Carbon quota based generation scheduling method for wind, solar, hydro and thermal power systems

Abstract

The application relates to the technical field of low-carbon scheduling of a wind-solar-hydro-thermal system, and provides a wind-solar-hydro-thermal system generation plan scheduling method based on carbon quotas. The method comprises the following steps: based on annual carbon quotas of the current year, monthly carbon quotas and daily carbon quotas of the current year are determined; based on the monthly carbon quotas of the current year, operation parameters of generation resources, an electricity abandonment penalty price and an excess carbon penalty price, monthly generation plans of the current year are determined; based on the monthly generation plans of the current year, daily carbon quotas of the current year, operation parameters of the generation resources, the electricity abandonment penalty price, the excess carbon penalty price and day-ahead predicted generation resources output, daily generation plans of the current year are determined; and the wind-solar-hydro-thermal system generation plan scheduling based on the carbon quotas is controlled according to the daily generation plans of the current year. The wind-solar-hydro-thermal system generation plan scheduling method based on the carbon quotas can effectively improve the operation optimality of the wind-solar-hydro-thermal system on the basis of realizing total carbon emission control.

Description

Technical Field

[0001] This application relates to the field of low-carbon dispatching technology for wind, solar, hydro, and thermal power systems, and in particular to a method for scheduling power generation plans for wind, solar, hydro, and thermal power systems based on carbon quotas. Background Technology

[0002] In recent years, my country's electricity demand has continued to grow, and new energy sources such as wind power and photovoltaics have developed rapidly. However, the power generation structure is still dominated by thermal power. As of 2024, the national installed capacity of thermal power reached 1,445 gigawatts (GW), accounting for about two-fifths of the total installed capacity, and its share of power generation has long been above 60%. For a considerable period in the future, thermal power will remain my country's main power source, but its high carbon emission characteristics have become a core challenge for my country in implementing total carbon emission control.

[0003] Reference Figure 1 As shown, a wind-solar-hydro-thermal system (also known as a wind-solar-hydro-thermal system) composed of multiple power sources, including wind, solar, hydro, and thermal power, can effectively reduce the proportion of thermal power generation through coordinated and optimized output among different power sources, providing a feasible technical path for building a low-carbon wind-solar-hydro-thermal system. Carbon emission control is mostly implemented on an annual basis, with long control periods and large time spans, posing unprecedented technical challenges to wind-solar-hydro-thermal systems.

[0004] In wind, solar, hydro, and thermal power systems, hydropower offers flexible regulation capabilities, while wind and solar power rely heavily on natural weather conditions, resulting in significant uncertainty in power output and making precise control difficult. Therefore, effectively improving the operational optimization of wind, solar, hydro, and thermal power systems while achieving total carbon emission control is a pressing issue that needs to be addressed. Summary of the Invention

[0005] This application provides a carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems, which can ensure the optimal operation of these systems while achieving total carbon emission control.

[0006] This application provides a carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems, applied to electronic equipment, including the following steps: Based on the annual carbon allowance for this year, determine the monthly and daily carbon allowances for this year; based on the monthly carbon allowances for this year, the operating parameters of power generation resources, the curtailment penalty price, and the over-carbon penalty price, determine the monthly power generation plan for this year; based on the monthly power generation plan for this year, the daily carbon allowances for this year, the operating parameters of power generation resources, the curtailment penalty price, the over-carbon penalty price, and the day-ahead forecast of power generation resource output, determine the daily power generation plan for this year; and control the scheduling of wind, solar, hydro, and thermal power generation plans based on carbon allowances according to the daily power generation plans for this year.

[0007] According to a method provided in this application, the carbon allowance for each month of the year is determined, which includes m months, including: When m equals 1, the carbon allowance for the m-th month of the current year is determined based on the historical carbon emission percentage of the m-th month and the annual carbon allowance; when m is greater than 1, the carbon allowance for the m-th month is determined based on the carbon emissions of the first m-1 months of the current year and the annual carbon allowance.

[0008] According to a method provided in this application, the m-th month includes n days, determining the daily carbon allowance for the year includes: When n equals 1, the carbon allowance for the nth day of the mth month of the current year is determined based on the proportion of carbon emissions on the nth day of the mth month in history and the carbon allowance for the mth month of the current year. When n is greater than 1, the carbon allowance for the nth day of the mth month of the current year is determined based on the carbon emissions of the first n-1 days of the mth month of the current year and the carbon allowance for the mth month of the current year.

[0009] According to a method provided in this application, a monthly power generation plan is determined based on the monthly carbon allowances, operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices for the current year, including: By inputting the monthly carbon allowances, power generation resource operating parameters, curtailment penalty prices, and excess carbon penalty prices for the current year into the medium- and long-term optimization dispatch model, the monthly power generation plan for the current year can be obtained.

[0010] According to a method provided in this application, a medium- to long-term optimization scheduling model includes a first objective function and first constraints. The first objective function aims to minimize the operating cost of the wind, solar, hydro, and thermal power systems in the current year. The first constraints include at least one of the following: The first constraint on renewable energy is used to limit the monthly output of renewable energy during the current year.

[0011] The first constraint on thermal power units; the first constraint on thermal power units is used to limit the monthly operation and carbon emissions of thermal power units in the current year.

[0012] The first constraint of the hydropower unit; the first constraint of the hydropower unit is used to limit the operation of the hydropower unit each month of the current year.

[0013] The first constraint on power balance is used to define the relationship between monthly power load and power generation for the current year.

[0014] According to a method provided in this application, operating costs include fuel costs for thermal power units, curtailment penalty costs for renewable energy, and excess carbon penalty costs. The first objective function is: , , , , in, The operating costs of the wind, solar, hydro, and thermal power systems for this year. This is the fuel cost for thermal power units this year. The cost of renewable energy curtailment penalties for this year, For the cost of excessive carbon emissions this year, This refers to the number of thermal power units. , , Let be the fuel coefficient of thermal power unit i. For the output of thermal power unit i in the m-th month of this year, This refers to the installed capacity of wind turbine units. This refers to the number of photovoltaic (PV) units installed. The price of wind curtailment penalty The price for abandoning light Let i be the amount of abandoned electricity generated by wind turbine i in the m-th month of this year. Let i be the amount of electricity wasted by photovoltaic unit i in the m-th month of this year. Price penalties for excessive carbon emissions. This represents the excess carbon amount for the mth month of this year.

[0015] According to a method provided in this application, a daily power generation plan for the current year is determined based on the monthly power generation plan for the current year, the daily carbon allowance for the current year, the operating parameters of power generation resources, the curtailment penalty price, the excess carbon penalty price, and the day-ahead forecast of power generation resource output, including: By inputting the monthly power generation plan for the current year, the daily carbon quota for the current year, the operating parameters of power generation resources, the curtailment penalty price, the over-carbon penalty price, and the output of the power generation resources predicted up to the day, the daily power generation plan for the current year can be obtained.

[0016] According to a method provided in this application, a short-run optimization scheduling model includes a second objective function and a second constraint. The second objective function aims to minimize the daily operating cost of the wind, solar, hydro, and thermal power systems. The second constraint includes at least one of the following: Carbon emission limits; carbon emission limits are used to restrict daily carbon emissions.

[0017] The second constraint on renewable energy is used to limit the daily output of renewable energy.

[0018] Second constraint on thermal power units; The second constraint on thermal power units is used to limit the daily operation and carbon emissions of thermal power units.

[0019] Second constraint of hydropower unit; The second constraint of hydropower unit is used to limit the daily operation of hydropower unit.

[0020] The second constraint on power balance is used to define the relationship between daily power load and power generation.

[0021] According to a method provided in this application, operating costs include fuel costs for thermal power units, curtailment penalty costs for renewable energy, and excess carbon penalty costs. The second objective function is: , , , , in, The daily operating costs of wind, solar, hydro, and thermal power systems, For the daily fuel cost of thermal power units, This is the sum of the daily renewable energy curtailment penalty cost and the hydropower curtailment penalty cost. The daily cost of over-carbon penalties, This represents the number of times thermal power unit i starts and stops per day. The cost of a single start-up and shutdown of a thermal power unit. =24, The price of wind curtailment penalty The price for abandoning light The price for water wastage This represents the predicted output of the wind turbines in time period t. This refers to the output of the photovoltaic units predicted earlier at time t. This is the predicted output of the hydropower unit at time t. This represents the actual output of the wind turbine at time t. This refers to the actual output of the photovoltaic unit at time t. This represents the actual output of the hydropower unit at time t. This represents the excess carbon content on the nth day of the mth month of this year.

[0022] This application also provides a carbon quota-based power generation planning and scheduling device for wind, solar, hydro, and thermal power systems, comprising the following modules: The first determination module is used to determine the monthly and daily carbon allowances for the current year based on the annual carbon allowance for the current year.

[0023] The second determining module is used to determine the monthly power generation plan for the current year based on the monthly carbon allowance, operating parameters of power generation resources, curtailment penalty price, and over-carbon penalty price.

[0024] The third determination module is used to determine the daily power generation plan for the current year based on the monthly power generation plan, daily carbon quotas for the current year, operating parameters of power generation resources, curtailment penalty price, over-carbon penalty price, and the output of power generation resources predicted in the current day.

[0025] The control module is used to control the scheduling of wind, solar, hydro, and thermal power generation plans based on carbon quotas, in accordance with the daily power generation plans for the year.

[0026] According to the carbon quota-based power generation planning and scheduling device for wind, solar, hydro, and thermal power systems provided in this application, the current year includes m months, and the first determining module is specifically used for: When m equals 1, the carbon quota for the m-th month of the current year is determined based on the historical carbon emission percentage of the m-th month and the annual carbon quota. When m is greater than 1, the carbon quota for the m-th month is determined based on the carbon emissions of the first m-1 months of the current year and the annual carbon quota.

[0027] According to the carbon quota-based power generation planning and scheduling device for wind, solar, hydro, and thermal power systems provided in this application, the m-th month includes n days, and the first determining module is specifically used for: When n equals 1, the carbon allowance for the nth day of the mth month of the current year is determined based on the proportion of carbon emissions on the nth day of the mth month in history and the carbon allowance for the mth month of the current year. When n is greater than 1, the carbon allowance for the nth day of the mth month of the current year is determined based on the carbon emissions of the first n-1 days of the mth month of the current year and the carbon allowance for the mth month of the current year.

[0028] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems as described above.

[0029] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems as described above.

[0030] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems as described above.

[0031] By using the above technical solutions, monthly and daily carbon quotas are decomposed from the annual carbon quota as a constraint. This can accurately transform the annual carbon emission reduction target into an executable time-segmented carbon quota constraint. This not only locks in the upper limit of the total annual carbon emissions from the source, ensuring the rigid implementation of the annual total carbon target, but also adapts to the operational needs of different scheduling cycles of wind, solar, hydro and thermal systems through hierarchical decomposition at multiple time scales, thereby improving the scientific nature and operability of carbon quota allocation. Based on this, a monthly power generation plan is formulated using monthly carbon quotas as constraints, combined with the operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices. Then, using the monthly power generation plan as a framework and daily carbon quotas as real-time constraints, a daily power generation plan is formulated by combining the operating parameters of power generation resources, curtailment penalty prices, excess carbon penalty prices, and the output of power generation resources predicted a day before. This constructs a multi-timescale linkage scheduling system of "carbon quotas - power generation plans," which realizes deep synergy between medium- and long-term resource optimization and short-term real-time scheduling. It effectively solves the technical problems of disconnect between long-term and short-term plans and the separation between carbon control and scheduling objectives in traditional scheduling, significantly improves the overall optimality of wind, solar, hydro, and thermal system operation, and provides a feasible and efficient technical path for the optimized scheduling of wind, solar, hydro, and thermal systems under carbon market constraints. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This is a schematic diagram of a wind, solar, water, and fire system provided in this application.

[0034] Figure 2 This is a flowchart illustrating a carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems provided in this application.

[0035] Figure 3 This is a schematic diagram of a wind, solar, hydro, and thermal power generation planning and scheduling device based on carbon quotas provided in this application.

[0036] Figure 4 This is a schematic diagram of the structure of an electronic device provided in this application. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0038] The following is combined Figures 2 to 4 This application describes a carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal power systems.

[0039] Figure 2 This is one of the flowcharts illustrating the carbon quota-based power generation planning and scheduling method for wind, solar, hydro, and thermal systems provided in this application, and it is applied to electronic equipment, such as... Figure 2 As shown, the method includes the following steps S201-S203.

[0040] S201, based on the annual carbon allowance for the current year, determines the monthly and daily carbon allowances for the current year.

[0041] The process of determining the monthly carbon allowance for electronic devices during the current year is described first.

[0042] In one example, the current year includes m months. Since a year has 12 months, m is at most 12. Accordingly, when m equals 1, electronic devices can determine the carbon allowance for the m-th month of the current year based on the historical carbon emission percentage of the m-th month and the annual carbon allowance for the current year. When m is greater than 1, electronic devices can determine the carbon allowance for the m-th month of the current year based on the carbon emissions of the first m-1 months of the current year and the annual carbon allowance for the current year.

[0043] The carbon emissions for the first m-1 months of the current year refer to the actual carbon emissions for the first m-1 months of the current year. For example, if m is 2, the carbon emissions for the first m-1 months of the current year refer to the actual carbon emissions for the first month of the current year.

[0044] When m equals 1, the carbon emission percentage of the m-th month in history refers to the carbon emission percentage of the first month in history, which can be determined based on the ratio between the average carbon emission of the first month in history over many years and the average carbon emission over many years in history.

[0045] In one example, an electronic device can determine its carbon allowance for each month of the year based on the following formula.

[0046] (Formula 1) Among them, among them, Indicates the first Monthly carbon allowance; Indicates the first year of history Average carbon emissions per month; This represents the average carbon emissions over many historical years. This indicates the annual carbon allowance for this year; This represents the average annual power generation, that is, the average power generation over many historical years. This represents the benchmark value for carbon emissions in the power industry. This means before the end of this year Actual carbon allowance consumption in a month.

[0047] In one example, before determining the carbon allowance for the first month of the year based on the carbon emission percentage of the first month in history and the annual carbon allowance, the aforementioned electronic device can also determine the initial monthly carbon allowance for each month of the year based on the annual carbon allowance for the year.

[0048] This application does not specify a particular method for determining the initial monthly carbon allowance for each month of the year. For example, the annual carbon allowance for the year can be evenly distributed to obtain the initial monthly carbon allowance for each month of the year. Alternatively, the annual carbon allowance can be differentiated by considering historical carbon emission patterns, seasonal electricity consumption characteristics, and power output distribution features to create initial monthly carbon allowances for each month that better reflect actual operating conditions.

[0049] Once the initial monthly carbon allowance is determined, electronic devices can use the above method to determine the carbon allowance for each month of the year, thereby enabling the adjustment of the monthly carbon allowance.

[0050] Determining the initial monthly carbon allowance for each month can provide an allocation benchmark. Subsequent adjustments based on historical data and actual operating conditions can avoid the irrationality of direct allocation and provide an initial iterative basis for rolling updates in subsequent months.

[0051] The process of determining daily carbon allowances for electronic devices is described next.

[0052] In one example, the m-th month can include n days. Accordingly, when n equals 1, the electronic device can determine the carbon allowance for the n-th day of the m-th month of the current year based on the carbon emissions percentage of the n-th day in the historical m-th month and the carbon allowance for the m-th month of the current year. When n is greater than 1, the electronic device can determine the carbon allowance for the n-th day of the m-th month of the current year based on the carbon emissions of the first n-1 days of the m-th month of the current year and the carbon allowance for the m-th month of the current year.

[0053] The carbon emissions for the first n-1 days of the m-th month of this year refer to the actual carbon emissions for the first n-1 days of the m-th month of this year.

[0054] In one example, an electronic device can determine the carbon allowance for the nth day of the mth month of the current year based on Formulas 2 and 3 below.

[0055] (Formula 2) (Formula 3) in, Indicates the first Month 1 Daily carbon allowance Indicates the first year of history Month 1 Average daily carbon emissions; Indicates the first From the 1st day of the month to the 2nd day of the month Actual daily carbon allowance consumption; Indicates the first The number of days in a month. Indicates the first Actual carbon allowance consumption in a month.

[0056] In one example, an electronic device may be equipped with a carbon quota decomposition model (also known as a multi-timescale carbon quota decomposition model), which can be used to determine the monthly and daily carbon quotas for the current year. The carbon quota decomposition model can be constructed using Equations 1, 2, and 3 mentioned above.

[0057] It should be noted that the embodiments of this application allow carbon emissions to exceed the preset carbon emission threshold on a single day and / or a single month, that is, it allows for situations where carbon emissions exceed the limit in stages. However, for the portion of emissions exceeding the limit, carbon penalties must be paid in accordance with the relevant rules.

[0058] As described above, in this embodiment of the application, the carbon quotas for each month and each day of the year can be allocated based on the annual carbon quota for the year. Furthermore, the carbon emissions for the following days can be precisely adjusted based on the actual carbon emissions for each day and / or month of the year. In other words, the carbon quota allocation can be adjusted in real time through rolling updates, thereby achieving precise control over the total amount of carbon emissions.

[0059] S202 determines the monthly power generation plan for the current year based on the monthly carbon allowances, operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices for each month of the current year.

[0060] Power generation resources may include, but are not limited to, thermal power units, hydropower units, and renewable energy units (such as photovoltaic units and wind power units).

[0061] The operating parameters of power generation resources can include multiple parameters from thermal power units, hydropower units, and renewable energy units (such as photovoltaic units and wind turbine units).

[0062] Operating parameters of thermal power units may include, but are not limited to, multiple parameters such as the number of thermal power units, the fuel coefficient of thermal power units, the carbon emission factor of thermal power units, the maximum output of thermal power units, the minimum output of thermal power units, the number of start-stop cycles of thermal power units, the cost of a single start-stop cycle of thermal power units, the minimum load rate of thermal power units, the uphill and downhill ramp rates of thermal power units, and the minimum allowable continuous operating time of thermal power units.

[0063] The operating parameters of a hydropower unit may include, but are not limited to, the hydropower unit's ramp rate, the reservoir capacity at the beginning of the month, the reservoir capacity at the end of the month, the fluctuation value of the outflow of the hydropower unit, the lower and upper limits of the reservoir capacity of the hydropower unit, the lower and upper limits of the outflow of the hydropower unit, and the lower and upper limits of the power generation of the hydropower unit.

[0064] The operating parameters of renewable energy units may include, but are not limited to, multiple parameters such as the number of wind turbine units, the number of photovoltaic units, the capacity of wind turbine units, the capacity of photovoltaic units, the maximum and minimum output of wind turbine units, and the maximum and minimum output of photovoltaic units.

[0065] The penalty price for curtailment may include, but is not limited to, at least one of the following: wind curtailment penalty price, solar curtailment penalty price, and hydropower curtailment penalty price. The wind curtailment penalty price refers to the unit price for curtailing wind power. The solar curtailment penalty price refers to the unit price for curtailing solar power. The hydropower curtailment penalty price refers to the unit price for curtailing hydropower.

[0066] In one example, an electronic device can be equipped with a medium- to long-term optimization scheduling model. The electronic device can input the monthly carbon allowance, power generation resource operating parameters, curtailment penalty price, and excess carbon penalty price for the current year into the medium- to long-term optimization scheduling model to obtain the monthly power generation plan for the current year.

[0067] Monthly power generation plans may include, but are not limited to, power generation plans for renewable energy sources, power generation plans for thermal power units, and power generation plans for hydropower units.

[0068] Renewable energy sources may include, but are not limited to, wind power and / or solar power.

[0069] In one example, the medium- to long-term optimization scheduling model may include a first objective function and a first constraint.

[0070] The first objective function aims to minimize the operating costs of the wind, solar, water, and thermal power systems for the current year.

[0071] The operating costs of wind, solar, hydro, and thermal power systems may include, but are not limited to, the fuel costs of thermal power units, the curtailment penalty costs of renewable energy, and the over-carbon penalty costs.

[0072] Taking the operating costs of a wind-solar-hydro-thermal system as an example, which include the fuel cost of thermal power units, the cost of renewable energy curtailment penalties, and the cost of excessive carbon emissions, and where renewable energy includes wind power and photovoltaics, the first objective function can be expressed as Equations 4 to 7 below: (Formula 4) (Formula 5) (Formula 6) (Formula 7) in, The operating costs of the wind, solar, hydro, and thermal power systems for this year. This is the fuel cost for thermal power units this year. The cost of renewable energy curtailment penalties for this year, This represents the cost of excessive carbon penalties for this year. This refers to the number of thermal power units. , , Let be the fuel coefficient of thermal power unit i. For the output of thermal power unit i in the m-th month of this year, This refers to the installed capacity of wind turbine units. This refers to the number of photovoltaic (PV) units installed. The price of wind curtailment penalty The price for abandoning light Let i be the amount of abandoned electricity generated by wind turbine i in the m-th month of this year. Let i be the amount of electricity wasted by photovoltaic unit i in the m-th month of this year. Price penalties for excessive carbon emissions. This represents the excess carbon amount for the mth month of this year.

[0073] When the monthly power generation plan includes a power generation plan for renewable energy, a power generation plan for thermal power units, and a power generation plan for hydropower units, the first constraint condition may include a first constraint for renewable energy, a first constraint for thermal power units, a first constraint for hydropower units, and a first constraint for power balance.

[0074] The first constraint for renewable energy, the first constraint for thermal power units, the first constraint for hydropower units, and the first constraint for power balance will be described below.

[0075] The first constraint on renewable energy is used to limit the monthly output of renewable energy during the current year. In one example, where renewable energy includes photovoltaic and wind power, the first constraint on renewable energy can be expressed as Equations 8 and 9 below.

[0076] (Formula 8) (Formula 9) in, Let i be the installed capacity of wind turbine unit i. Let i be the power generation guarantee rate of wind turbine i in the m-th month of this year. Let i be the power generation of wind turbine i in the m-th month of this year. This represents the grid connection volume of wind turbine unit i in the m-th month of this year. This represents the amount of abandoned electricity generated by wind turbine i in the m-th month of this year. For the installed capacity of photovoltaic unit i, Let i be the power generation guarantee rate for photovoltaic unit i in the m-th month of this year. Let i be the power generation of photovoltaic unit i in the m-th month of this year. For photovoltaic unit i, the amount of data connected to the grid in the m-th month of this year. This represents the amount of electricity wasted by photovoltaic unit i in the m-th month of this year.

[0077] The first constraint on thermal power units is used to limit the monthly operation and carbon emissions of thermal power units within the current year. In one example, the first constraint on thermal power units can be expressed as Equations 10 to 12 below.

[0078] (Formula 10) (Formula Eleven) (Formula 12) in, This represents the minimum output (or power generation) of thermal power unit i. This represents the maximum output of thermal power unit i. Let i be the actual output of thermal power unit i at time t. This represents the minimum load rate of thermal power unit i. This represents the actual carbon emissions of thermal power unit i in the m-th month of this year. The carbon emission factor for thermal power unit i. This represents the actual carbon emissions for the m-th month of this year. This refers to the carbon emission exceeding the limit in the mth month of this year.

[0079] The first constraint on hydropower units is used to limit the operation of hydropower units each month of the current year. In one example, the first constraint on hydropower units can be expressed as Formulas Thirteen to Sixteen below.

[0080] (Formula Thirteen) (Formula Fourteen) (Formula 15) (Formula Sixteen) in, This represents the lower limit of the reservoir capacity of hydropower unit i. Let i be the reservoir capacity of hydropower unit i at time t. This represents the upper limit of the reservoir capacity of hydropower unit i. This represents the lower limit of the outflow rate of hydropower unit i. Let i be the outflow rate of hydropower unit i at time t. This represents the upper limit of the outflow rate of hydropower unit i. This represents the lower limit of the power generation capacity of hydropower unit i. Let be the power generation of hydropower unit i at time t. This represents the upper limit of the power generation capacity of hydropower unit i. Let i be the inflow rate of hydropower unit i at time t. Let be the reservoir capacity at the initial time of time interval t+1 for hydropower unit i. Let t be the duration of time.

[0081] The first constraint on power balance is used to define the relationship between monthly power load and power generation for the current year. In one example, the first constraint on power balance can be expressed as Equation 17 below.

[0082] in, For the electricity load in month m, Let be the power generation of the i-th hydroelectric unit in month m.

[0083] It should be noted that the above medium- and long-term optimization scheduling model is a nonlinear programming problem, which can be transformed into a mixed-integer linear programming problem through linearization and solved using mature commercial solvers such as gurobi.

[0084] S203, based on the monthly power generation plan for the year, the daily carbon allowance for the year, the operating parameters of power generation resources, the curtailment penalty price, the over-carbon penalty price, and the day-ahead forecast of power generation resource output, determines the daily power generation plan for the year.

[0085] The power output of the power generation resources predicted in advance can include the power output of renewable energy units predicted in advance and the power output of hydropower units predicted in advance.

[0086] In one example, an electronic device may be equipped with a short-term optimization scheduling model. The electronic device can input the monthly power generation plan for the current year, the daily carbon quota for the current year, the operating parameters of power generation resources, the curtailment penalty price, the over-carbon penalty price, and the day-ahead forecast of the power generation resource output into the short-term optimization scheduling model to obtain the daily power generation plan for the current year.

[0087] Daily power generation plans may include, but are not limited to, power generation plans for renewable energy sources, power generation plans for thermal power units, and power generation plans for hydropower units.

[0088] In one example, a short-run optimization scheduling model may include a second objective function and a second constraint.

[0089] The second objective function aims to minimize the daily operating costs of the wind, solar, water, and thermal power systems.

[0090] The operating costs of wind, solar, hydro, and thermal power systems may include, but are not limited to, the fuel costs of thermal power units, the costs of renewable energy curtailment penalties, the costs of hydropower curtailment penalties, and the costs of excessive carbon emissions.

[0091] Taking the operating costs of a wind-solar-hydro-thermal system as including the fuel cost of thermal power units, the cost of renewable energy curtailment penalties, the cost of hydropower curtailment penalties, and the cost of excessive carbon emissions, and assuming that renewable energy includes wind power and photovoltaics, the second objective function can be expressed as Equations 18 to 21 below: (Formula 18) (Formula 19) (Formula 20) (Formula 21) in, The daily operating cost of wind, solar, hydro, and thermal power systems. For the daily fuel cost of thermal power units, This is the sum of the daily renewable energy curtailment penalty cost and the hydropower curtailment penalty cost. The cost of daily carbon overload penalties. This refers to the number of times a thermal power unit starts and stops within a single scheduling cycle (i.e., one day). This refers to the cost of a single start-up and shutdown of a thermal power unit. =24 means there are 24 hours in a day. The price of wind curtailment penalty The price for abandoning light The price for water wastage This represents the predicted output of the wind turbines in time period t. This represents the output of the photovoltaic units in time period t, as predicted recently. This is the predicted output of the hydropower unit in time period t. This represents the actual output of the wind turbine during time period t. This represents the actual output of the photovoltaic unit during time period t. This represents the actual output of the hydropower unit during time period t. This represents the excess carbon content on the nth day of the mth month of this year.

[0092] When the daily power generation plan includes the power generation plan of renewable energy, the power generation plan of thermal power units, and the power generation plan of hydropower units, the second constraint may include carbon emission constraints, renewable energy second constraints, thermal power unit second constraints, hydropower unit second constraints, and power balance second constraints.

[0093] The following sections will describe the carbon emission constraints, the second constraint on renewable energy, the second constraint on thermal power units, the second constraint on hydropower units, and the second constraint on power balance.

[0094] Carbon emission constraints are used to limit daily carbon emissions. In one example, a carbon emission constraint can be expressed as Equation 22 below.

[0095] (Formula 22) in, Let be the carbon emissions of thermal power unit i at time t. Referring to Formula 22, the carbon emissions can be calculated using a piecewise linearization method. Based on carbon emission factors, This refers to the power output range of thermal power units. , , , This is the correction amount for the carbon emission factor of thermal power units.

[0096] The second renewable energy constraint is used to limit the daily output of renewable energy. In one example, where renewable energy includes photovoltaic and wind power, the second renewable energy constraint can be expressed as Equations 23 and 24 below.

[0097] (Formula 23) (Formula 24) in, Let be the actual power generation of wind turbine i at time t. Let be the maximum power generation of wind turbine i at time t. Let be the actual power generation of photovoltaic unit i at time t. Let be the maximum power generation of photovoltaic unit i at time t.

[0098] The second constraint on thermal power units is used to limit the daily operation and carbon emissions of thermal power units. In one example, the first constraint on thermal power units can be expressed as Equations 25 to 30 below.

[0099] (Formula 25) (Formula 26) (Formula 27) (Formula 28) (Formula 29) (Formula 30) in, Let i be the start-stop state of thermal power unit i at time t. This represents the minimum load rate of thermal power unit i. This represents the actual output of thermal power unit i at time t+1. Let be the uphill speed of thermal power unit i. Let be the downhill ramp rate of thermal power unit i. Let be the continuous operating duration of thermal power unit i at time t-1. Let be the duration of continuous shutdown of thermal power unit i at time t-1. This represents the minimum allowed continuous operating time for thermal power unit i. This represents the minimum allowable continuous downtime for thermal power unit i. This represents the actual carbon emissions (carbon allowance consumption) on the nth day of the mth month of this year. This refers to the carbon emission exceeding the limit on the nth day of the mth month of this year.

[0100] The second constraint on the hydropower unit is used to limit the daily operation of the hydropower unit. In one example, the second constraint on the hydropower unit can be expressed as Equations 31 to 39 below.

[0101] (Formula 31) (Formula 32) (Formula 33) (Formula 34) (Formula 35) (Formula Thirty-Six) (Formula 37) (Formula 38) (Formula 39) in, The initial reservoir capacity of the hydropower unit reservoir scheduled on the first day of the m-th month. The initial value of the hydropower unit reservoir obtained from medium- and long-term scheduling is shown in the m-th month. The final reservoir capacity of the hydropower unit reservoir scheduled before the end of the m-th month. This represents the final value of the hydropower unit reservoir obtained from medium- and long-term scheduling in the m-th month. The value represents the fluctuation of the outflow. This represents the actual discharge flow from the reservoir on the nth day of the mth month. To allocate guidance values ​​for the discharge flow. Let i be the rate of ascent for hydropower unit i. Let be the inflow rate of the reservoir for hydropower unit i at time t.

[0102] The second energy balance constraint is used to define the relationship between daily energy load and generation. In one example, the second energy balance constraint can be expressed as Equation 40 below. The second energy balance constraint can also be called a short-term energy balance constraint.

[0103] (Formula 40) in, Let the load be at time t. Let be the power generation of the hydroelectric generator at time t. Let be the power generation of the wind turbine at time t. Let be the power generation of the photovoltaic unit at time t. Let be the power generation of the thermal power unit at time t.

[0104] It should be noted that the above short-run optimization scheduling model is a mixed-integer linear programming problem, which can be solved using mature commercial solvers such as gurobi.

[0105] As described above regarding the objective function and constraints of the short-term optimization scheduling model, short-term scheduling can use the scheduling results from medium- and long-term scheduling (such as water allocation results, power allocation results, and reservoir capacity) as scheduling boundary conditions. Furthermore, it incorporates over-carbon penalty prices and other guidelines to guide day-ahead resource utilization, decomposing monthly plans to daily levels. For example, the amount of water to be reduced or stored each month can be evenly distributed across each day as a flexible constraint in short-term scheduling. In addition, short-term scheduling can also consider the uncertainties in wind and solar power output, as well as complex timing constraints such as unit start-up, shutdown, and ramp-up, to obtain a short-term system operation plan and achieve refined short-term resource scheduling.

[0106] After the daily power generation plan of the power generation resources in this year is determined by the above method, the electronic equipment can control the power generation resources to operate according to the corresponding power generation plan.

[0107] By using the above technical solutions, monthly and daily carbon quotas are decomposed from the annual carbon quota as a constraint. This can accurately transform the annual carbon emission reduction target into an executable time-segmented carbon quota constraint. This not only locks in the upper limit of the total annual carbon emissions from the source, ensuring the rigid implementation of the annual total carbon target, but also adapts to the operational needs of different scheduling cycles of wind, solar, hydro and thermal systems through hierarchical decomposition at multiple time scales, thereby improving the scientific nature and operability of carbon quota allocation. Based on this, a monthly power generation plan is formulated using monthly carbon quotas as constraints, combined with the operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices. Then, using the monthly power generation plan as a framework and daily carbon quotas as real-time constraints, a daily power generation plan is formulated by combining the operating parameters of power generation resources, curtailment penalty prices, excess carbon penalty prices, and the output of power generation resources predicted a day before. This constructs a multi-timescale linkage scheduling system of "carbon quotas - power generation plans," which realizes deep synergy between medium- and long-term resource optimization and short-term real-time scheduling. It effectively solves the technical problems of disconnect between long-term and short-term plans and the separation between carbon control and scheduling objectives in traditional scheduling, significantly improves the overall optimality of wind, solar, hydro, and thermal system operation, and provides a feasible and efficient technical path for the optimized scheduling of wind, solar, hydro, and thermal systems under carbon market constraints.

[0108] The following describes the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling device provided in this application. The carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling device described below can be referred to in correspondence with the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling method described above.

[0109] Figure 3 This example illustrates a structural diagram of a carbon quota-based power generation planning and scheduling device for wind, solar, hydro, and thermal power systems. The device includes: The first determining module 301 is used to determine the monthly and daily carbon allowances for the current year based on the annual carbon allowance for the current year.

[0110] The second determining module 302 is used to determine the monthly power generation plan for the current year based on the monthly carbon quota, operating parameters of power generation resources, curtailment penalty price and over-carbon penalty price for each month of the current year.

[0111] The third determining module 303 is used to determine the daily power generation plan for the current year based on the monthly power generation plan for the current year, the daily carbon quota for the current year, the operating parameters of power generation resources, the curtailment penalty price, the over-carbon penalty price, and the output of the power generation resources predicted in the current day.

[0112] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include: a processor 401, a communication interface 402, a memory 403, and a communication bus 404. The processor 401, communication interface 402, and memory 403 communicate with each other via the communication bus 404. The processor 401 can call logic instructions in the memory 403 to execute a carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling method. This method includes: determining the monthly and daily carbon quotas for the current year based on the annual carbon quota; determining the monthly power generation plan for the current year based on the monthly carbon quotas, operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices; determining the daily power generation plan for the current year based on the monthly power generation plan, daily carbon quotas, operating parameters of power generation resources, curtailment penalty prices, excess carbon penalty prices, and the predicted output of power generation resources; and controlling the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling according to the daily power generation plans for the current year.

[0113] Furthermore, the logical instructions in the aforementioned memory 403 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0114] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling method provided by the above methods. The method includes: determining the monthly and daily carbon quotas for the current year based on the annual carbon quota for the current year; determining the monthly power generation plan for the current year based on the monthly carbon quota, the operating parameters of power generation resources, the curtailment penalty price, and the over-carbon penalty price; determining the daily power generation plan for the current year based on the monthly power generation plan, the daily carbon quota, the operating parameters of power generation resources, the curtailment penalty price, the over-carbon penalty price, and the day-ahead predicted output of power generation resources; and controlling the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling according to the daily power generation plan for the current year.

[0115] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program is implemented to perform the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling method provided by the above methods. The method includes: determining the monthly and daily carbon quotas for the current year based on the annual carbon quota for the current year; determining the monthly power generation plan for the current year based on the monthly carbon quota, operating parameters of power generation resources, curtailment penalty price, and excess carbon penalty price; determining the daily power generation plan for the current year based on the monthly power generation plan, the daily carbon quota, operating parameters of power generation resources, curtailment penalty price, excess carbon penalty price, and the day-ahead predicted output of power generation resources; and controlling the carbon quota-based wind, solar, hydro, and thermal power generation planning and scheduling according to the daily power generation plan for the current year.

[0116] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0117] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for scheduling power generation in wind, solar, hydro, and thermal systems based on carbon quotas, characterized in that, The method includes: Based on the annual carbon allowance for this year, determine the monthly and daily carbon allowances for the year. Based on the monthly carbon allowances, operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices for the current year, the monthly power generation plan for the wind, solar, hydro, and thermal systems for the current year is determined. Based on the monthly power generation plan for the current year, the daily carbon allowance for the current year, the operating parameters of the power generation resources, the curtailment penalty price, the over-carbon penalty price, and the current forecast output of the power generation resources, the daily power generation plan for the wind, solar, hydro, and thermal power systems for the current year is determined.

2. The method according to claim 1, characterized in that, The current year includes m months. Determining the carbon allowance for each month of the current year includes: When m equals 1, the carbon allowance for the m-th month of the current year is determined based on the historical carbon emission percentage of the m-th month and the annual carbon allowance. If m is greater than 1, the carbon allowance for the m-th month is determined based on the carbon emissions of the first m-1 months of the current year and the annual carbon allowance.

3. The method according to claim 2, characterized in that, The m-th month includes n days. Determining the daily carbon allowance for the current year includes: When n equals 1, the carbon allowance for day n in the m-th month of the current year is determined based on the proportion of carbon emissions on day n in the m-th month of the current year and the carbon allowance for the m-th month of the current year. When n is greater than 1, the carbon allowance for day n in month m of the current year is determined based on the carbon emissions of the first n-1 days of month m of the current year and the carbon allowance for month m of the current year.

4. The method according to any one of claims 1-3, characterized in that, The determination of the monthly power generation plan for the current year, based on the monthly carbon allowances, operating parameters of power generation resources, curtailment penalty prices, and excess carbon penalty prices for each month of the current year, includes: By inputting the monthly carbon allowances for the current year, the operating parameters of the power generation resources, the curtailment penalty price, and the over-carbon penalty price into the medium- and long-term optimization scheduling model, the monthly power generation plan for the current year can be obtained.

5. The method according to claim 4, characterized in that, The medium- and long-term optimization scheduling model includes a first objective function and a first constraint condition. The first objective function aims to minimize the operating cost of the wind, solar, hydro, and thermal systems in the current year. The first constraint includes at least one of the following: The first constraint on renewable energy is used to limit the monthly output of renewable energy sources for the current year. First constraint on thermal power units; the first constraint on thermal power units is used to limit the monthly operation and carbon emissions of thermal power units in the current year. First constraint on hydropower units; the first constraint on hydropower units is used to limit the operation of hydropower units each month of the current year; The first constraint on power balance is used to define the relationship between the monthly power load and power generation in the current year.

6. The method according to claim 5, characterized in that, The operating costs include the fuel costs of thermal power units, the curtailment penalty costs of renewable energy, and the over-carbon penalty costs; The first objective function is: ， ， ， ， in, The operating cost of the power generation resources in the current year. The fuel cost of the aforementioned thermal power units for this year. The cost of the renewable energy curtailment penalty for this year. The cost of the over-carbon penalty for this year, This refers to the number of thermal power units. , , Let be the fuel coefficient of thermal power unit i. For thermal power unit i, in the m-th month of this year, This refers to the installed capacity of wind turbine units. This refers to the number of photovoltaic (PV) units installed. The price of wind curtailment penalty The price for abandoning light Let i be the amount of abandoned electricity generated by wind turbine i in the m-th month of this year. Let i be the amount of electricity wasted by photovoltaic unit i in the m-th month of this year. The price of the super-carbon penalty. This refers to the excess carbon amount in the mth month of the current year.

7. The method according to any one of claims 1-3, characterized in that, The process of determining the daily power generation plan for the current year based on the monthly power generation plan for the current year, the daily carbon allowance for the current year, the operating parameters of the power generation resources, the curtailment penalty price, the over-carbon penalty price, and the day-ahead forecast of the power generation resource output includes: The monthly power generation plan for the current year, the daily carbon allowance for the current year, the operating parameters of the power generation resources, the curtailment penalty price, the over-carbon penalty price, and the previously predicted output of the power generation resources are input into the short-term optimization scheduling model to obtain the daily power generation plan for the current year.

8. The method according to claim 7, characterized in that, The short-term optimization scheduling model includes a second objective function and a second constraint. The second objective function aims to minimize the daily operating cost of the wind, solar, hydro, and thermal power systems. The second constraint includes at least one of the following: Carbon emission constraints; the carbon emission constraints are used to limit daily carbon emissions; Second constraint on renewable energy; the second constraint on renewable energy is used to limit the daily output of renewable energy. Second constraint on thermal power units; the second constraint on thermal power units is used to limit the daily operation and carbon emissions of thermal power units; Second constraint on hydropower units; the second constraint on hydropower units is used to limit the daily operation of hydropower units; The second constraint on power balance is used to define the relationship between daily power load and power generation.

9. The method according to claim 8, characterized in that, The operating costs include the fuel costs of thermal power units, the curtailment penalty costs of renewable energy, and the over-carbon penalty costs; The second objective function is: ， ， ， ， in, The daily operating cost of the aforementioned wind, solar, water, and fire system. The daily fuel cost of the aforementioned thermal power units. The sum of the daily renewable energy curtailment penalty cost and the hydropower curtailment penalty cost. The daily cost of the aforementioned carbon penalty, This represents the number of times thermal power unit i starts and stops per day. The cost of a single start-up and shutdown of a thermal power unit. =24, The price of wind curtailment penalty The price for abandoning light The price for water wastage This represents the predicted output of the wind turbines in time period t. This refers to the output of the photovoltaic units predicted earlier at time t. This is the predicted output of the hydropower unit at time t. This represents the actual output of the wind turbine at time t. This refers to the actual output of the photovoltaic unit at time t. This represents the actual output of the hydropower unit at time t. This represents the excess carbon content on the nth day of the mth month of this year.

10. A power generation planning and scheduling device for wind, solar, hydro, and thermal power systems based on carbon quotas, characterized in that, The device includes: The first determining module is used to determine the monthly and daily carbon allowances for the current year based on the annual carbon allowance for the current year. The second determining module is used to determine the monthly power generation plan for the current year based on the monthly carbon quota, operating parameters of power generation resources, curtailment penalty price and over-carbon penalty price for each month in the current year. The third determining module is used to determine the daily power generation plan for the current year based on the monthly power generation plan for the current year, the daily carbon quota for the current year, the operating parameters of the power generation resources, the curtailment penalty price, the over-carbon penalty price, and the output of the power generation resources predicted in the current day.

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