A method of tracking and reporting energy performance for businesses
An enterprise, performance technology, applied in data processing applications, instruments, computing, etc.
Pending Publication Date: 2015-12-23
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AI-Extracted Technical Summary
Problems solved by technology
Each time period is less t...
 In general, there are several barriers to making existing and new SMEs more energy efficient. For example, business owners may have insufficient understanding of the benefits of energy performance tracking to their business operations. Business owners may lack the knowledge or resources (financial or time) to i) maintain a service to track energy performance of their business or ii) deploy an energy performance tracking solution for their business. Other financial or regulatory constraints may also exist. By providing energy information, barriers to being more energy efficient in running a business are removed or substantially lowered as it relates to business operations requiring little involvement from business owners or managers.
 FIG. 5E illustrates a hypothetical email report 562, according to an embodiment. The report 562 can provide a detailed description 564 of the factors used to determine similar business locations. Instructions 564 may provide criteria used in similar business analysis. Description 564 may provide information related to the customer's premises, which may be common to similar business premises used in the analysis. Thus, the statement 564 provides the customer with a ...
Methods and computer systems report and track resource performance for business customers. The computer system receives usage data about a resource associated with a customer of a utility, including hourly usage information about the resource metered at a business premises of the customer. The computer system receives operational data associated with the business premises, including hours of operations information describing when the business premises is open to patrons. The computer system determines resource performance data for the business premises using the received usage data and the received operational data, including information about: (i) resource usage at the business premises during the hours when open to patrons, and (ii) resource usage at the business premises during the hours when closed to patrons. The computer system causes a reporting of this information to the customer of the resource.
Data processing applicationsTechnology management
Network performanceResource use +5
- Experimental program(1)
 The term "small and medium enterprise" (used interchangeably with the term "small business" in this article) generally refers to the utility company designation of customers with business accounts in which the average resources drawn by the customers (for example, drawn The pull power) is within a predefined limit. Small and medium-sized enterprises may include businesses (e.g., retail, service, construction, etc.), industry (e.g., manufacturing), and government offices and functions (e.g., post office, administrative bureau, police station, etc.). For example, if a business has a peak demand of using 300 kilowatts or less per month, the utility company may refer to the business as small. Of course, there are other limits, which are based on allegations provided by the utility company.
 "Local Directory Service Provider" refers to a third-party service that maintains a record of enterprise characteristic information, such as:
 ·Type of business (retail, service, restaurant, cinema, legal service, accounting service, dental office, etc.);
 ·Professional or sub-type (for example, for restaurants, the sub-type may include the type of cooking, the availability of delivery services, on-site service only, etc.);
 · General corporate information (for example, operating hours, address, number of employees, size of corporate premises); and
 · Resident information (for example, the type of heating, the service life of the premises, the presence of air conditioners, the size of the premises, the existence of photovoltaic systems, etc.).
 "Corporate premises" refers to the buildings or real estate where the company operates.
 "Similar business premises" refers to the premises of small and medium-sized enterprises with a predetermined number of public characteristics as the business premises of customers. Customers usually refer to the customers of the utility company and the person or entity for whom the report is being prepared.
 "Corporate location" refers to the building or real estate where the company operates.
 "Resources" refer to commodities provided by utility companies and may include electricity, water, and natural gas.
 Generally, there are multiple obstacles to making existing and new small and medium-sized enterprises more energy efficient. For example, business owners may have insufficient understanding of the benefits of energy performance tracking for their business operations. Business owners may lack the knowledge or resources (financial or time) to i) maintain services to track the energy performance of their business or ii) subordinate energy performance tracking solutions to their business. There may also be other financial or regulatory constraints. By providing energy information, since it involves business operations that require little participation from business owners or managers, it eliminates or greatly reduces the barriers to more energy efficient operation of the business.
 Other benefits can also be expected. Utility companies usually send corporate customers the same types of billing statements as residential customers, but they maintain records for customer accounts for small businesses. This embodiment may allow a utility company to use information and data from its Advanced Meter Infrastructure (AMI) system and its database to provide new services or energy-efficient programs for small and medium-sized enterprise customers. Similarly, utility companies can realize the value of their investments in AMI projects and smart grid initiatives by providing integrated customized solutions to corporate customers.
 figure 1 The schematic diagram illustrates a flowchart of a method for tracking resource performance for enterprise customers according to an embodiment. "Customer" generally refers to an entity or person that receives services including resource delivery from a utility company. figure 2 The schematic diagram illustrates a system utilizing methods according to various embodiments. will figure 1 with 2 Describe in conjunction with each other.
 The computer system 202 (labeled "server 202") may receive usage data 204 regarding resources associated with the customer from the utility server 206 (step 102). Resources can be any type of commodities provided by utility companies to customers, including electricity, natural gas, water, etc. The usage data 204 may include hourly usage information of resources metered at the customer's business premises 208 and stored at the utility company's data server 206. Of course, the usage data 204 can be retrieved by the computer system 202 directly from the meter at the enterprise premises 208. The meter can be a communication meter or an advanced meter infrastructure (AMI) meter. The server 206 may receive the data 204 via a communication network (e.g., the Internet) via an FTP file downloaded by an email, an XML feed, or a metered feed, for example. However, in other embodiments, the global communication network is not used. Alternatively, the resource usage data is sent by, for example, ordinary mail.
 The computer system 202 may receive operational data 210 associated with the business premises 208. The operating data 210 may include information associated with operating hours when the business premises are opened and closed to customers. Customers generally refer to customers of businesses operating at the premises.
 ·Type of business (for example, retail, restaurant, cinema, legal service, accounting service, dental clinic, etc.);
 ·Professional or sub-type (for example, for restaurants, the sub-type may include the type of cooking, the availability of delivery services, on-site service only, etc.);
 · General corporate information (for example, operating hours, corporate address, number of employees, corporate location, etc.); and
 · Resident information (for example, such as the type of heating, the age of the building, the presence of air conditioners, the size of the premises, the presence of photovoltaic systems, etc.).
 Alternatively, the computer system 202 may receive operating data 210 from a third-party service 214 such as Dun & Bradstreet, Infogroup, or Factual. The third-party service 214 is generally a company that maintains a database of enterprise-related information, including enterprise type and operating time information. The operating data 210 can be obtained by purchasing from a third-party service 214.
 Alternatively, the operational data 210 can be retrieved directly from the company's publications. For example, an enterprise may publish the operating hours of its enterprise premises on the enterprise website 216. The survey service 218 can retrieve operating hours information directly from corporate publications on its website 216 automatically or manually.
 Alternatively, the operational data 210 may be retrieved from a web portal 220 that is operatively linked to the computer system 202. Companies can voluntarily provide additional information to allow more precise analysis. For example, a company can provide characteristic information related to its type, specialty, submarket, size, number of employees, annual revenue, customer demographics, working hours, and scheduling. Companies can also provide information related to their facilities, including the size of the building, the age of the building, the type of heating, and the type of cooling. This information can be used, for example, to identify other similar business premises for comparative analysis of the use of various resources.
 In addition to the operational data 210, the consumer's corporate premises characteristic data may be received from third-party sources, including local service catalogs and third-party services. Characteristic data can also be retrieved from various records, such as property tax assessment records, real estate sales records, aggregators of consumer data collected through surveys, insurance policies, customer loyalty programs, etc. In some embodiments, consumer profile data may be received from third-party sources (eg, email, downloaded FTP files, and XML feeds) via a communication network. However, in other embodiments, ordinary mail may be used to receive consumer characteristic data.
 The computer system 202 may determine the usage performance of the enterprise premises resources based on the received usage data 204 and the received operation data 210. The performance can include information related to:
 (i) The resource usage of the corporate premises 208 during the time period when it is open to customers;
 (ii) The use of resources at corporate premises 208 during the time period when the customer is closed;
 (iii) The ratio of resource usage at the business premises 208 between the time when it is open to customers and the time when it is closed to customers.
 Figure 3A It is a graph of hypothetical usage data 204 of utility meter readings. The x-axis 302 indicates the time of day, and the y-axis indicates the corresponding meter reading 304. For electrical resources, kilowatt hours (kWh) can be used to represent meter readings. The usage data may be the average usage during the reporting period shown during the day. Other types of meter readings may be used, which may have readings expressed in gallons for water resources, British Thermal Units (BTU) for natural gas resources, or kilocalories, etc.
 Figure 3B A hypothetical operating data 210 is shown, including operating hours 306 when the business premises are open to customers (12:00PM (that is, noon) to 9:00PM from Monday to Friday, and 4:00AM to 9:00PM on Saturdays). If only the opening hours are available from the operating data 210, the closing time can be obtained by assuming that the enterprise is closed at all times when it is not open.
 Figure 3C Shows with Figure 3B Related to operating data Figure 3A Usage data. The x-axis 308 indicates the time of day, and the y-axis indicates the corresponding resource usage (referring to hourly usage data 310). The operation data 210 is shown with respect to the corresponding usage data 310. Figure 3C The data of the operation opening time 306 and the acquired operation closing time 312 are shown.
 Figure 4 Is according to the embodiment Figure 3C A comparison chart of the opening time usage data 402 and the closing time usage data 404 of. Other performance metrics can be obtained from open time use and closed time use. For example, the computer system 202 can calculate the ratio of the closing time usage data 404 to the opening time usage data 402.
 Back to reference figure 1 with 2 , The computer system 202 may cause a report of the determined resource performance data to the client (step 108). The report can be formed in different ways. For example, the computer system 202 may generate or direct another computer system to generate an electronic message, which may be an email message. The report can be sent directly to the consumer via electronic message. The report may also be sent to an intermediary, such as a utility company or a service provider, and for example, the intermediary may include the report in the utility company bill. The report can also be made available via a web portal for consumers. Of course, the channel can be used to send reports in paper mail.
 Optionally, the report may be part of a set of reports sent to the intermediary. The intermediary can use the collection of reports for further analysis. For example, the collection of reports can be segmented to identify a subset of corporate customers that are targeted for promotions, energy efficiency programs, marketing analysis, and the like. The collection of reports can be structured data files (for example, XML files), text or spreadsheets defined by commas, or binary data. The computer system 202 can use the API to communicate with the intermediary computer system. The API can be web-based, part of an enterprise API management and database system (for example, Oracle, SQL Server, DB2, Sybase, MySQL, PostgreSQL, Teradata, Informix, Ingres, SimpleDB, etc.), or can be a standalone application. Of course, other means of transferring data between the computer system and the network can be used.
 The computer system 202 may receive resource performance data for similar business premises. The computer system 202 may be combined with the customer's resource performance data to generate reports of similar enterprise premises resource performance data to the customer. Similar business premises refer to at least one premises that has the same predetermined number of characteristics as the business premises for which the report is being prepared.
 Figure 5A The figure shows a hypothetical email report according to an illustrative embodiment. As shown, the report 502 may include an introductory statement 504 (not shown-see for example Figure 5E ), utility company name 505, account number 506, resource performance information 508 including open time usage data 402 and closing time usage data 404, comparative performance information 510 of similar companies including opening time usage 512 and closing time usage 514, trend information 516, and suggest one or more ways to help reduce the use of text 518. The resource performance information 508 is normalized to the comparative performance information 510 in percentage, and is represented as a bar graph.
 The resource usage information 508 and the comparison information 510 may allow the customer to compare its performance with the performance of similar business premises. For example, the opening time usage data 402 for corporate premises is shown as 100%, and the opening time usage 512 for similar corporate premises is shown as 94%. In other words, similar business premises use less energy than the target business premises during the opening hours, that is, 94%. The customer can easily observe that the energy usage at his or her corporate premises is slightly higher, and there should be opportunities to reduce usage. More significantly here, the closing time usage data 404 for corporate premises is shown as 100%, and the closing time usage 514 for similar corporate premises is shown as 48%. This observation indicates to the customer that his or her corporate premises operations are different from the practices of his or her peer companies.
 According to some embodiments, the computer system 202 may generate suggestions or recommendations for inclusion in the report 502 based on the comparison information 510 during the opening time and/or the closing time. For example, if the comparison information 510 shows that similar business premises use less than a threshold amount of energy (eg, 50%) during the closing time, the computer system 202 may generate a specific recommendation or a collection of recommendations. If the comparison information 510 shows that similar business premises use less than a threshold amount of energy (eg, 80%) during opening hours, the computer system 202 may generate another suggestion or set of suggestions. The recommendation can be further customized based on the type of business or other information associated with the business.
 in Figure 5A In, text 518 provides instructions and/or suggestions to reduce usage. In addition, this observation provides customers with objectively obtained data-driven information about the company's premises operations, which can trigger customer actions. The customer may investigate the operation of the business to determine, for example, that the thermostat at the business premises was not properly set during the closing time, or the lighting or equipment in the back office is still on. In addition, when an employee performs certain business operations (such as performing a closing procedure during a day when the business premises are open to customers), they can suggest that there is an opportunity to transfer time. The resident resource usage information 508 and the comparison information 510 may be average values of data acquired in a monthly period. Of course, other durations can be used, such as averages within a billing cycle, fiscal quarter, fiscal year, etc.
 Figure 5B The figure shows a hypothetical email report 520 according to another embodiment. The report 520 may include a comparative analysis 522 of data between the business premises 524 and similar business premises 526, expressed as a bar graph. The comparative analysis 522 may include:
 ●The average, range, maximum, minimum and standard deviation of the energy use of the corporate premises when the premises are open to customers (referred to as the opening time energy use 528);
 ●The average, range, maximum, minimum and standard deviation value of the energy use of the corporate premises when the premises are closed to customers (called the closing time energy use 530);
 ●Average, range, maximum, minimum and standard deviation of energy use of similar business premises when the premises are open to customers (referred to as the opening time energy use of other premises 532);
 ●Average, range, maximum, minimum and standard deviation of energy use of similar business premises when the premises are closed to customers (referred to as the closing time energy use of other premises 534);
 ●The ratio of closing time energy usage 528 to opening time energy usage 530 (called the closing percentage of opening 536); and
 ●The ratio of closing time energy use 532 to opening time energy use 534 (called the closing percentage of opening 538).
 As an alternative to being normalized to a percentage, the data of energy usage 528, 530, 532, 534 can be represented by usage units such as kWh or BTU. Alternatively, the data of energy usage 528, 530, 532, 534 may be expressed in terms of cost (USD). Therefore, energy use may indicate the average expenditure during a given business opening time in a monthly period.
 Energy usage data 528, 530, 532, 534 can indicate potential actions to customers to reduce energy and costs. For example, data on the ratio of energy usage 528 during closing time may indicate to customers that their business operations are different from those of business premises in similar operating environments and models. In some cases, similar business premises 538 may include competitors (ie, business entities that participate in business activities for similar or identical customers). As provided in the figure, the data for the ratio 536 of corporate premises is shown as 81%, while the data for the ratio of energy usage between closing and opening of similar corporate premises is shown as 32%. This information can easily convey to the customer that his or her operations are very inefficient compared to similar businesses, and he or she should be able to significantly reduce his or her energy use.
 Figure 5C The figure shows a hypothetical email report 540 according to another embodiment. The email report 540 allows for direct data comparison between energy usage during opening time 402, energy usage during closing time 404, and energy usage during closing time 514, represented as a bar graph. The energy usage data can be normalized to the percentage of energy usage during the opening hours 402. In addition, the report 540 may include a graphical illustration 542 of the difference between the energy usage data during the closing time of the business premises 404 and the similar business premises 514.
 Report 540 organizes the information to emphasize closing time operations. The energy usage data of the corporate premises during the opening hours 542 are normalized to 100%. Regarding the opening time, energy usage data during the closing time for the business premises 544 and for the similar business premises 546 are shown. The report 540 may illustrate the difference 548 in energy usage between the business premises and similar business premises (including, for example, competitors) during the closed time. For example, the data for open time energy usage 542 can be read as 100%, while closing time energy usage 544 can be read as 72%, and closing time energy usage 546 for similar business premises can be read as 50%. The difference in energy usage 548 during the off time can be read as 22%. Therefore, the owner of the business premises can observe the efficiency of his or her business operations during the closing time with regard to the opening hours, and can further observe that his or her efficiency is very poor with respect to other similar enterprises (including, for example, competitors) .
 It should be noted that as customers take actions to reduce the energy use of the corporate premises, similar corporate premises can also receive similar customized reports and can take actions to reduce their energy use. Therefore, the report provides a feedback loop for the business owner or manager to modify his or her business operations to match those in his or her respective industry. The difference in energy use 548 is the observable feedback given to customers to reduce their energy use to be consistent with other similar businesses. The customer can easily determine his or her performance with respect to similar businesses (including, for example, competitors). In a large number of companies, this feedback loop can normalize the company's energy use to a level specific to the corresponding industry and market location.
 Figure 5D The figure shows a hypothetical email report 550 according to another embodiment. The email report 550 allows visual observation of data on energy usage between closing 552 and opening time 554, as a percentage of total usage compared to similar business premises (closing time 556 and opening time 558), expressed as a pie chart. The report 550 may further provide an indication 560 of the number of hours the business is open to customers compared to other similar businesses (including, for example, competitors).
 Figure 5E The figure shows a hypothetical email report 562 according to an embodiment. The report 562 may provide a detailed description 564 of the factors used to determine the location of similar businesses. Description 564 can provide criteria used in the analysis of similar companies. The description 564 may provide information related to the customer's premises, which may be shared by similar business premises used in the analysis. Therefore, the description 564 provides the customer with the confidence that the analysis is related to his/her business operations. By showing customers that similar business premises in the report are in fact located similarly, the report can motivate customers to save energy. For example, suppose the customer is a pizza shop. Use a set of public criteria to determine similar business premises, and can include: (1) whether the premises is located in the urban area, (2) whether it is a pizzeria, doughnut shop, or other takeaway food service, (3) its Does it have gas heating, (4) Does it have less than 10 employees, (5) Is it located within 10 miles of the business, and (6) Is it rented out. The report 562 may include a map 566 to illustrate the proximity of similar business premises employed in the analysis. The report 562 may include an input field 568 to allow the customer to provide information about the business. Figure 5F The figure shows a user interface for a customer to input enterprise information according to an embodiment. By showing the customer that similar business premises in the report are actually similarly located, the report can motivate the customer to voluntarily provide more information about his/her business to provide a more refined search.
 In an embodiment, the factors employed to determine similar business premises may be the same between different reports to provide consistent tracking metrics over time. For example, the first report may be configured to provide at least a pre-specified number of business premises to ensure a sufficient group size for comparison. However, in subsequent reports, the number of pre-specified number of corporate premises can be relaxed within a pre-specified tolerance, and this factor can be maintained. The group size of similar business premises may be, for example, at least 50. Of course, other numbers can be used. The report 562 may provide input 570 for the customer to modify the group size of similar businesses. The report can provide ranges including minimum and maximum values to ensure that the analysis has a sufficient population size.
 In another embodiment, the description 564 can provide information that can be used in the computer system 202 that is not used but can be considered in the analysis. Therefore, description 564 provides an opportunity for the customer to augment, confirm, modify, or remove information about his/her business operations.
 Figure 5G The figure illustrates a user interface 570 for adjusting parameters to determine similar business premises according to an embodiment. The user interface 570 may be used by the user to select the number of similar businesses to be compared with the user's businesses or to select the number of closest matching businesses to be used in the comparison. The minimum number of enterprises 572 can be limited to 25 to ensure a large enough group size. The maximum number of businesses 574 may be specified by the number of available businesses that meet the criteria when not restricted by proximity. For example, if there are 532 pizzerias, in an urban area, with gas heating, with fewer than 10 employees, and in a leased premises, the input may allow up to 532 for analysis. The maximum value can be rounded to 500 to simplify the interface. Alternatively, the best ranking result according to public criteria may be provided as the result.
 Figure 6A —6C is a hypothetical graph of energy usage data for the customer’s corporate premises and similar corporate premises. specifically, Figure 6A Data on the energy usage of the customer 602 in a 24-hour period and the energy usage of similar business premises 604 in the same time period are shown. Figure 6B The figure shows the relationship between customers and similar business premises during the closing time Figure 6A Comparison of data. In this example, the customer's corporate premises are open to customers between noon and 9pm, and closed to customers between 9pm and noon. Figure 6C Figure shows Figure 6A Energy use analysis of the data. The numbers above each bar provide data on the customer's energy usage during opening hours 606 and closing time 608 and the energy usage of similar business premises during opening hours 610 and closing time 612. Here, the data about the customer's energy usage during the opening time 606 is 13 kWh, and the energy usage during the closing time 608 is 9.5 kWh. Conversely, the data for energy usage of similar business premises during the opening time 610 is 11.9 kWh, and the energy usage during the closing time 612 is 4.2 kWh.
 Text 518 ( Figure 5A ) Is layered to emphasize the key takeaways for customers based on the master list. For example, the total list may include ten actions that can help reduce energy use. The text 518 may select key gains from the master list based on, for example, analysis of the usage data 310 and operational data 312 of the customer's business premises and similar business premises. This key gain can further motivate customers to take energy reduction actions by providing more appropriate information and analysis. For example, in Figure 3C It should be observed that resource usage 310 started to increase three hours before the corporate premises began to open to customers. This transition period may represent the cleaning time for the corporate premises, which may include activation of the climate control system, turning on the lights, etc. The computer system can compare the transition time of the customer with the transition time of similar business premises. When the customer’s transition time is longer (for example, in a similar business premises with a two-hour transition time and the customer’s is three hours) and the total energy use is high (for example, the total energy use is higher during the transition period 10%), the report 502 may include a detailed statement 518 to further help reduce energy usage during the transition period. Statement 518 can be read. For example, "Your energy usage before opening hours seems to start one hour earlier than other similar business premises. Do you consider delaying your programmable thermostat to start one hour late?"
 Likewise, during the closing time, if the transition time between the opening time and the closing time is longer than similar business premises, the customer's business may use more resources during the windowing down period. The report may include a statement 518 that reads "Your energy use during the shutdown period appears to be 2 hours longer than other similar corporate premises. Are you considering programming your thermostat to turn off one hour earlier?"
 Statement 518 can quantify the amount of savings (reduced cost) or environmental impact and connect such information to the description. For example, statement 518 can read "Your energy usage before opening hours seems to start one hour earlier than other similar business premises. Are you considering delaying your programmable thermostat to one hour late? You can change it every year Save up to $100."
 Alternatively, as an alternative to using monetary units, the statement 518 may quantify the amount of savings in environmental impact. For example, statement 518 can read "Your energy use before opening hours seems to start one hour earlier than other similar business premises. Have you considered delaying your programmable thermostat to one hour late? How much is the savings equivalent to? Plant a new tree every year.” On the Environmental Protection Agency’s Clean Energy Calculation and Reference Website (www.epa.ov/cleanrgy/energy-resources/refs.html) you can find a way to convert energy savings including kWh into different Calculation of equivalent units of type (including carbon sequestration from trees). You can use the EPA Greenhouse Gas Equivalent Calculator to automatically perform these calculations online at www.epa.gov/cleanrgy/energy-resources/calculator.html. From this website, kilowatt hours (KW-hr) can be equivalent to 7.0555×10-4 metric tons of CO2; kilocalories of natural gas can be equivalent to 0.005 metric tons of CO2; and trees in a city provide 0.039 metric tons of CO2 savings. Therefore, 55 kilowatt hours (KW-hr) of electricity reduction is equivalent to a city's trees.
 The various reports described in this article can be used individually or combined in statements to customers. The report can be an electronic or hard copy statement, which includes resource usage information and analysis results using the methods disclosed in this application. It can also include billing information.
 Other analysis results can be added in conjunction with this report. For example, various reports can be used to report disaggregated energy usage information, including climate control and non-climate control loads. Methods for decomposing climatic and non-climatic loads are disclosed in U.S. Patent Application No. 13/839,082 entitled "AMethod to Identify Heating and Cooling System Power-Demand" and U.S. Patent Publication No. 2011/0106471 entitled "Method and System for Disaggregating Heating and Cooling Energy Use From Other Building Energy Use". These applications are incorporated herein by reference in their entirety.
 Similar business locations
 In another aspect of the embodiments of the present invention, a method and system for determining similar business premises are provided. Determining similar business locations is described in a US patent application (Publication No. US2012/0310708) filed on May 4, 2012 by Richard Tyler Curtis and Kyle Yost, which is incorporated herein by reference in its entirety.
 Figure 7 Contains a flowchart illustrating a computerized method for reporting consumer resource usage by determining similar business locations according to an embodiment. The method starts by retrieving characteristic data for the consumer's business premises and business premises collection (step 702). The characteristic data includes a plurality of characteristics related to each enterprise premises. For example, the characteristic data may include enterprise type and classification, enterprise-related characteristics, and building data related to the physical characteristics of the premises (for example, the size of the physical asset, the heating system, and/or the service life of the asset).
 The characteristic data may include characteristic data related to the physical assets of each enterprise premises, such as the following non-limiting list selected from examples:
 ·Public building and/or factory type;
 ·Public meter reading cycle;
 ·Public heating fuel;
 ·The size or floor space of public buildings and/or factories;
 · Common types of equipment located on site, including manufacturing equipment;
 ·Enclosure structure and residential characteristics of public buildings;
 · The public number of building occupants, including the number of employees, visitors or customers;
 · The public presence of solar panel systems (for example, photovoltaics);
 · The public presence of air conditioners;
 ·The service life of public buildings and/or factories;
 ·Public commercial type for one or more building and/or factory occupants; and
 · Location of public buildings and/or factories.
 The characteristic data may also include characteristic data related to the occupant itself, such as the following non-limiting list selected from examples:
 ·The number of employees in the company's premises;
 ·The age of the employee; and
 · Is the employee a seasonal employee, temporary employee, or independent contractor.
 The characteristic data may also include characteristic data related to business operations, such as the following non-limiting list selected from examples:
 · Residents located in urban or suburban locations;
 ·Type of business and services provided;
 ·Enterprise scale (employee's #, customer's #, enterprise's human flow, income, etc.);
 · Operating hours; and
 ·All or lease.
 Business types and classifications can include: service types (for example, agriculture, mining, construction, manufacturing, retail, transportation and warehousing, information, finance and insurance, real estate, professional services, company management, educational institutions, administration, waste services, medical Health and social assistance, art, entertainment, leisure, accommodation, catering services, and public administration), customer type (for example, luxury, standard, bargaining), service location (for example, on-site, off-site). Types of services can include classification systems defined for surveys, such as the North American Industry Classification System (NAICS) provided in Appendix A and incorporated herein by reference in its entirety, and by professions also incorporated herein by reference in its entirety. The Standard Industry Classification (SIC) published by the General Administration of Safety and Health (OSHA). Service types also include industry-generated classifications. For example, companies such as Yelp and Zagat maintain service categories, such as catering, nightlife, shopping, bars, beauty and weight loss centers, health and medical care, automobiles, local services, etc. Such classifications can include types and sub-categories of business types.
 "Local Directory Service Provider" refers to a third-party service that maintains a record of enterprise characteristic information, such as:
 ·Type of business (for example, retail, service, restaurant, cinema, legal service, accounting service, dental clinic, etc.),
 ·Professional or sub-type (for example, for a restaurant, the sub-type may include the type of cooking, the availability of delivery services, on-site service only, etc.),
 ·General corporate information (for example, operating hours, address, number of employees, business location scale)
 · Resident information (for example, such as the type of heating, the age of the building, the presence of air conditioners, the size of the premises, the presence of photovoltaic systems, etc.).
 The customer can be any party associated with the building (for example, business owner, renter, or business manager).
 Certain characteristic data related to the physical assets of the premises can also be obtained from publicly available sources, including maps, street view images, and satellite imaging. For example, the envelope and residential characteristics of public or different buildings may include:
 The number and location of entrances and windows (for example, the presence of windows facing the sun, which may include windows facing south for a residence located in the northern hemisphere);
 ·The existence of solar panels or wind energy generators;
 · The presence of structures on the roof (eg chimneys, central climate control system);
 The existence and number of window air conditioning units;
 · The existence of an outdoor swimming pool;
 · Roof type (for example, flat or angled);
 ·Building color, floor size, and height;
 · Building orientation and location (for example, longitude and latitude); and
 • The presence and extent of shelter from neighboring structures, obstacles (e.g., mountains, signs/billboards), and/or trees and leaves.
 In particular, in urban and suburban locations where a single corporate premises resides in a single building envelope, the information obtained from the image analysis of the corporate envelope or the premises can be attributed to the corporate premises. The imaging data may be, for example, received from a third-party service, such as a mapping, street view, navigation, or satellite imaging service.
 The method also includes receiving resource usage data for various customers (step 704). For example, in one embodiment, the resource usage data may include electricity usage data reported in kilowatt hours. In additional or alternative embodiments, the resource usage data may include natural gas reported in British Thermal Units (BTU), heating oil reported in gallons, and/or wood pellets reported in pounds. In addition, in the illustrative embodiment, the resource usage data may include any one or more of electricity usage data, gas usage data, waste usage data, water usage data, sewer usage data, garbage usage data, and recycling usage data. Related data.
 In an exemplary embodiment, the computer system selects at least one enterprise similar to the customer's enterprise premises from the enterprise premises set based on at least five criteria common between the enterprise premises characteristic data and the enterprise premises characteristic data set Station (step 706). The common criterion may be a match between the characteristics of the customer's characteristic data and the characteristics of other corporate premises. For example, when the customer's business and other business premises are the same type of business (for example, both of them are pizza shops), there is a public rule. In another example, when the customer's business and other business premises are catering services, there are public guidelines. In yet another example, when the customer's business and other business premises both use the same heating fuel, there are common guidelines. For example, two business premises use electricity to heat the premises. Therefore, a corporate location that uses gas for heating will not be selected as a corporate location similar to the customer's corporate location. In yet another example, when the customer’s business and other business locations both have similar geographic locations (for example, both businesses are located in the same area type (ie, city or suburb), zip code, city, or state) , There are public guidelines.
 In an alternative or additional embodiment, the common criterion is a match between the scope and the characteristic data of another business premises. For example, in one embodiment, the common criterion is a match between the size of other business premises and a range determined based on the size of the customer's business premises. In an illustrative embodiment, the range is the size (in square feet) of the customer's corporate premises plus/minus 8%. If the size of other corporate premises (in square feet) falls within this range, the size of the premises is a common criterion between the customer’s corporate premises and other corporate premises. In another example, the common criterion is the match between the distance and the distance range between other business premises and the customer's business premises. For example, the distance range may include all business premises within a 20-mile radius of the customer's business premises. If other corporate premises fall within a 20-mile radius, it matches the client’s corporate premises location criteria. Business locations that fall outside a 20-mile radius were not selected as similar business locations. In another example, if other business premises have an occupant range such as 1-9 employees, customer business premises with less than 10 employees may be matched.
 in Figure 7 In the embodiment shown in, the corporate premises of similar customers are selected based on five common criteria. However, in other embodiments, similar business premises may be selected based on other numbers of public criteria, such as 3, 5, 10, or 25 public criteria. In a particular embodiment, similar business locations are selected based on: (1) public city/suburban location, (2) public business type, (3) public business size, (4) public operating hours Collections, and (5) Common asset ownership status, such as ownership or lease of premises.
 If the number of selected similar business premises is less than the predetermined number of business premises (step 708), an action is taken to expand the group of similar businesses. In an illustrative embodiment, the predetermined number is 50, and therefore the goal is to select 50 similar business premises that are most similar to the customer's business premises. If the number of initially selected business premises is less than 50, the criteria can be changed to find more or additional similar businesses by using another criterion in another selection process. For example, in order to augment the five public criteria, one of the public criteria may be expanded so that there are five public criteria for selecting similar consumers, but one of the criteria may include two categories. The categories may be based on a predefined classification system, such as NAICS codes, SID codes, or other classification codes defined by local service providers. In this way, a larger number of corporate premises will meet public guidelines.
 In an embodiment, a full-service pizzeria may have the NAICS code number 722511. Code 722511 includes other types of full-service restaurants, such as bagels, food trucks, doughnut shops, family restaurants, fine restaurants, pizzerias, and steakhouses. The first search may include public criteria for pizzerias. The second search may be based on broader selection criteria, such as by including in the same NAICS code public criteria for at least one other restaurant type, such as bagels, food trucks, doughnut shops, family restaurants, fine restaurants, pizzerias , And steak shop.
 In another embodiment, the second search may entail moving up the classification code tree. Picture 9 The figure shows part of the North American Industry Classification System (NAICS). For example, NAICS code 722511 (902) is a subcategory (904) of NAICS code 72251, which includes NAICS code 722511 (ie, full service restaurants) (902), 722513 (ie, limited service restaurants) (906), 722514 (ie , Cafeterias, barbecue restaurants, and buffet bars) (908), and 722515 (snacks and non-alcoholic beverage bars) (910). The second search may include businesses with NAICS code 72251 (904), which includes 722511 (902), 722513 (906), 722514 (908), and 722515 (910).
 The second search may require searching for equivalent classification codes in other classification systems. For example, a pizzeria may have NAICS code number 722511 (902). NAICS code number 722511 (902) has crosswalks with SIC code number 5812 (912) for "public catering business". The second search may include SIC code number 5812 (912) as one of the public criteria. Attachment B provides a table of crossovers between NAICS codes and SIC codes. The attachment is incorporated herein by reference in its entirety.
 In an additional or alternative embodiment, if the number of selected similar business premises is less than a predetermined number, then actions are taken to lower (relax) the public criteria. The reduction may include removing at least one common criterion from the selection process. For example, in order to reduce the five public criteria, one of the public criteria is removed so that there are only four public criteria for selecting similar business locations. In this way, a larger number of similar business premises will meet public guidelines.
 In an additional or alternative embodiment, the criterion is reduced by increasing at least one range for at least one of the common criteria. For example, in one illustrative embodiment, increasing the proximity of a business premises from a 20-mile range to a 50-mile business premises allows a larger number of other business premises to fall into this range. Once the criterion is lowered, the selection process is run again. The selection and reduction process may be performed iteratively until the number of similar business premises is equal to or greater than the predetermined number of business premises (for example, 50 similar business premises). For example, if four public criteria have not yet produced 50 similar consumers, then the public criteria may be further reduced by, for example, removing another public criteria and/or by increasing the scope for at least one of the public criteria. Once the selection process selects the number of similar business premises equal to or greater than the predetermined number of similar business premises, it is prompted to use the list of similar business premises to generate an electronic report (step 712).
 The selection process 706 can be implemented in various ways. For example, in one embodiment, when the distance range is increased from 20 miles to 50 miles, the selection process 706 searches for similar consumers within a radius of 50 miles from the customer's corporate premises. In another embodiment, the selection process 706 avoids reanalyzing the geographic area within 20 miles of the customer's business premises, and instead searches for similar business premises within the geographic area between 20 and 50 miles from the customer's business premises. In this way, the selection process 706 saves computational time and effort because the geographic area within 20 miles of the customer's corporate premises has been analyzed in previous iterations.
 Figure 8 The application of the computerized method according to the embodiment is shown. The computerized method starts with five common criteria (802): (1) the suburban location of the premises (choose between the city/suburban location); (2) the pizza shop business (choose as the business type); (3) Businesses with less than 10 employees (selected as business size), (4) within 20 miles of distance, and (5) business premises are leased (choose between leased or owned). The predetermined number of similar business premises in this embodiment is 50. When using these five criteria to run the selection process (804), 25 similar business locations are found (806). Since 25 similar business sites are less than the predetermined 50 similar business sites, the five public criteria can be reduced or expanded. For the second iteration, the distance criterion was increased by 30 miles, from 20 miles to 50 miles (808). When the selection process is run again, 3 additional similar business premises are selected (810). Therefore, the total number of similar business premises found after two iterations is 28. Since 28 similar business locations are less than the predetermined 50 similar business locations, the five public criteria are reduced or expanded again. For the third iteration, use the second category to expand the type of enterprise. Specifically, the category of "pizza shop" is expanded to include "doughnut shop" (812). When running the selection process, it selects 10 more similar consumers (814). Since the 35 similar business locations are less than the predetermined 50 similar business locations, the five public criteria are reduced or expanded again. For the fourth iteration, the third category, specifically "takeaway food service", is used to expand the type of enterprise (816). When running the selection process, it selects 19 more similar consumers (820). Therefore, the total number of similar business premises at this time is 54 and the iteration process stops because the number of selected similar business premises is at least the predetermined number 50.
 In the illustrative assumption, if four more business locations are found in the fourth iteration, 54 similar business locations will be used in the report. However, in another embodiment, the additional four business premises may be ranked according to, for example, distance or square feet, and the best 15 business premises from the 19 matches are selected as used for a total of 50 similar business premises Similar business locations.
 In another embodiment, the computerized method may be additionally configured to "adapt" to the number of similar consumers selected in the iterative process. As above relative to Figure 7 It is explained that if the number of selected similar consumers is less than the predetermined number, the common criterion is amplified to some extent. In the computerized method of FIG. 5, the extent to which those public criteria are augmented may depend on the number 706 of similar consumers selected.
 For example, an adaptive process can be applied to common criteria such as the distance between the premises, the range associated with the size of the household, the meter reading cycle, and the number of businesses in the premises can also be based on similar businesses selected in the last iteration The number of stations and/or the number of similar stations selected in all iterations increases. In other illustrative embodiments, an "adaptive" process is applied such that the number of common criteria that are reduced (eg, removed) from the iterative process depends on the number of similar business premises selected.
 Some public standards may be more meaningful than other public standards in analyzing resource use. The inventors found that city and suburb locations are meaningful criteria. Compared with suburban locations, corporate locations in urban locations tend to be within a certain type of corporate structure. Especially in urban locations, multiple companies can reside in a single building structure. The type of business is a very important criterion. The type of enterprise category provides the public conditions and patterns that the enterprise experiences during the enterprise operation process at various operating hours, including the time when customers appear and when they do not appear on the premises. Operating time (for example, time depends on market factors) also affects the operation of the enterprise. For example, if a restaurant enterprise provides breakfast service, the time that employees and staff will have to be on site tends to be similar compared to a restaurant that only provides dinner service. Another important criterion is whether the company premises are owned or leased. Companies that own their premises tend to invest more in the structure, and the lessee may simply adjust the available settings. Another criterion is the physical enclosure of the corporate premises. Corporate premises with windows facing south, for example, can receive more daylight for lighting and heating during winter. Such corporate premises can use fewer resources for lighting and heating. On the other hand, windows facing south can increase the air conditioning load.
 In another embodiment, the augmentation of the common criteria for searching 706 may be based on a similarity index. The similarity index may have a form as shown in Equation 1.
 S=a_1*Factor_l+a_2*factor_2+a_n*factor_n (Equation 1)
 The coefficients a_1, a_2, and a_n may represent weight values ranging from 0 to 1, where n is the number of factors used to generate the exponent. Factors can include public descriptions, public NAICS codes, public SIC codes, and public local service catalog descriptions.
 Picture 10 A computer system 202 according to an illustrative embodiment is schematically illustrated. The server 202 includes a processor 1002, a memory 1004, and a communication port 1006. The processor 1002 can be programmed with any one or more of the following software modules stored in the memory 1004, including:
 ·Communication module of utility company for receiving resource usage data.
 ·Third-party source communication module for receiving characteristic data of enterprise premises.
 · Website modules for supporting websites.
 A storage module used to store the characteristic data and resource usage data of the enterprise premises.
 · A retrieval module for retrieving customer resource usage data and customer characteristic data.
 ·A selection module for selecting similar business locations.
 ·Analysis module used to determine the opening time and closing time performance of corporate premises.
 · A decomposition module for determining the climate and non-climate control load of the company's premises.
 • A reporting module for generating reports showing resource usage data for consumers and other similar consumers.
 A customer communication module for delivering reports to customers via, for example, a website or email.
 · A printing module for sending reports to customers via regular mail.
 The communication port 1006 is operatively linked to the external communication port 1008, which may be part of another computer system, network routing/packet switching equipment, programmable logic device, another electronic computing device, and the like. The link may be part of a local area network, a wide area network, or a combination thereof, and may include any of various standard protocols (such as IEEE-802) and proprietary protocols.
 The report can be delivered to the customer in various ways. In one example, the report is sent to the customer via an email (email) to the customer's email account. In another example, the customer receives the report in hard copy via regular mail. In yet another illustrative embodiment, the customer can log into his or her profile on the website and view the report in the web page. In some embodiments, the report is part of the resource usage bill. In other embodiments, the report is provided to the customer separately from the bill.
 It should be noted that terms such as "processor" and "server" can be used herein to describe devices that can be used in certain embodiments of the present invention, and should not be construed to limit the present invention to any specific device type or system , Unless the context requires otherwise. Therefore, without limitation, the system may include clients, servers, computers, appliances, or other types of equipment. Such devices generally include one or more network interfaces for communicating through a communication network and a processor (for example, a microprocessor and/or a microprocessor with memory and other peripherals) configured to perform device and/or system functions accordingly. Or dedicated hardware). Communication networks may generally include public and/or private networks; may include local area networks, wide area networks, metropolitan area networks, storage, and/or other types of networks; and may use communication technologies, including but not limited to analog technology, digital technology, Optical technology, wireless technology, networking technology, and network interconnection technology.
 The various components of the control program can be implemented individually or in combination. For example, each component or a dedicated server or a collection of servers configured in a distributed manner can be implemented.
 It should also be noted that the device may use communication protocols and messages (eg, messages created, transmitted, received, stored, and/or processed by the system), and such messages may be communicated by a communication network or medium. Unless the context requires otherwise, the present invention should not be interpreted as being limited to any specific communication message type, communication message format, or communication protocol. Therefore, communication messages may generally include frames, packets, datagrams, user datagrams, cells, or other types of communication messages without limitation. Unless the context requires otherwise, references to specific communication protocols are exemplary, and it should be understood that alternative embodiments may appropriately employ variations of such communication protocols (for example, modifications or extensions of the protocol that may be implemented from time to time) Or other protocols known or developed in the future.
 It should also be noted that the logic flow is described herein to demonstrate various aspects of the invention, and should not be construed as limiting the invention to any specific logic flow or logic implementation. The logic can be divided into different logic blocks (for example, programs, modules, interfaces, functions, or subroutines) without changing the overall result or otherwise departing from the true scope of the present invention. It is often possible to add, modify, omit, and execute logic elements in a different order, or use different logic structures (for example, logic gates, loop primitives, conditional logic, and other logic structures) without changing the overall result or in other ways Depart from the true scope of the present invention.
 The present invention can be embodied in many different forms, including but by no means limited to computer program logic for use with a processor (for example, a microprocessor, microcontroller, digital signal processor, or general-purpose computer), for use with programmable logic Logic devices (for example, Field Programmable Gate Array (FPGA) or other Programmable Logic Device (PLD)) used together with programmable logic, discrete components, integrated circuits (for example, application specific integrated circuits (ASIC)), or any of them Any other device in combination. In a typical embodiment of the present invention, all the logic is mainly implemented as a set of computer program instructions, which are converted into a computer executable form, similarly stored in a computer-readable medium, and controlled by the operating system The microprocessor executes.
 The computer program logic that realizes all or part of the functions previously described in this article can be implemented in various forms, including but not limited to source code form, computer executable form, and various intermediate forms (for example, by assembler, compiler , Linker, or locator generated form). The source code may include implementation in any of various programming languages (for example, object code, assembly language, or high-level languages such as FORTRAN, C, C++, JAVA or HTML) for use with various operating systems or operating environments A series of computer program instructions used. The source code can define and use various data structures and communication messages. The source code may be in a computer executable form (e.g., via an interpreter), or the source code can be converted (e.g., via a converter, assembler, or compiler) into a computer executable form.
 The computer program can be permanently or transiently fixed in a tangible storage medium in any form (for example, source code formation, computer executable form, or intermediate form), such as a semiconductor memory device (for example, RAM, RO, PROM, EEPROM, Or flash programmable RAM), magnetic memory device (for example, magnetic disk or fixed disk), optical memory device (for example, CD-ROM), PC card (for example, PCMCIA card), or other memory device. The computer program can be fixed in the signal in any form, and the signal can be transmitted to the computer using any of various communication technologies, including but not limited to analog technology, digital technology, optical technology, wireless technology, networking Technology, and network interconnection technology. The computer program can be distributed in any form as a removable storage medium using accompanying printing or electronic files (for example, compressed and packaged software), preloaded by the computer system (for example, on a system ROM or fixed disk), or through a communication system (For example, the Internet or World Wide Web) is distributed from a server or electronic bulletin board.
 Traditional manual methods can be used to design hardware logic (including programmable logic for use with programmable logic devices) that implement all or part of the functions previously described in this article, or various tools can be used to electronically design, capture, Simulation, or documentation, such as computer aided design (CAD), hardware description language (for example, VHDL or AHDL), or PLD programming language (for example, PALASM, ABEL or CUPL).
 Programmable logic can be permanently or transiently fixed in tangible storage media, such as semiconductor memory devices (for example, RAM, ROM, PROM, EEPROM, or flash programmable RAM), magnetic memory devices (for example, magnetic disks or fixed Disk), optical storage device (for example, CD-ROM), or other storage device. Programmable logic can be fixed in a signal, which can be transmitted to a computer using any of various communication technologies, including but not limited to analog technology, digital technology, optical technology, wireless technology (for example, Bluetooth), networking technology, and network interconnection technology. Programmable logic can be distributed with accompanying printing or electronic files (for example, compressed and packaged software) as a removable storage medium, pre-loaded by a computer system (for example, on a system ROM or fixed disk), or through a communication system (for example, , Internet or World Wide Web) from a server or electronic bulletin board. Of course, some embodiments of the present invention can be implemented as a combination of both software (for example, a computer program product) and hardware. Other embodiments of the present invention are implemented as all hardware or all software.
 The embodiments of the present invention described above are intended to be exemplary only; many changes and modifications will be apparent to those skilled in the art. All such changes and modifications are intended to be within the scope of the present invention.
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