Energy business risk determination method and device, storage medium and electronic equipment

Abstract

The invention discloses an energy business risk determination method and device, a storage medium and electronic equipment. The method comprises the following steps: according to an energy emission type, an energy storage type, an energy cooperation type and an energy hosting type, determining a target type of business needing risk assessment; performing feature extraction based on the historical project data of the target type of business, and determining a plurality of risk indexes of the target type of business; determining risk weights corresponding to the plurality of risk indexes according to historical risk occurrence frequencies corresponding to the plurality of risk indexes in the historical project data; and based on the risk weights corresponding to the plurality of risk indexes, determining a risk identification result of the target type of business. According to the invention, the technical problem that the energy business risk assessment effect is not ideal in the prior art is solved.

Description

Technical Field

[0001] The present application relates to the field of energy management and risk assessment, and in particular to an energy business risk determination method, device, storage medium and electronic device. Background Art

[0002] Risks are unavoidable in the process of project construction and operation of integrated energy service business. In order to better deal with potential risks, risk assessment is needed to help relevant personnel identify, analyze and quantify potential risks. The risk assessment model in related technologies fails to fully consider the uniqueness and complexity of integrated energy business. Related technologies have the problem of generalized risk assessment models, relying more on subjective judgment or limited historical data, single risk indicators, and failing to fully cover technical issues such as multi-dimensional risk factors such as technology and operation.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a method, device, storage medium and electronic device for determining energy business risk, so as to at least solve the technical problem of unsatisfactory energy business risk assessment effect existing in the related art.

[0005] According to one aspect of an embodiment of the present application, a method for determining energy business risk is provided, including: determining a target type of business that requires risk assessment according to energy emission type, energy storage type, energy collaboration type, and energy hosting type; performing feature extraction based on historical project data of the target type of business to determine multiple risk indicators of the target type of business; determining risk weights corresponding to the multiple risk indicators based on historical risk occurrence frequencies corresponding to the multiple risk indicators in the historical project data; and determining risk identification results for the target type of business based on the risk weights corresponding to the multiple risk indicators.

[0006] Optionally, the target business that needs to be risk assessed is determined according to the energy emission type, energy collaboration type, and energy trusteeship type, including: determining that the energy collaboration type is an energy complementary and collaborative business in which multiple energy sources collaborate with each other, wherein the multiple energy sources include at least electric energy, thermal energy, and fossil energy; determining that the energy emission type is clean energy, and the energy storage type is a clean instant supply business of a non-energy storage type; determining that the energy trusteeship type is clean energy, and the energy storage type is an electrochemical energy storage business of an energy storage type; determining that the energy trusteeship type is an energy trusteeship business that uses a third-party service for energy control; and taking the energy complementary and collaborative business, the clean instant supply business, the electrochemical energy storage business, and the energy trusteeship business as the target business.

[0007] Optionally, the feature extraction is performed based on the historical project data of the target type of business to determine multiple risk indicators of the target type of business, including: determining, in chronological order, the timing weights corresponding to the multiple project data included in the historical project data; determining the correlation between the multiple project data; and based on the timing weights and correlations corresponding to the multiple project data, performing feature extraction on the historical project data to obtain the multiple risk indicators.

[0008] Optionally, the method of performing feature extraction on the historical project data based on the timing weights and correlations respectively corresponding to the multiple project data to obtain the multiple risk indicators includes: clustering the historical project data based on the timing weights and correlations respectively corresponding to the multiple project data to obtain clustering results; performing feature extraction based on the energy benefit data indicated in the clustering results to obtain first category indicators; performing feature extraction based on the energy facility construction data indicated in the clustering results to obtain second category indicators; and obtaining the multiple risk indicators based on the first category indicators and the second category indicators.

[0009] Optionally, the method further includes: determining the storage nodes that are allowed to be read in the blockchain according to the access rights of the target type of business; and desensitizing the initial project data in the storage nodes based on the desensitization strategy of the target type of business to obtain the historical project data.

[0010] Optionally, determining the risk identification result of the target type of business based on the risk weights corresponding to the multiple risk indicators includes: obtaining the risk probabilities corresponding to the multiple risk indicators respectively from the blockchain; obtaining the indicator risk results corresponding to the multiple risk indicators respectively based on the risk weights and risk probabilities corresponding to the multiple risk indicators; and obtaining the risk identification result of the target type of business based on the indicator risk results corresponding to the multiple risk indicators respectively.

[0011] Optionally, the risk identification result of the target business is obtained based on the indicator risk results corresponding to the multiple risk indicators, including: storing the indicator risk results corresponding to the multiple risk indicators on the blockchain; when there are abnormal indicators among the multiple risk indicators whose indicator risk results are greater than a predetermined risk threshold, based on the abnormal indicators, using the smart contract in the blockchain to execute the risk identification result carrying the prompt information of the abnormal indicators to be sent to a predetermined risk monitoring terminal.

[0012] According to another aspect of an embodiment of the present application, an energy business risk determination device is provided, including: a target business determination module, which is used to determine the target business that needs to be risk assessed according to energy emission type, energy storage type, energy collaboration type, and energy hosting type; a risk indicator determination module, which is used to perform feature extraction based on historical project data of the target business and determine multiple risk indicators of the target business; a risk weight determination module, which is used to determine the risk weights corresponding to the multiple risk indicators based on the historical risk occurrence frequencies corresponding to the multiple risk indicators in the historical project data; and a risk identification result determination module, which is used to determine the risk identification result of the target business based on the risk weights corresponding to the multiple risk indicators.

[0013] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, wherein the non-volatile storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing any one of the energy business risk determination methods.

[0014] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the energy business risk determination methods.

[0015] In the embodiment of the present application, the target business that needs to be risk assessed is determined according to the energy emission type, energy storage type, energy collaboration type, and energy trusteeship type; feature extraction is performed based on the historical project data of the target business to determine multiple risk indicators of the target business; the risk weights corresponding to the multiple risk indicators are determined based on the historical risk occurrence frequencies corresponding to the multiple risk indicators in the historical project data; and the risk identification results of the target business are determined based on the risk weights corresponding to the multiple risk indicators. The purpose of accurately identifying and assessing energy business risks is achieved, the accuracy and reliability of energy business risk assessment is effectively improved, and a more scientific and detailed risk control strategy is provided to decision makers. The technical problem of unsatisfactory energy business risk assessment results existing in related technologies is solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0017] Figure 1is a flow chart of an optional energy business risk determination method provided according to an embodiment of the present application;

[0018] Figure 2 is a first schematic diagram of an optional energy business risk determination system provided according to an embodiment of the present application;

[0019] Figure 3 is a second schematic diagram of an optional energy business risk determination system provided according to an embodiment of the present application;

[0020] Figure 4 It is a schematic diagram of an optional energy business risk determination device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] According to an embodiment of the present application, a method embodiment of energy business risk determination is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] Figure 1 is a flowchart of an optional energy business risk determination method provided according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0025] Step S102, determining target businesses that require risk assessment according to energy emission type, energy storage type, energy collaboration type, and energy trusteeship type;

[0026] It can be understood that fine-grained classification of energy business according to four types, namely energy emission type, energy storage type, energy collaboration type, and energy hosting type, and determination of target businesses that require risk assessment, will help focus on the assessment object, ensure that risk analysis is closely related to business reality, and improve the practicality of risk assessment.

[0027] In an optional embodiment, target businesses that require risk assessment are determined according to energy emission types, energy collaboration types, and energy trusteeship types, including: determining the energy collaboration type as an energy complementary and collaborative business in which multiple energy sources collaborate with each other, wherein the multiple energy sources include at least electric energy, thermal energy, and fossil energy; determining the energy emission type as clean energy, and the energy storage type as a clean instant supply business of a non-energy storage type; determining the energy trusteeship type as clean energy, and the energy storage type as an electrochemical energy storage business of an energy storage type; determining the energy trusteeship type as an energy trusteeship business that uses a third-party service for energy control; and taking energy complementary and collaborative businesses, clean instant supply businesses, electrochemical energy storage businesses, and energy trusteeship businesses as target businesses.

[0028] It can be understood that energy complementary and synergistic businesses are identified, and the businesses involve the mutual cooperation of multiple energy sources such as electricity, heat and fossil energy; the energy emission type is determined to be clean energy, and the energy storage type is clarified as non-storage type clean instant supply business, and the clean instant supply business focuses on the instant supply of clean energy, such as solar energy, wind energy, etc.; electrochemical energy storage business is positioned, which is also based on clean energy, but emphasizes the use of electrochemical energy storage (such as lithium batteries); energy trusteeship business that uses third-party services for energy control is confirmed, and energy complementary and synergistic business, clean instant supply business, electrochemical energy storage business, and energy trusteeship business are targeted businesses. In-depth understanding of the risk characteristics under different business models provides a clear business scenario for subsequent risk assessment and enhances the accuracy and pertinence of the assessment.

[0029] Optionally, multi-energy complementary and coordinated supply refers to energy complementary and coordinated services. Multi-energy complementary and coordinated supply optimizes the combination of multiple energy forms such as electricity, heat, cold, and natural gas to meet the diverse needs of users, achieve efficient operation of the energy system, improve energy utilization efficiency, and reduce dependence on a single energy source, thereby enhancing the reliability and flexibility of energy supply. Distributed photovoltaic refers to clean instant supply services. As an important part of the business, distributed photovoltaic uses localized photovoltaic power generation to achieve self-generation and self-use near the user end or load center, reduce power grid transmission losses, and relieve power supply pressure during peak hours to support local consumption of green energy. Electrochemical energy storage services. Electrochemical energy storage uses battery energy storage technology to achieve peak frequency regulation and storage of electricity, provide users with flexible power regulation solutions, and balance supply and demand in the case of unstable renewable energy, thereby enhancing the emergency guarantee capability and operational stability of the entire energy system. Public energy trusteeship refers to energy trusteeship services. Public energy trusteeship provides one-stop energy management for large public facilities or parks through professional energy management services, helping users effectively reduce operating costs, optimize energy utilization efficiency, and achieve efficient integration and convenience of energy services.

[0030] Optionally, the mathematical expression for calculating the risk impact degree of the above energy complementary synergy business includes at least:

[0031] LM 违约支付 =R 计划 -R 实际

[0032] Where, LM 违约支付 Indicates the impact degree after the occurrence of “default payment risk”, R 计划 represents the planned return, R 实际 Indicates actual revenue.

[0033] LM 持续经营 =(OY 计划 -OY 实际 ) / OY 计划 *R

[0034] Where, LM 持续经营 Indicates the degree of impact after the occurrence of "going concern risk", OY 计划 Indicates the planned operating life, OY 实际 represents the actual operating years, and R represents the total revenue.

[0035] LM 工艺变化 =L 业务变化 +C 技术改造

[0036] Where, LM 工艺变化 Indicates the impact degree after the occurrence of "production process change risk", L 业务变化Indicates the loss caused by business change, C 技术改造 Represents the cost of technology upgrade and transformation.

[0037] LM 使用量偏差 =D 使用量 *P 能源

[0038] Where, LM 使用量偏差 Indicates the impact degree after the occurrence of "customer energy usage deviation risk", D 使用量 Indicates the usage deviation, P 能源 Represents energy price.

[0039] LM 期限较长 =R 计划 -R 实际 +C 新设备

[0040] Where, LM 期限较长 Indicates the impact of the "risk of a longer contract term" after it occurs, R 计划 represents the planned return, R 实际 represents the actual return, C 新设备 Represents the cost of purchasing new equipment.

[0041] LM 对象不一致 =R 计划 -R 实际

[0042] Where, LM 对象不一致 Indicates the impact degree after the occurrence of "Contract Object and Charge Object Consistency Risk", R 计划 represents the planned return, R 实际 Indicates actual revenue.

[0043] LM 收益模式 =(P 市场 -P 固定 )*Q 能源

[0044] Where, LM 收益模式 Indicates the impact degree after the occurrence of "fixed income model risk", P 市场 represents the market price, P 固定 represents a fixed price, Q 能源 Indicates energy consumption.

[0045] LM 面积争议 =A 争议 / A 总 *R

[0046] Where, LM 面积争议 Indicates the impact degree after the occurrence of “charge area dispute risk”, A 争议Indicates the disputed area, A 总 represents the total area and R represents the total revenue.

[0047] LM 远期 =(D 规划 -D 实际 )*P 能源 *RC 分摊

[0048] Where, LM 远期 Indicates the impact degree after the occurrence of "forward demand uncertainty risk", D 规划 Indicates planning function requirements, D 实际 Indicates the actual needs of customers, P 能源 represents energy price, RC 分摊 Indicates the allocation ratio coefficient.

[0049] LM 期限一致 =(OY 合同 -OY 实际 )*R 平均

[0050] Where, LM 期限一致 Indicates the impact of "risk of inconsistency between contract term and service period" after it occurs, OY 合同 Indicates the term agreed in the contract, OY 实际 represents the actual operation period, R 平均 Represents the average term return.

[0051] LM 建设内容 =C 增项

[0052] Where, LM 建设内容 Indicates the impact degree after the occurrence of "risk of inconsistency between investment and construction content and operation and maintenance content", C 增项 Indicates additional cost.

[0053] LM 电价 =△P 电 *Q 电

[0054] Where, LM 电价 is the impact degree of “the risk of electricity price fluctuation caused by environmental factors” after it occurs, △P 电 Indicates the change in electricity price, Q 电 Indicates power consumption.

[0055] LM 电力市场 =△P 电 *Q 电

[0056] In the formula, LM power market represents the impact degree after the occurrence of "risks brought by power market and development", that is, the risk of changes in power regulation strategy, △P 电 Indicates the change in electricity price, Q 电 Indicates power consumption.

[0057] LM 其他能源 =△P 其他 *Q 其他

[0058] In the formula, LM other energy represents the impact of the "risk of price changes of other energy sources other than electricity" after it occurs, that is, the risk of energy changes other than electricity, △P 其他 represents the change in other energy prices, Q 其他 Indicates other energy usage.

[0059] LM 供能 =C 增项

[0060] Where, LM 供能 Indicates the degree of impact after the occurrence of "ignoring the risk of equipment operation noise and not taking effective control measures", C 增项 Indicates additional cost.

[0061] LM 盈利 =R 计划 -R 实际

[0062] Where, LM 盈利 It indicates the degree of impact after the occurrence of the risk of "exaggerating equipment performance or energy-saving transformation effects and deviating from the actual operating level", R 计划 represents the planned return, R 实际 Indicates actual revenue.

[0063] LM 罚款 =ADV 工程

[0064] Where, LM 罚款 It is expressed as the degree of impact after the occurrence of "the risk of delay in construction progress leading to failure to complete on schedule", ADV 工程 Represents the advance payment in project costs.

[0065] LM 安全 =Es

[0066] Where, LM 安全 It represents the degree of impact after the occurrence of “construction safety accident risk”, and Es represents special expenses.

[0067] LM 运行期 =Es

[0068] LM 运行期It indicates the degree of impact after the occurrence of "safety accidents and risks of energy supply failure", and Es indicates special expenses.

[0069] LM 事故 =Es

[0070] Where, LM 事故 It represents the degree of impact after the occurrence of "gas leakage and other safety accident risks", and Es represents special expenses.

[0071] LM 设备 =C 增项

[0072] Where, LM 设备 Indicates the degree of impact after the "equipment or system performance does not meet the expected risk" occurs, C 增项 Indicates additional cost.

[0073] LM 项目收益 =C 实际 -C 预期

[0074] Where, LM 项目收益 Indicates the impact degree after the occurrence of "risk of main equipment and main material unit price deviating from the actual market price level", C 实际 Indicates the actual cost, C 预期 Indicates the expected cost.

[0075] LM 收益预期 =C 额外运维

[0076] Where, LM 收益预期 Indicates the degree of impact after the occurrence of "unreasonable reservation of operation and maintenance fees in the early stage and the risk of new expenditure items during the operation period", C 额外运维 Indicates additional operation and maintenance costs.

[0077] LM 能耗超标 =(E 实际 -E 预期 )*P 能源

[0078] Where, LM 能耗超标 It indicates the impact degree after the occurrence of "the risk of actual energy consumption during operation exceeding the expected energy consumption in the feasibility study", Eactual indicates the actual energy consumption, E 预期 represents the expected energy consumption, P 能源 Represents energy price.

[0079] Optionally, the mathematical expression for calculating the impact of the clean instant supply business can be: a mathematical expression for the impact of the investment risk of distributed photovoltaic projects, that is, a mathematical expression for calculating the impact of the clean instant supply business:

[0080] LM估算不准 =(RA 预期 -RA 实际 )*CA 装机 *h*(P 电 -P 上网 )

[0081] Where, LM 估算不准 It indicates the degree of impact after the occurrence of "inaccurate estimation risk caused by insufficient feasibility study demonstration". Insufficient feasibility study demonstration means that the historical data is less than the expected data amount. 预期 represents the expected absorption rate, RA 实际 Indicates the actual consumption rate, CA 装机 represents installed capacity, h represents annual utilization hours, P 电 represents the electricity price, P 上网 Indicates the on-grid electricity price.

[0082] LM 负偏差 =CA 装机 *h*R 效率 *R 偏差 *P 电

[0083] Where, LM 负偏差 Indicates the degree of impact after the occurrence of "the risk of insufficient feasibility study leading to actual power generation lower than the feasibility study level", CA 装机 represents installed capacity, h represents annual utilization hours, R 效率 Represents power generation efficiency, R 偏差 Indicates power generation deviation.

[0084] LM 屋面 =CA 装机 *P 单价

[0085] Where, LM 屋面 Indicates the degree of impact after the occurrence of "roof load-bearing capacity deficiency and water leakage risk", CA 装机 Indicates installed capacity, P 单价 Represents the cost per unit area.

[0086] LM 分时电价 =△P 电 *CA 装机 *h*R 效率

[0087] Where, LM 分时电价 It indicates the degree of impact after the occurrence of "the risk of time-of-use electricity price adjustment or the change of general industrial and commercial users from a single system to a two-part system", △P 电 represents the electricity price difference, CA 装机 represents installed capacity, h represents annual utilization hours, R 效率 Indicates power generation efficiency.

[0088] LM 绿电 =△P 绿电 *CA 装机 *h*R 效率

[0089] Where, LM 绿电 Indicates the impact degree after the occurrence of "green electricity regulation change risk", △P 绿电 represents the green electricity price difference, CA 装机 represents installed capacity, h represents annual utilization hours, R 效率 Indicates power generation efficiency.

[0090] LM 业主破产 =(P 电 -P 上网 )*CA 装机 *h

[0091] Where, LM 业主破产 It indicates the impact degree after the occurrence of "the risk that the new owner will not cooperate in signing a new contract after the owner goes bankrupt or sells the assets", P 电 represents the electricity price, P 上网 Indicates the on-grid electricity price, CA 装机 represents installed capacity, and h represents annual utilization hours.

[0092] LM 屋面处置 =P 电 *CA 装机 *h*R 效率

[0093] Where, LM 屋面处置 Indicates the degree of impact after the occurrence of "roof disposal right risk", CA 装机 represents installed capacity, h represents annual utilization hours, P 电 represents the electricity price, R 效率 Indicates power generation efficiency.

[0094] LM 工期 =(TO 预期 -TO 实际 )*R 单位年限

[0095] Where, LM 工期 Indicates the degree of impact after the occurrence of "construction delay risk", TO 预期 Indicates the expected operating time, TO 实际 Indicates the actual operation time, R 单位年限 Represents the income per unit year.

[0096] LM 发电 =P 电 *CA 装机 *h*R运营效率

[0097] Where, LM 发电 Indicates the degree of impact after the occurrence of "the risk of power generation loss caused by equipment operation not meeting expectations", P 电 Indicates the electricity price, CA 装机 represents installed capacity, h represents annual utilization hours, R 运营效率 Indicates the power generation efficiency during the operation period.

[0098] LM 设备 =CA 装机 *h*P 电

[0099] Where, LM 设备 Indicates the impact degree after the occurrence of "equipment handling dispute risk", P 电 For electricity prices, CA 装机 represents installed capacity, and h represents annual utilization hours.

[0100] Optionally, the mathematical expression for calculating the impact degree of the electrochemical energy storage business at least includes:

[0101] Mathematical expression for the impact of investment risk on electrochemical (lithium iron phosphate) energy storage projects:

[0102] LM 容量租赁 =Rre*P 出租 *CA 装机 *h

[0103] Where, LM 容量租赁 It indicates the impact degree after the occurrence of “capacity leasing income risk”, Rre indicates the occupancy rate, P 出租 Indicates rental price, CA 装机 represents installed capacity, and h represents annual utilization hours.

[0104] LM 电量回收 =P 能源 *CA 装机 *R 效率 *h

[0105] Where, LM 电量回收 Indicates the impact of “the risk of revenue from wind and solar power recovery and additional power generation after storage” after the occurrence of 回收 Indicates the change in recovery volume. 能源 represents the energy price, and h represents the annual utilization hours.

[0106] LM 参数 =(η 预计 -η 实际 ) / η 预计 *R 预计

[0107] Where, LM 参数 Indicates the impact degree after the occurrence of “key operating parameter value risk”, η 预计 represents the expected system efficiency, η 实际 Indicates the actual system efficiency, R 预计 Indicates expected revenue.

[0108] LM 电费 =CA 装机 *h*P 容量

[0109] Where, LM 电费 Indicates the impact degree after the occurrence of "capacity electricity fee risk", CA 装机 represents installed capacity, h represents power generation duration, P 容量 Indicates capacity electricity price.

[0110] LM 资产处置 =P 电池回收 *CA 装机

[0111] Where, LM 资产处置 Indicates the degree of impact after the occurrence of “asset disposal compliance risk”, P 电池回收 Indicates the battery recycling price, CA 装机 Indicates installed capacity.

[0112] LM 残值 =P 单位 *CA 装机 *R 残值 *TR

[0113] Where, LM 残值 Indicates the impact of the "risk of residual value tax" after it occurs, P 单位 Indicates unit cost, CA 装机 represents installed capacity, TR represents tax rate, R 残值 Represents the residual value ratio.

[0114] LM 峰谷差 =△X 峰谷 *CA 装机 *h*η 预计

[0115] Where, LM 峰谷差 Indicates the impact degree after the occurrence of "electricity price peak-to-valley difference risk", △X 峰谷 Indicates the change in peak-to-valley difference, CA 装机 represents installed capacity, h represents annual utilization hours, η 预计 Indicates the expected system efficiency.

[0116] LM 峰谷调整 =△Q充放 *CA 装机 *h*η 预计 *P 电

[0117] Where, LM 峰谷调整 Indicates the impact degree after the occurrence of "peak-valley period adjustment risk", △Q 充放 Indicates the change in charge and discharge times, CA 装机 represents installed capacity, h represents annual utilization hours, η 预计 Indicates the expected system efficiency.

[0118] LM 电力市场 =P 现货 *CA 装机 *h

[0119] Where, LM 电力市场 Indicates the impact degree after the occurrence of “power regulation strategy change risk”, P 现货 represents the spot market electricity price, CA 装机 represents installed capacity, and h represents annual utilization hours.

[0120] LM 超温 =CA 装机 *D 超温 *T 充放电 *R 效率

[0121] Where, LM 超温 Indicates the impact degree after the occurrence of "over-temperature risk of major equipment operation", CA 装机 Indicates installed capacity, D 超温 Indicates the number of days with overtemperature, T 充放电 Indicates the number of charge and discharge times per day, R 效率 Indicates the charge and discharge efficiency.

[0122] LM 储能设备 =CA 装机 *h*P 电

[0123] Where, LM 储能设备 Indicates the impact of the "energy storage equipment price fluctuation risk" after it occurs, CA 装机 represents installed capacity, h represents annual utilization hours, P 电 Indicates the electricity price.

[0124] LM 运维 =CA 装机 *h*P 电

[0125] Where, LM 运维 Indicates the impact of "unclear division of operation and maintenance responsibilities or unreasonable risks" after the occurrence of CA装机 represents installed capacity, h represents annual utilization hours, P 电 Indicates the electricity price.

[0126] Optionally, the mathematical expression for calculating the impact of the above energy trusteeship business (i.e., public institution energy trusteeship business) includes at least:

[0127] Mathematical expression for the impact of investment risk on public institution energy trusteeship business:

[0128] LM 能耗 =(Q 实际 -Q 预期 )*P 电

[0129] Where, LM 能耗 Q is the impact degree after the occurrence of “energy consumption base risk”, 实际 is the actual consumption, Q 预期 represents the expected consumption, P 电 Indicates the electricity price.

[0130] LM 其他能源 =△P 其他 *Q 其他

[0131] Where, LM 其他能源 Indicates the impact of "water, gas and other energy price risks" after they occur, △P 其他 represents the change in other energy prices, Q 其他 Indicates other energy usage.

[0132] LM 费用托管 =(P 市场 -P 包干 )*Q 能源

[0133] Where, LM 费用托管 Indicates the impact degree after the occurrence of “energy cost trusteeship model risk”, P 市场 represents the market price, P 包干 Indicates the lump sum price, Q 能源 Indicates energy consumption.

[0134] LM 消耗托管 =(Q 实际 -Q 预期 )*P 市场

[0135] Where, LM 消耗托管 Indicates the impact of the "energy consumption management risk" after it occurs, Q 实际 Indicates the actual consumption, Q 预期 represents the expected consumption, P 市场Indicates market price.

[0136] LM 合同期限 =(T 合同 -T 实际 )*R 预期

[0137] Where, LM 合同期限 Indicates the impact degree after the occurrence of “contract term risk”, T 合同 Indicates the trusteeship period specified in the contract, T 实际 Indicates the actual age, R 预期 Represents expected return.

[0138] LM 电价 =△P 电 *Q 电

[0139] Where, LM 电价 Indicates the degree of impact after the occurrence of "electricity price fluctuation risk", △P 电 Indicates the change in electricity price, Q 电 Indicates power consumption.

[0140] LM 电力市场 =△P 电 *Q 电

[0141] Where, LM 电力市场表示 The impact degree after the occurrence of "future electricity market price change risk", △P 电 Indicates the change in electricity price, Q 电 Indicates power consumption.

[0142] LM 节能率 =C 托管扣款

[0143] Where, LM 节能率 Indicates the impact degree after the occurrence of the risk that the predetermined energy saving rate or energy saving amount index cannot be achieved, C 托管扣款 Represents the hosting fee deducted as a penalty.

[0144] LM 工期 =C 预支

[0145] Where, LM 工期 Indicates the impact degree after the occurrence of "construction period risk", C 预支 Represents the advance payment in project costs.

[0146] LM 施工 =C 专项

[0147] Where, LM 施工Indicates the impact degree after the occurrence of “construction safety risk”, C 专项 Indicates special expenses.

[0148] LM 运行 =C 专项

[0149] Where, LM 运行 Indicates the impact degree after the occurrence of “operational safety risk”, C 专项 Indicates special expenses.

[0150] LM 超标 =(E 实际 -E 预期 )*P 能源

[0151] Where, LM 超标 is the impact degree after the occurrence of “annual energy consumption exceeding standard risk”, E 实际 is the actual energy consumption, E 预期 represents the expected energy consumption, P 能源 Represents energy price.

[0152] LM 提前消耗 =(EGR 实际 -EGR 分摊 )*BV 能耗 *P 能源

[0153] Where, LM 提前消耗 Indicates the degree of impact after the occurrence of "risk of early profit and late loss due to the amortization of energy consumption growth", EGR 实际 Indicates the actual energy consumption growth rate, EGR 分摊 Indicates the growth rate of energy consumption, BV 能耗 Represents the energy consumption base, P 能源 Represents energy price.

[0154] LM 造价 =C 实际 -C 预期

[0155] Where, LM 造价 Indicates the impact degree after the occurrence of "risk of material and equipment prices deviating from the actual market level", C 实际 Indicates the actual cost, C 预期 Indicates the expected cost.

[0156] Step S104, extracting features based on historical project data of the target business to determine multiple risk indicators of the target business;

[0157] It can be understood that the target business is identified, its historical project data is deeply analyzed, and multiple risk indicators closely related to the business type are extracted through feature extraction technology. Data-driven feature extraction aims to screen out the most representative and influential features from massive project data to provide data support for the construction of risk assessment models.

[0158] Optionally, based on historical data, the probability of occurrence of various risk factors can be objectively calculated. Specifically, the probability of occurrence of risk factors can be calculated by statistically analyzing the frequency of historical data. The specific mathematical expression is as follows:

[0159] Probability of risk factor occurrence = frequency of occurrence of the risk factor in historical projects / total number of historical projects * 100%

[0160] In an optional embodiment, feature extraction is performed based on historical project data of the target type of business to determine multiple risk indicators of the target type of business, including: determining, in chronological order, the time series weights corresponding to the multiple project data included in the historical project data; determining the correlation between the multiple project data; and extracting features from the historical project data based on the time series weights and correlations corresponding to the multiple project data to obtain multiple risk indicators.

[0161] It can be understood that the historical project data is assigned time series weights in chronological order and the correlation between project data is calculated. By setting time series weights, it is ensured that recent project data has a greater impact on the determination of risk indicators, and recent project data can better reflect the current market and technical environment. At the same time, the analysis of correlation helps to identify the interaction between different project data and reveal the inherent connection between risk factors.

[0162] In an optional embodiment, based on the time series weights and correlations respectively corresponding to the multiple project data, feature extraction is performed on the historical project data to obtain multiple risk indicators, including: based on the time series weights and correlations respectively corresponding to the multiple project data, the historical project data is clustered to obtain clustering results; based on the energy revenue data indicated in the clustering results, feature extraction is performed to obtain first-category indicators; based on the energy facility construction data indicated in the clustering results, feature extraction is performed to obtain second-category indicators; based on the first-category indicators and the second-category indicators, multiple risk indicators are obtained.

[0163] It can be understood that cluster analysis is performed based on the time series weights and mutual correlations of historical project data, and project data with similar characteristics are grouped together, revealing the common patterns of different types of business risks. Subsequently, energy revenue data is separated from the clustering results, and the volatility and uncertainty of these data are deeply analyzed to extract the first type of indicators. The second type of indicators are obtained by extracting the features of energy facility construction data. Finally, these two types of indicators are considered comprehensively to form a comprehensive risk indicator system for evaluating the potential risks of target businesses. Cluster analysis enhances the systematicness and accuracy of feature extraction, makes risk indicators more in line with business reality, improves the effect of risk assessment, and provides strong support for energy investment decisions.

[0164] In an optional embodiment, the method further includes: determining the storage nodes that are allowed to be read in the blockchain according to the access rights of the target type of business; and desensitizing the initial project data in the storage node based on the desensitization strategy of the target type of business to obtain historical project data.

[0165] It can be understood that the access rights of target businesses are managed through blockchain technology, the reading rights of data are determined, and only authorized storage nodes can access relevant project data. At the same time, the desensitization strategy is applied to process the initial project data in the storage node to eliminate sensitive information and protect data privacy. The data access control and privacy protection mechanism maintains the security and compliance of data, promotes the effective sharing of data under the premise of protecting privacy, and provides a rich and secure data foundation for risk assessment.

[0166] Step S106, determining risk weights corresponding to the multiple risk indicators according to the historical risk occurrence frequencies corresponding to the multiple risk indicators in the historical project data;

[0167] It can be understood that by analyzing the historical risk occurrence frequency of multiple risk indicators in historical project data, the risk weight of each risk indicator is determined. The historical risk occurrence frequency reflects the actual frequency of each risk indicator in past projects. It is an important quantitative indicator of risk probability, which enhances the reality and pertinence of the risk assessment model and improves the accuracy of risk prediction.

[0168] Step S108: determining the risk identification result of the target business based on the risk weights corresponding to the multiple risk indicators.

[0169] It can be understood that based on the risk weights corresponding to multiple risk indicators, the overall risk level of the target business is comprehensively analyzed and calculated to obtain the risk identification results. Quantifying the risk and integrating the impact of different risk indicators into a comprehensive risk identification framework through weighted average or other statistical methods provides a deeper understanding of the business risk situation, helping decision makers to prioritize and manage those risks with higher weights among many possible risks, effectively optimizing resource allocation and reducing potential losses.

[0170] Alternatively, the rational quantification and assessment of various risks is the key to ensuring business sustainability and effective management. The mathematical expression for comprehensive energy business risk assessment is as follows:

[0171] R i =P i ×LM i

[0172] Among them, R i Represents the risk value of a specific risk indicator, that is, the risk result of the target business, P i is the probability of the risk occurring, LM i The impact of the risk on the business, that is, the parameter marked with LM above.

[0173] Each comprehensive energy business risk factor needs to be quantitatively analyzed in combination with the actual business scenario when calculating. First, for each risk indicator, determine its probability of occurrence P i Secondly, the impact level LM i It represents the actual impact (loss) on the integrated energy business once the risk occurs.

[0174] The risks faced by integrated energy business often cover multiple aspects. Therefore, when conducting risk assessment, it is necessary to list these risks one by one and calculate the specific risk value R for each risk. i The comprehensive risk level of the integrated energy business can be calculated by the following formula:

[0175]

[0176] Among them, R total is the comprehensive risk level of the integrated energy business, which is obtained by adding up the risk values ​​of all risk factors; n is the number of risk factors included in the integrated energy business.

[0177] In an optional embodiment, based on the risk weights corresponding to multiple risk indicators, the risk identification result of the target type of business is determined, including: obtaining the risk probabilities corresponding to the multiple risk indicators from the blockchain; based on the risk weights and risk probabilities corresponding to the multiple risk indicators, obtaining the indicator risk results corresponding to the multiple risk indicators; based on the indicator risk results corresponding to the multiple risk indicators, obtaining the risk identification result of the target type of business.

[0178] It can be understood that the risk probabilities corresponding to multiple risk indicators are obtained through blockchain technology, which ensures the immutability and transparency of data and improves the security and reliability of information. Then, using risk weights and risk probabilities, the indicator risk results of each risk indicator are obtained through weighted calculation, and the potential impact of each risk is quantified, making the description of risk more specific and intuitive. Finally, all indicator risk results are integrated to form the risk identification results of the target business. The fairness of the evaluation process and the authority of the data are guaranteed by blockchain, which greatly improves the efficiency and decision-making quality of energy business risk management.

[0179] In an optional embodiment, based on the indicator risk results corresponding to multiple risk indicators, a risk identification result of the target business is obtained, including: in the blockchain, the indicator risk results corresponding to the multiple risk indicators are stored on the chain; when there are abnormal indicators in the multiple risk indicators whose indicator risk results are greater than a predetermined risk threshold, based on the abnormal indicators, the smart contract in the blockchain is used to execute the risk identification result carrying the prompt information of the abnormal indicator to the predetermined risk monitoring terminal.

[0180] It can be understood that, first of all, the risk results based on multiple risk indicators are stored on the chain to ensure the security and immutability of the data. At the same time, the distributed ledger characteristics of the blockchain are used to achieve transparent sharing of risk results and enhance the trust basis for multi-party collaboration. Focusing on the monitoring of abnormal indicators, that is, when the risk result of a certain risk indicator exceeds the predetermined risk threshold, the smart contract mechanism in the blockchain is automatically triggered to send a prompt message containing the details of the abnormal indicator to the predetermined risk monitoring terminal, realizing the automation and immediacy of risk warning, and improving the response speed and management efficiency.

[0181] Through the above step S102, the target business that needs to be risk assessed is determined according to the energy emission type, energy storage type, energy collaboration type, and energy trusteeship type; step S104, feature extraction is performed based on the historical project data of the target business to determine multiple risk indicators of the target business; step S106, based on the historical risk occurrence frequency corresponding to the multiple risk indicators in the historical project data, the risk weights corresponding to the multiple risk indicators are determined; step S108, based on the risk weights corresponding to the multiple risk indicators, the risk identification result of the target business is determined, which can achieve the purpose of accurately identifying and assessing the risks of the energy business, and effectively improve the accuracy and reliability of the risk assessment of the energy business, and provide decision makers with a more scientific and detailed risk control strategy. The technical effect solves the technical problem of unsatisfactory risk assessment effect of energy business existing in related technologies.

[0182] Based on the above embodiments and optional embodiments, the present application proposes an optional implementation manner.

[0183] In step S1, it can be understood that energy services are finely classified according to the four types of energy emission, storage, collaboration and hosting, and the target type of business that needs to be risk assessed is determined. This process helps to accurately focus on the assessment object, ensure that risk analysis is closely related to business reality, and improve the practicality of risk assessment.

[0184] Optionally, multi-energy complementary and coordinated supply refers to energy complementary and coordinated services. Multi-energy complementary and coordinated supply optimizes the combination of multiple energy forms such as electricity, heat, cold, and natural gas to meet the diverse needs of users, achieve efficient operation of the energy system, improve energy utilization efficiency, and reduce dependence on a single energy source, thereby enhancing the reliability and flexibility of energy supply. Distributed photovoltaic refers to clean instant supply services. As an important part of the business, distributed photovoltaic uses localized photovoltaic power generation to achieve self-generation and self-use near the user end or load center, reduce power grid transmission losses, and relieve power supply pressure during peak hours to support local consumption of green energy. Electrochemical energy storage refers to electrochemical energy storage services. Electrochemical energy storage uses battery energy storage technology to achieve peak frequency regulation and storage of electricity, provide users with flexible power regulation solutions, and balance supply and demand in the case of unstable renewable energy, thereby enhancing the emergency guarantee capability and operational stability of the entire energy system. Public energy trusteeship refers to energy trusteeship services. Public energy trusteeship provides one-stop energy management for large public facilities or parks through professional energy management services, helping users effectively reduce operating costs, optimize energy utilization efficiency, and achieve efficient integration and convenience of energy services.

[0185] Step S2, determine the target business, deeply analyze its historical project data, and extract multiple risk indicators closely related to the business type through feature extraction technology. Data-driven feature extraction aims to screen out the most representative and influential features from massive project data to provide data support for the construction of risk assessment models.

[0186] Step S3, by analyzing the historical risk occurrence frequency of multiple risk indicators in the historical project data, determine the risk weight of each risk indicator. The historical risk occurrence frequency reflects the actual frequency of each risk indicator in past projects, and is an important quantitative indicator of risk probability, which enhances the reality and pertinence of the risk assessment model and improves the accuracy of risk prediction.

[0187] Step S4, based on the risk weights corresponding to multiple risk indicators, comprehensively analyze and calculate the overall risk level of the target business, thereby obtaining the risk identification result. Quantifying the risk, integrating the impact of different risk indicators into a comprehensive risk identification framework through weighted average or other statistical methods, provides a deeper understanding of the business risk situation, helps decision makers prioritize and manage those risks with higher weights among many possible risks, effectively optimizes resource allocation, and reduces potential losses.

[0188] Figure 2 is a first schematic diagram of an optional energy business risk determination system provided according to an embodiment of the present application, such as Figure 2 As shown in Figure 1, the risk matrix is ​​a visualization tool that takes into account the probability and impact of risks, usually in the form of a matrix graphic. This tool helps to classify different risks into low, medium, and high risks, allowing decision makers to quickly understand the relative importance of risks. The probability of a risk refers to the likelihood of a specific risk event occurring, usually expressed as a percentage, probability score, or descriptive terms such as low, medium, and high. The assessment of probability is the basis of risk assessment, which helps to determine which risks are more likely to occur and which risks are less likely. The impact of a risk refers to the negative impact or loss that may occur to a project or system after a risk event occurs. These impacts can include financial losses, reputation damage, casualties, waste of resources, production interruptions, etc. The impact of a risk is usually manifested from multiple dimensions such as operations, environment, and society. Understanding the impact of a risk helps determine the importance and urgency of the risk. The impact of different risks may vary due to their nature and degree, and need to be considered comprehensively. Figure 2 The letters next to the circular mark, such as A, B, D, etc., are only schematic symbols of different risks.

[0189] Figure 3 is a second schematic diagram of an optional energy business risk determination system provided according to an embodiment of the present application, such as Figure 3As shown in the figure, a comprehensive energy project investment risk matrix diagram uses oblique lines and vertical lines to represent different risk levels, and the risk levels are from low to high: the lower left blank part < the upper left and lower right oblique lines < the upper right vertical lines, "1" represents the risk of default payment; "2" represents the risk of sustainable operating ability; "3" represents the risk of production process changes; "4" represents the risk of customer energy usage deviation; "5" represents the risk of a long contract term; "6" represents the risk of consistency between the contract object and the charging object; "7" represents the risk of a fixed income model; "8" represents the risk of disputes over the charging area; "9" represents the risk of uncertainty in future demand; "10" represents the inconsistency between the contract term and the service period; "11" represents the inconsistency between the investment and construction content and the operation and maintenance content. "12" indicates the risk of electricity price fluctuations; "13" indicates the risk of changes in macro electricity prices; "14" indicates the risk brought about by the development of the electricity market; "15" indicates the prices of energy sources other than electricity; "16" indicates the reduction or cancellation of standards; "17" indicates the risk of energy supply security and noise; "18" indicates the risk of profit falling short of expectations; "19" indicates the risk of fines or contract termination; "20" indicates the risk of safety accidents; "21" indicates the risk of safety accidents and failure to supply energy; "22" indicates the risk of safety accidents; "23" indicates the risk of equipment or system performance not meeting expectations; "24" indicates the risk of project returns; "25" indicates the risk of project returns falling short of expectations; "26" indicates the risk of excessive energy consumption.

[0190] The above optional implementation methods achieve at least the following effects: the secure storage and transparent sharing of risk data are enhanced through blockchain technology, and the instant automatic early warning of abnormal risk indicators is realized by combining smart contracts, which significantly improves the efficiency and accuracy of risk identification and management, and provides solid technical support for energy business investment decisions. At the same time, it optimizes the trust mechanism in cross-organizational collaboration, promotes the fairness and authority of risk assessment results, effectively reduces the decision-making risks caused by information delays or misjudgments, and ensures the stable operation and sustainable development of the business.

[0191] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0192] In this embodiment, an energy business risk determination device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the terms "module" and "device" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0193] According to an embodiment of the present application, there is also provided an apparatus embodiment for implementing the energy business risk determination method. Figure 4 is a schematic diagram of an energy business risk determination device according to an embodiment of the present application, such as Figure 4 As shown, the energy business risk determination device includes a target business determination module 402, a risk indicator determination module 404, a risk weight determination module 406, and an identification result determination module 408. The device is described below.

[0194] The target business determination module 402 is used to determine the target business that needs to be risk assessed according to the energy emission type, energy storage type, energy collaboration type, and energy trusteeship type;

[0195] The risk indicator determination module 404 is connected to the target business determination module 402 and is used to perform feature extraction based on the historical project data of the target business to determine multiple risk indicators of the target business;

[0196] The risk weight determination module 406 is connected to the risk indicator determination module 404 and is used to determine the risk weights corresponding to the multiple risk indicators according to the historical risk occurrence frequencies respectively corresponding to the multiple risk indicators in the historical project data;

[0197] The identification result determination module 408 is connected to the risk weight determination module 406 and is used to determine the risk identification result of the target business based on the risk weights corresponding to the multiple risk indicators.

[0198] In an energy business risk determination device provided by an embodiment of the present application, a target business determination module 402 is set to determine the target business that needs to be risk assessed according to the energy emission type, energy storage type, energy collaboration type, and energy trusteeship type; a risk indicator determination module 404 is connected to the target business determination module 402, and is used to extract features based on the historical project data of the target business to determine multiple risk indicators of the target business; a risk weight determination module 406 is connected to the risk indicator determination module 404, and is used to determine the risk weights corresponding to multiple risk indicators according to the historical risk occurrence frequency corresponding to multiple risk indicators in the historical project data; an identification result determination module 408 is connected to the risk weight determination module 406, and is used to determine the risk identification result of the target business based on the risk weights corresponding to multiple risk indicators. The purpose of accurately identifying and evaluating energy business risks is achieved, the accuracy and reliability of energy business risk assessment are effectively improved, and a more scientific and detailed risk control strategy is provided to decision makers. The technical effect solves the technical problem of unsatisfactory energy business risk assessment effect existing in the related technology.

[0199] It should be noted that the above modules can be implemented by software or hardware. For example, for the latter, it can be implemented in the following ways: the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0200] It should be noted that the above target business determination module 402, risk indicator determination module 404, risk weight determination module 406, and identification result determination module 408 correspond to steps S102 to S108 in the embodiment, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments. It should be noted that the above modules can be run in a computer terminal as part of the device.

[0201] It should be noted that the optional or preferred implementation of this embodiment can refer to the relevant description in the embodiment, which will not be repeated here.

[0202] The above-mentioned energy business risk determination device may also include a processor and a memory. The target business determination module 402, the risk indicator determination module 404, the risk weight determination module 406, the identification result determination module 408, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0203] The processor includes a kernel, which retrieves the corresponding program unit from the memory. There can be one or more kernels. The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0204] An embodiment of the present application provides a non-volatile storage medium having a program stored thereon, which implements an energy business risk determination method when executed by a processor.

[0205] The embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and can be run on the processor. When the processor executes the program, the following steps are implemented: according to the energy emission type, energy storage type, energy collaboration type, and energy trusteeship type, determine the target type of business that needs to be risk assessed; extract features based on the historical project data of the target type of business to determine multiple risk indicators of the target type of business; determine the risk weights corresponding to the multiple risk indicators based on the historical risk occurrence frequencies corresponding to the multiple risk indicators in the historical project data; determine the risk identification results of the target type of business based on the risk weights corresponding to the multiple risk indicators. The device in this article can be a server, a PC, etc.

[0206] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: determining the target type of business that needs to be risk assessed according to the energy emission type, energy storage type, energy collaboration type, and energy hosting type; performing feature extraction based on the historical project data of the target type of business to determine multiple risk indicators of the target type of business; determining the risk weights corresponding to the multiple risk indicators based on the historical risk occurrence frequencies corresponding to the multiple risk indicators in the historical project data; and determining the risk identification results of the target type of business based on the risk weights corresponding to the multiple risk indicators.

[0207] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0208] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0209] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0210] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0211] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0212] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0213] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0214] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0215] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0216] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining energy business risk, characterized in that: include: Determine the target businesses that require risk assessment according to energy emission type, energy storage type, energy collaboration type, and energy hosting type; Extracting features based on historical project data of the target business to determine multiple risk indicators of the target business; Determining risk weights corresponding to the multiple risk indicators according to the historical risk occurrence frequencies respectively corresponding to the multiple risk indicators in the historical project data; Based on the risk weights corresponding to the multiple risk indicators, a risk identification result of the target type of business is determined.

2. The method according to claim 1, characterized in that The target businesses that require risk assessment are determined according to energy emission types, energy collaboration types, and energy trusteeship types, including: Determining that the energy collaboration type is an energy complementary collaboration business in which multiple energy sources collaborate with each other, wherein the multiple energy sources include at least electric energy, thermal energy, and fossil energy; Determine that the energy emission type is clean energy, and the energy storage type is a clean instant supply business of non-energy storage type; Determining that the energy hosting type is clean energy, and the energy storage type is an electrochemical energy storage business of energy storage type; Determining that the energy trusteeship type is an energy trusteeship business that uses third-party services to control energy; The energy complementary and collaborative business, the clean instant supply business, the electrochemical energy storage business, and the energy trusteeship business are taken as the target business.

3. The method according to claim 1, characterized in that The feature extraction based on the historical project data of the target business to determine multiple risk indicators of the target business includes: Determine, in chronological order, time sequence weights corresponding to the plurality of project data included in the historical project data; Determining the degree of association between the plurality of project data; Based on the time series weights and correlations respectively corresponding to the plurality of project data, feature extraction is performed on the historical project data to obtain the plurality of risk indicators.

4. The method according to claim 3, characterized in that: The extracting features of the historical project data based on the time series weights and correlations respectively corresponding to the plurality of project data to obtain the plurality of risk indicators includes: Clustering the historical project data based on the time series weights and correlations respectively corresponding to the plurality of project data to obtain a clustering result; Performing feature extraction based on the energy benefit data indicated in the clustering result to obtain a first category of indicators; Extracting features based on the energy facility construction data indicated in the clustering results to obtain a second type of indicator; Based on the first category of indicators and the second category of indicators, the multiple risk indicators are obtained.

5. The method according to claim 1, characterized in that The method further comprises: According to the access rights of the target business, determine the storage nodes that are allowed to read in the blockchain; Based on the desensitization strategy of the target type of business, the initial project data in the storage node is desensitized to obtain the historical project data.

6. The method according to any one of claims 1 to 5, characterized in that The determining the risk identification result of the target business based on the risk weights corresponding to the multiple risk indicators includes: Obtaining risk probabilities corresponding to the multiple risk indicators respectively from the blockchain; Based on the risk weights and risk probabilities corresponding to the multiple risk indicators, obtaining indicator risk results corresponding to the multiple risk indicators respectively; Based on the indicator risk results respectively corresponding to the multiple risk indicators, a risk identification result of the target type of business is obtained.

7. The method according to claim 5, characterized in that The risk identification result of the target business is obtained based on the indicator risk results respectively corresponding to the multiple risk indicators, including: In the blockchain, the indicator risk results corresponding to the multiple risk indicators are stored on the blockchain; In the case that there is an abnormal indicator among the multiple risk indicators whose indicator risk result is greater than a predetermined risk threshold, based on the abnormal indicator, the smart contract in the blockchain is used to execute the risk identification result carrying the prompt information of the abnormal indicator to be sent to the predetermined risk monitoring terminal.

8. An energy business risk determination device, characterized in that: include: A module for determining target business types, which is used to determine target business types that require risk assessment according to energy emission types, energy storage types, energy collaboration types, and energy trusteeship types; A risk indicator determination module, configured to perform feature extraction based on historical project data of the target business and determine a plurality of risk indicators of the target business; A risk weight determination module is used to determine the risk weights corresponding to the multiple risk indicators in the historical project data according to the historical risk occurrence frequencies respectively corresponding to the multiple risk indicators; The risk identification result determination module is used to determine the risk identification result of the target type of business based on the risk weights corresponding to the multiple risk indicators.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the energy business risk determination method described in any one of claims 1 to 7.

10. An electronic device, characterized in that: include: One or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the energy business risk determination method described in any one of claims 1 to 7.

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