JP2016163443A - Contract content optimization method - Google Patents

Contract content optimization method Download PDF

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JP2016163443A
JP2016163443A JP2015040940A JP2015040940A JP2016163443A JP 2016163443 A JP2016163443 A JP 2016163443A JP 2015040940 A JP2015040940 A JP 2015040940A JP 2015040940 A JP2015040940 A JP 2015040940A JP 2016163443 A JP2016163443 A JP 2016163443A
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contract
power consumption
menu
power
optimization method
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JP6491499B2 (en
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淳 吉永
Atsushi Yoshinaga
淳 吉永
広之 野崎
Hiroyuki Nozaki
広之 野崎
幸三 折茂
Kozo Orimo
幸三 折茂
太郎 只野
Taro Tadano
太郎 只野
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INFOMETIS CO Ltd
Tokyo Electric Power Co Holdings Inc
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INFOMETIS CO Ltd
Tokyo Electric Power Co Holdings Inc
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

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  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

PROBLEM TO BE SOLVED: To provide a contract content optimization method capable of automatically distinguishing a factor of a consumption power variation from accumulated data and proposing an optimum power contract by rapidly reflecting a user's consumption power variation.SOLUTION: The contract content optimization method includes: continuously measuring user's (user house's) consumption power (S202); separating by device the measured consumption power data to estimate increase/decrease of devices (S206) when there is a large variation in consumption power (S204); calculating by simulation a load curve including the increased/decreased devices (S208); and presenting a contract power amount or a contract menu suitable for the load curve (S216).SELECTED DRAWING: Figure 2

Description

本発明は、需要家に対して最適な契約電力量または契約メニュー契約を提示する契約内容最適化方法に関する。   The present invention relates to a contract content optimizing method for presenting an optimal contract power amount or contract menu contract to a consumer.

電気事業者では、需要家の電力使用パターンや消費電力量に応じた複数の契約メニューや契約電力量を設定している。しかし、需要家は、家族構成の変化や家電機器の新規購入等により消費電力量に大きな変化があった場合、既契約メニューや契約電力量が必ずしも最適な電力契約をしているとは限らなかった。そこで例えば特許文献１では、電気料金が最低となる最適契約メニューを選定する使用電力最適化提案システムが提案されている。   The electric power company sets a plurality of contract menus and contract power amounts according to the power usage patterns and power consumption of the consumers. However, if there is a significant change in power consumption due to changes in the family structure, new purchases of home appliances, etc., the customer may not necessarily have an optimal power contract with the existing contract menu or contract power consumption. It was. Therefore, for example, Patent Document 1 proposes a power usage optimization proposal system that selects an optimum contract menu that minimizes the electricity bill.

特許文献１の使用電力最適化提案システムでは、まず過去の一定期間の電力の使用実績を測定して記録する。そして、その過去の一定期間における電力の使用実績と同一の使用条件下で、複数の電気料金契約メニューのそれぞれに基づく電気料金を演算することにより、電気料金が最低になる最適契約メニューを選定することができるとしている。   In the power usage optimization proposing system disclosed in Patent Document 1, firstly, a power usage record for a certain period in the past is measured and recorded. Then, under the same usage conditions as the actual power usage in the past certain period, the optimum contract menu that minimizes the electricity bill is selected by calculating the electricity bill based on each of the electricity bill contract menus. You can do that.

特開２００４−１６４００９号公報JP 2004-164209 A

しかしながら、特許文献１の技術であると、長期間（例えば６ヶ月〜１年程度）の電力の使用実績のデータを蓄積しないと電気料金の演算を行うことができない。このため、需要家における消費電力の変動に迅速に対応することは難しい。また特許文献１の技術では、消費電力の変動が何に起因するものかを判断することができない。このため、大幅な消費電力の変動の要因を把握するためには、従来のように電気事業者の計測員が需要家を訪ねて聞き取りを行うというという煩雑な作業を回避することができない。   However, with the technique of Patent Document 1, it is not possible to calculate the electricity bill without accumulating long-term (for example, about six months to one year) power usage data. For this reason, it is difficult to respond quickly to fluctuations in power consumption at the consumer. Further, the technique of Patent Document 1 cannot determine what causes the fluctuation in power consumption. For this reason, in order to grasp the factor of the fluctuation | variation of a large power consumption, the troublesome operation | work that an electrician's measurer visits a consumer and listens like the past cannot be avoided.

本発明は、このような課題に鑑み、消費電力の変動の要因を蓄積したデータから自動で判別することができ、且つ需要家における消費電力の変動を迅速に反映させて最適な電力契約を提案することが可能な契約内容最適化方法を提供することを目的としている。   In view of such a problem, the present invention proposes an optimum power contract that can automatically determine the factor of fluctuation of power consumption from the accumulated data and quickly reflect the fluctuation of power consumption in the consumer. The purpose is to provide a contract content optimization method that can be used.

上記課題を解決するために、本発明にかかる契約内容最適化方法の代表的な構成は、需要家の消費電力を継続的に計測し、計測した消費電力のデータを機器分離し、消費電力に大幅な変動があった場合に機器の増減を推定し、増減した機器を含めたロードカーブをシミュレーションによって算出し、ロードカーブに適した契約電力量または契約メニューを提示することを特徴とする。   In order to solve the above-mentioned problems, the typical configuration of the contract content optimization method according to the present invention continuously measures the power consumption of the consumer, separates the measured power consumption data into equipment, and reduces the power consumption. It is characterized in that when there is a significant change, the increase or decrease of the device is estimated, a load curve including the increased or decreased device is calculated by simulation, and a contract power amount or a contract menu suitable for the load curve is presented.

上記構成によれば、機器分離を行うことにより、消費電力の変動の要因となる機器を、需要家への聞き取りを行うことなく、すなわち自動的に特定することができる。そして、その機器を含めたロードカーブをシミュレーションによって算出することにより、需要家の電力消費パターンに最も適した契約電力量や契約メニューを選択することができる。また消費電力の変動の起因となる機器を含めてシミュレーションを行うため、変動の要因を契約電力量や契約メニューの提示に迅速に反映することが可能である。   According to the above configuration, by separating the devices, it is possible to automatically identify a device that causes a variation in power consumption without listening to the customer. Then, by calculating a load curve including the device by simulation, it is possible to select a contract power amount and a contract menu that are most suitable for a consumer's power consumption pattern. In addition, since the simulation is performed including the device that causes the fluctuation of the power consumption, it is possible to quickly reflect the fluctuation factor in the contract power consumption and the presentation of the contract menu.

当該契約内容最適化方法では、シミュレーションしたロードカーブと、既存の契約メニューの典型的なロードカーブとの相関度を算出し、相関度が所定値未満であった場合には新規メニューを作成するとよい。かかる構成によれば、需要家の電力消費パターンにより適した契約メニューを提案することができ、顧客満足度を高めることが可能である。なお相関度はロードカーブ全体を用いての比較であるが、さらに簡略にはピークタイムやピーク時間帯でその電力消費パターンが既存の契約メニューに含まれるか否かを判断してもよい。   In the contract content optimization method, the degree of correlation between the simulated road curve and the typical road curve of the existing contract menu is calculated, and if the degree of correlation is less than a predetermined value, a new menu may be created. . According to this configuration, it is possible to propose a contract menu that is more suitable for the consumer's power consumption pattern, and to increase customer satisfaction. The correlation is a comparison using the entire road curve, but more simply, it may be determined whether the power consumption pattern is included in the existing contract menu at the peak time or peak time zone.

本発明によれば、消費電力の変動の原因を蓄積したデータから自動で判別することができ、且つ需要家における消費電力の変動を迅速に反映させて最適な電力契約を提案することが可能な契約内容最適化方法を提供することができる。   According to the present invention, it is possible to automatically determine the cause of fluctuations in power consumption from accumulated data, and it is possible to propose an optimal power contract by quickly reflecting fluctuations in power consumption in consumers. A contract content optimization method can be provided.

本実施形態にかかる契約内容最適化方法を説明する概略図である。It is the schematic explaining the contract content optimization method concerning this embodiment. 本実施形態にかかる契約内容最適化方法を説明するフローチャートである。It is a flowchart explaining the contract content optimization method concerning this embodiment.

以下に添付図面を参照しながら、本発明の好適な実施形態について詳細に説明する。かかる実施形態に示す寸法、材料、その他具体的な数値などは、発明の理解を容易とするための例示に過ぎず、特に断る場合を除き、本発明を限定するものではない。なお、本明細書及び図面において、実質的に同一の機能、構成を有する要素については、同一の符号を付することにより重複説明を省略し、また本発明に直接関係のない要素は図示を省略する。   Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The dimensions, materials, and other specific numerical values shown in the embodiments are merely examples for facilitating understanding of the invention, and do not limit the present invention unless otherwise specified. In the present specification and drawings, elements having substantially the same function and configuration are denoted by the same reference numerals, and redundant description is omitted, and elements not directly related to the present invention are not illustrated. To do.

図１は、本実施形態にかかる契約内容最適化方法を説明する概略図である。図１に示すように、需要家宅１００には、エアコン１０２ａ、テレビ１０２ｂ、冷蔵庫１０２ｃ、ヒートポンプ式貯湯装置（以下、貯湯装置１０２ｄと称する）、電気自動車１００ｅ等、様々な電気機器が設置されている。   FIG. 1 is a schematic diagram for explaining a contract content optimization method according to the present embodiment. As shown in FIG. 1, various electric devices such as an air conditioner 102 a, a television 102 b, a refrigerator 102 c, a heat pump hot water storage device (hereinafter referred to as a hot water storage device 102 d), and an electric vehicle 100 e are installed in the customer's house 100. .

上記の電気機器は、需要家宅１００に設置されたスマートメータ１０４に通信回線によって接続されている。そして、スマートメータ１０４は、通信網１０６によってサーバ１１０に接続されている。なお、理解を容易にするために、以下の説明では、本実施形態の契約内容最適化方法をサーバ１１０によって実行する場合を例示して説明する。また本実施形態では、電気機器をスマートメータ１０４によって通信回線に接続する構成を例示したが、これに限定するものではなく、例えばスマートメータ１０４に換えて負荷電流計測装置を用いることも可能である。   The electrical equipment is connected to a smart meter 104 installed in the customer's house 100 via a communication line. The smart meter 104 is connected to the server 110 via the communication network 106. In order to facilitate understanding, in the following description, the case where the contract content optimization method of the present embodiment is executed by the server 110 will be described as an example. Further, in the present embodiment, the configuration in which the electric device is connected to the communication line by the smart meter 104 is illustrated, but the present invention is not limited to this. For example, a load current measuring device can be used instead of the smart meter 104. .

図２は、本実施形態にかかる契約内容最適化方法を説明するフローチャートである。図２に示すように、本実施形態の契約内容最適化方法では、まずサーバ１１０は、スマートメータ１０４から送信されてくる需要家宅１００の消費電力を継続的に計測する（ステップＳ２０２）。そして、サーバ１１０は、計測している消費電力に大幅な変動が検出されたら（ステップＳ２０４）、消費電力のデータを機器分離し、変動の原因を推定する（ステップＳ２０６）。   FIG. 2 is a flowchart for explaining the contract content optimizing method according to the present embodiment. As shown in FIG. 2, in the contract content optimizing method of the present embodiment, first, the server 110 continuously measures the power consumption of the customer's house 100 transmitted from the smart meter 104 (step S202). Then, when a significant fluctuation is detected in the measured power consumption (step S204), the server 110 separates the power consumption data from the device and estimates the cause of the fluctuation (step S206).

詳細には、ステップＳ２０６における機器分離では、サーバ１１０は、消費電力のデータ（波形データ）を機器（電気機器）ごとに分離する。これにより、どのような機器が増えたまたは減ったことにより消費電力の変動が生じたか、すなわち消費電力の変動の原因となった機器を推定することができる。したがって、従来のような需要家からの申請もしくは需要家への聞き取りを行うことなく、消費電力の変動原因を推定可能となる。   Specifically, in device separation in step S206, the server 110 separates power consumption data (waveform data) for each device (electric device). As a result, it is possible to estimate a device that has caused a variation in power consumption due to an increase or decrease in the number of devices, that is, a device that has caused the variation in power consumption. Therefore, it is possible to estimate the cause of fluctuations in power consumption without performing an application from a consumer or an interview with the consumer as in the prior art.

機器分離を行ったら、サーバ１１０は、推定した機器、すなわち増減した機器を含めたロードカーブをシミュレーションによって算出する（ステップＳ２０８）。具体的には、例えば需要家宅１００における消費電力の大幅な変動は、電気自動車１００ｅを新たに使用開始したことである、換言すれば電気自動車１００ｅが消費電力の変動原因を推定された場合、サーバは、需要家宅１００にて使用されている各電気機器の消費電力の標準的なロードカーブを積算して（積み上げて）、その需要家宅１００におけるロードカーブをシミュレーションする。   After the device separation, the server 110 calculates a load curve including the estimated device, that is, the increased or decreased device, by simulation (step S208). Specifically, for example, a significant fluctuation in power consumption in the customer's house 100 is that the electric vehicle 100e has been newly used. In other words, when the electric vehicle 100e is estimated to cause fluctuations in power consumption, Integrates (stacks) the standard load curves of the power consumption of each electric device used in the customer's house 100, and simulates the load curve in the customer's house 100.

上記シミュレーションを行ったら、サーバ１１０は、シミュレーションによって算出したロードカーブ（以下、シュミレーションしたロードカーブと称する）における最大電力量と、需要家宅１００が現在契約している契約電力量とを比較し、電力量の裕度が適正であるかを判断する（ステップＳ２１０）。裕度が適正ではなかった場合（ステップＳ２１０のＮＯ）、すなわち裕度が大きすぎるまたは小さすぎる場合、サーバ１１０は、既存の契約電力量の中から、裕度が最適となる契約電力量を提示する（ステップＳ２１２）。   When the simulation is performed, the server 110 compares the maximum power amount in the road curve calculated by the simulation (hereinafter referred to as a simulated load curve) with the contract power amount that the customer's house 100 is currently contracting, and It is determined whether the amount tolerance is appropriate (step S210). When the margin is not appropriate (NO in step S210), that is, when the margin is too large or too small, the server 110 presents the contract power amount with the optimum margin among the existing contract power amounts. (Step S212).

裕度が適正であった場合（ステップＳ２１０のＹＥＳ）、または最適な契約電力量を提示した後（ステップＳ２１２）、サーバ１１０は、シミュレーションしたロードカーブと、既存の各契約メニューの標準ロードカーブとを比較する。そして、既存の契約メニューの中に、ロードカーブの形状が、シミュレーションしたロードカーブの形状に近い契約メニューがあるかを判断する（ステップＳ２１４）。   When the margin is appropriate (YES in step S210), or after presenting the optimum contracted electric energy (step S212), the server 110 calculates the simulated load curve, the standard load curve of each existing contract menu, and Compare Then, in the existing contract menu, it is determined whether there is a contract menu in which the shape of the road curve is close to the simulated shape of the load curve (step S214).

ステップＳ２１４におけるロードカーブの形状の判断では、例えばシミュレーションしたロードカーブと、既存の契約メニューの典型的なロードカーブとの相関度を算出し、相関度が所定値以上であったらそれらのロードカーブの形状が近いと判断することができる。これにより、判断を簡略化することができる。なお、相関度はロードカーブ全体を用いての比較であるが、ピークタイムやピーク時間帯でその電力消費パターンが既存の契約メニューに含まれるか否かを判断することにより、処理をより簡略化することが可能である。   In the determination of the shape of the road curve in step S214, for example, the degree of correlation between the simulated road curve and the typical road curve of the existing contract menu is calculated, and if the degree of correlation is equal to or greater than a predetermined value, It can be determined that the shapes are close. Thereby, judgment can be simplified. The degree of correlation is a comparison using the entire road curve, but the process is further simplified by determining whether the power consumption pattern is included in the existing contract menu at peak times or peak hours. Is possible.

シミュレーションしたロードカーブの形状に近い既存の契約メニューがあった場合（ステップＳ２１４のＹＥＳ）、すなわち相関度が所定値以上の既存の契約メニューがあった場合、サーバ１１０は、その契約メニューを最適な契約メニューとして提示する（ステップＳ２１６）。このとき提示する「最適な契約メニュー」には、現在選択されている契約メニューも含まれる。この場合には、契約メニューを変更する必要がないことが確認できる。   If there is an existing contract menu that is close to the shape of the simulated road curve (YES in step S214), that is, if there is an existing contract menu with a correlation value equal to or greater than a predetermined value, the server 110 selects the contract menu that is optimal. The contract menu is presented (step S216). The “optimum contract menu” presented at this time includes the currently selected contract menu. In this case, it can be confirmed that there is no need to change the contract menu.

一方、シミュレーションしたロードカーブの形状に近い既存の契約メニューがなかった場合（ステップＳ２１４のＮＯ）、すなわちすべての既存の契約メニューの相関度が所定値未満であった場合、サーバ１１０は、シミュレーションしたロードカーブの形状に対応した新規の契約メニューを作成する（ステップＳ２１８）。新規の契約メニューは、機器分離によりロードカーブが変動した要因が特定されていることから、それらの使用時間帯や負荷特性、普及率などを勘案したうえで契約メニューを検討する。他にも、例えば夜間割引の契約メニューがあったとして、昼夜の切り替わり時刻が朝７時であったところ、これを朝８時にすれば大幅な料金低減が見込めるとすれば、そのような新規の契約メニューを作成する。新たに構築した契約メニューは、ロードカーブが推定できることから、採算性や合理性を検証評価可能となる。これにより、需要家の電力消費パターンにより適した契約メニューを提案することができ、顧客満足度の向上を図ることが可能である。   On the other hand, when there is no existing contract menu close to the shape of the simulated road curve (NO in step S214), that is, when the correlation degree of all existing contract menus is less than a predetermined value, the server 110 performs the simulation. A new contract menu corresponding to the shape of the road curve is created (step S218). The new contract menu identifies the factors that caused the load curve to fluctuate due to device separation, so the contract menu should be considered after taking into account their usage time, load characteristics, and penetration rate. In addition, for example, there is a contract menu for night discounts, and the switching time between day and night was 7:00 am. Create a contract menu. Since the newly constructed contract menu can estimate the road curve, the profitability and rationality can be verified and evaluated. This makes it possible to propose a contract menu that is more suitable for the consumer's power consumption pattern and to improve customer satisfaction.

上記説明したように、本実施形態の契約内容最適化方法では、機器分離によって消費電力の大幅な変動の要因となった機器と推定することができる。シミュレーションによってその機器による影響を踏まえたロードカーブを算出することにより、従来であれば長期間の電力の使用実績のデータが必要であったところ、迅速に、かつ高い精度で、変動の要因を反映させた新しいロードカーブを取得することができる。そしてシミュレーションしたロードカーブと既存の契約電力量や契約メニューを比較することにより、需要家の電力消費パターン（ロードカーブ）に最も適した契約電力量や契約メニューを選択することが可能となる。   As described above, in the contract content optimizing method of the present embodiment, it can be estimated that the device has caused a significant fluctuation in power consumption due to device separation. By calculating the load curve based on the effects of the equipment through simulation, it was necessary to use long-term power usage data in the past. Reflecting the factors of fluctuation quickly and with high accuracy A new road curve can be acquired. Then, by comparing the simulated road curve with the existing contract power amount and contract menu, it becomes possible to select the contract power amount and contract menu most suitable for the power consumption pattern (load curve) of the consumer.

以上、添付図面を参照しながら本発明の好適な実施形態について説明したが、本発明は係る例に限定されないことは言うまでもない。当業者であれば、特許請求の範囲に記載された範疇内において、各種の変更例または修正例に想到し得ることは明らかであり、それらについても当然に本発明の技術的範囲に属するものと了解される。   As mentioned above, although preferred embodiment of this invention was described referring an accompanying drawing, it cannot be overemphasized that this invention is not limited to the example which concerns. It will be apparent to those skilled in the art that various changes and modifications can be made within the scope of the claims, and these are naturally within the technical scope of the present invention. Understood.

本発明は、需要家に対して最適な契約電力量または契約メニュー契約を提示する契約内容最適化方法として利用することができる。   INDUSTRIAL APPLICABILITY The present invention can be used as a contract content optimization method for presenting an optimal contract power amount or contract menu contract to a consumer.

１００…需要家宅、１００ｅ…電気自動車、１０２ａ…エアコン、１０２ｂ…テレビ、１０２ｃ…冷蔵庫、１０２ｄ…貯湯装置、１０４…スマートメータ、１０６…通信網、１１０…サーバ DESCRIPTION OF SYMBOLS 100 ... Consumer house, 100e ... Electric vehicle, 102a ... Air conditioner, 102b ... Television, 102c ... Refrigerator, 102d ... Hot water storage device, 104 ... Smart meter, 106 ... Communication network, 110 ... Server

Claims (2)

需要家の消費電力を継続的に計測し、
前記計測した消費電力のデータを機器分離し、
消費電力に大幅な変動があった場合に機器の増減を推定し、
前記増減した機器を含めたロードカーブをシミュレーションによって算出し、
前記ロードカーブに適した契約電力量または契約メニューを提示することを特徴とする契約内容最適化方法。 Continuously measure consumer power consumption,
Device separation of the measured power consumption data,
If there is a significant fluctuation in power consumption, estimate the increase or decrease in equipment,
Calculate the load curve including the increased and decreased equipment by simulation,
A contract content optimizing method comprising presenting a contract power amount or a contract menu suitable for the road curve. シミュレーションしたロードカーブと、既存の契約メニューの典型的なロードカーブとの相関度を算出し、相関度が所定値未満であった場合には新規メニューを作成することを特徴とする請求項１に記載の契約内容最適化方法。   The degree of correlation between a simulated road curve and a typical road curve of an existing contract menu is calculated, and a new menu is created when the degree of correlation is less than a predetermined value. The contract content optimization method described.
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