the subsystem that will improve the KPI compared to the initial resource allocation plan when the resources are reallocated based on the additional allocation amount by solving an optimization problem for each of the subsystems with an amount of additional resource allocation as a constraint and an amount of additional resource allocation as an objective function; calculates a resource reallocation plan for reallocating resources to the plurality of subsystems based on the additional allocation amount and an expected value of the KPI that each of the plurality of subsystems is expected to achieve when the resources are reallocated based on the resource reallocation plan; a resource management system comprising: calculating an estimated value of the KPI that each of the plurality of subsystems will actually achieve when the resources are reallocated based on the resource reallocation plan; comparing the estimated value of the KPI with an expected value, and deciding whether or not to accept the resource reallocation plan if the calculated value of the KPI deteriorates, and accepting the plan if the calculated value does not deteriorate; and deciding whether or not to adopt the resource reallocation plan based on the acceptance for each of the plurality of subsystems.

2. A resource management system as described in claim 1, wherein a processor of the resource management system calculates the KPI obtained from an optimization problem in which constraint conditions based on the additional allocation amount and an objective function based on the KPI are set as a standard KPI, calculates the KPI obtained from an optimization problem in which constraint conditions based on the KPI and an objective function based on the additional allocation amount are set as an improved KPI, and when the improved KPI is calculable, calculates the additional allocation amount based on the difference between the standard KPI and the improved KPI.

3. A resource management system as described in claim 1, wherein each of the plurality of subsystems is an EMS (Energy Management System) that calculates, for each base of vehicles including EVs equipped with distributed power sources and EV (Electric Vehicle) chargers, a power supply and demand plan and a vehicle operation plan that are resource utilization plans based on the initial resource allocation plan and the resource reallocation plan, and the resource management system is a fleet energy management system including an integrated EMS that integrates the plurality of EMSs, the resource is surplus power per unit time totaled across all of the bases, and the KPI is CO2 emissions associated with the operation of the vehicles, the integrated EMS has a processor and a memory, and the processor of the integrated EMS calculates, for each unit time, the initial resource allocation plan and the resource reallocation plan, and an expected value of the KPI, and determines whether or not to adopt the resource reallocation plan, and the processor of each of the plurality of EMSs, for each unit time, a resource management system that calculates the KPI, the additional allocation amount, and a calculated value of the KPI, and determines whether or not to accept the resource reallocation plan.

4. A resource management system as described in claim 3, wherein the processor of each of the multiple EMSs calculates, for each unit time, the CO2 emissions obtained from an optimization problem having a constraint condition that fixes the additional allocation amount of the surplus power to 1 and an objective function that minimizes the CO2 emissions as a standard KPI, calculates the CO2 emissions obtained from an optimization problem having a constraint condition that sets an upper limit on the CO2 emissions and an objective function that minimizes the additional allocation amount as an improved KPI, and when the improved KPI is calculable, calculates the additional allocation amount based on the difference between the improved KPI and the standard KPI.

5. A resource management system as described in claim 4, characterized in that the processor of the integrated EMS or each of the EMSs displays on a display screen the change in the KPI associated with the reallocation of resources based on the additional allocation amount.

6. A resource management system as described in claim 1, wherein the resource management system includes an integrated system having a processor and a memory, each of the plurality of subsystems having a processor and a memory, the processor of each of the plurality of subsystems calculates, for each of the subsystems, the KPI, the additional allocation amount, the expected value of the KPI, the calculated value of the KPI, and a difference between the expected value of the KPI and the calculated value of the KPI, and the processor of the integrated system determines the acceptance for each of the subsystems, and instead of deciding whether to adopt the resource reallocation plan based on the acceptance for each of the plurality of subsystems, compares the total value of the calculated values ​​of the KPIs for all of the plurality of subsystems with the total value of the expected values ​​of the KPIs for all of the plurality of subsystems, and decides to adopt the resource reallocation plan if there is an improvement, and decides not to adopt the resource reallocation plan if there is no improvement.

7. A resource management system as claimed in claim 1, comprising: an integrated system having a processor and a memory; each of the plurality of subsystems having a processor and a memory; the processor of each of the plurality of subsystems calculates, for each of the subsystems, the KPI, the additional allocation amount, an expected value of the KPI, a calculated value of the KPI, and a difference value between the expected value of the KPI and the calculated value of the KPI; and instead of determining the acceptability for each of the subsystems, generates a plurality of combinations of the additional allocation amount and the difference value; and instead of determining whether to adopt the resource reallocation plan based on the acceptability for each of the subsystems, the processor of the integrated system determines a combination which gives the best total value of the difference value for all of the plurality of subsystems from among the combinations of the additional allocation amount and the difference value for all of the plurality of subsystems; and notifies each of the subsystems of the additional allocation amount for each of the determined combinations.

8. An integrated resource management device that calculates a resource allocation plan for allocating resources to a plurality of subsystems, the integrated resource management device having a processor and a memory, the processor of the integrated resource management device calculates an initial resource allocation plan for implementing initial allocation of resources to the plurality of subsystems, calculates a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is implemented based on the initial resource allocation plan, and calculates a resource reallocation plan for reallocating resources to the plurality of subsystems based on an additional allocation amount of resources in the subsystem that will improve the KPI compared to the initial resource allocation plan when the reallocation of resources is implemented based on the additional allocation amount, the additional allocation amount being calculated by solving an optimization problem for each of the subsystems with an amount of change in the KPI as a constraint and an amount of additional allocation of resources as an objective function, and calculates an expected value of the KPI that each of the plurality of subsystems is expected to achieve when the resources are reallocated based on the resource reallocation plan, an integrated resource management device that determines whether to adopt the resource reallocation plan based on an acceptance decision that rejects the acceptance of the resource reallocation plan if the KPI calculated value that each of the plurality of subsystems will actually achieve when the resources are reallocated based on the resource reallocation plan, which is determined for each subsystem, is compared with an expected value of the KPI, and if the KPI deteriorates, the acceptance of the resource reallocation plan is rejected, and if the KPI does not deteriorate, the acceptance is accepted.

9. A resource management method executed by a resource management system including a plurality of subsystems and calculating a resource allocation plan for allocating resources to the plurality of subsystems, the resource management system having a processor and a memory, the processor of the resource management system performing the following steps: calculating an initial resource allocation plan for implementing initial allocation of resources to the plurality of subsystems; calculating a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is implemented based on the initial resource allocation plan; calculating an additional allocation amount for the subsystem that will improve the KPI compared to the initial resource allocation plan when the resources are reallocated based on the additional allocation amount by solving an optimization problem for each of the subsystems with an amount of additional resource allocation as a constraint and an amount of change in the KPI as an objective function; and calculating a resource reallocation plan for reallocating the resources to the plurality of subsystems based on the additional allocation amount and an expected value of the KPI that each of the plurality of subsystems is expected to achieve when the resources are reallocated based on the resource reallocation plan.

1. A resource management method comprising: a step of calculating an estimated value of the KPI that each of the plurality of subsystems will actually achieve when the resources are reallocated based on the resource reallocation plan; a step of comparing the estimated value of the KPI with an expected value, and deciding whether to accept the resource reallocation plan for each of the plurality of subsystems, rejecting the acceptance of the resource reallocation plan if the calculated value of the KPI deteriorates, and accepting the acceptance if the calculated value does not deteriorate; and a step of deciding whether to adopt the resource reallocation plan based on the acceptance for each of the plurality of subsystems.

10. A resource management method as described in claim 9, wherein the resource management system includes an integrated system having a processor and a memory, each of the plurality of subsystems has a processor and a memory, the processor of each of the plurality of subsystems calculates, for each of the subsystems, the KPI, the additional allocation amount, the expected value of the KPI, the calculated value of the KPI, and a difference between the expected value of the KPI and the calculated value of the KPI, and the processor of the integrated system determines the acceptability for each of the subsystems, and instead of deciding whether to adopt the resource reallocation plan based on the acceptability for each of the plurality of subsystems, the processor of the integrated system compares the total value of the expected values ​​of the KPIs for all of the plurality of subsystems with the total value of the calculated values ​​of the KPIs for all of the plurality of subsystems, and if there is an improvement, decides to adopt the resource reallocation plan, and if there is no improvement, decides not to adopt the resource reallocation plan.

11. A resource management method according to claim 9, wherein the resource management system includes an integrated system having a processor and a memory, each of the plurality of subsystems has a processor and a memory, and the processor of each of the plurality of subsystems calculates, for each of the subsystems, the KPI, the additional allocation amount, an expected value of the KPI, a calculated value of the KPI, and a difference value between the expected value of the KPI and the calculated value of the KPI, and instead of the step of determining the acceptability for each of the subsystems, comprises a step of generating a plurality of patterns of combinations of the additional allocation amount and the difference value, and instead of the step of determining whether or not to adopt the resource reallocation plan based on the acceptability for each of the subsystems, the processor of the integrated system comprises a step of determining, from among combinations of the additional allocation amount and the difference value for all of the plurality of subsystems, a combination which gives the best total value of the difference value for all of the plurality of subsystems, and a step of notifying each of the subsystems of the additional allocation amount for each of the subsystems related to the determined combination.

12. A resource management method executed by an integrated resource management device that calculates a resource allocation plan for allocating resources to a plurality of subsystems, the integrated resource management device having a processor and a memory, the processor of the integrated resource management device performing the following steps: calculating an initial resource allocation plan for implementing initial allocation of resources to the plurality of subsystems; calculating a KPI (Key Performance Indicator) that each of the plurality of subsystems will achieve when the initial allocation is implemented based on the initial resource allocation plan; and calculating a resource reallocation plan for reallocating resources to the plurality of subsystems based on an additional allocation amount of resources in the subsystem that will improve the KPI compared to the initial resource allocation plan when the reallocation of resources is implemented based on the additional allocation amount, the additional allocation amount being calculated by solving an optimization problem for each of the subsystems with a change in the KPI as a constraint and an additional allocation amount of resources as an objective function, and calculating an expected value of the KPI that each of the plurality of subsystems is expected to achieve when the resources are reallocated based on the resource reallocation plan. and determining whether to adopt the resource reallocation plan based on the acceptability step of rejecting the acceptance of the resource reallocation plan if the calculated value of the KPI that each of the plurality of subsystems will actually achieve when the resources are reallocated based on the resource reallocation plan, which is determined for each subsystem, deteriorates when compared with the expected value of the KPI, and accepting the acceptance if the KPI does not deteriorate.

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