Electricity rate design system and electricity rate design method

Abstract

This electricity rate design system comprises: a variable equipment operation plan calculation unit that calculates an operation plan and electricity costs for variable equipment by applying a variable rate or fixed rate to the variable equipment under estimated operation conditions; a non-variable equipment electricity cost calculation unit that calculates electricity costs for non-variable equipment by applying a variable rate or fixed rate to measurement data of the non-variable equipment; and an electricity cost aggregation unit that aggregates the electricity costs calculated by the variable equipment operation plan calculation unit and the electricity costs calculated by the non-variable equipment electricity cost calculation unit and presents the aggregated data to consumers as electricity rate design data.

Description

Power Tariff Design System and Power Tariff Design Method

[0001] The present invention relates to a power tariff design system and a power tariff design method.

[0002] The power tariff charged by a retail electricity business operator to a customer who uses electricity generally consists of a basic charge determined by the contract capacity and an electricity quantity charge calculated according to the electricity quantity used. Usually, the electricity quantity charge is calculated using the unit price per kWh (hereinafter referred to as the "kWh unit price"). A retail electricity business operator is, for example, a business operator who procures electricity through power market transactions or bilateral transactions and mediates the sale and purchase of electricity. A customer is generally a person who consumes electricity in factories, homes, buildings, etc.

[0003] The electricity quantity charge is designed taking into account the wholesale power trading market, procurement costs from power generation business operators, entrusted delivery costs paid to power transmission and distribution business operators, supply and demand management costs required for the planned value at the same time and the same quantity, etc. Among these costs, when a retail electricity business operator procures electricity from the wholesale power trading market, the procurement unit price per unit kWh (for example, 1 kWh) changes with the date and time. For example, in the short term, the procurement unit price tends to decrease during the daytime when the power generation amount of solar power generation increases, and tends to increase in the evening when the power generation amount of solar power generation decreases and the power generation amount of thermal power generation increases. Also, in the long term, the procurement unit price increases or decreases due to the influence of fuel prices such as LNG (Liquefied Natural Gas). In the design of power tariffs, these short- and long-term procurement unit price fluctuations are also taken into account.

[0004] The electricity quantity charge is broadly classified into a fixed charge and a variable charge. Here, the fixed charge refers to a charge with a constant kWh unit price regardless of the time zone when electricity is used. The variable charge refers to a charge with a changing kWh unit price depending on the time zone when electricity is used.

[0005] In the fixed charge, fluctuations in the procurement unit price are partially reflected in the form of a fuel cost adjustment amount, a market price adjustment amount, etc. However, since fluctuations in the procurement unit price are settled on a monthly basis or the like in the fixed charge, there is no effect of inducing electricity use by customers to the low-price time zone of the market. On the other hand, the variable charge has the effect of demand shift that induces electricity use by customers to the low-price time zone of the market due to the kWh unit price that changes over time.

[0006] Variable rates are classified into time-of-day rates, where the kWh price changes during the day but not daily, and constant rates, where the price also changes daily. A typical example of time-of-day rates is the nighttime discount electricity rate plan, which lowers the kWh price at night to utilize surplus electricity at night. There are also daytime discount electricity rate plans, which lower the kWh price during daytime hours, due to the expansion of solar power generation. A typical example of constant rates is the market-linked rate, where the kWh price is linked to the procurement price (for example, the 30-minute contract price in the market a day in advance). Market-linked rates are a mechanism that passes on the risk of fluctuations in market procurement prices directly to consumers without the retail electricity provider bearing the risk.

[0007] As prior art concerning a combination of fixed and variable rates, Patent Document 1 discloses a form of applying multiple electricity rate plans to a single customer.

[0008] Patent Document 1 states that "electricity demand information is divided into base electricity demand information, which represents the standard electricity demand based on the minimum electricity usage, and load-following electricity demand information, which represents the electricity demand that follows or fluctuates according to the load (specifically, the amount of electricity used)." It also states that "when the electricity demand information is divided, the total electricity charge, which is the sum of the first electricity charge based on the first rate plan information and the base electricity demand information, and the second electricity charge based on the second rate plan information and the load-following electricity demand information, is calculated sequentially for each of the following three cases. The first case is when the first rate plan information is contracted for a specific contracted power. The second case is when the electricity is contracted for a predetermined amount increased from that specific contracted power. The third case is when the electricity is contracted for a predetermined amount decreased from that specific contracted power." Patent Document 1 also lists demand response (DR) type rate plan information, which is a type of variable rate, as one of the applicable rate plans. Here, DR is defined as "a system that sets electricity rates by time of day and encourages reduced usage by paying compensation to consumers who refrain from using electricity during peak hours, thereby reducing peak electricity consumption and ensuring a stable supply of electricity."

[0009] Patent No. 6711077

[0010] As mentioned above, a method has been disclosed for reducing a customer's electricity costs by applying both fixed and variable rates to a single customer. However, in the example in Patent Document 1, although the target to which different rate plans are applied is divided into base power demand and load-following power demand, the variability of individual electrical equipment that uses electricity is not mentioned. For example, if the electrical equipment is variable equipment whose power consumption can be changed, electricity costs can be reduced by applying variable rates. However, if it is non-variable equipment whose power consumption cannot be changed, the period of high power consumption may coincide with the period of high kWh unit price, which may actually increase electricity costs. Alternatively, if variable and non-variable equipment are mixed, a trade-off may arise where a variable rate designed to reduce the electricity costs of variable equipment increases the electricity costs of non-variable equipment. This problem is not limited to the example in Patent Document 1, but can similarly occur when applying variable rates without distinguishing between electrical equipment downstream of the power receiving point.

[0011] This invention was made in view of these circumstances, and aims to design a combination of fixed and variable charges in a way that allows consumers to judge the effect of reducing electricity costs.

[0012] The electricity rate design system according to the present invention includes a variable rate database storing variable rate unit price data, a fixed rate database storing fixed rate unit price data, a variable device measurement database storing variable device measurement data acquired from a variable device measurement device that measures the amount of energy used by a customer's variable device, a variable device specification database storing variable device specification data, an operating condition estimation unit that estimates the operating conditions of the variable device based on the variable device measurement data and the variable device specification data, and a variable rate design system that applies variable rates or fixed rates under the operating conditions. The system comprises: a variable equipment operation plan calculation unit that calculates the operation plan and electricity costs of equipment; a variable equipment measurement database that stores variable equipment measurement data acquired from a variable equipment measurement device that measures the amount of energy used by the customer's non-variable equipment; a non-variable equipment electricity cost calculation unit that calculates the electricity costs of non-variable equipment by applying variable or fixed charges to the non-variable equipment measurement data; and an electricity cost aggregation unit that aggregates the electricity costs calculated by the variable equipment operation plan calculation unit and the electricity costs calculated by the non-variable equipment electricity cost calculation unit and presents this aggregated data to the customer as electricity rate design data.

[0013] According to the present invention, a combination of fixed and variable charges can be designed in a way that allows consumers to judge the effect of reducing electricity costs. Other issues, configurations, and effects will be clarified by the following description of embodiments. The above electricity rate design system is one aspect of the present invention, and an electricity rate design method that reflects one aspect of the present invention is configured in the same way as the above electricity rate design system.

[0014] This is a block diagram showing an example of the functional configuration of the electricity rate design system according to the first embodiment of the present invention. This is a block diagram showing an example of the hardware configuration of the electricity rate design system according to the first embodiment of the present invention. This is a graph showing the calculation procedure for the demand shift operation plan in the electricity rate design system according to the first embodiment of the present invention. This is a table showing an example of the configuration of a rate plan in the electricity rate design system according to the first embodiment of the present invention. This is a graph showing a comparison of rate plans in the electricity rate design system according to the first embodiment of the present invention. This is a graph showing a comparison of rate plans in the electricity rate design system according to the first embodiment of the present invention. This is a graph showing a comparison of rate plans in the electricity rate design system according to the first embodiment of the present invention. This is a graph showing the suitability of a rate plan in the electricity rate design system according to the first embodiment of the present invention. This is a flowchart showing the rate plan comparison procedure in the electricity rate design system according to the first embodiment of the present invention. This is a data table of electricity rate design data in the electricity rate design system according to the first embodiment of the present invention. This is a block diagram showing an example of the functional configuration of the electricity rate design system according to the second embodiment of the present invention. This is a graph showing the quantification of the breakdown of kWh unit price in the electricity rate design system according to the second embodiment of the present invention. This is a graph showing the adjustment of the breakdown of kWh unit price in the electricity rate design system according to the second embodiment of the present invention. This is a graph showing the adjustment of variable charges in the electricity rate design system according to the second embodiment of the present invention. This is a graph showing rate plan comparison and electricity cost adjustment in the electricity rate design system according to the second embodiment of the present invention. This is a data table of electricity rate design data in the electricity rate design system according to the second embodiment of the present invention. This is a data table of variable charges before and after adjustment in the electricity rate design system according to the second embodiment of the present invention. This is a graph showing the player's profit distribution in the electricity rate design system according to the second embodiment of the present invention.

[0015] Hereinafter, embodiments for carrying out the present invention will be described with reference to the accompanying drawings. In this specification and drawings, components having substantially the same function or configuration are denoted by the same reference numerals, and redundant descriptions are omitted.

[0016] <First Embodiment> Figure 1 is a block diagram showing an example of the functional configuration of the electricity rate design system 21 according to this embodiment. The electricity rate design system 21 consists of equipment on the business side, including retail electricity businesses, and equipment on the consumer side.

[0017] The equipment on the operator's side includes a variable rate database 101, a fixed rate database 102, a variable equipment measurement database 105, a variable equipment specification database 106, an operating condition estimation unit 107, a variable equipment operation plan calculation unit 108, a non-variable equipment power cost calculation unit 112, and a power cost aggregation unit 113. In the diagram, each database is abbreviated as DB.

[0018] The variable rate database 101 stores the variable rate per kWh in the form of time-series data, as variable rate kWh rate data (an example of variable rate electricity unit price data).

[0019] The fixed-rate database 102 stores the fixed-rate kWh unit price as fixed-rate kWh unit price data (an example of fixed-rate electricity unit price data). If the fixed-rate kWh unit price data does not change throughout the year, it is scalar data. However, if monthly fuel cost adjustments or market price adjustments are taken into account, it is stored in the fixed-rate database 102 as time-series data.

[0020] The customer-side equipment includes a variable device 103, a variable device measuring device 104, a non-variable device 109, and a non-variable device measuring device 110, which are shown enclosed by dashed lines in the figure.

[0021] The customer's variable equipment 103 includes, for example, thermal storage equipment such as thermal storage air conditioning systems and hot water supply heat pumps, energy storage equipment such as batteries and EVs (Electric Vehicles), production lines whose production schedules can be changed, and P2G (Power to Gas) plants that produce fuels such as hydrogen.

[0022] The variable equipment measuring device 104 measures the amount of energy used by the customer's variable equipment 103. The amount of energy used is, for example, the amount of electricity used by the variable equipment 103. The variable equipment measuring device 104 also measures equipment usage data, such as the amount of hot water stored in a hot water supply heat pump.

[0023] The variable device measurement database 105 stores variable device measurement data measured by the variable device measurement device 104 and acquired from the variable device measurement device 104. The variable device measurement data is, for example, power consumption data representing the amount of power consumed by the variable device 103.

[0024] The variable equipment specification database 106 stores specification data representing the specifications of the variable equipment 103. For example, if the variable equipment 103 is a hot water storage type heat pump, the specification data stored in the variable equipment specification database 106 would include the hot water storage tank capacity, heat pump output, and heat pump efficiency.

[0025] The operating condition estimation unit 107 estimates the operating conditions of the variable equipment 103 based on the variable equipment measurement data stored in the variable equipment measurement database 105 and the specification data stored in the variable equipment specification database 106, using a method described later. Operating conditions include, for example, the time change in heat demand associated with hot water use in the case of a hot water storage type heat pump, and in the case of an EV, the timing of entry and exit and the required amount of charge. Alternatively, operating conditions may include, for example, the production volume required by a predetermined deadline in the case of a production line or plant.

[0026] The variable equipment operation plan calculation unit 108 calculates the operation plan and electricity costs for the variable equipment 103, applying variable or fixed charges under the operating conditions estimated by the operation condition estimation unit 107. For example, the variable equipment operation plan calculation unit 108 calculates an operation plan that minimizes electricity costs under the operating conditions, using the variable charges stored in the variable charge database 101 and the fixed charges stored in the fixed charge database 102, by the method described later. Then, the variable equipment operation plan calculation unit 108 calculates the electricity costs based on the calculated operation plan and outputs these electricity costs to the electricity cost aggregation unit 113.

[0027] For example, with regard to a storage-type hot water heat pump, even if the amount of electricity used and the amount of hot water stored can be measured as operational results, it is not possible to know under what operating conditions those amounts of electricity used and hot water stored. Without knowing the operating conditions, it is not possible to know what other operating plans can be taken besides the measured operational results, that is, the degree of freedom for demand shifting. However, by estimating the operating conditions of the variable equipment 103 using the operating condition estimation unit 107, the variable equipment operation plan calculation unit 108 can calculate an operating plan for the variable equipment 103.

[0028] The customer's non-variable equipment 109 is, for example, business or living equipment that is operated on a case-by-case basis according to the workflow or lifestyle, and that does not have room for energy storage, heat storage, or demand shifting. The non-variable equipment measuring device 110 measures the amount of electricity used by the non-variable equipment 109. The non-variable equipment measurement database 111 stores the data measured by the non-variable equipment measuring device 110.

[0029] The variable equipment power cost calculation unit 112 calculates the power cost of the variable equipment 109 by applying variable or fixed rates to the variable equipment measurement data. For example, the variable equipment power cost calculation unit 112 multiplies the amount of electricity used by the variable equipment 109 stored in the variable equipment measurement database 111 by the kWh unit price of the variable rate stored in the variable rate database 101, and then by the kWh unit price of the fixed rate stored in the fixed rate database 102. In this way, the variable equipment power cost calculation unit 112 calculates the power cost of the variable equipment 109 for both variable and fixed rates, and outputs the calculated power cost to the power cost aggregation unit 113. Here, the expression "multiplying" is used for the amount of electricity used, which is time-series data, and the kWh unit price of the variable rate, which is also time-series data. This expression means the sum of the products of the time-series data, that is, the dot product calculation when the two are viewed as vectors. In this specification, multiplication of time series data means the same dot product calculation unless otherwise specified, for example, by explicitly indicating a particular element of the time series data.

[0030] The power cost aggregation unit 113 aggregates the power costs calculated by the variable equipment operation plan calculation unit 108 and the power costs calculated by the non-variable equipment power cost calculation unit 112, and presents the aggregated power costs to the consumer as power rate design data. Power rate design data is data used for reaching an agreement between the retail electricity provider, which is the entity responsible for designing power rates, and the consumer, which is the entity responsible for selecting power rates. The agreement between the retail electricity provider and the consumer on what kind of power contract to conclude is called reaching an agreement. Furthermore, "aggregation" means aggregating the costs calculated by the variable equipment operation plan calculation unit 108 and the non-variable equipment power cost calculation unit 112, as shown in Figure 15, which will be described later.

[0031] The power cost aggregation unit 113 may receive the operation plan from the variable equipment operation plan calculation unit 108 and provide the operation plan to the customer along with the power rate design data. In addition to the power costs shown in Figure 5 and later, the customer can also check the operation plan.

[0032] Figure 2 is a block diagram showing an example of the hardware configuration of the electricity rate design system 21 according to the first embodiment.

[0033] The electricity rate design system 21 includes an input / output device 211, a communication device 212, a computing device 213, and a storage device 214. The electricity rate design system 21 is implemented on computer hardware owned by the retail electricity provider, or on cloud computing hardware used by the retail electricity provider.

[0034] The input / output device 211 is used to set variable rates to be stored in the variable rate database 101, fixed rates to be stored in the fixed rate database 102, and specification data to be stored in the variable equipment specification database 106. The input / output device 211 is also used to present the electricity rate design data aggregated by the electricity cost aggregation unit 113 to the retail electricity provider, which is the entity responsible for designing electricity rates. The input / output device 211 may include, for example, a liquid crystal display monitor to display processing results, etc., to the user of the electricity rate design system 21. The input / output device 211 may also include, for example, a keyboard, mouse, etc., which allow the user of the electricity rate design system 21 to perform predetermined operation inputs and instructions.

[0035] The communication device 212 receives measurement data measured by the variable equipment measuring device 104 and the non-variable equipment measuring device 110 from the customer system 22 via the communication device 222. It also transmits electricity rate design data aggregated by the power cost aggregation unit 113 to the communication device 222. The communication device 212 may be a NIC (Network Interface Card), for example. The communication device 212 can send and receive various types of data between devices via a LAN (Local Area Network), the Internet, a dedicated line, etc., connected to the terminals of the NIC.

[0036] The arithmetic unit 213 is responsible for the calculation processing of the aforementioned operating condition estimation unit 107, variable equipment operation plan calculation unit 108, non-variable equipment power cost calculation unit 112, and power cost aggregation unit 113. The arithmetic unit 213 includes, for example, a CPU (Central Processing Unit), ROM (Read Only Memory), and RAM (Random Access Memory). The CPU reads the program code of the software that realizes each function according to this embodiment from the ROM, loads it into the RAM, and executes it. Variables and parameters that arise during the CPU's calculation processing are temporarily written to the RAM, and these variables and parameters are read out by the CPU as appropriate.

[0037] The storage device 214 is responsible for storing the variable charge database 101, the fixed charge database 102, the variable equipment measurement database 105, the variable equipment specification database 106, and the non-variable equipment measurement database 111. The storage device 214 is composed of non-volatile storage such as an HDD (Hard Disk Drive), SSD (Solid State Drive), optical disk, magneto-optical disk, magnetic tape, or non-volatile memory. This non-volatile storage stores the OS (Operating System), various parameters, and programs necessary for the operation of the arithmetic unit 213. ROM and non-volatile storage store programs and data necessary for the CPU to operate. In other words, ROM and non-volatile storage are used as examples of non-transient storage media that are readable by a computer and store programs executed by the computer.

[0038] The customer system 22 includes an input / output device 221, a communication device 222, a variable device 103, a variable device measuring device 104, a non-variable device 109, and a non-variable device measuring device 110.

[0039] The communication device 222 transmits measurement data measured by the variable instrument measuring device 104 and the non-variable instrument measuring device 110 to the electricity rate design system 21, and receives electricity rate design data from the electricity rate design system 21. The communication device 222 may be, for example, a NIC. The communication device 222 can send and receive various types of data between devices via a LAN, the internet, a dedicated line, etc., connected to the terminals of the NIC.

[0040] The input / output device 221 is, for example, a PC (Personal Computer) or tablet terminal installed in the customer system 22, and is used to present the electricity rate design data received by the communication device 222 to the customer. The input / output device 221 may be, for example, a liquid crystal display monitor that displays the processing results, etc., to the user of the customer system 22. Alternatively, the input / output device 221 may be, for example, a keyboard, mouse, etc., that allows the user of the customer system 22 to perform predetermined operation inputs and instructions.

[0041] Figure 3 is a schematic diagram showing the calculation processes of the operation condition estimation unit 107 and the variable device operation plan calculation unit 108. Here, an example of the variable device 103 will be described as a storage type water heating heat pump, which is an example of a device that supplies cold, warm, and hot water using electricity. The measurement data of the variable device 103, which is measured by the variable device measurement device 104 and stored in the variable device measurement database 105, includes the amount of stored water and the operation mode in addition to the amount of electricity used.

[0042] Graph 31 is a graph showing the change in the amount of stored water over time, where the horizontal axis represents time and the vertical axis represents the amount of stored water. Each bar in the bar graph of Graph 31 is called a time frame. To identify the time frame, time frame numbers are assigned in order from left to right as 1, 2, 3,... for each bar graph.

[0043] Period 311 represents the stored water operation mode in which stored water is heated to boiling, and during period 311 (in this example, from 0:00 to 6:00), the boiling continues. Over the 6 hours of period 311, water is added while being heated simultaneously to reach a predetermined temperature. Period 312 is a hot water supply operation mode in which boiling is not performed and only hot water supply is carried out. Therefore, the amount of stored water gradually decreases during period 312.

[0044] The stored water temperature is stored as specification information (specification data) in the variable device specification database 106. Generally, the insulation of the tank of a storage type water heating heat pump is high, so here, for simplicity, it is assumed that the heat loss due to natural heat dissipation can be ignored. Therefore, from the change in the amount of stored water over time in the hot water supply operation mode, the heat demand Q(f) in hot water supply can be converted using the following mathematical formula (1).

[0045] Q(f) = (V(f - 1) - V(f)) × (T - T0) × C...(1)

[0046] In the mathematical formula (1), f is the time frame number of the time series data, Q(f) is the heat demand to be calculated, V(f) is the amount of stored water measured by the variable device measurement device 104, T and T0 are the stored water temperature and tap water temperature as specification constants, and C is the specific heat of water as a physical constant. The right side of the mathematical formula (1) represents the amount of heat taken out from the stored water tank as the amount of stored water changes over time.

[0047] Graph 32 is a graph showing the heat demand obtained by converting the hot water storage amount using the mathematical formula (1). In Graph 32, it is shown that the heat demand occurs at the timing when the hot water storage amount shown in Graph 31 decreases.

[0048] The operation condition estimation unit 107 estimates the heat demand related to the variable device 103 as an operation condition based on the power consumption data used and the specification data of the variable device 103. In the example of the storage-type hot water supply heat pump, this heat demand is the operation condition to be calculated by the operation condition estimation unit 107. In Graph 32, the time axis is set to 24 hours, but the length of the time series of the measurement data may be one month, one year, etc. Also, by replacing the stored hot water temperature T with the specification constant as the measurement data, or by replacing the tap water temperature T0 that changes with the season with the specification constant as the measurement data, it is also possible to convert the heat demand with higher accuracy.

[0049] Note that there are various models of storage-type hot water supply heat pumps, such as models that can perform hot water storage and hot water supply simultaneously, and models in which the hot water storage tank is a circulation type and performs heat exchange with the tap water pipe to supply hot water. However, the heat demand conversion methods for these are well-known and will not be particularly mentioned here. Furthermore, the present invention does not limit the variable device 103 to a storage-type hot water supply heat pump, nor does it limit the storage-type hot water supply heat pump to one model.

[0050] Next, based on the operation conditions calculated by the operation condition estimation unit 107, the variable device operation plan calculation unit 108 will explain the method of calculating the operation plan for the variable charge and the fixed charge, and the method of calculating the power cost for the variable charge and the fixed charge. The variable device operation plan calculation unit 108 formulates an operation plan that minimizes the power cost of the variable device 103 under the variable charge or the fixed charge, with the constraint condition of satisfying the heat demand.

[0051] The operation plan and the power cost are calculated by solving a mathematical programming problem defined by the following objective function (mathematical formula (2)) and constraint conditions (mathematical formulas (3), (4)) using a solver. Here, the method of calculating the operation plan and the power cost will be explained by referring to the following mathematical formula (2).

[0052] min. Σ_f(Y(f) × w(f))…(2)

[0053] Formula (2) is the objective function, and Σ_f represents the sum over time frame f. Y(f) is a given kWh price stored in the variable price database 101 or the fixed price database 102. The kWh price is time-series data, but for fixed prices, it will be a constant value if monthly changing fuel cost adjustments and market price adjustments are not taken into account. In the example of a storage-type hot water heat pump, w(f) is the amount of electricity used per time frame for heating (kWh). Formula (2) means minimizing the sum of the products of the kWh price and the amount of electricity used, that is, minimizing the electricity cost of the variable equipment 103.

[0054] v(f) = v(f-1)+w(f)×E / ((T-T0)×C)…(3)

[0055] v(f-1)×(T-T0)×C ≧ Q(f)…(4)

[0056] Equations (3) and (4) are constraints. In equation (3), E is the heat pump efficiency. Equation (3) represents the time change in the amount of hot water stored v(f) associated with the heat output from the heat pump. Equation (4) represents the constraint that the amount of heat that can be extracted from the hot water storage tank does not fall below the heat demand calculated in equation (1), that is, that the hot water supply does not run out during the operation of the hot water storage type heat pump. In addition, there are other obvious constraints, such as upper and lower limits on the amount of hot water stored and upper and lower limits on the output of the heat pump.

[0057] Here, the hot water storage temperature T and water temperature T0 are treated as scalar constants, but they may be replaced with time-series constants based on measurement data, similar to the operating condition estimation unit 107. If the hot water storage temperature T and water temperature T0 are replaced with time-series constants, the operating conditions passed from the operating condition estimation unit 107 to the variable equipment operation plan calculation unit 108 include the measurement data obtained from the variable equipment measurement database 105. Alternatively, the hot water storage temperature T and water temperature T0 may be treated as statistical time-series constants. In that case, such statistical values ​​are stored in the variable equipment specification database 106 in advance.

[0058] Furthermore, the heat pump efficiency E is a constant that depends on the ambient temperature, and is sometimes listed as efficiency curve data in the catalog information for storage-type hot water heat pumps. For this reason, time-series constants calculated in advance based on this data and meteorological data may be stored in the variable equipment specification database 106 and used in equation (3). In this way, it is possible to improve the accuracy of the operation plan by replacing the scalar constants used in equations (3) and (4) with time-series constants.

[0059] When solving the mathematical programming problem explained in equations (2) to (4), if the kWh unit price is variable, a solution is calculated that satisfies the constraints on the amount of hot water stored in equations (3) and (4) while heating the water during the time when the kWh unit price is as low as possible. Graphs 33 and 34 in Figure 3 show the calculated solution.

[0060] Graph 33 shows an example of variable rates per kWh, and Graph 34 shows an example of electricity consumption corresponding to the variable rates. The variable rates are stored in the variable rate database 101 mentioned above. In this example, the operation plan shows that hot water storage operation is performed at the maximum output of the heat pump during the time when the kWh rate is lowest, and the amount of hot water that cannot be stored by hot water storage operation alone is supplemented by hot water storage operation in the following time period. Furthermore, Graph 33 shows that the variable rates are lower during the daytime (around 10am) and higher during the evening (around 8pm). In recent years, due to the installation of many solar power generation systems, there is often a surplus of electricity during the daytime, so the variable rate per kWh is lower during the daytime. However, in the evening, solar power generation is shut down all at once, but electricity demand is high. Therefore, it is necessary to operate thermal power plants, so the variable rate per kWh is higher.

[0061] Graph 34 shows that when water heating is performed during the daytime (around 10:00 AM), when variable rates are lower, electricity consumption increases. Furthermore, since the daytime hours alone are insufficient to meet the heat demand shown in Graph 32, additional water heating is performed between 3:00 PM and 4:00 PM, further increasing electricity consumption.

[0062] In the case of a fixed rate, the timing of water heating is determined by the kWh unit price and does not have time dependence. However, if, for example, the hot water storage temperature T and heat pump efficiency E are used as time-series constants as described above, a solution with minimal natural heat loss and high heat pump efficiency will be calculated. Graph 35 in Figure 3 shows this solution. This example shows an operation plan that performs water heating during the time when the temperature is high and the heat pump efficiency is high. For example, with a fixed rate, by operating the heat pump during the time before the heat demand increases and during the time when the temperature is high (between 10:00 and 16:00), heat loss can be reduced.

[0063] In the example described above, all electricity is assumed to be used for heating. Graph 31 assumes, for example, that the hot water storage operation mode is fixed to heat water from 0:00 to 6:00 using a timer. Therefore, when expressed in terms of electricity consumption, the bar graph will be the same height as in Graph 35, and will be lined up from 0:00 to 6:00. On the other hand, in Graph 34, the heating timing is planned dynamically within the range that satisfies the heat demand, and the time period of the hot water storage operation mode changes.

[0064] Based on the above calculation method, the variable equipment operation plan calculation unit 108 calculates the operation plan and outputs the power cost calculated as the objective function.

[0065] The non-variable equipment power cost calculation unit 112 does not solve operation planning problems like the variable equipment operation plan calculation unit 108, but calculates power costs based on measurement data of the non-variable equipment 109 using the following formula (5).

[0066] Σ_f(Y(f)×W(f))…(5)

[0067] Y(f) is a given kWh unit price stored in the variable rate database 101 or the fixed rate database 102, similar to equation (2). W(f) is the amount of electricity consumed by the variable equipment 109, stored in the variable equipment measurement database 111.

[0068] Furthermore, in the case of the variable equipment operation plan calculation unit 108, if the electricity rate applied to the variable equipment 103 from the beginning is a fixed rate, the calculation of the operation plan is omitted when calculating the electricity cost based on the fixed rate database 102. Then, the variable equipment operation plan calculation unit 108 may calculate the electricity cost in the same manner as formula (5) based on the amount of electricity used, which is the measurement data of the variable equipment 103.

[0069] Figure 4 is a table illustrating the aggregation of electricity costs by the electricity cost aggregation unit 113. In this table, each column represents the case where fixed charges and variable charges are applied to variable equipment 103, and each row represents the case where fixed charges and variable charges are applied to non-variable equipment 109.

[0070] Rate Plan 1 is an electricity rate design that applies a fixed rate to both variable equipment 103 and non-variable equipment 109. The electricity rate design of Rate Plan 1 corresponds to a form in which the customer enters into a fixed-rate supply contract on a point-of-reception basis. In Rate Plan 1, the customer's cost burden is the sum of the electricity cost calculated using formula (2) for the variable equipment operation plan calculation unit 108 with a fixed kWh unit price, and the electricity cost calculated using formula (5) for the non-variable equipment electricity cost calculation unit 112 with a fixed kWh unit price.

[0071] Rate Plan 2 is an electricity rate design that applies variable rates to both variable equipment 103 and non-variable equipment 109. The electricity rate design of Rate Plan 2 corresponds to a form in which the customer enters into a variable rate supply contract on a point-of-reception basis. In Rate Plan 2, the customer's cost burden is the sum of the electricity cost calculated using formula (2) for the variable equipment operation plan calculation unit 108, which uses a variable rate per kWh, and the electricity cost calculated using formula (5) for the non-variable equipment electricity cost calculation unit 112, which uses a variable rate per kWh.

[0072] Rate Plan 3 is an electricity rate design that applies a variable rate to variable equipment 103 and a fixed rate to non-variable equipment 109. The electricity rate design of Rate Plan 3 corresponds to a form in which a consumer has different supply contracts depending on the electrical equipment downstream from the point of power reception. In Rate Plan 3, the consumer's cost burden is the sum of the electricity cost calculated using formula (2) for the variable equipment operation plan calculation unit 108, where the kWh unit price is a variable rate, and the electricity cost calculated using formula (5) for the non-variable equipment electricity cost calculation unit 112, where the kWh unit price is a fixed rate.

[0073] Rate Plan 4 is an electricity rate design that applies a fixed rate to variable equipment 103 and a variable rate to non-variable equipment 109. The electricity rate design of Rate Plan 4 corresponds to a situation where the consumer has different supply contracts depending on the electrical equipment downstream from the point of power reception, and the application of variable and fixed rates is reversed compared to Rate Plan 3. In Rate Plan 4, the consumer's cost burden is the sum of the electricity cost calculated using formula (2) for the variable equipment operation plan calculation unit 108 with a fixed kWh unit price, and the electricity cost calculated using formula (5) for the non-variable equipment electricity cost calculation unit 112 with a variable kWh unit price.

[0074] Figure 5 shows an example of a display that visualizes the electricity costs aggregated by the electricity cost aggregation unit 113. The input / output device 211 or input / output device 221 visualizes the electricity costs aggregated by the electricity cost aggregation unit 113, allowing retail electricity providers or consumers to check their electricity costs.

[0075] The bar graphs shown in Figure 5 represent rate plans 1, 2, and 3 from left to right. For each of rate plans 1, 2, and 3, areas 51, 53, and 55 represent the electricity costs related to variable equipment 103, and areas 52, 54, and 56 represent the electricity costs related to non-variable equipment 109. Note that the bar graphs shown from Figure 5 onward do not represent hourly electricity costs as shown in Figure 3, but rather the combined electricity costs of variable equipment 103 and non-variable equipment 109 on a monthly or yearly basis.

[0076] Comparing pricing plan 1 and pricing plan 2, the change from a fixed rate to a variable rate reduces the electricity costs of variable equipment 103, but the electricity costs of non-variable equipment 109 actually increase. This is the trade-off regarding the electricity costs of variable equipment 103 and non-variable equipment 109 that was explained in the problems of the conventional technology.

[0077] On the other hand, we compare rate plans 1 and 2 with rate plan 3. In this case, regarding the power cost reduction effect of variable equipment 103, the power cost in rate plan 2 is the same as in rate plan 3. Furthermore, in rate plan 3, the power cost of the non-variable equipment 109 can be made the same as that of the non-variable equipment 109 in rate plan 1 without causing the side effect of increasing the power cost of the non-variable equipment 109. As a result, it can be seen that rate plan 3 has a greater total cost reduction effect than rate plans 1 and 2.

[0078] By looking at the bar graph shown in Figure 5, consumers can quantitatively confirm that there is indeed a cost-saving effect from an electricity rate design that distinguishes between variable equipment 103 and non-variable equipment 109 and applies variable rates only to variable equipment 103. Furthermore, quantitative confirmation allows for agreement on electricity rate design between retail electricity providers and consumers. For example, a retail electricity provider can recommend rate plan 3 to a consumer.

[0079] Figure 6 illustrates rate plans 1 and 2 in the same manner as Figure 5. Areas 61 and 63 represent the electricity costs related to variable equipment 103, and areas 62 and 64 represent the electricity costs related to non-variable equipment 109.

[0080] The difference between the bar graph in Figure 6 and the bar graph in Figure 5 is that the application of variable pricing has increased both the electricity costs of the variable equipment 103 and the electricity costs of the non-variable equipment 109. This corresponds to a situation where a demand shift from high-priced kWh periods to low-priced periods cannot be implemented due to operational constraints on the variable equipment 103.

[0081] For consumers, even if the electricity rate design limits the application of variable rates to variable equipment 103, there is no benefit in changing from a fixed rate to a variable rate. In other words, in this case, an agreement is reached between the retail electricity provider and the consumer that variable rates will not be applied to either the variable equipment 103 or the non-variable equipment 109.

[0082] Figure 7 illustrates rate plans 1, 2, and 4 in the same manner as in Figure 5. Areas 71, 73, and 75 represent the electricity costs related to variable equipment 103, while areas 72, 74, and 76 represent the electricity costs related to non-variable equipment 109.

[0083] The difference between the bar graph shown in Figure 7 and the bar graph shown in Figure 5 is that the application of variable pricing has increased the electricity costs of the variable equipment 103, while conversely, the electricity costs of the non-variable equipment 109 have decreased. This indicates that the operational constraints on the variable equipment 103 prevent a demand shift from high-price kWh periods to low-price periods.

[0084] On the other hand, the non-variable equipment 109 initially consumed a large amount of electricity during the low-price period and a small amount during the high-price period, which corresponds to a situation suitable for variable pricing. In this case, the retail electricity provider and the consumer reach an agreement, contrary to the example in Figure 5, to distinguish between the variable equipment 103 and the non-variable equipment 109 and to apply the variable pricing only to the non-variable equipment 109, as in pricing plan 4.

[0085] Furthermore, in the case shown in Figure 7, the expectation of cost reduction related to the combination of variable equipment 103 and variable charges is not always met. Through the calculation of electricity costs by the operating condition estimation unit 107 and the variable equipment operation plan calculation unit 108, it is possible to show the customer that the opposite situation can also occur. This has the effect of prompting the customer to make a quantitative judgment.

[0086] One of the advantages of the electricity rate design system 21 according to this embodiment is that it can avoid the trade-offs that may arise from the uniform application of variable rates by distinguishing between variable equipment 103 and non-variable equipment 109 and applying variable or fixed rates to each. Furthermore, the electricity rate design system 21 can present the variable rate after application in a way that allows consumers to quantitatively judge whether or not there is a benefit to applying variable rates, depending on the operating constraints of the variable equipment 103. By presenting information to consumers, the electricity rate design system 21 also has the effect of supporting the formation of agreements regarding electricity rate design between retail electricity providers and consumers.

[0087] Figure 8 illustrates, using a time-series graph, a situation where a trade-off occurs between variable equipment 103 and non-variable equipment 109, as shown in rate plan 2 in Figure 5. Graph 81 shows the kWh unit price for variable rates. Graph 82 shows the amount of electricity used by variable equipment 103, and graph 83 shows the amount of electricity used by non-variable equipment 109. Graph 82 shows the amount of electricity used before the demand shift 821 and the amount of electricity used after the demand shift 822. In the example shown in Figure 8, a demand shift has been achieved for variable equipment 103 from a high-price period to a low-price period. In other words, due to the demand shift, the amount of electricity actually used by variable equipment 103 is only the amount of electricity used 822.

[0088] On the other hand, the non-variable equipment 109 uses less electricity during off-peak hours and more electricity during off-peak hours, so applying variable rates increases electricity costs compared to fixed rates. For example, consider a situation where a restaurant that opens in the evening is subject to daytime discount electricity rates. In this situation, although the hot water storage heat pump can store hot water in advance during the day, the majority of the store's electricity consumption occurs during business hours, so it is clear that applying variable rates uniformly does not benefit the customer. In such cases, it is more beneficial for the customer to limit the application of variable rates to the variable equipment 103, as in rate plan 3.

[0089] The functional block diagram shown in Figure 1 illustrates a configuration in which power costs are passed from the variable equipment operation plan calculation unit 108 and the non-variable equipment power cost calculation unit 112 to the power cost aggregation unit 113. In addition to this configuration, power consumption data based on the operation plan or measured power consumption data may be passed, and a time-series graph as shown in Figure 8 may be presented to the customer as an explanation to supplement the graph in Figure 5. This presentation allows the customer to more concretely understand the issues related to rate plan 2 and the effects related to rate plan 3.

[0090] Figure 9 is a flowchart illustrating the process of supporting consensus building between retail electricity providers and consumers, following the functional configuration shown in Figure 1.

[0091] S901 is the operation condition estimation process of the variable device 103 performed by the operation condition estimation unit 107.

[0092] S902 is the process by the Variable Equipment Operation Plan Calculation Unit 108 to calculate the operation plan for the variable equipment 103. The Variable Equipment Operation Plan Calculation Unit 108 calculates the operation plan for the variable equipment 103 based on the operating conditions and calculates the power cost of the variable equipment 103 based on the operation plan.

[0093] S903 is the process of calculating the power cost of the variable equipment 109 by the variable equipment power cost calculation unit 112.

[0094] S904 is the process by which the power cost aggregation unit 113 aggregates the power costs of the variable equipment 103 calculated by the variable equipment operation plan calculation unit 108, and aggregates the power costs of the non-variable equipment 109 calculated by the non-variable equipment power cost calculation unit 112.

[0095] S905 is a process in which the power cost aggregation unit 113 compares rate plan 2, as explained using Figure 4, with rate plan 1 (see, for example, Figure 5). As a result of this comparison process, in the evaluation of conditional branch S906, it is determined whether or not the power cost of the non-variable equipment 109 has decreased in rate plan 2 compared to rate plan 1. If the power cost of the non-variable equipment 109 has decreased (Yes in S906), the power cost aggregation unit 113 then evaluates conditional branch S907. If the power cost of the non-variable equipment 109 has not decreased (No in S906), the power cost aggregation unit 113 then evaluates conditional branch S908.

[0096] In the evaluation of conditional branch S907, if the electricity cost of the variable equipment 103 is lower in rate plan 2 compared to rate plan 1 (Yes in S907), then a cost reduction effect can be expected by uniformly applying variable rates to both the variable equipment 103 and the non-variable equipment 109 compared to uniformly applying fixed rates. For this reason, the electricity cost aggregation unit 113 recommends rate plan 2 to the customer in S909.

[0097] In the evaluation of conditional branch S907, if the power cost of the variable equipment 103 has not decreased (No. in S907), it corresponds to rate plan 2 shown in Figure 7. In this case, the power usage pattern of the non-variable equipment 109 is suitable for variable rates from the beginning, but the variable equipment 103 cannot implement a demand shift that takes advantage of variable rates due to operational constraints. For this reason, the power cost aggregation unit 113 recommends rate plan 4 to the customer in S910.

[0098] If the electricity cost of the non-variable equipment 109 has not decreased (No in S906), the electricity cost aggregation unit 113 evaluates the conditional branch S908. In the evaluation of the conditional branch S908, if the electricity cost of the variable equipment 103 has decreased in rate plan 2 compared to rate plan 1 (Yes in S908), then it corresponds to rate plan 2 shown in Figure 5. In this case, the cost reduction due to the application of variable rates to the variable equipment 103 is offset by the cost increase due to the application of variable rates to the non-variable equipment 109. For this reason, the electricity cost aggregation unit 113 recommends rate plan 3, which is effective in resolving the trade-off between the two, to the customer in S911.

[0099] In the evaluation of conditional branch S908, if the power cost of the variable equipment 103 has not decreased in rate plan 2 compared to rate plan 1 (No. in S908), it corresponds to rate plan 2 as shown in Figure 6. In this case, the variable equipment 103 cannot implement demand shifting that takes advantage of variable charges due to operational constraints. For this reason, the power cost aggregation unit 113 recommends rate plan 1, which uniformly applies a fixed charge, to the customer in S912.

[0100] Figure 10 shows an example of a data table for electricity rate design data. The data table for electricity rate design data is transmitted from the electricity rate design system 21 to the customer system 22 in the block diagram shown in Figure 2. The electricity cost aggregation unit 113 lists the electricity costs of variable equipment 103 to which the variable equipment operation plan calculation unit 108 has applied variable or fixed rates, and the electricity costs of non-variable equipment 109 to which the non-variable equipment electricity cost calculation unit 112 has applied variable or fixed rates, and presents them to the customer in the data table shown in Figure 10.

[0101] The data table shown in Figure 10 stores the charges applied to the variable equipment 103 and the non-variable equipment 109 for each of the rate plans 1 to 4 shown in Figure 4, as well as the amount of electricity costs calculated by the variable equipment operation plan calculation unit 108 and the non-variable equipment power cost calculation unit 112 corresponding to the applied charges. It also stores whether the plan is recommended or not to the customer, depending on the amount of electricity costs. In this example, rate plan 3, which applies a variable charge to the variable equipment 103 and a fixed charge to the non-variable equipment 109, has the lowest total cost, so this plan is recommended. The plan that the power cost aggregation unit 113 recommends to the customer is a combination of variable and fixed charges that results in lower electricity costs for both the variable equipment 103 and the non-variable equipment 109.

[0102] It should be noted that the presentation of fixed and variable kWh unit prices from retail electricity providers to consumers is self-evident and not limited to this embodiment, so it is omitted here. Furthermore, the operation of the variable equipment 103 can be carried out, for example, by solving a mathematical programming problem similar to that of the variable equipment operation plan calculation unit 108 each day to calculate an operation plan, and then setting that operation plan to the variable equipment 103. However, since such a method is a well-known technique, it is omitted here.

[0103] In the above explanation, the measured values ​​of the variable equipment 103 and the non-variable equipment 109 are assumed to be historical performance data. However, the data input to the operating condition estimation unit 107 and the non-variable equipment power cost calculation unit 112 may be, for example, time-series data of predicted values ​​based on the measured values ​​of the measurement data. Such prediction of time-series data can be performed using known techniques such as machine learning.

[0104] [Effects] As described above, the electricity rate design system 21 estimates the operating conditions in the operating condition estimation unit 107 based on measurement data acquired from the customer's variable equipment 103. The electricity rate design system 21 then calculates an operating plan and electricity costs based on the operating conditions in the variable equipment operating plan calculation unit 108 by referring to the kWh unit price stored in the variable rate database 101 or the fixed rate database 102. In addition, the electricity rate design system 21 calculates electricity costs based on the measurement data acquired from the customer's non-variable equipment 109 by referring to the kWh unit price in the non-variable equipment electricity cost calculation unit 112. These electricity costs are aggregated in the electricity cost aggregation unit 113, and by comparing combinations of fixed and variable rates in a way that allows the customer to judge the effect of electricity cost reduction, it is possible to support agreement between retail electricity providers and customers regarding the design of electricity rates.

[0105] Conventionally, even EVs have variable charge and discharge timings that are limited, similar to commercial vehicles. Furthermore, conventionally, some variable devices, such as storage-type water heaters and thermal storage air conditioning systems, have operational flexibility constraints stemming from heat demand. In such cases, it was not obvious whether applying variable rates would lead to reduced electricity costs. This meant that consumers could not decide whether to adopt variable rates, and retail electricity providers could not propose variable rates to consumers with solid justification. Additionally, in services using specific meters (such as EV chargers), a system is used where variable rates are applied to EV chargers among the consumer's electrical equipment, while fixed rates are applied to other electrical equipment. On the other hand, the electricity rate design system 21 according to this embodiment can propose variable rates with solid justification, enabling agreement on electricity rate design between retail electricity providers and consumers.

[0106] <Second Embodiment> Next, an example of the configuration and operation of the electricity rate design system according to the second embodiment of the present invention will be described with reference to Figures 11 to 18. Figure 11 is a block diagram showing an example of the functional configuration of the electricity rate design system 21A according to the second embodiment of the present invention.

[0107] Of the functional configurations of the electricity rate design system 21A, the variable rate database 101 to the non-variable equipment power cost calculation unit 112 are the same as the functional configuration example of the electricity rate design system 21 according to the first embodiment shown in Figure 1. The difference between Figure 11 and Figure 1 is that the electricity rate design system 21A includes a power cost aggregation unit 113A instead of the power cost aggregation unit 113, and also includes an aggregation constant database 1101 and a gain allocation adjustment support unit 1102.

[0108] The power cost aggregation unit 113A calculates the market risk management unit price by the method described below and reflects it in the aggregation of power costs. Here, the market risk management unit price is the unit price of the cost to prepare for fluctuations in the procurement unit price in the wholesale power trading market (hereinafter referred to as market risk). For example, it is a margin that is incorporated in advance into the kWh unit price charged to consumers so that retail electricity businesses do not suffer losses even if the procurement unit price in the market rises.

[0109] The power cost aggregation unit 113A calculates a market risk management cost to prepare for fluctuations in procurement unit prices by subtracting at least one of the following from the power costs under the operation plan of the variable equipment 103 to which the variable rate has been applied by the variable equipment operation plan calculation unit 108: procurement costs, transmission costs, supply and demand management costs, and profits, which are calculated by multiplying the power consumption data under the operation plan by a constant stored in the aggregation constant database 1101. The power cost aggregation unit 113A then calculates the market risk management cost as the market risk management unit price by dividing the market risk management cost by the total value of the power consumption data and converting it to an amount per kWh of power.

[0110] The aggregated constant database 1101 stores constants as aggregated constants, which are time-series data or scalar data that include at least one of the following per kWh of electricity related to retail sales: procurement unit price, transmission unit price, supply and demand management unit price, and profit unit price. The aggregated constants are used in the calculation process of the electricity cost aggregation unit 113A. In the electricity cost aggregation unit 113A, in order to adjust variable charges as part of the aggregation process, it refers to aggregated constants such as the commission unit price (also called the minimum commission unit price), which does not include the procurement unit price, transmission unit price, or market risk management unit price.

[0111] The gain distribution adjustment support unit 1102 visualizes and supports the consensus-building process, which includes not only the retail electricity provider and the consumer, but also the equipment provider responsible for the leasing, operation, or maintenance of the variable equipment 103, using the method described later and shown in Figure 18. This support process is presented to the retail electricity provider via the input / output device 211 and to the consumer via the input / output device 221, similar to the first embodiment. For the equipment provider, in managing the variable equipment 103 shown in Figure 2, they may share the input / output device 221 with the consumer, or they may use a separate input / output device similar to the input / output device 221, although this is not shown in Figure 2.

[0112] Figure 12 illustrates the concept of market risk management unit price. Generally, the average kWh unit price of electricity supplied by a retail electricity provider to a customer is broken down into average procurement unit price 1201, transmission unit price 1202 (payment to transmission and distribution companies), and commission unit price 1203. The average procurement unit price 1201 is the unit price required for electricity procurement and is calculated by weighting publicly available time-series data of procurement unit prices with electricity usage data under the operating plan of the variable equipment 103. The transmission unit price 1202 is the unit price paid to transmission and distribution companies and is publicly available. The commission unit price 1203 is the retail electricity provider's gross profit (hereinafter referred to as profit) as well as supply and demand management costs required to maintain the planned value and quantity, converted into an amount per kWh. The market risk management unit price 1204 is a value set considering the market risk when a retail electricity provider procures electricity. The commission rate 1203 includes the market risk management rate 1204. However, the market risk management rate 1204 is generally not expressed quantitatively. Note that the numerical values ​​of each rate shown in Figure 12 and Figure 13 (described later) are hypothetical values ​​and not actual values.

[0113] The power cost aggregation unit 113A separates and quantifies the market risk management unit price 1204 from the commission unit price 1203. The power cost aggregation unit 113A calculates the market risk management unit price R for a predetermined period, such as one year, using the following formula (6).

[0114] R = Σ_f(Y(f)×w(f)) / Σ_f(w(f)) - Σ_f((P1(f)+P2+P3)×w(f)) / Σ_f(w(f))...(6)

[0115] Regarding equation (6), the numerator of the first term on the right-hand side is the same as that of equation (2), which is the objective function of the variable equipment operation plan calculation unit 108. The numerator of this first term on the right-hand side is the electricity cost paid by the consumer for the variable equipment 103 over a predetermined period, and from the perspective of the retail electricity provider, it corresponds to sales. In the first term on the right-hand side, sales are divided by the total amount of electricity used over the predetermined period to convert it to sales per kWh.

[0116] In the numerator of the second term on the right-hand side, P1(f) is time-series data of the procurement unit price, for example, the actual value of the contract price in the market one day prior. P2 is the transmission unit price of 1202, which is often set by the transmission and distribution company as a constant value independent of time, but under a nodal price system, for example, it becomes time-series data that fluctuates over time. P3 is the commission unit price excluding the market risk management unit price, and the input / output device 211 sets the minimum amount necessary to secure, assuming the profit unit price per kWh and the supply and demand management unit price.

[0117] In formula (6), P1 to P3 are constants stored in the aggregated constant database 1101. Multiplying P1 to P3 by the amount of electricity used by the variable equipment 103 w(f) calculated by the variable equipment operation plan calculation unit 108 results in the sum of the retail electricity provider's procurement costs, transmission costs, supply and demand management costs, and the retail electricity provider's profit over a predetermined period. The second term on the right side is obtained by dividing the total amount by the total amount of electricity used over the predetermined period to convert it into an amount that combines the cost and profit per kWh. By subtracting the second term on the right side from the first term on the right side calculated in this way, the market risk management unit price R is calculated as the difference. For this reason, the variable equipment operation plan calculation unit 108 calculates the difference between the amount obtained by multiplying the amount of electricity used data when a fixed charge or a variable charge is applied by the procurement unit price stored in the aggregated constant database 1101, respectively, as the amount of reduction in procurement costs achieved by demand shift based on a variable charge.

[0118] In the above explanation, P1(f) is expressed as the procurement unit price in formula (6), and in Figure 12, it is shown as the average procurement unit price of 1201 in the graph. The reason for this is to distinguish that P1(f) expressed in formula (6) is a time-varying parameter, while the average procurement unit price of 1201 shown in Figure 12 is a weighted average of P1(f) by the amount of electricity used w(f). Expressing the average procurement unit price of 1201 using the symbols of formula (6), it is shown as follows in formula (7).

[0119] Average procurement unit price = Σ_f(P1(f)×w(f)) / Σ_f(w(f)) …(7)

[0120] Thus, it is shown that the average procurement cost 1201 depends not only on the procurement cost P1(f) but also on the time variation of the amount of electricity used w(f). For this reason, in this embodiment, the power cost aggregation unit 113A calculates the market risk management cost by referring to the calculation results of the operating condition estimation unit 107 and the variable equipment operation plan calculation unit 108.

[0121] The fact that the average procurement cost depends on both the procurement cost and the amount of electricity used means that, from the perspective of a retail electricity provider, the factors influencing procurement costs exist on both the market and the consumer side. On the other hand, if a market-linked rate is applied to the variable device 103 as a variable rate, the retail electricity provider does not need to manage market risk for the amount of electricity used by the variable device 103. Therefore, there is no need to include the market risk management rate 1204 in the commission rate 1203. Also, from the consumer's perspective, since the amount of electricity used is a factor they can manage themselves, the factors influencing electricity costs are limited to the market.

[0122] Therefore, in this embodiment, market risk management is entrusted from the retail electricity provider to the consumer in the form of market-linked pricing, and a variable price is presented to the consumer after deducting the market risk management unit price. This example will be explained with reference to Figure 13.

[0123] Figure 13 shows an example of a variable charge presented to a customer. As shown in Figure 13, the market-linked fee unit price 1301 is determined by subtracting the market risk management unit price 1204 calculated using formula (6) from the fee unit price 1203, and this value is then used to adjust the kWh unit price of the variable charge. Figures 12 and 13 were schematic diagrams showing the average value of the kWh unit price without showing the change in the variable charge over time. However, when the difference between the two kWh unit prices is illustrated, including the change in the variable charge over time, the graph shown in Figure 14 is obtained.

[0124] Figure 14 is a graph showing the time fluctuations of the kWh unit price. In Figure 14, the unadjusted variable rate 1401 is the original variable rate stored in the variable rate database 101. The unadjusted variable rate 1401 includes the commission unit price 1203. Furthermore, a portion of the commission unit price 1203 corresponds to the market risk management unit price 1204 calculated using formula (6).

[0125] The electricity cost aggregation unit 113A, when the variable rate is a market-linked rate, makes an adjustment by subtracting the market risk management unit price from the variable rate and presents the adjusted variable rate to the customer. For example, if the variable rate is a market-linked rate, the electricity cost aggregation unit 113A changes the commission unit price 1203 to the market-linked commission unit price 1301. The electricity cost aggregation unit 113A can then present the adjusted variable rate 1402 to the customer, which is the variable rate that includes the market-linked commission unit price 1301 and the market risk management unit price 1204 (the variable rate before adjustment 1401). At this time, the electricity costs shown in Figures 5 to 7 can also be visualized after making a similar adjustment (reduction of the market risk management unit price 1204).

[0126] Figure 15 shows an example of adjusted electricity costs. For example, taking Figure 5 as an example, the regions (electricity costs) 51, 53, and 55 related to the variable equipment 103 are adjusted to electricity costs 1501, 1502, and 1503 in Figure 15, respectively. These electricity costs were initially calculated by minimizing formula (2), but the adjusted electricity costs are calculated using the following formula (8).

[0127] Σ_f((Y(f)-R)×w(f))…(8)

[0128] In formula (8), R is the market risk management unit price calculated in formula (6). (Y(f) - R) is the adjusted variable charge 1402 explained in Figure 14. w(f) is the amount of electricity used. The market risk management unit price R is a value set by retail electricity providers to hedge risks when procuring electricity. If the variable charge is a market-linked charge, the retail electricity provider charges the customer the market-linked charge as is when providing electricity purchased at the market-linked charge. In this case, the retail electricity provider does not need to take the market risk management unit price R. For this reason, the electricity cost aggregation unit 113A can reduce the commission unit price 1203 and adjust the electricity costs 1501, 1502, and 1503 for each rate plan.

[0129] As described above, the power cost aggregation unit 113A calculates the market risk management unit price in addition to the processing performed by the power cost aggregation unit 113. The power cost aggregation unit 113A also adjusts the variable charges stored in the variable charge database 101 based on the market risk management unit price. The power cost aggregation unit 113A then presents the adjusted variable charges and power costs to retail electricity providers and consumers through the visualization shown in Figure 14 or Figure 15.

[0130] In the second embodiment, the data table for electricity rate design data shown in Figure 10 is expanded as shown in Figure 16. Figure 16 shows an example of the expanded data table for electricity rate design data. The amounts in parentheses in this data table represent the adjusted electricity costs calculated using formula (8).

[0131] The power cost aggregation unit 113A adjusts the power cost of the variable equipment 103 calculated by the variable equipment operation plan calculation unit 108 by subtracting the market risk management cost, and presents the adjusted power cost to the customer. For example, in rate plan 2, when a variable rate is applied to the variable equipment 103, the adjusted power cost is 17,000 yen, which is shown in parentheses. The data table of the expanded power rate design data is sent to the customer, and the customer can check the expanded power rate.

[0132] Figure 17 shows an example of a data table that stores variable charges before and after adjustment.

[0133] Market-linked rates are constantly fluctuating rates that also change from day to day. However, the data table shown in Figure 17 is an example of the fluctuating rates before and after adjustment for a given day. This data table uses a market risk management unit price of 3 yen / kWh to illustrate the fluctuating rates before and after adjustment. This data table may also be sent to customers so that they can check the rates hour by hour.

[0134] In the above explanation, the example given was that the variable charge applies to the variable equipment 103. However, as described in the first embodiment, the variable charge may also apply to the non-variable equipment 109. In that case, by replacing the amount of electricity used w(f) calculated for the variable equipment 103 with the amount of electricity used W(f) measured for the non-variable equipment 109 in formulas (6) to (8), the effect of reducing electricity costs by applying market-linked charges and excluding market risk management unit prices can be calculated in the same way.

[0135] Furthermore, the breakdown of the kWh unit price of electricity includes, in addition to the aforementioned procurement unit price, transmission unit price, supply and demand management unit price, and profit unit price, consumption tax and renewable energy surcharges may also be included, as well as discounts such as subsidies. Although not explicitly stated here, consumption tax, renewable energy surcharges, and subsidies can be treated similarly to transmission unit prices and reflected in the calculation of market risk management unit prices.

[0136] In the present invention, the first embodiment describes a method for determining whether to apply variable and fixed rates when differentiating between electrical equipment downstream of the power receiving point and applying variable and fixed rates, by evaluating the effect of reducing electricity costs through demand shifting. Furthermore, the description so far has shown that in the first embodiment, when market-linked rates are applied as variable rates, the retail electricity provider can further reduce electricity costs for consumers by deducting the market risk management unit price from the kWh unit price.

[0137] In the following sections, we will consider equipment upgrade costs, such as replacing existing non-variable equipment 109 with variable equipment 103, and position the equipment provider that provides the variable equipment 103 as a third player, in addition to retail electricity providers and consumers. Then, we will explain the method of supporting consensus building for distributing the gains obtained in the two-stage electricity cost reduction process among the players as a visualization function of the gain distribution adjustment support unit 1102. An equipment provider is a business that handles the leasing, operation, or maintenance of equipment, and is also called an EaaS (Energy as A Service) provider.

[0138] Figure 18 is a triangular graph representing the profit distribution among retail electricity providers, consumers, and equipment providers. The profit here refers to the costs that retail electricity providers can reduce when consumers adopt variable pricing and shift demand, and it serves as the source of funds for reducing electricity costs for consumers and recovering investments for equipment providers. The profit distribution shown in the triangular graph of Figure 18 is adjusted by the profit distribution adjustment support unit 1102 in Figure 11. The profit distribution adjustment support unit 1102 positions the reduction in procurement costs calculated by the variable equipment operation plan calculation unit 108 as the profit obtained by the cooperation of retail electricity providers who sell electricity, consumers who purchase electricity, and equipment providers who provide variable equipment 103 for a fee, and visualizes the profit distributed to each player.

[0139] The triangular graph shown in Figure 18 utilizes the geometric property that the sum of the lengths of the perpendiculars drawn from any point inside an equilateral triangle to each side is equal to the height of the triangle. Here, the sum of the lengths of the perpendiculars corresponds to the total amount of gain, and the length of each perpendicular represents the gain allocated to the retail electricity provider, the consumer, and the equipment provider.

[0140] The height 1803 of the equilateral triangle 1801 represents the procurement cost reduction achieved when consumers perform a demand shift, as shown in the first embodiment, causing the timing of electricity procurement by retail electricity providers to shift from high-price periods to low-price periods in the market. This reduction in procurement cost is calculated using the procurement unit price P1(f) in formula (6) and the following formula (9).

[0141] Procurement cost reduction = Σ_f(P1(f)×w_fix(f))−Σ_f(P1(f)×w_var(f))…(9)

[0142] In formula (9), w_fix(f) is the amount of electricity used by the variable equipment 103 calculated by applying a fixed charge in the variable equipment operation plan calculation unit 108, and w_var(f) is the amount of electricity used calculated by applying a variable charge. By multiplying the amount of electricity used calculated by applying a fixed charge and the amount of electricity used calculated by applying a variable charge by the procurement unit price P1(f), the first term calculates the procurement cost without demand shift, and the second term calculates the procurement cost with demand shift. Then, using formula (9), the difference between the first and second terms is calculated as the amount of reduction in procurement cost due to demand shift.

[0143] The difference 1804 between the height 1803 of equilateral triangle 1801 (white part) and the height of equilateral triangle 1802 (shaded part including the white part) represents the market risk management costs that retail electricity providers can reduce when consumers adopt market-linked pricing, as described in this embodiment. The market risk management costs are the value before converting formula (6) to an amount per kWh, and are expressed by the following formula (10) using the symbols of formula (6).

[0144] Market risk management cost = R × Σ_f(w(f)) ... (10)

[0145] Next, we will explain the meaning of each perpendicular line and the meaning of the line segments obtained by dividing each perpendicular line. Line segment 1805 represents the profit allocated to the retail electricity provider. The retail electricity provider's profit is adjusted, for example, by offsetting the variable rate shown in graph 33 of Figure 3. Using the symbol Y(f) for the kWh unit price shown in equation (2), we can express this as equation (11).

[0146] Y'(f) = Y(f)+ΔY...(11)

[0147] ΔY is the offset amount, and Y'(f) is the offset variable charge. A larger positive offset amount increases the retail electricity provider's profit, while a larger negative offset amount decreases it. Furthermore, even if Y'(f) is used instead of Y(f) in equations (2) to (4), the structure of the mathematical programming problem remains unchanged. Consequently, the demand shift operation plan also remains unchanged, and this offset adjustment does not alter the total profit, which is the height of 1803 or the difference of 1804.

[0148] Line segment 1806 represents the gains allocated to consumers in a demand shift using variable rates. Line segment 1807 represents the gains allocated to consumers when market-linked rates are applied as variable rates. When market-linked rates are applied, consumers bear the market risk, so it is reasonable that the reduction in market risk management costs should be returned to consumers. This is represented in the construction of the triangular graph by making the length of line segment 1807 the same as the length of difference 1804. Furthermore, the gain allocation adjustment support unit 1102 positions the market risk management costs that become unnecessary for retail electricity providers when the variable rate is a market-linked rate as additional gains added to the gains, and allocates these additional gains to consumers who bear the risk of fluctuations in procurement unit prices.

[0149] Line segment 1808 represents the profit allocated to the equipment provider to cover the costs incurred in leasing, operating, or maintaining the variable equipment 103. Line segment 1809 represents the profit allocated to the equipment provider as their profit. For the equipment provider's business to be viable, a predetermined amount must be secured as line segment 1808, and line segment 1809 must be longer than zero. The profit allocated to the equipment provider is distributed as a payment from the customer to the equipment provider, and is therefore adjusted by the pricing agreement between the customer and the equipment provider.

[0150] Furthermore, if the equipment provider is not involved as a player and the customer installs the equipment themselves, the gains of line segments 1808 and 1809 also belong to the customer. Also, if the customer performs demand shifting using the variable equipment 103 that they already own and does not install any new equipment, the lengths of line segments 1808 and 1809 will be zero.

[0151] Thus, the second embodiment visualizes the distribution of gains using a triangular graph. This visualization helps to facilitate consensus building among the three parties regarding how to distribute the gains generated by the setting of variable rates by retail electricity providers, demand shifts by consumers, and the provision of variable equipment 103 by equipment providers, based on a quantitative common understanding and adjustment means.

[0152] In addition to the triangular graph shown on the left side of Figure 18, the gain distribution adjustment support unit 1102 can also represent the lengths of each perpendicular line of the triangular graph as three bar graphs, or divide a single bar graph into three parts. For example, the right side of Figure 18 shows an example where a single bar graph is divided into three parts. When converting the triangular graph to a bar graph, the overall height of the bar graph is kept constant. In other words, the gain distribution adjustment support unit 1102 constructs the bar graph with an overall height equivalent to the height of the triangular graph. The bar graph for consumer gain consists of the demand shift portion and the market risk assumption portion. The equipment provider gain consists of the cost equivalent and the profit equivalent. Even with such bar graphs, the retail electricity provider gain, consumer gain, and equipment provider gain are clearly represented.

[0153] It should be noted that the present invention is not limited to the embodiments described above, and various other applications and modifications can be taken as long as they do not deviate from the gist of the present invention as described in the claims. For example, the embodiments described above describe the configuration of the electricity rate design system in detail and concretely in order to explain the present invention in an easy-to-understand manner, and are not necessarily limited to having all the configurations described. Furthermore, it is possible to replace some of the configurations of the embodiments described here with the configurations of other embodiments, and it is also possible to add the configurations of other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace some of the configurations of each embodiment with other configurations. Furthermore, the control lines and information lines shown are those that are considered necessary for explanation, and do not necessarily show all control lines and information lines in the product. In practice, it can be assumed that almost all configurations are interconnected. Also, when referring to the number of elements, etc. (including number, numerical value, quantity, range, etc.) in the embodiments described above, unless specifically stated or clearly limited to a particular number in principle, it is not limited to that particular number, and may be more or less than or equal to that particular number. Furthermore, the system or apparatus in each of the embodiments described above may be a physical computer system (one or more physical computers) or a system built on a group of computing resources such as a cloud infrastructure (multiple computing resources). The computer system or group of computing resources may include one or more interface devices (e.g., including communication devices and input / output devices), one or more storage devices (e.g., including memory (main memory) and auxiliary storage devices), and one or more arithmetic units.

[0154] Furthermore, in each of the embodiments described above, if the function is realized by the execution of a program by an arithmetic unit, the defined processing is carried out using a memory device and / or interface device as appropriate, so the function may be at least a part of one or more arithmetic units. The processing described with a function as the subject may be processing performed by a system including one or more arithmetic units. Also, in each of the embodiments described above, the program may be installed from a program source. The program source may be, for example, a program distribution computer or a computer-readable storage medium (for example, a computer-readable non-transient storage medium). The description of each function is an example, and multiple functions may be combined into one function, or one function may be divided into multiple functions.

[0155] 21...Electricity Rate Design System, 22...Customer, 101...Variable Rate Database, 102...Fixed Rate Database, 103...Variable Equipment, 104...Variable Equipment Measurement Device, 105...Variable Equipment Measurement Database, 106...Variable Equipment Specification Database, 107...Operating Condition Estimation Unit, 108...Variable Equipment Operation Plan Calculation Unit, 109...Non-Variable Equipment, 110...Non-Variable Equipment Measurement Device, 111...Non-Variable Equipment Measurement Database, 112...Non-Variable Equipment Power Cost Calculation Unit, 113...Power Cost Aggregation Unit, 211...Input / Output Device, 212...Communication Device, 213...Calculation Unit, 214...Storage Device

Claims

1. A variable rate database storing variable rate electricity unit price data; a fixed rate database storing fixed rate electricity unit price data; a variable rate measurement database storing variable rate measurement data acquired from a variable rate measurement device that measures the energy consumption of variable rate equipment of a customer; a variable rate specification database storing specification data of the variable rate equipment; an operating condition estimation unit that estimates the operating conditions of the variable rate equipment based on the variable rate measurement data and the variable rate specification data; a variable rate operation plan calculation unit that calculates the operation plan and electricity costs of the variable rate equipment by applying the variable rate or the fixed rate under the operating conditions; a non-variable rate equipment measurement database storing non-variable rate equipment measurement data acquired from a non-variable rate equipment measurement device that measures the energy consumption of non-variable rate equipment of a customer; and a non-variable rate equipment electricity cost calculation unit that calculates the electricity costs of the non-variable rate equipment by applying the variable rate or the fixed rate to the non-variable rate equipment measurement data. A power rate design system comprising: a power cost aggregation unit that aggregates the power costs calculated by the variable equipment operation plan calculation unit and the power costs calculated by the non-variable equipment power cost calculation unit and presents the aggregated data to the consumer as power rate design data.

2. The electricity rate design system according to claim 1, wherein the electricity cost aggregation unit lists the electricity costs of the variable equipment to which the variable equipment operation plan calculation unit applies the variable rate or the fixed rate, and the electricity costs of the non-variable equipment to which the non-variable equipment electricity cost calculation unit applies the variable rate or the fixed rate, in a data table and presents them to the customer.

3. The electricity rate design system according to claim 2, wherein the variable equipment is equipment that uses electricity to supply heating and cooling, the variable equipment measurement data is power consumption data, and the operating condition estimation unit estimates the heat demand for the variable equipment as an operating condition based on the power consumption data and the variable equipment specification data.

4. The electricity rate design system according to claim 3, wherein the variable equipment operation plan calculation unit calculates an operation plan that minimizes the electricity cost of the variable equipment under the variable rate or the fixed rate, with the constraint that the heat demand is satisfied.

5. The electricity rate design system according to claim 2, wherein the electricity cost aggregation unit presents the customer with a combination of the variable rate and the fixed rate that results in lower electricity costs for the variable equipment and the fixed equipment, respectively.

6. An electricity rate design system according to claim 2, comprising an aggregated constant database storing constants in time series data or scalar data, which include at least one of the procurement unit price, transmission unit price, supply and demand management unit price, and profit unit price per kWh of electricity for retail sale of electricity, wherein the electricity cost aggregation unit calculates a market risk management cost to prepare for fluctuation risk of the procurement unit price by subtracting at least one of the procurement cost, transmission cost, supply and demand management cost, and profit, which are calculated by multiplying the electricity usage data under the operation plan by a constant stored in the aggregated constant database, from the electricity cost under the operation plan of the variable equipment to which the variable rate has been applied by the variable equipment operation plan calculation unit, and calculates a market risk management cost to prepare for fluctuation risk of the procurement unit price by dividing the market risk management cost by the total value of the electricity usage data to obtain an amount per kWh of electricity.

7. The electricity rate design system according to claim 6, wherein the electricity cost aggregation unit, when the variable rate is a market-linked rate, performs an adjustment by subtracting the market risk management unit price from the variable rate and presents the adjusted variable rate to the customer.

8. The electricity rate design system according to claim 6, wherein the electricity cost aggregation unit makes an adjustment by subtracting the market risk management cost from the electricity cost of the variable equipment calculated by the variable equipment operation plan calculation unit, and presents the adjusted electricity cost to the customer.

9. The electricity rate design system according to claim 6, comprising: a variable equipment operation plan calculation unit that calculates the difference in the amount obtained by multiplying the electricity usage data when the fixed rate or the variable rate is applied by the procurement unit price stored in the aggregated constant database, as the amount of reduction in procurement costs achieved by the demand shift based on the variable rate; a profit distribution adjustment support unit that positions the amount of reduction in procurement costs as the gain obtained by the cooperation of the retail electricity business operator that sells electricity, the consumer that purchases electricity, and the equipment provider that provides the variable equipment for a fee, as players, and visualizes the gains to be distributed to each player.

10. The electricity rate design system according to claim 9, wherein the profit distribution adjustment support unit, when the variable rate is a market-linked rate, positions the market risk management costs that are unnecessary for the retail electricity provider as additional profits added to the profits, and distributes the additional profits to the consumers who assume the risk of fluctuations in the procurement unit price.

11. A method for designing electricity rates, comprising the steps of: estimating the operating conditions of a variable device based on variable device measurement data of a customer's variable device stored in a variable device measurement database and specification data of the variable device stored in a variable device specification database; calculating an operating plan and electricity costs for the variable device with the variable or fixed rates applied under the operating conditions based on variable rate electricity unit price data stored in a variable rate database, fixed rate electricity unit price data stored in a fixed rate database, and specification data of the variable device; calculating the electricity costs for the non-variable device with the variable or fixed rates applied to the non-variable device measurement data of the customer's non-variable device stored in a non-variable device measurement database; and presenting data aggregating the electricity costs calculated for the variable device and the electricity costs calculated for the non-variable device to the customer as electricity rate design data.

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