Power supply and demand adjustment system

Abstract

[Problem] To provide a power supply and demand adjustment system capable of improving the accuracy of demand control including peak cut control and yielding a large profit in selling surplus power. [Solution] A power supply and demand adjustment system includes: a prediction means 10A that has a power-consumption amount prediction means 11 for predicting a power consumption amount, a power-generation amount prediction means 12 for predicting a power generation amount, and a power price prediction means 14 for predicting a selling price; and an optimization means 10B that has a demand control means 15 for performing demand control for grid power on the basis of a power consumption amount prediction value from the power-consumption amount prediction means 11, an appropriate power selection means 16 for, on the basis of a power generation amount prediction value, selecting appropriate power to be consumed for the demand control from among power of an in-house power generator 40 and power of another power supply means other than the grid power and determining the power consumption amount, and an arbitrage trading determination means 17 for determining, on the basis of a result of the appropriate power selection means 16, whether to sell power and the selling price at a power trading market, and the period and the power amount for the selling.

Description

Power supply and demand adjustment system

[0001] The present invention relates to a power supply and demand adjustment system, and particularly to a power supply and demand adjustment system related to both peak cutting and arbitrage (selling and buying electricity in the electricity trading market).

[0002] Conventionally, in addition to suppressing electricity usage fees by performing so-called peak cutting by using the electricity generated by various power generation facilities such as solar power generation devices within the facility, surplus electricity has been sold (see, for example, Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2023-132221

[0004] However, in the electricity trading market, the trading price changes, and there may be a large difference in the profits obtained depending on the timing and time of selling and buying electricity in arbitrage transactions. Also, even when using the generated electricity within the facility, if peak cutting control fails, significant losses may be incurred, and improvement in the method of using the generated electricity has been demanded.

[0005] The present invention has been made in view of such problems, and an object thereof is to provide a power supply and demand adjustment system that can improve the accuracy of demand control including peak cutting control and can generate large profits from the trading of surplus electricity.

[0006] To achieve this objective, the present invention provides a prediction means comprising: a power consumption prediction means for predicting the subsequent power consumption of a facility based on the measurement results of the facility's power consumption; a power generation prediction means for predicting the subsequent power generation of the company's own power generation equipment based on the measurement results of the power generation of the company's own power generation equipment; and a buying and selling price prediction means for predicting the subsequent buying and selling price of the electricity trading market based on the trend of buying and selling prices in the electricity trading market. The present invention also provides an optimization means for optimizing the power status of the facility based on the prediction results of the prediction means, wherein the optimization means optimizes the demand for grid power based on the power consumption prediction value of the power consumption prediction means. The power supply and demand adjustment system is characterized by comprising: a demand control means for performing demand control; an appropriate power selection means for selecting appropriate power to be used for demand control by the demand control means from the power of the company's own power generation equipment and power from other power supply means other than the grid power, based on the power generation amount prediction value of the power generation amount prediction means, and determining the amount to be used; and an arbitrage transaction decision means for determining whether or not to sell the power of the company's own power generation equipment, and if so, the timing and amount of power to be sold, based on the result of the appropriate power selection means and the buying and selling price of the power trading market predicted by the buying and selling price prediction means.

[0007] Furthermore, in addition to the configuration described above, the present invention is characterized in that the optimization means comprises a first optimization means and a second optimization means, the first optimization means performs demand control based on the predicted power consumption values ​​up to the previous day, the predicted power generation values ​​and the buying and selling prices in the power trading market, and determines the selection and amount of power to be used in the demand control, as well as the timing and amount of power to be sold, the second optimization means performs a second demand control that is more precise than the first demand control based on the predicted power consumption values ​​and the predicted power generation values ​​for the day in the prediction means, and determines the selection and amount of power to be used in the second demand control, thereby providing a power supply and demand adjustment system.

[0008] Furthermore, in addition to the configuration described above, the present invention is characterized in that the second optimization means performs a third demand control that is more precise than the second demand control, based on the measurement results of the power consumption of the facility immediately before and the measurement results of the power generation amount of the company's own power generation device immediately before, and determines the selection and amount of power to be used in the third demand control.

[0009] Furthermore, in addition to the configuration described above, the present invention is characterized in that the prediction means has a storage amount prediction means that predicts the subsequent storage amount of the storage battery based on the measurement results of the storage amount of the storage battery owned, the appropriate power selection means selects at least one of the power from the power generation amount prediction value of the power generation amount prediction means, the buying and selling price prediction value of the buying and selling price prediction means and the storage amount prediction value of the storage amount prediction means as appropriate power to be used for the demand control by the demand control means, and determines the amount to be used, and the arbitrage transaction determination means is configured to determine whether to sell the power from the power generation device and / or the storage battery, and if so, the timing and amount of power to be sold, based on the result of the appropriate power selection means.

[0010] Furthermore, in addition to the configuration described above, the present invention is characterized in that the demand control means performs the demand control so that the amount of power consumption of the grid power falls between two thresholds: an upper threshold set for the purpose of peak cut control and a lower threshold set for the purpose of reverse power flow control.

[0011] Furthermore, in addition to the configuration described above, the present invention is characterized in that the in-house power generation device is a power supply and demand adjustment system that includes a renewable energy power generation device.

[0012] According to the present invention, since it includes a prediction means for predicting the amount of electricity used and generated by a facility, as well as the buying and selling prices in the electricity trading market, and an optimization means for optimizing the facility's power situation based on these prediction results, the accuracy of demand control can be improved, and significant profits can be made from buying and selling surplus electricity after demand control. Furthermore, appropriate power selection can be made in demand control. As a result, it is possible to find ways to reduce grid power costs and effectively utilize on-site power generation in various power situations.

[0013] Furthermore, according to the present invention, there is a first optimization means based on information up to the previous day and a second optimization means based on information for the current day, and after demand control by the first optimization means, a second demand control is performed by the second optimization means, so that demand control can be performed with higher accuracy.

[0014] Furthermore, according to the present invention, since the second optimization means performs a third demand control based on measured values ​​after the second demand control, even more accurate demand control can be achieved.

[0015] Furthermore, according to the present invention, it is possible to predict the amount of electricity including that stored in batteries and make appropriate power selections in demand control, and to sell surplus electricity, including that stored in batteries, thereby more effectively reducing grid power costs and finding ways to utilize in-house power generation and storage.

[0016] Furthermore, according to the present invention, since demand control is performed so that the amount of power consumption of grid power falls between the upper threshold set for the purpose of peak cut control and the lower threshold set for the purpose of reverse power flow control, it is possible to reduce grid power costs and prevent problems caused by reverse power flow.

[0017] Furthermore, according to the present invention, since the company's own power generation equipment includes renewable energy power generation equipment, it is possible to aim for cost reduction and profit improvement while being more environmentally conscious.

[0018] This is a system configuration diagram illustrating a power supply and demand adjustment system according to an embodiment of the present invention. This is a functional flow diagram illustrating the flow of the power supply and demand adjustment system according to the same embodiment. This is a diagram illustrating the flow of the third demand control of the power supply and demand adjustment system according to the same embodiment. This is a separate diagram illustrating the flow of the third demand control of the power supply and demand adjustment system according to the same embodiment. This is a table showing examples of the measurement results for the previous day and the forecast results for the next day of the power supply and demand adjustment system according to the same embodiment. This is a table showing examples of the measurement results for the current day and the forecast results for the current day of the power supply and demand adjustment system according to the same embodiment.

[0019] Hereinafter, embodiments of the present invention will be described with reference to Figures 1 to 6.

[0020] The following describes the power supply and demand adjustment system 1 according to this embodiment. The power supply and demand adjustment system 1 of this embodiment is a system that adjusts the supply and demand of electricity required by a predetermined facility (for example, one building, one factory, one business establishment, etc.) in order to reduce the cost of using grid electricity, sell electricity at a higher price, or buy electricity at a lower price, thereby achieving an overall cost-effective state of electricity usage.

[0021] First, an overview of the power supply and demand adjustment system 1 of this embodiment will be described using Figure 1. The power supply and demand adjustment system 1 of this embodiment consists of a power supply and demand adjustment device 10, which comprises a computer device installed in the cloud and a LocalEMS 70 installed at the local site where the facility is located, and is electrically connected to the demand 20, owned storage batteries 30, company-owned power generation equipment 40, power trading market 50, etc., via a network such as the Internet.

[0022] Here, the LocalEMS 70 of the power supply and demand adjustment device 10 installed at the local site monitors the demand 20, storage battery 30, and in-house power generation equipment 40 via a gateway device 60. This LocalEMS 70 is configured to exchange information with the prediction and optimization means of the power supply and demand adjustment device 10 installed in the cloud. Note that Figure 1 only illustrates the exchange of information, and the illustration of the power supply flow, etc., is omitted.

[0023] The power supply and demand adjustment device 10 in this embodiment is a cloud-based computer device having a CPU, RAM, memory, ROM, etc., and the CPU instructs each means to store data based on the data stored in RAM, memory, ROM, etc., to perform appropriate processing, and to place orders for power supply and power buying and selling.

[0024] Furthermore, as shown in Figure 1, the power supply and demand adjustment device 10 of this embodiment has a prediction means (prediction engine) 10A and optimization means (optimization engines) 10B and 10C, of ​​which the optimization means has two different means (engines): a first optimization means 10B and a second optimization means 10C.

[0025] Furthermore, the prediction means 10A includes prediction means 11 for electricity usage, 12 for power generation, 13 for stored energy, and 14 for electricity price prediction.

[0026] Furthermore, the first optimization means 10B is configured to have the functions of a demand control means 15, an appropriate power selection means 16, and an arbitrage transaction decision means 17.

[0027] Furthermore, the second optimization means 10C is configured to have the functions of a demand control means 15C and an appropriate power selection means 16C.

[0028] Of these, the power consumption prediction means 11 stores the measurement results of the facility's power consumption from the demand 20, and also makes and stores predictions of future power consumption (for example, tomorrow, the next 30-minute interval, etc.). Here, the AI ​​is configured to acquire and measure results such as the weather and the demand situation within the facility each day and hour, and based on these results, predict the power consumption every 30 minutes for tomorrow, as shown in the demand column of Figure 5. Furthermore, the AI ​​may also be configured to predict power consumption for the next week or month and output the prediction results.

[0029] Furthermore, the power generation prediction means 12 measures the amount of power generated by the company's own power generation equipment 40, and, taking into account the weather and conditions within the facility each day and hour, predicts the amount of power generated every 30 minutes tomorrow, as shown in the "generation" column of Figure 5. In this case, the company's own power generation equipment 40 is a solar power generation system, and the power generation prediction is performed using this system.

[0030] Furthermore, the energy storage amount prediction means 13 measures the amount of energy stored in the battery 30, which stores a portion (or all, depending on the time, etc.) of the electricity generated by the company's own power generation device 40, as well as purchased electricity. Based on the results, taking into account the weather and conditions within the facility each day and each hour, it is configured to predict the amount of energy stored every 30 minutes tomorrow, as shown in the charge column of Figure 5.

[0031] Furthermore, the electricity price forecasting means 14 measures the trends in buying and selling prices in the electricity trading market, and, taking into account the weather and general situation at each time of day, is configured to predict the buying and selling prices every 30 minutes for the next day, as shown in the spot_price column of Figure 5. Here, JEPX (Japan Electric Power Exchange) and EPRX (Supply and Demand Adjustment Market) are specified as the markets for which buying and selling prices are measured and predicted. In addition, here, it is configured to measure and predict not only the selling price but also the buying price of electricity (only the selling price for the Supply and Demand Adjustment Market).

[0032] These four measurements and forecasts for electricity consumption and price are updated regularly or irregularly on a daily basis and stored in each forecasting device.

[0033] Furthermore, the first optimization means 10B optimizes the amount of electricity used, generated, stored, and electricity buying and selling status for tomorrow (the next day) based on the prediction results of the prediction means 10A, and creates an optimized state as shown in the table in Figure 5.

[0034] Furthermore, the demand control means 15 of the first optimization means 10B, based on the predicted value of the power usage prediction means 11, performs peak cut control (demand control) at predicted points (for example, 2022-04-01 16:30 in Figure 5) where the hourly power usage of the grid power exceeds the upper threshold of the pricing system (Upper_threhold in Figure 5, here 1400 kWh), by stopping the grid power before the power usage exceeds the threshold and supplementing the power using other power means. This allows the pricing system for the grid power to be kept below the upper threshold, thereby reducing costs.

[0035] Furthermore, in this embodiment, the demand control means 15 of the first optimization means 10B, based on the predicted value of the power usage prediction means 11, performs reverse power flow control (demand control) at predicted points (for example, 2022-04-01 07:00 in Figure 5) where the total power usage per hour falls below the lower threshold (Lower_threhold in Figure 5, here 50 kWh), by stopping the grid power before the power usage falls below the lower threshold and supplementing the power using other power means. This prevents the power usage from falling below the threshold and continuing to decline into negative values, causing reverse power flow and avoiding problems such as damage to facility equipment and penalties from grid power due to reverse power flow.

[0036] Furthermore, the appropriate power selection means 16 of the first optimization means 10B selects the appropriate power to be used for demand control by the demand control means 15 of the first optimization means 10B from the power of the company's own power generation equipment 40 and the power of any other power supply means other than grid power, based on the power generation amount prediction value of the power generation amount prediction means 12, and also determines the amount to be used. Here, based on the power generation amount prediction value of the power generation amount prediction means 12, the buying and selling price prediction value of the power price prediction means 14, and the storage amount prediction value of the storage amount prediction means 13, the appropriate power to be used for demand control by the demand control means 15 is selected from at least one of the power of the company's own power generation equipment 40, power procured from the power buying and selling market 50, and power from the storage battery 30, and also determines the amount to be used (here, this is determined every 30 minutes).

[0037] For example, if the power generation capacity of the power generator 40 is sufficient to cover the shortfall, the system switches to supplying power solely from the power generator 40. If the power generation capacity of the power generator 40 alone is insufficient to cover the shortfall, the system uses power stored in the battery 30 in conjunction with the power generator 40, or power purchased from the electricity trading market 50 in conjunction with the power generator 40. The system then selects the power to be used for demand control under these conditions.

[0038] Furthermore, the arbitrage transaction decision means 17 of the first optimization means 10B decides whether to sell electricity if there is a surplus of electricity from the company's own power generation equipment 40, based on the results of the appropriate power selection means 16 of the first optimization means 10B. If it is decided to sell electricity, it identifies the time when the selling price will be high based on the predicted value of the electricity price prediction means 14 and determines the amount of electricity to sell. In addition, in this embodiment, the arbitrage transaction decision means 17 of the first optimization means 10B decides whether to buy electricity during the time when the purchase price is low, taking into account various circumstances such as the amount of electricity used per day. If it is decided to buy electricity, it identifies the time when the purchase price will be low based on the predicted value of the electricity price prediction means 14 and determines the amount of electricity to buy.

[0039] Furthermore, the second optimization means 10C, based on the prediction results of the prediction means 10A, adds more detailed information such as the weather on that day and re-optimizes the amount of electricity used, generated, and stored for the time period later on that day (for example, for 30-minute intervals after the current 30-minute interval) to create an even more detailed optimization state.

[0040] Furthermore, the demand control means 15C of the second optimization means 10C, based on the predicted value of the power usage prediction means 11 for the day, performs peak-cut control again (second demand control) by stopping the power supply to the grid before the power usage exceeds the threshold (for example, 2022-04-01 16:30 in Figure 6) and supplementing the power using other power means, at predicted points (for example, 2022-04-01 16:30 in Figure 6) where the hourly power usage of the grid power exceeds the upper threshold of the rate system (upper_threhold in Figure 6, here 1400 kWh). This makes it possible to keep the rate system for the grid power below the upper threshold in a more precise manner, thereby reducing costs. Furthermore, in this embodiment, the demand control means 15C of the second optimization means 10C, based on the predicted value of the power usage prediction means 11 for the day, performs reverse power flow control again (second demand control) at predicted points (for example, 2022-04-01 07:00 in Figure 6) where the total hourly power usage falls below the lower threshold (lower_threhold in Figure 6, here 50 kWh), by stopping the grid power before the power usage falls below the lower threshold and supplementing the power using other power means. This prevents reverse power flow from occurring when the power usage falls below the threshold and continues to decline into a negative value, thus avoiding problems such as damage to facility equipment and penalties from grid power caused by reverse power flow.

[0041] Furthermore, the appropriate power selection means 16C of the second optimization means 10C selects the appropriate power to be used for the second demand control by the demand control means 15C of the second optimization means 10C from the power of the company's own power generation device 40 and the power of any other power supply means other than grid power, based on the predicted power generation amount of the power generation amount prediction means 12 for the day, and also determines the amount to be used. Here, based on the predicted power generation amount of the power generation amount prediction means 12, the predicted buying and selling price of the power price prediction means 14, and the predicted storage amount of the storage amount prediction means 13, the appropriate power to be used for the second demand control by the demand control means 15C is selected from at least one of the power of the company's own power generation device 40, the power procured from the power buying and selling market 50, and the power of the storage battery 30, and the amount to be used is determined again (here, determined every 30 minutes).

[0042] For example, when the shortage can be compensated by the power generation amount of the power generation device 40, the power supply is switched only to the power supply from the power generation device 40. Further, when the shortage cannot be compensated only by the power generation amount of the power generation device 40, etc., the power stored in the storage battery 30 is used in combination with the power generation device 40, or the power purchased from the power trading market 50 is used in combination with the power generation device 40. The power used for the second demand control is selected in such a state.

[0043] Further, the demand control means 15C and the appropriate power selection means 16C of the second optimization means 10C perform demand control (third demand control) for the future time of the day (for example, every 1 minute or every 1 second within the current 30 - minute unit) based on the measurement result of the power consumption of the previous facility and the measurement result of the power generation amount of the in - house power generation device 40 immediately before. Thereby, more precise demand control can be performed, and demand control can be performed more reliably. The details of the third demand control will be described later.

[0044] Next, with reference to FIG. 2, a more specific processing flow of the power supply - demand adjustment system 1 will be described.

[0045] First, the LocalEMS 70 measures the power consumption of the demand 20 daily (step S1), and then the power consumption prediction means 11 predicts the power consumption of the demand 20 for a specific period (step S2).

[0046] Also, the LocalEMS 70 measures the power generation amount of the in - house power generation device 40 daily (step S3), and then the power generation amount prediction means 12 predicts the power generation amount of the in - house power generation device 40 for a specific period (step S4).

[0047] Also, the LocalEMS 70 measures the stored power amount of the storage battery 30 held daily (step S5), and then the stored power amount prediction means 13 predicts the stored power amount of the storage battery 30 held for a specific period (step S6).

[0048] Also, the power price prediction means 14 measures the price trend of the power trading market 50 daily (step S7), and then the power price prediction means 14 predicts the selling and buying prices of power for a specific period (step S8).

[0049] Next, the demand control means 15 of the first optimization means 10B determines the time and amount of power to perform demand control based on the predicted value of the electricity usage prediction means 11 (step S9).

[0050] Next, the appropriate power selection means 16 of the first optimization means 10B determines, from the perspective of cost, efficiency, etc., the appropriate power to be used to supplement grid power in demand control, based on the time and amount of power for demand control determined by the demand control means 15 of the first optimization means 10B, by comprehensively selecting the type and amount of power to be used from the power of the company's own power generation equipment 40 and the power of other power supply means other than grid power (in this embodiment, the predicted power generation amount of the company's own power generation equipment 40 by the power generation amount prediction means 12, the predicted buying and selling price of the electricity trading market 50 by the power price prediction means 14, and the predicted storage amount of the storage battery 30 owned by the storage amount prediction means 13). (Step S10)

[0051] Furthermore, it is not necessary to decide on only one type of electricity to be used; in some cases, two or more types of electricity may be used in appropriate proportions.

[0052] Next, the arbitrage transaction decision means 17 of the first optimization means 10B decides whether or not to sell the electricity generated by the company's power generation equipment 40, based on the results of the appropriate power selection means 16 and the power price prediction means 14 of the first optimization means 10B, and if it decides to sell the electricity, it determines the time and amount of electricity that can be sold at the highest price. Furthermore, the arbitrage transaction decision means 17 of the first optimization means 10B decides whether or not to purchase electricity during a time when the purchase price is low, taking into account various circumstances such as the amount of electricity used per day. If it decides to purchase electricity, it identifies the time when the purchase price will be low based on the predicted value of the power price prediction means 14 and determines the amount of electricity to purchase (step S11).

[0053] This process is predicted and decided at least the day before, and this is repeated.

[0054] Next, I will explain the processing flow for the second demand control on that day.

[0055] First, the LocalEMS 70 measures the electricity usage of Demand 20 on a daily basis, and then the electricity usage prediction means 11 predicts the electricity usage of Demand 20 for the day (in 30-minute intervals after the current 30-minute interval).

[0056] Furthermore, LocalEMS 70 measures the amount of power generated by the in-house power generator 40 on a daily basis, and then the power generation prediction means 12 predicts the amount of power generated by the in-house power generator 40 for the day (for every 30-minute interval after the current 30-minute interval).

[0057] Furthermore, the LocalEMS 70 measures the amount of charge stored in the battery 30 on a daily basis, and then the charge amount prediction means 13 predicts the amount of charge stored in the battery 30 for the day (every 30-minute interval after the current 30-minute interval).

[0058] Next, the demand control means 15C of the second optimization means 10C determines the time and amount of power to perform the second demand control based on the predicted value of the electricity usage prediction means 11 (every 30-minute interval after the current 30-minute interval).

[0059] Next, the appropriate power selection means 16C of the second optimization means 10C determines, from the perspective of cost, efficiency, etc., the appropriate power to be used to supplement grid power in the second demand control, based on the time and amount of power for the second demand control determined by the demand control means 15C of the second optimization means 10C, and from the power of the company's own power generation equipment 40 and other power supply means other than grid power (in this embodiment, the predicted power generation amount of the company's own power generation equipment 40 by the power generation amount prediction means 12, the predicted buying and selling price of the electricity trading market 50 by the electricity price prediction means 14, and the predicted storage amount of the battery 30 owned by the storage amount prediction means 13). This determines the type and amount of power to be used in the second demand control, based on the time and amount of power for the second demand control determined by the demand control means 15C of the second optimization means 10C.

[0060] Furthermore, it is not necessary to decide on only one type of electricity to be used; in some cases, two or more types of electricity may be used in appropriate proportions.

[0061] This process predicts and makes decisions every 30 minutes from the present time onward, and this is repeated continuously (for example, every 30 minutes).

[0062] Next, we will explain the processing flow for the third demand control on the day (executed in minute increments, such as every 1 to 10 minutes) using Figure 3.

[0063] First, the gateway device 60 reads the register information (power consumption, power generation, and stored energy), writes it to the LocalEMS 70 database, and transmits the data to the power supply and demand adjustment device 10 (step S21).

[0064] Next, control instructions are obtained from the power supply and demand adjustment device 10 and written to the LocalEMS 70 database (step S22).

[0065] Next, maintenance information is obtained from the power supply and demand adjustment device 10 and written to the LocalEMS 70 database (step S23).

[0066] Next, the state of real_demand (= Demand-Generation) is obtained and a control decision is made (step S24).

[0067] Here, if reverse power flow control and peak cut control have not been performed for the past 10 minutes (i.e., lower_threhold < real_demand < upper_threhold), the ESS active power adjustment is performed as planned (step S25). Note that during maintenance, the facility's demand decreases significantly, but if solar power generation continues as usual, there is a risk of reverse power flow. Therefore, during maintenance, the PV active power adjustment is set to 0%, and otherwise it is set to 100%, and a planned control instruction is issued to write these instructions to the LocalEMS database.

[0068] In parallel with the above control, device alert monitoring is performed to acquire the status of device alerts and, if an alert exists, to send it to a pre-configured email address (step S26).

[0069] Finally, the LocalEMS database is cleared for more than one week (step S27).

[0070] Furthermore, if reverse power flow control or peak cut control has been performed in the last 10 minutes, step S25 is not performed, and steps S26 and S27 are performed instead.

[0071] Next, we will explain the processing flow for the third demand control on that day (executed in seconds, for example, every 1 to 30 seconds) using Figure 4.

[0072] First, the gateway device 60 reads the register information (power consumption, power generation, and stored energy), writes it to the LocalEMS 70 database, and transmits the data to the power supply and demand adjustment device 10 (step S31).

[0073] Next, maintenance information is obtained from the power supply and demand adjustment device 10, and it is determined whether maintenance is in progress (step S32). If maintenance is in progress, maintenance control is performed (step S36). Note that while the facility's demand decreases significantly during maintenance, there is a risk of reverse power flow if solar power generation continues as usual, so the PV active power adjustment is set to 0% during maintenance.

[0074] Next, the state of real_demand (= Demand-Generation) is obtained and a control decision is made (step S33).

[0075] If reverse power flow control and peak cut control have not been performed for the past 10 minutes (i.e., lower_threhold < real_demand < upper_threhold), then nothing is done and the process terminates.

[0076] Furthermore, if reverse power flow control has been performed in the last 10 minutes or if real_demand < lower_threhold, the system calculates ESS target power = real_demand - reverse power flow target power if maintenance is not in progress, and calculates ESS target power = demand power - reverse power flow target power if maintenance is in progress. The system then sets the value of ESS target power to the value of ESS active power adjustment, sets PV active power adjustment to 0% if maintenance is in progress, and sets it to 100% otherwise, and performs reverse power flow control by writing the instructions to the LocalEMS database (step S34).

[0077] Furthermore, if peak cut control has been performed in the last 10 minutes or if real_demand > upper_threhold, if maintenance is not in progress, the ESS target power = peak cut target power - real_demand is calculated; if maintenance is in progress, the ESS target power = peak cut - demand power is calculated; the value of the ESS target power is set to the value of the ESS active power adjustment; if maintenance is in progress, the PV active power adjustment is set to 0%; otherwise, it is set to 100%; and the instruction is written to the LocalEMS database to perform peak cut control (step S35).

[0078] As described above, the power supply and demand adjustment system 1 of this embodiment includes a prediction means 10A that predicts the amount of electricity used and generated by a facility, as well as the buying and selling prices in the electricity trading market, and optimization means 10B and 10C that optimize the power situation of the facility based on these prediction results. Therefore, it is possible to improve the accuracy of demand control and to make a large profit from buying and selling surplus electricity after demand control. Furthermore, it is possible to make appropriate power selections in demand control. As a result, it is possible to find ways to cut grid power costs and effectively utilize on-site power generation in various power situations.

[0079] Furthermore, the power supply and demand adjustment system 1 of this embodiment includes a first optimization means 10B based on information up to the previous day and a second optimization means 10C based on information for the current day. Since the second optimization means 10C performs a second demand control after the first optimization means 10B has performed a demand control, more accurate demand control can be achieved.

[0080] Furthermore, according to the power supply and demand adjustment system 1 of this embodiment, the second optimization means 10C performs a third demand control based on measured values ​​after the second demand control, thereby enabling even more accurate demand control.

[0081] Furthermore, according to the power supply and demand adjustment system 1 of this embodiment, it is possible to predict the amount of electricity including the storage battery 30 and make appropriate power selection in demand control, and surplus electricity including the power from the storage battery 30 can be sold back to the grid, thereby enabling more effective cost reduction of grid power and the discovery of ways to utilize in-house power generation and storage.

[0082] Furthermore, according to the power supply and demand adjustment system 1 of this embodiment, demand control is performed so that the amount of power consumption of grid power falls between the upper threshold set for the purpose of peak cut control and the lower threshold set for the purpose of reverse power flow control. As a result, grid power costs can be reduced, and problems caused by reverse power flow can also be prevented.

[0083] Furthermore, according to the power supply and demand adjustment system 1 of this embodiment, since the company's own power generation equipment 40 includes renewable energy power generation equipment, it is possible to aim for cost reduction and profit improvement while being more environmentally conscious.

[0084] Although the present invention has been described using the embodiments described above, these embodiments are intended to facilitate understanding of the present invention and are not intended to limit its interpretation. The present invention can be modified and improved without departing from its spirit, and equivalents thereof are also included.

[0085] For example, in the embodiment described above, a solar power generation system was used as the in-house power generation system 40, but it is not limited to this, and the in-house power generation system 40 may be other renewable energy power generation systems such as wind power generation systems or geothermal power generation systems. Furthermore, the in-house power generation system 40 may be a system other than a renewable energy power generation system, such as a thermal power generation system.

[0086] Furthermore, in the above-described embodiment, the prediction means 10A, the first optimization means 10B, and the second optimization means 10C were configured to function with different programs (engines), but the system is not limited to this, and may be configured so that all or more functions are handled by a single engine.

[0087] Furthermore, in the embodiment described above, demand control was performed for the previous day, a second demand control for the current day, and a third demand control based on the actual measured value for the current day. However, the embodiment is not limited to this, and it is also possible to perform only one or two of the demand controls instead of performing all of them.

[0088] Furthermore, in the embodiment described above, the second and third demand control for the day were set to be performed in minute and second increments, respectively, but this is not the only option; they can be set to be performed at appropriate intervals.

[0089] Furthermore, during periods when electricity usage is nearly constant (for example, at night when factories or facilities are not operating, and electricity usage is known to be low and nearly constant), the threshold will not be exceeded even without frequent peak cutting or reverse power flow assessments. Therefore, the intervals between the second and third demand control measures can be widened. Conversely, during periods when electricity usage is prone to change (for example, during specific daytime hours when electricity usage is known to fluctuate significantly due to special operations), the threshold may be exceeded if peak cutting or reverse power flow assessments are not performed frequently. Therefore, the intervals between the second and third demand control measures can be narrowed. The control system may be configured to vary depending on the time of day.

[0090] 1. Supply and Demand Adjustment System 10. Power Supply and Demand Adjustment Device 10A. Prediction Means 10B. First Optimization Means (Optimization Means) 10C. Second Optimization Means (Optimization Means) 11. Power Consumption Prediction Means 12. Power Generation Prediction Means 13. Energy Storage Prediction Means 14. Power Price Prediction Means 15. Demand Control Means 15C. Demand Control Means 16. Appropriate Power Selection Means 16C. Appropriate Power Selection Means 17. Arbitrage Transaction Decision Means 20. Demand 30. Storage Battery 40. Power Generation Device 50. Power Trading Market 60. Gateway Device 70. LocalEMS

Claims

1. Prediction means comprising: power consumption prediction means for predicting the subsequent power consumption of the facility based on the measurement results of the facility's power consumption; power generation prediction means for predicting the subsequent power generation of the company's own power generation equipment based on the measurement results of the power generation of the company's own power generation equipment; and trading price prediction means for predicting the subsequent trading price of the electricity trading market based on the trend of trading prices in the electricity trading market; and optimization means for optimizing the power status of the facility based on the prediction results of the prediction means, wherein the optimization means comprises: demand control means for performing grid power demand control based on the power consumption prediction value of the power consumption prediction means; appropriate power selection means for selecting appropriate power to be used for the demand control by the demand control means from the power of the company's own power generation equipment and power from other power supply means other than the grid power, and determining the amount to be used; and arbitrage transaction decision means for determining whether to sell the power of the company's own power generation equipment, and if so, the timing and amount of power to be sold, based on the result of the appropriate power selection means and the trading price of the electricity trading market predicted by the trading price prediction means. A power supply and demand adjustment system characterized by having the following features.

2. The power supply and demand adjustment system according to claim 1, characterized in that the optimization means comprises a first optimization means and a second optimization means, the first optimization means performs demand control based on the predicted power consumption values ​​up to the previous day, the predicted power generation values, and the buying and selling prices in the power trading market, and determines the selection and amount of power to be used in the demand control, as well as the timing and amount of power to be sold, and the second optimization means performs a second demand control that is more precise than the first demand control based on the predicted power consumption values ​​and the predicted power generation values ​​for the day in the prediction means, and determines the selection and amount of power to be used in the second demand control.

3. The power supply and demand adjustment system according to claim 2, characterized in that the second optimization means further performs a third demand control that is more precise than the second demand control, based on the measurement results of the power consumption of the facility immediately before and the measurement results of the power generation of the company's own power generation equipment immediately before, and determines the selection and amount of power to be used in the third demand control.

4. The power supply and demand adjustment system according to any one of claims 1 to 3, characterized in that the prediction means has a charge amount prediction means that predicts the subsequent charge amount of the battery based on the measurement results of the charge amount of the battery owned, the appropriate power selection means selects at least one of the power from the power generation prediction value of the power generation prediction means, the buying and selling price prediction value of the buying and selling price prediction means, and the charge amount prediction value of the charge amount prediction means, as appropriate power to be used for the demand control by the demand control means, and determines the amount to be used, and the arbitrage transaction determination means is configured to determine whether to sell the power from the company's power generation device and / or the power from the battery, and if so, the timing and amount of power to be sold.

5. The power supply and demand adjustment system according to claim 1, characterized in that the demand control means performs demand control so that the amount of power consumption of the grid power falls between an upper threshold set for the purpose of peak cut control and a lower threshold set for the purpose of reverse power flow control.

6. The power supply and demand adjustment system according to claim 1, characterized in that the company's own power generation equipment includes a renewable energy power generation equipment.

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