A low-carbon economic dispatching method for a power system based on combined operation of a carbon capture power plant and a pumped storage

Abstract

The application provides a low-carbon economic dispatching strategy of a power system based on combined operation of a carbon capture power plant and pumped storage. The strategy effectively realizes low-carbon economic operation of the power system while improving new energy consumption capacity. The strategy overcomes the problems of high carbon emission and insufficient peak shaving capacity of traditional thermal power plants, copes with the defects of carbon capture power plants participating in dispatching and enhances new energy consumption capacity, provides a theoretical basis and a practical solution for realizing the "carbon peak and carbon neutral" goal of China, and realizes low-carbon economic complementary cooperation in the whole period through flexible operation of the carbon capture power plant and the pumped storage. The strategy provides a feasible solution for large-scale application of the carbon capture power plant from the advantages of combined dispatching of the current system flexible resources.

Description

Technical Field

[0001] This invention patent relates to a low-carbon economic dispatch method for power systems. In particular, during the accelerated construction of a new type of power system based on new energy sources, it proposes a practical dispatch strategy that achieves complementary and synergistic low-carbon economic operation of the power system throughout the entire time period by flexibly operating carbon capture power plants and pumped storage. This provides a feasible solution for the large-scale application of carbon capture power plants and an effective path to quickly achieve the "dual carbon" goal. Background Technology

[0002] Under the "dual carbon" goals, while electricity demand grows year by year, the proportion of thermal power is gradually decreasing, while the proportion of new energy sources such as wind and solar power is increasing, becoming a trend. Carbon capture power plants, as an important transitional power source for ensuring power supply and reducing carbon emissions, face limitations in their coordination with new energy sources due to liquid storage capacity constraints and the anti-peak-shaving characteristics of wind and solar power. Pumped storage, as a large-capacity energy storage element, can effectively cope with the anti-peak-shaving characteristics of wind and solar power due to its rapid ramp-up bidirectional power regulation performance, compensating for the shortcomings of carbon capture power plants. Therefore, this paper proposes a two-stage dispatching method for low-carbon economic power systems that considers the flexible operation of carbon capture power plants and the joint operation of pumped storage. First, the advantages and limitations of flexible carbon capture power plants and pumped storage operation are analyzed. Taking into full account the time-shifting characteristics of energy consumption and the double regulation capacity of pumped storage, and combined with the typical peak-valley characteristics of net load, a low-carbon economic complementary and synergistic mechanism for the joint operation of flexible carbon capture power plants and pumped storage is designed for all time periods. Then, fuzzy parameters are introduced to characterize the uncertainty of net load, and a two-stage low-carbon economic dispatch model is constructed with the goal of minimizing the comprehensive cost that balances operating costs, net load loss, and carbon emissions. An improved particle swarm optimization algorithm is used to solve the model. Finally, simulations verify that the dispatch method proposed in this paper can effectively combine the advantages of both to improve the low-carbon economic benefits of the system. Summary of the Invention

[0003] The purpose of this invention is to address the above-mentioned situation by proposing a low-carbon economic dispatch strategy for power systems based on the combined operation of flexible carbon capture power plants and pumped storage. This strategy achieves low-carbon economic operation while improving the capacity for renewable energy absorption through the complementary and synergistic low-carbon economic mechanism of the two.

[0004] The above-mentioned technical problems of the present invention are mainly solved by the following technical solutions: The combined operation of carbon capture power plants and pumped storage has complementary and synergistic low-carbon economic characteristics, which include the following steps.

[0005] Step 1: Analyze the low-carbon economic characteristics of flexibly operating carbon capture power plants. The net output of the carbon capture power plant units is expressed as: (1) In the formula: This refers to the net output power of the units in a carbon capture power plant. The equivalent output power of the carbon capture power plant unit (i.e., the active power generated by fuel combustion). Fixed energy consumption (energy consumption caused by changes in the power plant's operating structure due to the introduction of carbon capture can be considered a fixed value); Energy consumption for the operation of carbon capture power plants.

[0006] The energy consumption required for carbon capture operation, as well as the energy consumption supplied to the carbon capture system by the carbon capture power plant and the power grid respectively, can be expressed as follows: (2) (3) (4) In the formula: and These are the operating energy consumption required for carbon capture and the operating energy consumption supplied by the power grid, respectively. Energy consumption per unit of carbon capture; The ratio of CO2 flowing out of / into the flooded storage tank; This refers to the flue gas split ratio; Carbon emission intensity per unit of carbon capture power plant; The CO2 capture rate of a carbon capture power plant is typically between 80% and 95%. The proportion of compressed electrical energy provided to the carbon capture unit. , a Refers to regenerated thermal energy, etc. The proportion of efficient energy consumption to total operating energy consumption.

[0007] The net output of a flexibly operating carbon capture power plant can then be equivalent to: (5) The maximum and minimum net active power output of the flexible carbon capture power plant are: (6) (7) In the formula: , and These represent the maximum CO2 outflow / inflow ratio from the rich liquid storage tank, the maximum CO2 capture rate of the carbon capture power plant, and the maximum flue gas split ratio, respectively. and These correspond to the maximum and minimum equivalent output power, respectively. Under the maximum net output condition, only CO2 is stored, not processed. Under the minimum net output condition, the amount of CO2 processed is the maximum, and all operating energy consumption is provided by the carbon capture unit.

[0008] From equations (6) and (7), the range of net output power variation of the carbon capture power plant can be obtained as follows: (8) The range of net output power variation for conventional thermal power plants is as follows: (9) Comparison with conventional thermal power units shows that flexible carbon capture power plants, due to their time-shifted energy consumption characteristics, expand their net output range and provide greater peak-shaving depth. The high capture energy consumption during peak load periods can be supplied by inexpensive carbon capture power plants or additional renewable energy output during off-peak periods, ensuring high carbon capture while reducing peak-to-valley differences and promoting renewable energy consumption. However, due to the reverse peak-shaving characteristics of wind and solar power and the gradually increasing peak-to-valley load difference, carbon capture power plants face significant output pressure during peak load periods, resulting in insufficient on-spin reserve and frequent start-ups and shutdowns of additional thermal power plants or prolonged deep peak-shaving operations. During off-peak periods, the time-shifted capture energy consumption may not fully offset the wind power margin, leading to significant wind curtailment.

[0009] Step 2: Analyze the low-carbon economic characteristics of pumped storage power stations.

[0010] The main operating conditions of pumped storage hydroelectric power stations are power generation and pumping. The typical output model for a pumped storage power station is as follows: (10) In the formula: , , H and The water turbine is respectively t The power generation capacity, efficiency, head height, and flow rate at any given time; , , H and The water pump is respectively in t Pumping power, efficiency, head height, and flow rate at any given time; g This is the acceleration due to gravity.

[0011] The principles of low-carbon characteristics of pumped storage are mainly as follows: 1) Sufficient pumped storage can offset the peak-shaving characteristics of wind power, shift the output of new energy to achieve peak shaving and valley filling, and promote the consumption of new energy; 2) It can alleviate the output pressure of thermal power plants during peak load periods and reduce the carbon emissions of the system; 3) The peak shaving characteristics reduce the system reserve pressure, and at the same time, pumped storage can replace the spinning reserve capacity that should be provided by thermal power.

[0012] Step 3: Study the low-carbon economic complementarity of flexible carbon capture power plants and pumped storage combined operation. The power system structure of flexible carbon capture power plants combined with pumped storage is as follows: Figure 4 As shown. Considering the need to unify the volatility of load and the uncertainty of wind and solar power generation, wind and solar are treated as unschedulable resources, and a definition is established. tNet load at any given time is the actual load minus unschedulable generating capacity. (11) In the formula: For the first t Net load requirements of the time-of-use system; For the first t The load requirements of the time-of-use system; For the first t Real-time wind power output forecast; For the first t Real-time photovoltaic power output forecast.

[0013] Figure 5 To illustrate the low-carbon economic complementarity mechanism of the joint operation of carbon capture power plants and pumped storage throughout the entire time period, a comparative analysis of the low-carbon economic status under four scenarios is conducted during typical net load peak and off-peak periods.

[0014] (1) Peak net load period ( Figure 5 (Period III): Scenario 2 has a large net load and capture demand, requiring time-shifted capture energy consumption or a reduced capture level to alleviate output pressure, thus increasing output demand compared to Scenario 1. Scenario 3 pumped storage can reduce the output of high-carbon units by converting pumped power to electricity, converting power during shutdown, or increasing the output of the generating unit. Similarly, due to the peak shaving effect of pumped storage, Scenario 4 can increase capture energy consumption compared to Scenario 2, and the reduced time-shifted energy consumption pressure relatively lowers the storage tank capacity requirement.

[0015] (2) Low net load period: When wind and solar power curtailment is not a significant issue ( Figure 5 (Period II): In Scenario 2, the time-shifted capture energy consumption is provided by carbon capture power plants, exhibiting low-carbon characteristics; the overall carbon capture level is also correspondingly improved. In Scenario 3, the increased load during pumping operations is provided by high-carbon units during this period, lacking low-carbon characteristics. Scenario 4, like Scenario 2, exhibits low-carbon characteristics, and its peak shaving and valley filling capabilities are more prominent.

[0016] When wind and solar power curtailment is prominent ( Figure 5 (Period I): In Scenario 2, the time-shifted capture energy consumption is provided by the additional renewable energy absorbed during that period, but its effect on promoting renewable energy absorption is limited. Scenario 3, like Scenario 2, is low-carbon, but its support for renewable energy absorption is greater. Scenario 4 has a lower amount of wind and solar energy curtailment compared to Scenario 3, and its renewable energy absorption capacity is optimal.

[0017] In summary, the flexible operation of carbon capture power plants and pumped storage combined can achieve complementary and synergistic low-carbon economic benefits throughout the entire time period. The advantages of combined operation are: 1) Its peak-shaving and valley-filling characteristics can greatly alleviate the net output pressure of carbon capture power plants; the capacity requirement for storage tanks can be relatively reduced. 2) The spin-on reserve capacity it provides reduces the reserve pressure of carbon capture power plants, masking the drawback of increased peak load due to capture energy consumption, and reducing the possibility of needing to start high-carbon units to provide spin-on reserve. 3) Pumped storage can effectively compensate for the insufficient renewable energy absorption capacity; the total capture demand of the system is reduced, while a larger proportion of capture energy consumption is equivalent to being provided by the original curtailed wind and solar power, further enhancing the low-carbon economic characteristics.

[0018] Step 4: Introduce a two-stage low-carbon economic dispatch method.

[0019] Two-stage scheduling diagram as follows Figure 6 As shown, since the accuracy of net load forecasting improves over time, this patent introduces a two-stage scheduling method to coordinate the solution of the joint operation mechanism and strategy of carbon capture power plants and pumped storage, so as to maximize the achievement of low-carbon economic goals.

[0020] The dispatching system is based on a 1-hour timeframe to develop a full-day dispatching plan and determine the start-up and shutdown plans for thermal power units. The intraday dispatching system is based on a net load curve with higher forecast accuracy, rolling the plan every 15 minutes and optimizing the 1-hour plan each time. The revision of pumped storage and carbon capture plans is the main focus, without changing the unit start-up and shutdown plans developed in advance. The system also modifies the output plans, carbon capture plans, and final spinning reserve plans for each unit.

[0021] Step 5: Determine the objective function.

[0022] Considering the difficulty and inherent errors in collecting actual wind and solar load forecasts, this paper employs fuzzy parameters to characterize the uncertainty of the system's net load, establishes fuzzy chance constraints, and performs a clear-equivalent solution to these constraints. The optimal problem with fuzzy parameters under the fuzzy chance constraints is formulated as follows: (12) In the formula: The objective function is... For constraint functions; This is the confidence expression. The confidence level.

[0023] The fuzzy opportunity constraints include: day-ahead scheduling constraints and intraday rolling optimization scheduling constraints.

[0024] The dispatcher recently formulated a dispatch plan based on net load forecasts, and introduced a carbon trading mechanism while considering economic dispatch. The objective function is to minimize the overall system operating cost, as shown below: (13) In the formula: For the overall system cost; Costs associated with the start-up and shutdown of thermal power units; The operating cost of pumped storage; Coal consumption cost of thermal power units; Cost of carbon emissions; The cost of net load mismatch penalty.

[0025] in: 1) Start-up and shutdown costs of thermal power units

[0026] (14) In the formula: , These are the start-up and shutdown costs for a single thermal power unit; thermal power units include... K conventional units and I Taiwan carbon capture unit; , The first n Taiwan thermal power units during the period t Internal start / stop status; a value of 1 or 0 indicates that the device is in or not in this state. 2) Operating costs of pumped storage units

[0027] The operating cost of a pumped storage unit includes the start-up cost for power generation and the start-up cost for pumping: (15) In the formula: and These are the power generation and pumping start-up costs for a single pumped storage unit, respectively. , These are the power generation status indication and pumping status indication of the pumped storage unit, respectively, with values ​​of 1 or 0.

[0028] 3) Coal consumption cost of thermal power units

[0029] (16) In the formula: Cost per unit of coal consumption; For the unit n During the period t The internal running state variable takes the value 1 or 0; , and For thermal power units n The constant coefficient of coal consumption characteristics; For thermal power units tEquivalent output power over a given time period.

[0030] 4) Carbon emission costs

[0031] To fully leverage the role of carbon capture power plants, carbon emission trading rules have been introduced. The system's carbon emissions mainly originate from conventional coal-fired units and carbon capture units, with a total daily carbon emission of: (17) In the formula: For conventional coal-fired units k carbon emission intensity per unit; For conventional coal-fired units t Equivalent output power over a given time period.

[0032] Total daily carbon emission allowance for the system: (18) In the formula: This refers to the carbon emission quota coefficient for thermal power plants.

[0033] Carbon trading involves paying a fee if emissions exceed the allowance, and allowing trading of the remaining allowance for rewards if emissions do not exceed the allowance. Carbon emission cost calculation: (19) In the formula: This refers to the price of carbon trading.

[0034] 5) Net load mismatch penalty cost

[0035] (20) In the formula: This is the net load mismatch penalty coefficient; for t Actual net load supply during the period.

[0036] Based on the optimized scheduling plan obtained recently, and using the updated net load forecast, intraday rolling optimized scheduling is conducted. This maintains the established start-up and shutdown status of thermal power units, while fully utilizing the regulation capabilities of the carbon capture system and pumped storage to perform a secondary matching of the updated net load curve. The objective function for intraday rolling optimized scheduling is: (twenty one) Step 6: Determine the constraints.

[0037] Day-ahead scheduling constraints: 1) System power transfer constraints This includes line transmission power limits and power balance constraints: (twenty two) (twenty three) In the formula: and The lines are respectively l The upper and lower limits of power; and The first j Taiwan pumped storage units during the period t Internal power generation and pumping capacity.

[0038] 2) Output constraints of conventional coal-fired power units and carbon capture units (twenty four) (25) 3) Climbing constraints for conventional coal-fired power units and carbon capture units (26) In the formula: For the unit n Downhill / uphill speed (hourly); For the unit n The rate of ascent.

[0039] 4) Start-up and shutdown constraints for conventional coal-fired power units and carbon capture units Due to the physical characteristics of coal-fired power units and the coal consumption costs of starting and stopping them, the units must meet minimum start-up and shutdown time constraints and start-up and shutdown operating state constraints: (27) In the formula: This is the minimum start-up time for the unit. This is the minimum downtime for the unit; different types of units have different start-up and shutdown time parameters.

[0040] 5) Flexible operation of carbon capture system constraints Flue gas split ratio constraint: (28) In the formula: This is the limit value for the flue gas split ratio.

[0041] Solution storage in t Storage capacity during different time periods t- Reserves in period 1 and t It is related to the inflow and outflow volume during a certain period, that is: (29) In the formula: and For carbon capture systems in t The amount of rich and poor liquid storage tanks during the time period; , , and For carbon capture units t The inflow and outflow of the memory during a given time period; the mass of CO2 Converted to solution volume : (30) In the formula: The molar mass of CO2; The molar mass of MEA; This refers to the analytical quantity of the analytical tower; The concentration of the solution; Let be the solution density; then the solution flow satisfies the following relationship: (31) Solution storage capacity constraints: (32) In the formula: , This represents the maximum storage capacity for both rich and poor solution storage devices.

[0042] To ensure the proper operation of the day-ahead periodic scheduling system, the solution storage capacity must remain constant throughout the scheduling process, i.e.: (33) 6) Operating constraints of pumped storage units (34) In the formula: , , and These are the upper and lower limits of the pumping / power generation capacity of pumped storage units, respectively. Pumped storage power station t The reservoir capacity during a given period; , These are the upper and lower limits of the upper reservoir capacity of the pumped storage power station, respectively. and This is the water / electricity conversion factor under pumping or power generation conditions. and The upper reservoir capacity is the starting and ending point of the daily dispatch of the pumped storage power station. Since the lower reservoir capacity is larger, the constraints on the upper reservoir capacity are the same as those on the lower reservoir capacity, so there is no need to impose constraints on the lower reservoir.

[0043] 7) Spinning standby credible opportunity constraint To ensure the system's operational flexibility, various resources need to be allocated as spinning reserves to respond to random fluctuations in net load. The main spinning reserves come from carbon capture power plants, conventional thermal power units, and pumped storage units, and are divided into upper spinning reserve constraints and lower spinning reserve constraints, leading to the calculations in equations (35) and (36).

[0044] (35) (36) In the formula: for t Clear equivalence of net load during a given period and These are the up / down spinning reserves that can be provided during the day-ahead dispatch of the pumped storage power station, calculated according to equations (37) and (38): (37) (38) Intraday rolling optimization scheduling constraints: In addition to power balance constraints, thermal power unit output constraints, and carbon capture system constraints as of today, intraday rolling optimization scheduling constraints, unit ramp-up constraints, pumped storage start-up and shutdown constraints, and spinning reserve constraints need to be adjusted as the time scale decreases.

[0045] 1) Intraday ramp-up constraints for thermal power units (39) in, The equivalent output power of thermal power unit n during time period t; 2) Constraints for Pumped Storage Operating Condition Transition In intraday rolling scheduling, the following constraints must be met during the transition between operating conditions: (40) 3) Intraday spinning reserve credible opportunity constraint The intraday rotational reserve is similar to the daytime reserve, but the ramp rate in the constraints needs to be updated from the hourly level to the 15-minute level, and the up / down rotational reserve that pumped storage can provide also needs to be adjusted accordingly, calculated according to equations (41) and (42). Specific constraints will not be elaborated.

[0046] (41) (42) Step 7: Solve the model.

[0047] Solving fuzzy chance constraints: confidence level At that time, the net load trapezoidal fuzzy parameter is clearly equivalent to: (43) (44) In the formula: F Representing load, wind power, and solar power, For their respective fuzzy parameters, This is the membership parameter.

[0048] The clear equivalent solution for the fuzzy opportunity constraint of the daytime rotating reserve is as follows; the intraday rotating reserve constraint is similar.

[0049] (45) (46) Meanwhile, the scheduling model for the flexible operation of carbon capture power plants combined with pumped storage is complex, with many variables and difficulties in linearization. Therefore, an improved particle swarm optimization (IPSO) algorithm is considered for solving the problem. The proposed IPSO overcomes the premature convergence and early convergence issues inherent in traditional PSO iterations. Improvements are made to the inertia weight, self-learning factor, and social learning factor to increase convergence speed while avoiding local optima. The algorithm flow is as follows: Figure 7 As shown.

[0050] First, a compression factor is introduced into the inertia weight, and the particle... i The speed and position updates are as follows: (47) (48) (49) In the formula: Inertial weights; For flight speed; For group position; , For self- and social learning factors; , For the optimal position for both the individual and the global; and It is a random number between (0,1).

[0051] Using nonlinear inverse cosine acceleration pairs , Adaptive time-varying adjustments are implemented, focusing on individual historical information in the early stages of particle flight and emphasizing global experience in the later stages. The improvements are as follows: (50) (51) In the formula: , , , The initial and final values ​​for the iteration are typically 2.5, 0.5, 0.5, and 2.5. This represents the current iteration number; This represents the maximum number of iterations.

[0052] Addressing the high carbon emissions of traditional thermal power plants and the volatility of new energy sources, the introduction of carbon capture power plants, coupled with pumped hydro storage—the most mature large-scale energy storage resource in the current power system—highlights the complementary and synergistic advantages of the two in low-carbon economics throughout the entire lifecycle. The unique advantages of the combination of the two in terms of economic cost, carbon emission reduction, and new energy consumption can provide a feasible reference for the clean and low-carbon transformation of the power system. Attached Figure Description

[0053] Figure 1 Comparison of net output between flexible carbon capture power plants and conventional thermal power plants Figure 2 Typical operating condition conversion diagram of pumped storage unit Figure 3 Schematic diagram of the low-carbon characteristics of pumped hydro storage Figure 4 Power system architecture diagram including flexible carbon capture power plants and pumped storage Figure 5 Diagram illustrating the complementary low-carbon economic mechanism of flexible operation of carbon capture power plants and pumped storage. Figure 6 Two-stage scheduling diagram Figure 7 Algorithm solution flowchart Figure 8 Improved IEEE-30 node topology Figure 9 Recent wind power, solar power, load forecast and net load curves Figure 10 Intraday Wind Power, Solar Power, Load Forecast and Net Load Curve Detailed Implementation The technical solution of the present invention will be further described below through embodiments and in conjunction with the accompanying drawings.

[0054] This invention patent relates to a low-carbon economic dispatch method, particularly a method for addressing the low-carbon economic dispatch of power systems before the realization of the "dual-carbon" goals of the new power system. Carbon capture, utilization, and storage (CCUS) technology is currently the fastest and most cost-effective option for achieving emission reduction targets, making carbon capture power plants the best choice for flexible low-carbon retrofitting of thermal power plants. Currently, no domestic or international research literature has thoroughly investigated the low-carbon complementary and synergistic advantages of combining these two low-carbon methods. Therefore, this strategy needs to delve into the limitations of both methods based on their low-carbon principles, and then analyze the low-carbon economic complementary and synergistic mechanism of their combination, achieving low-carbon economic operation while improving the capacity for renewable energy absorption, all while ensuring a balance between power generation and consumption.

[0055] Example The technical solution of this invention is mainly based on the flexible operation of carbon capture power plants and pumped storage. By solving the model through algorithms, it is verified that the joint operation can improve the low-carbon performance of the system while reducing economic costs.

[0056] First, let me introduce the principle of this invention.

[0057] The principle of the invention is the same as steps 1-7 above, and will not be repeated here.

[0058] II. The example uses a modified IEEE-30 node system. The system topology is shown below. Figure 8 Wind and solar power plants are connected to nodes 5 and 8 respectively. G1 and G2 are FCCPP (Fuel Concentrated Capacity Controlled Power Plant), G1 remains online, G4 is a pumped storage unit, and G3, G5, and G6 are conventional thermal power units. Forecast curves for wind power, solar power, and load are shown below. Figure 9 and 10 .

[0059] To verify the effectiveness of the low-carbon economic dispatch method that combines flexible operation of carbon capture power plants and pumped storage, a comparative analysis of dispatch results under three scenarios was conducted: 1) Includes two-stage dispatching of flexible carbon capture power plants; 2) Two-stage scheduling including pumped storage; 3) Includes two-stage scheduling of flexible carbon capture power plants and pumped storage.

[0060] Two-stage scheduling result analysis: The predicted typical daily load curve is divided into 24 segments, with a maximum load of 1110.60MW, a minimum load of 253.90MW, an average load of 704.32MW, and a maximum peak-to-valley difference of 856.70MW.

[0061] Since pumped storage power stations require a pricing mechanism to generate revenue and sustain operations, time-of-use pricing is determined based on the difference between load and average load. The off-peak price is set at 200 yuan / MWh, the on-grid price during normal periods is 400 yuan / MWh, and the peak price is 600 yuan / MWh. The determined time-of-use pricing is shown in Table 1. Table 1 Time-of-use electricity prices for different time periods

[0062] The specific scheduling of the system in the above three scenarios is as follows: Table 2. Results of dispatching operations prior to the date of dispatch.

[0063] As shown in Table 2, during day-ahead dispatch, the net load loss in Scenario 2 was 519.60 MWh less than in Scenario 1, while carbon emissions increased by 4930 t. The results indicate that systems incorporating flexible carbon capture power plants and pumped storage each have their advantages in reducing carbon emissions and promoting renewable energy consumption. Scenario 3, using a combination of both, reduced operating costs by 4.39% compared to Scenario 1. This is because the participation of pumped storage increased renewable energy consumption, reduced the load proportion borne by thermal power, and thus reduced coal consumption and carbon emissions. The net load loss cost in Scenario 2 was 75.86% lower than in Scenario 1, and the net load loss cost in Scenario 3 was 85.96% lower than in Scenario 1, indicating that both carbon capture power plants and pumped storage have the ability to promote renewable energy consumption, with pumped storage playing a primary role and the role of carbon capture power plants limited. The carbon emissions of Scenario 3 are reduced by 15.47% compared to Scenario 1 and by 65.49% compared to Scenario 2; the total cost of Scenario 3 is reduced by 21.49% compared to Scenario 1 and by 24.61% compared to Scenario 2. These conclusions indicate that when both scenarios are jointly involved in day-ahead scheduling, the low-carbon and economic characteristics of the system are significantly improved.

[0064] Table 3. Results of Intraday Rolling Scheduling

[0065] As shown in Table 3, during the intraday rolling scheduling phase, the total cost of Scenario 3 was reduced by 22.53% and 26.97% compared to Scenario 1 and 2, respectively; carbon emissions were reduced by 20.65% and 68.37%; and net load loss costs were reduced by 90.29% and 53.95%. The intraday rolling scheduling results demonstrate that the combination of the two approaches has the superiority of low-carbon economic complementarity and synergy throughout the entire time period, verifying the effectiveness of the low-carbon economic scheduling model proposed in this patent.

[0066] The system suffers from wind and solar power curtailment, which is due to the need to discard some wind power during the start-up and shutdown of thermal power plants. At the same time, due to the lack of large-capacity energy storage, although the time shift of carbon capture energy consumption can promote the consumption of some new energy sources, the effect is minimal. In addition, the time shift of energy consumption alleviates the peak-valley difference of net load to some extent.

[0067] In Scenario 2, the curtailment of wind and solar power in the system is significantly alleviated due to the presence of pumped storage. The output demand of thermal power plants during peak net load periods is significantly reduced, relieving the standby pressure on high-carbon units. However, since no carbon capture device is installed, the net load is still mainly provided by high-carbon units, and the carbon emissions of the system remain very high.

[0068] To address the limitations of Scenario 1 and Scenario 2, Scenario 3 emphasizes the synergy between the two. Compared to Scenario 1, it not only significantly reduces wind and solar curtailment but also greatly alleviates the pressure of carbon capture energy consumption shifting, improving the flexible control characteristics of carbon capture energy consumption and reducing the demand for solution storage capacity. Compared to Scenario 2, the shifting of carbon capture energy consumption over time further enhances the system's ability to absorb new energy sources. At the same time, due to the configuration of capture equipment, the system's net load is mainly provided by low-carbon carbon capture power plants, greatly improving the system's low-carbon performance.

[0069] The unit combination in Scenario 3 is better than Scenario 1 and Scenario 2 in promoting the widespread consumption of clean energy, highlighting that the coordinated use of pumped storage and solution storage can achieve better low-carbon economic benefits.

[0070] During peak net load periods, the flue gas split ratio in Scenario 3 is generally higher than that in Scenario 1. This is because the presence of pumped storage alleviates the output pressure on carbon capture power plants, allowing them to maintain a certain proportion of capture energy consumption during peak periods and maximizing the storage capacity of solution storage devices to improve carbon capture levels. Scenario 1 has a total daily carbon output of 9546.70t and a carbon capture of 6145.34t; Scenario 3 has a total daily carbon output of 9131.31t and a carbon capture of 6256.26t. Scenario 3's total daily carbon output is 415.39t lower than Scenario 1, while its carbon capture is 110.92t higher. The results indicate that the addition of pumped storage can significantly alleviate the peak-shaving and valley-filling pressure on flexible carbon capture equipment, allowing it to focus more on reducing carbon emissions.

[0071] In Scenario 1, due to the high output pressure of the carbon capture power plant, the peak shaving and valley filling effect of time-shifted energy consumption is more obvious, and the maximum carbon capture energy consumption occurs at 3 pm during the lowest net load period of the day. In Scenario 3, due to the participation of pumped storage, the pressure of peak shaving by time-shifted capture energy consumption is significantly reduced, and the peak shaving characteristics are not significantly prominent. Moreover, the time when the maximum carbon capture energy consumption occurs is much earlier than in Scenario 1, and the maximum carbon capture energy consumption is also less than in Scenario 1. This indicates that the introduction of pumped storage has a significant effect on alleviating the peak shaving pressure of the carbon capture power plant, and the peak value of the solution storage volume is also significantly reduced. Therefore, the system's demand for the storage tank capacity is also reduced.

[0072] Under the typical daily load of this patent, the net daily revenue of the pumped storage unit in Scenario 2 is 3.5498 × 10⁻⁶. 5 Yuan, the net profit for the whole day under scenario 3 is 3.5850×10. 5 The net profit of the pumped storage unit in Scenario 3 increased by RMB 3517.87 compared to Scenario 2. This indicates that the introduction of carbon capture equipment slightly increased the output pressure during peak hours, allowing pumped storage to focus more on providing peak load output, thus improving efficiency and increasing economic benefits. When wind and solar curtailment is not severe, the net profit difference between Scenario 3 and Scenario 2 will further widen, resulting in considerable long-term accumulated benefits.

[0073] Table 4 shows the impact of pumped storage capacity: Larger pumped storage capacity can effectively cope with the peak-shaving characteristics of wind and solar power and achieve low-carbon and economical dispatch of the system, but this comes with high construction costs and site selection conditions. Considering the economics of having an optimal installed capacity, it is necessary to analyze the carbon emissions and overall costs of pumped storage under different capacities.

[0074] Table 4 Impact of Pumped Storage Capacity

[0075] As shown in Table 4, with the increase in pumped storage capacity, the net load cost of the system decreases significantly and eventually stabilizes. This is because pumped storage can effectively absorb wind and solar power output during off-peak hours through pumping operation. The absorption capacity is related to the capacity itself; above 200MW, the decrease in net load cost is smaller, indicating that this capacity is basically sufficient for the system to fully absorb new energy sources. Furthermore, at an installed capacity of 300MW, high-carbon thermal power G3 plants do not need to be started to provide spinning reserve, significantly reducing start-up and shutdown costs.

[0076] The carbon emissions and overall cost of the system show a downward trend as the pumped storage capacity increases; when the installed capacity reaches 200MW and 300MW, the carbon emissions and overall cost tend to stabilize respectively; the lowest point of the overall cost depends on the system confidence level, and the higher the confidence level, the larger the required pumped storage capacity.

[0077] The scheduling model employs fuzzy chance constraints. This section discusses the impact of different confidence levels on the joint operation scheduling results. Regarding confidence levels... α Comparison of some parameters from 0.5 to 1.

[0078] Table 5 Impact of Confidence Level in Scenario 3

[0079] As shown in Table 5, for systems that combine flexible carbon capture power plants with pumped storage, the confidence level... αThe increase in confidence level significantly increases both the system's spinning reserve capacity and the required reserve from high-carbon thermal power plants, showing a positive correlation. Simultaneously, carbon emissions and overall costs also gradually increase. This is because the confidence level reflects the reliability of system dispatching. α The higher the value, the more abundant the spinning reserve, and the higher the reliability and cost.

[0080] By comparing the total spinning reserve and the reserve required by high-carbon thermal power plants with and without pumped storage in dispatch models at different confidence levels, the overall trend shows a positive correlation.

[0081] The comparison revealed that the growth trend of rotating reserve in scenario 3 was greater than that in scenario 2, and Scenario 3 requires more backup power. This is because Scenario 1 itself has insufficient downsizing capacity, and its ability to absorb wind and solar power is weaker than that of Scenario 3; the higher the confidence level, the more conservative the fuzzy parameters of wind and solar power, and the greater the value of clear net load. Scenario 3 requires far more wind and solar power to be connected to the grid during scheduling than Scenario 1. α The increase in the number of high-carbon thermal power plants necessitates a faster growth rate in the required spinning reserve. Similarly, comparing different confidence levels, scenario 3 requires significantly less spinning reserve from high-carbon thermal power plants than scenario 1. This is due to the peak-shaving and valley-filling capabilities and ample spinning reserve capacity of pumped storage. This contrast of "more and less" illustrates that the introduction of pumped storage can significantly improve absorption capacity while reducing the reserve capacity of high-carbon thermal power plants. Furthermore, scenario 1... α The increase in high-carbon reserve during the 0.8-1 hour period is due to the additional need for high-carbon thermal power to provide backup power during the peak 9-11 hour period.

[0082] In summary, confidence level α This determines the trend of system reliability and cost. Therefore, it is necessary to select an appropriate confidence level based on the actual impact, balancing security and economy.

[0083] The simulation results of the proposed method of combining flexible carbon capture power plants and pumped storage power plants demonstrate that the two have complementary and synergistic advantages in low-carbon economy throughout the entire cycle. The model has unique advantages in terms of economic cost, carbon emission reduction and new energy consumption, and can provide a feasible solution to help achieve "carbon peak and carbon neutrality".

[0084] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Those skilled in the art can make various modifications or compensations to the specific examples described, but without departing from the scope defined by the appended claims.

Claims

1. A low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage, characterized in that: This study analyzes the low-carbon economic characteristics of flexible carbon capture power plants, pumped storage power plants, and the low-carbon economic complementary characteristics of the combined operation of flexible carbon capture power plants and pumped storage power plants. A two-stage low-carbon economic dispatch method is established, using fuzzy parameters to characterize the uncertainty of the system's net load, establishing fuzzy opportunity constraints, and performing a clear equivalent solution to the fuzzy opportunity constraints; the optimal problem containing fuzzy parameters under the fuzzy opportunity constraints is expressed as: In the formula: The objective function is... For constraint functions; This is the confidence expression. Confidence level; The fuzzy opportunity constraints include: day-ahead scheduling constraints and intraday rolling optimization scheduling constraints. The dispatching system recently formulated a dispatching plan based on net load forecasts. Taking into account economic dispatching, a carbon trading mechanism was introduced, with the objective function being the minimum overall system operating cost, as shown below: In the formula: For the overall system cost; Costs associated with the start-up and shutdown of thermal power units; The operating cost of pumped storage; Coal consumption cost of thermal power units; Cost of carbon emissions; The cost of net load mismatch penalty.

2. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 1, characterized in that: When analyzing the low-carbon economic characteristics of flexibly operating carbon capture power plants, the net output of the carbon capture power plant units is expressed as: In the formula: This refers to the net output power of the units in a carbon capture power plant. The equivalent output power of the carbon capture power plant unit is the active power generated by fuel combustion. Fixed energy consumption, i.e., the energy consumption caused by changes in the power plant's operating structure due to the introduction of carbon capture, is considered a fixed value; Energy consumption for the operation of carbon capture power plants; The energy consumption required for carbon capture operation, as well as the energy consumption supplied to the carbon capture system by the carbon capture power plant and the power grid respectively, can be expressed as follows: In the formula: and These are the operating energy consumption required for carbon capture and the operating energy consumption supplied by the power grid, respectively. Energy consumption per unit of carbon capture; The ratio of CO2 flowing out of / into the flooded storage tank; This refers to the flue gas split ratio; Carbon emission intensity per unit of carbon capture power plant; The CO2 capture rate of a carbon capture power plant is typically between 80% and 95%. The proportion of compressed electrical energy provided to the carbon capture unit. , a This refers to the proportion of energy consumption equivalent to regenerated thermal energy to the total operating energy consumption; The net output of a flexibly operating carbon capture power plant unit can be equivalent to: The maximum and minimum net active power output of the flexible carbon capture power plant are as follows: In the formula: , and These represent the maximum CO2 outflow / inflow ratio from the rich liquid storage tank, the maximum CO2 capture rate of the carbon capture power plant, and the maximum flue gas split ratio, respectively. and These correspond to the maximum and minimum equivalent output power, respectively; under the maximum net output condition, only CO2 is stored and not processed, while under the minimum net output condition, the amount of CO2 processed is the maximum, and all operating energy consumption is provided by the carbon capture unit.

3. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 1, characterized in that: When analyzing the low-carbon economic characteristics of pumped storage power stations, the principles underlying these characteristics include: 1) Sufficient pumped storage can offset the anti-peak-shaving characteristics of wind power, and time-shifted new energy output can achieve peak shaving and valley filling, thus promoting the consumption of new energy. 2) Alleviate the pressure on thermal power plant output during peak load periods and reduce system carbon emissions; 3) Peak shaving characteristics reduce the system's standby pressure, while pumped storage can replace the spinning standby capacity that would otherwise be provided by thermal power.

4. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 1, characterized in that: When considering the low-carbon economic complementarity of flexibly operating carbon capture power plants and pumped storage combined, the first step is to reconcile the volatility of loads with the uncertainty of wind and solar power generation, treating wind and solar as unschedulable resources, and defining... t Net load at any given time is the actual load minus unschedulable generating capacity. In the formula: For the first t Net load requirements of the time-of-use system; For the first t The load requirements of the time-of-use system; For the first t Real-time wind power output forecast; For the first t Real-time photovoltaic power output forecast.

5. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 4, characterized in that: Since the accuracy of net load forecasting improves as time shortens, a two-stage scheduling method is adopted to coordinate the solution of the joint operation mechanism and strategy of carbon capture power plants and pumped storage, so as to maximize the achievement of low-carbon economic goals. The dispatching system now uses 1-hour time intervals to develop a full-day dispatching plan and determine the start-up and shutdown schedules for thermal power units. Intraday scheduling is based on a net load curve with higher forecast accuracy, rolling once every 15 minutes, optimizing the plan for 1 hour each time, taking the revision of pumped storage and carbon capture plans as the main focus, without changing the unit start-up and shutdown plans formulated before the day, and revising the output plans, carbon capture plans and final spinning reserve plans of each unit.

6. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 4, characterized in that: 1) Start-up and shutdown costs of thermal power units In the formula: , These are the start-up and shutdown costs for a single thermal power unit; thermal power units include... K conventional units and I Taiwan carbon capture unit; , The first n Taiwan thermal power units during the period t Internal start / stop status; a value of 1 or 0 indicates that the device is in or not in this state. 2) Operating costs of pumped storage units The operating cost of a pumped storage unit includes the start-up cost for power generation and the start-up cost for pumping: In the formula: and These are the power generation and pumping start-up costs for a single pumped storage unit, respectively. , These are the power generation status indication and pumping status indication of the pumped storage unit, respectively, with values ​​of 1 or 0; 3) Coal consumption cost of thermal power units In the formula: Cost per unit of coal consumption; For the unit n During the period t The internal running state variable, taking the value 1 or 0; , and For thermal power units n The constant coefficient of coal consumption characteristics; For thermal power units t Equivalent output power over a given time period; 4) Carbon emission costs To fully leverage the role of carbon capture power plants, carbon emission trading rules have been introduced. The system's carbon emissions mainly originate from conventional coal-fired units and carbon capture units, with a total daily carbon emission of: In the formula: For conventional coal-fired units k carbon emission intensity per unit; For conventional coal-fired units t Equivalent output power over a given time period; Total daily carbon emission allowance for the system: In the formula: Carbon emission quota coefficient for thermal power plants; Carbon trading involves paying a fee if emissions exceed the allowance, and trading the remaining allowance to earn revenue if emissions do not exceed the allowance; carbon emission cost calculation: In the formula: For carbon trading prices; 5) Net load mismatch penalty cost In the formula: This is the net load mismatch penalty coefficient; for t Actual net load supply during the period; Based on the optimized scheduling plan obtained recently, and using the updated net load forecast, intraday rolling optimization scheduling is conducted. This process does not change the already determined start-up and shutdown status of thermal power units, but fully utilizes the regulation capabilities of the carbon capture system and pumped storage to perform a secondary matching of the updated net load curve. The objective function for intraday rolling optimization scheduling is: 。 7. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 4, characterized in that: The constraints include: Day-ahead scheduling constraints: 1) System power transfer constraints This includes line transmission power limits and power balance constraints: In the formula: and The lines are respectively l The upper and lower limits of power; and The first j Taiwan pumped storage units during the period t Internal power generation and pumping capacity; 2) Output constraints of conventional coal-fired power units and carbon capture units （22） 3) Climbing constraints for conventional coal-fired power units and carbon capture units In the formula: For the unit n Downhill / uphill speed (hourly); For the unit n The rate of ascent; 4) Start-up and shutdown constraints for conventional coal-fired power units and carbon capture units Due to the physical characteristics of coal-fired power units and the coal consumption costs of starting and stopping them, the units must meet minimum start-up and shutdown time constraints and start-up and shutdown operating state constraints: In the formula: This is the minimum start-up time for the unit. This refers to the minimum downtime of the unit; the start-up and shutdown time parameters vary for different types of units. 5) Flexible operation of carbon capture system constraints Flue gas split ratio constraint: In the formula: This refers to the limit value for the flue gas split ratio; Solution storage in t Storage capacity during different time periods t- Reserves in period 1 and t It is related to the inflow and outflow volume during a certain period, that is: In the formula: and For carbon capture systems in t The amount of rich and poor liquid storage tanks during the time period; , , and For carbon capture units t The inflow and outflow of memory during a given time period; CO2 mass Converted to solution volume : In the formula: The molar mass of CO2; The molar mass of MEA; This refers to the analytical quantity of the analytical tower; The concentration of the solution; The density of the solution; The solution flow satisfies the following relationship: Solution storage capacity constraints: In the formula: , This represents the maximum storage capacity for both rich and poor solution storage devices. To ensure the proper operation of the day-ahead periodic scheduling system, the solution storage capacity must remain constant throughout the scheduling process, i.e.: 6) Operational constraints of pumped storage units In the formula: , , and These are the upper and lower limits of the pumping / power generation capacity of pumped storage units, respectively. Pumped storage power station t The reservoir capacity during a given period; , These are the upper and lower limits of the upper reservoir capacity of the pumped storage power station, respectively. and This is the water / electricity conversion factor under pumping or power generation conditions. and The upper reservoir capacity is the starting and ending point of the daily dispatch of the pumped storage power station. Since the lower reservoir capacity is larger, the constraint on the upper reservoir capacity is the same as the constraint on the lower reservoir capacity, so there is no need to impose constraints on the lower reservoir. 7) Spinning standby credible opportunity constraint To ensure the system's operational flexibility, various resources need to be allocated as spinning reserves to respond to random fluctuations in net load. The main spinning reserves come from carbon capture power plants, conventional thermal power units, and pumped storage units, and are divided into upper spinning reserve constraints and lower spinning reserve constraints, which are calculated by the following formula. In the formula: for t Clear equivalence of net load during a given period and These represent the on-day / off-day spinning reserves available for pumped storage power stations during day-ahead dispatch, calculated according to the following formula: Intraday rolling optimization scheduling constraints: In addition to power balance constraints, thermal power unit output constraints, and carbon capture system constraints as of the day, the intraday rolling optimization scheduling constraints, unit ramping constraints, pumped storage start-up and shutdown constraints, and spinning reserve constraints need to be adjusted as the time scale decreases. 1) Intraday ramp-up constraints for thermal power units in, The equivalent output power of thermal power unit n during time period t; 2) Constraints for Pumped Storage Operating Condition Transition In intraday rolling scheduling, the following constraints must be met during the transition between operating conditions: 3) Intraday spinning reserve credible opportunity constraint Intraday rotational reserve is similar to that of the daytime, but the ramp rate in the constraints needs to be updated from the hourly level to the 15-minute level, and the up / down rotational reserve that pumped storage can provide also needs to be adjusted accordingly, calculated according to the following formula; specific constraints will not be elaborated. 。 8. The low-carbon economic dispatch method for power systems based on the combined operation of carbon capture power plants and pumped storage as described in claim 4, characterized in that: The solution method for the model is as follows: Solving fuzzy chance constraints: confidence level At that time, the net load trapezoidal fuzzy parameter is clearly equivalent to: In the formula: F Representing load, wind power, and solar power, For their respective fuzzy parameters, Membership parameter; The clear equivalent solution for the fuzzy opportunity constraint of the daytime rotating reserve is as follows; the intraday rotating reserve constraint is similar. An improved particle swarm optimization algorithm is adopted, with improvements made to inertia weight, self-learning factor, and social learning factor. First, a compression factor is introduced into the inertia weight, and the particle... i The speed and position updates are as follows: In the formula: Inertial weights; For flight speed; For group position; , For self- and social learning factors; , For the optimal position both individually and globally; and A random number between (0, 1); Using nonlinear inverse cosine acceleration pairs , Adaptive time-varying adjustments are implemented, focusing on individual historical information in the early stages of particle flight and emphasizing global experience in the later stages; improvements are as follows: In the formula: , , , These are the initial and final values ​​for the iteration; This represents the current iteration number; This represents the maximum number of iterations.

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