Wind-solar pumped storage multi-source double-layer joint system operation method based on differential pricing and energy right transaction

Abstract

A wind and light pumped storage multi-source double-layer combined system operation method based on differential pricing and energy right trading is characterized in that a wind power plant, a photovoltaic power station and a pumped storage power station are included in the combined system, and power generation price models of all power generation and utilization equipment adopt a differential pricing mode; the bidding model can dynamically and reasonably guide multi-source equipment to participate in electricity market optimization according to information such as output power and load distribution condition of each piece of equipment; meanwhile, different devices can carry out energy-right transactions, the device with sufficient energy right can sell profits to other devices, and operation parameters, including the upper limit of operation power, efficiency and the like, of each device can be obtained in a scheduling period; an operation characteristic model and a network topology structure model of each device are constructed, a double-layer optimization scheduling model of the multi-source joint system is further constructed, and a CPLEX solver is adopted to carry out joint solution on the double-layer model, so that mutual benefit and win-win between the multi-source devices and the power market are realized, and the energy utilization rate and the wind and light power generation consumption level are improved.

Description

Technical Field

[0001] The present invention belongs to the field of energy technology and relates to an operation method of a wind-solar-pumped-storage multi-source double-layer joint system based on differentiated pricing and energy rights trading. Background Art

[0002] At present, environmental pollution and energy shortage are becoming increasingly prominent, and the contradiction between the growing energy demand and energy development is surging. The energy distribution is not uniform enough. In areas with high load, there is less renewable energy generation, and the dependence on fossil energy is relatively large. The excessive burning of fossil energy produces a large amount of polluting gas, causing environmental problems. The environmental pollution caused by traditional fossil energy has reached a point where it can not be delayed. The rapid development of wind and solar power generation, which is the backbone of the transformation from traditional energy to new energy, provides ideas for problems such as tight energy supply and serious environmental pollution. The widespread application of wind and solar power generation has alleviated the power supply pressure of traditional fossil energy.

[0003] However, with the rapid development of renewable energy power generation represented by wind and solar, the power of wind and solar power generation has gradually increased, and it has become increasingly difficult to consume wind and solar power generation on the spot. Therefore, large-scale access to the grid for wind and solar power has become a key method for absorbing wind and solar power generation. In addition, due to the uncertainty and randomness of wind and solar power generation, wind and solar power generation will have a certain impact on the safe and stable operation of the power grid, which will lead to limited power of wind and solar power generation connected to the grid, and cause problems such as wind and solar power abandonment. Therefore, how to effectively promote the grid connection and consumption of high proportions of wind and solar power has become a key issue that needs to be solved urgently.

[0004] As a large-scale, low-cost, and highly efficient energy storage method, pumped storage plays an important role in balancing the load of the power grid and improving energy efficiency. With the rapid development of renewable energy such as wind power and photovoltaics, the construction and operation management of pumped storage power stations are particularly important.

[0005] The construction of pumped-storage power stations can not only provide grid regulation services, but also promote the efficient consumption and utilization of new energy, and provide capacity support and peak-shaving capabilities for the power system. Pumped storage plays a key role in the transformation of energy structure and the construction of new power systems.

[0006] In summary, how to make up for the difference in wind and solar power generation in the power market and reduce the impact of wind and solar power generation uncertainty on the operation of the power market is a problem currently faced. In addition, in the traditional power market model, only thermal power units participate, and the bidding method is relatively simple. With the addition of multi-source joint systems, the traditional bidding model is no longer applicable.

[0007] The current problem is how to design a more flexible and responsive dynamic pricing and energy rights trading mechanism to better coordinate the interests of energy operators and promote the effective consumption of renewable energy.

[0008] Disadvantages of existing technology: (1) The energy pricing mechanism model has not been established; (2) There is a lack of a mechanism to determine the optimal solution for the joint efforts of the two-level game players; (3) There are few design solutions for energy rights trading mechanisms; (4) The quantitative analysis of the impact of energy quota constraints on the profitability of participating in the electricity market has not yet been addressed. Summary of the invention

[0009] The technical problem to be solved by the present invention is to provide a method for operating a wind-solar-pumped-storage multi-source two-layer joint system based on differentiated pricing and energy rights trading, which fully considers the operating characteristics of multi-source equipment, takes minimizing operating costs and carbon emission costs as optimization goals, and achieves mutual benefit and win-win results between power generation operators and the power market.

[0010] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading, comprising the following steps: S1, construct the operating characteristic models of the above equipment, including wind farm, photovoltaic power station and pumped storage power station models; S2, based on the price elasticity theory, considering the output power of each power supply equipment, constructs a differentiated bidding model for each power generation and consumption equipment; S3, based on the initial allocation plan of energy rights, build an energy rights trading mechanism between devices to realize the interaction of energy rights between multiple power generation and power consumption devices; S4, construct a two-layer optimization model for a multi-source joint system, where the upper layer is the power market and the lower layer is the power generation operator. The lower layer provides the clearing price and power of each device to the upper layer. The upper layer updates the clearing power according to the power market demand and transmits it to the lower layer, and the upper and lower layers iterate to solve the problem. S5, using CPLEX solver to iteratively solve the two-level optimization model of the multi-source joint system. When the upper and lower layer costs no longer change, the solution is completed.

[0011] In S1, in the wind farm model, the wind turbine output power and wind speed present a piecewise functional relationship. P WT The actual wind speed v The functional relationship between them can be described as: ; Where: , and Respectively represent the cut-in wind speed, cut-out wind speed and rated wind speed; is the rated output power of the fan.

[0012] In S1, the Hay model is introduced into the photovoltaic power station model to consider the impact of different hemispheres on the sky diffuse radiation. The sky diffuse radiation of this model can be expressed as: ; Where: is the amount of scattered radiation in the air; is the scattered radiation on the horizontal surface; is the direct scattering amount on the horizontal plane; Direct radiation on the inclined surface / direct radiation on the horizontal surface; is the solar radiation at the horizontal surface outside the atmosphere; is the inclination angle; combined with the above formula, the formula for solar radiation on the inclined surface can be derived: ; Where: is the total radiation on the horizontal plane; is the reflectivity of the ground surface; In addition to the amount of solar radiation, the output power of photovoltaic power generation is also related to the power conversion efficiency of the solar panel and the area of ​​the solar panel exposed to radiation, as follows: ; Where: is the output power of photovoltaic power generation; is the energy conversion efficiency; is the radiation area.

[0013] In S1, in the pumped storage power station model, without considering the factors of water loss during the operation of the pumped storage power station, the operating constraints of the pumped storage power station and the pumping conditions can be specifically described as: the relationship between pumping, power generation, efficiency and head of the pumped storage power station under the pump-turbine power generation condition and pumping condition: ; Where: Electricity consumption for water pumping; is the amount of electricity generated; To regulate water volume; is the average pumping head; is the average water head for power generation; The pumping efficiency of the pump-turbine; is the power generation efficiency of the pump turbine; 367.2 is the conversion factor; the primary cycle efficiency of the pumped storage power station can be expressed as: ; Under power generation and pumping conditions, the output of the pumped storage power station is related to the flow rate, which can be described specifically as: ; Where: for t Power generation during the period; for t Power generation flow during the period; for t Water head under power generation status during the period; for t Power generation efficiency during the period; for t Pumping power during the period; for t Pumping flow rate during the period; for t Head under period pumping state; for t Pumping efficiency during the period; In addition, starting from the operation constraints of the pumped storage power station itself, the constraints of the pumped storage power station include state constraints, power constraints and extraction balance constraints, as follows: ; In the formula, and They are the upper and lower limits of the reservoir capacity of the pumped storage power station, respectively; is the initial capacity of the pumped storage power station; and They are the power generation and pumping power of the pumped storage power station; and They are the power generation and pumping status of the pumped storage power station, which are 0-1 variables; and They are the power generation and pumping efficiency of pumped storage power plants, respectively; and They are the upper limits of power generation and pumping power of pumped-storage power stations respectively.

[0014] In S2, the differentiated bidding models for various power generation and consumption equipment are constructed, including price models for wind farms, photovoltaic power stations, and pumped storage power stations. In the price models for wind farms and photovoltaic power stations, the prices for wind and photovoltaic power generation can be described as: ; In the formula, Bidding prices for wind and solar; is the wind and solar price adjustment coefficient; The cost of wind and solar electricity; It is the upper limit of wind and solar prices; and They are respectively the energy right interaction power and energy right price adjustment coefficient between wind and solar power generation and other equipment. It should be noted that the energy right interaction power between the equipment has positive and negative values. The selling energy right is a positive value and the purchasing energy right is a negative value. The selling energy right will increase the bidding price of the equipment in the next iteration. On the contrary, purchasing energy right will reduce the bidding price of the equipment in the next iteration.

[0015] In S2, the electricity price model of the hydropower station can be described as: ; In the formula, bidding prices for pumped storage power stations; It is the price adjustment coefficient of power generation of pumped storage power station; The cost of generating electricity for pumped storage power stations; capping the price of electricity generated by pumped storage plants; and They are the energy rights interaction power and energy rights price adjustment coefficient between the pumped storage power station and other equipment; It is the discharge state of the pumped-storage power station, which is a 0-1 variable. When the discharge state is 1, the pumped-storage power station quotes to the electricity market; when the discharge state is 0, the pumped-storage power station does not quote to the electricity market.

[0016] In S3, the energy price model of each power generation and consumption equipment can be described as: ; In the formula, It is the price of energy rights interaction between various devices; among which, the energy rights price should meet the operating characteristics of each power supply equipment, and the energy rights interaction price cannot be higher than the price quoted by the device with the lowest power generation cost to the power market.

[0017] In S4, the proposed multi-source joint system optimization scheduling model includes: A. Upper-level electricity market optimization model: 1) Objective function, The upper-level electricity market operation cost is the electricity purchase cost for the lower-level multi-source joint system, which is described as follows: ; 2) Constraints, In addition, load satisfaction constraints are set to ensure that the electric load demand response operates within a reasonable range; ; In the formula, for t The lower limit of power shift of electric load during the period; The interruptible load ratio of the electric load; B. Lower-level multi-source joint system optimization model, 1) Objective function, The operating costs of the lower-level power generation operators include: the cost of wind and solar power abandonment and the income from selling electricity to the upper level. Combining the above costs, the operating costs of the lower-level power generation operators in a dispatch cycle are It can be expressed as: ; In the formula, is the cost of wind and solar power abandonment; the cost of wind and solar power abandonment can be expressed as: ; In the formula, is the penalty coefficient for wind and solar power abandonment, is the abandoned wind power; is the abandoned optical power; 2) Constraints, At the same time, the lower-level multi-source joint system needs to meet the electricity demand of the upper-level power market, and the balance constraint is the electric power balance constraint, which is as follows: ; In the formula, , and They are the initial electric load demand, time-shiftable load power and interruptible load power in the power market; For a certain node, the sum of the injected node power, the inflow node power, the outflow node power and the corresponding line network loss is 0. Based on this, the node power balance constraint can be expressed as: ; In the formula, and They are t Time j Node active and reactive power, and They are t Time jk Branch active and reactive power, for t Time jk Branch current, and They are ij Branch resistance and reactance; The node voltage constraint can be described as: ; In the formula, For the distribution network branch, and are the voltage values ​​at nodes i and j respectively.

[0018] In S4, in order to facilitate the solution, the multi-source joint system power flow model is converted into a second-order cone optimization model, which is compatible with CPELX efficient solution; the second-order cone model after the conversion is as follows: ; In the formula, is the two-norm; The static VAR compensation (SVC) has the ability to absorb and generate inductive reactive power. The SVC operation constraints can be described as: ; In the formula, for t Time j Node SVC output reactive power, and They are the upper and lower limits of SVC output reactive power respectively; Other constraints include three-phase distribution network current constraints and node voltage constraints, as follows: ; In the formula, and They are t Time i Node generator active and reactive power, and They are i The upper and lower limits of the active output of the node generator, and They are i The upper and lower limits of the node generator reactive output.

[0019] In S5, the constructed optimization model is solved to obtain the optimal operation result, including the CPLEX solver solution steps, as follows: CPELX solver for minimizing arbitrary objective functions F The main steps are as follows: Step 1: Use heuristics to find a solution to the problem X ; Store value Y = F ( X ); X will be marked as the best solution found so far and used as an upper bound for the candidate solutions; Step 2: Initialize a queue to hold partial solutions that do not contain problem variables; Step 3: Loop until the queue is empty: Step 3-1, obtain node NN from the queue; Step 3-2, if NN represents a single candidate solution X and F ( X )< Y ,but X This is the best solution so far. X And set Y ← F ( X ); Step 3-3, otherwise, branch on the NN node to generate a new node NN i , for each newly generated node, if, F ( NN i )> Y , keep the previous solution, otherwise, NN i Stored in a queue.

[0020] The main beneficial effects of the present invention are: A differentiated bidding model is proposed to set individual prices for each power generation and consumption equipment. At the same time, considering that energy rights can be traded between different equipment, equipment with sufficient energy rights can be sold to other equipment for profit, thus achieving mutual benefit and win-win results between power generation operators and power market operators.

[0021] The bidding mechanism, energy trading method and joint system two-tier dispatch method can achieve mutual benefit and win-win results between multi-source equipment and the power market through coordinated operation among various devices, and further improve energy utilization and the level of wind and solar power generation consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0023] Figure 1 It is a flow chart of the present invention.

[0024] Figure 2 It is the optimization flow chart of the present invention.

[0025] Figure 3 This is the CPELX solution flow chart of the present invention. DETAILED DESCRIPTION

[0026] like Figure 1~Figure 3 In the present invention, a method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading includes the following steps: S1, construct the operating characteristic models of the above equipment, including wind farm, photovoltaic power station and pumped storage power station models; S2, based on the price elasticity theory, considering the output power of each power supply equipment, constructs a differentiated bidding model for each power generation and consumption equipment; S3, based on the initial allocation plan of energy rights, build an energy rights trading mechanism between devices to realize the interaction of energy rights between multiple power generation and power consumption devices; S4, construct a two-layer optimization model for a multi-source joint system, where the upper layer is the power market and the lower layer is the power generation operator. The lower layer provides the clearing price and power of each device to the upper layer. The upper layer updates the clearing power according to the power market demand and transmits it to the lower layer, and the upper and lower layers iterate to solve the problem. S5, using CPLEX solver to iteratively solve the two-level optimization model of the multi-source joint system. When the upper and lower layer costs no longer change, the solution is completed.

[0027] Embodiment 1, Specifically, a multi-source joint operation system such as Figure 1 As shown, it includes wind farms, photovoltaic power stations and pumped storage power stations.

[0028] Furthermore, the present invention also provides a multi-source participation in the power market bidding mechanism, a multi-source energy rights trading model and a joint system double-layer optimization scheduling scheme, such as Figure 2 As shown, the following steps are included: 1) Construct the operating characteristic models of the above equipment, including wind farms, photovoltaic power plants, and pumped storage power plants; A. Wind farm model Existing literature shows that the output power of a wind turbine is piecewise proportional to the wind speed. P WT The actual wind speed v The between can be described as: ; Where: , and They represent cut-in wind speed, cut-out wind speed and rated wind speed respectively; and is the rated output power of the fan.

[0029] B. Photovoltaic power station model In order to describe the influence of this factor on solar radiation, this section introduces the Hay model to consider the influence of different hemispheres on the sky diffuse radiation. The formula of the sky diffuse radiation and the solar radiation on the inclined surface in this model can be expressed as: ; Where: is the amount of scattered radiation in the air; is the scattered radiation on the horizontal surface; is the direct scattering amount on the horizontal plane; Direct radiation on the inclined surface / direct radiation on the horizontal surface; is the solar radiation at the horizontal surface outside the atmosphere; is the tilt angle; is the total radiation on the horizontal plane; is the reflectivity of the ground surface.

[0030] In addition to the amount of solar radiation, the output power of photovoltaic power generation is also related to the power conversion efficiency of the solar panel and the area of ​​the solar panel exposed to radiation, as follows: ; Where: is the output power of photovoltaic power generation; is the energy conversion efficiency; is the radiation area.

[0031] C. Pumped Storage Power Station Model Without considering the water loss during the operation of the pumped storage power station, the operating constraints of the pumped storage power station's power generation and pumping conditions can be specifically described as the relationship between pumping, power generation, efficiency and head of the pumped storage power station under the pump-turbine power generation and pumping conditions: ; Where: Electricity consumption for water pumping; is the amount of electricity generated; To regulate water volume; is the average pumping head; is the average water head for power generation; The pumping efficiency of the pump-turbine; is the power generation efficiency of the pump turbine; 367.2 is the conversion factor.

[0032] In addition, starting from the operation constraints of the pumped-storage power station itself, the constraints of the pumped-storage power station include state constraints, power constraints and extraction balance constraints, as follows.

[0033] ; In the formula, and They are the upper and lower limits of the reservoir capacity of the pumped storage power station, respectively; is the initial capacity of the pumped storage power station; and They are the power generation and pumping power of the pumped storage power station; and They are the power generation and pumping status of the pumped storage power station, which are 0-1 variables; and are the power generation and pumping efficiency coefficients of the pumped storage power station, respectively; and They are the upper limits of power generation and pumping power of pumped-storage power stations respectively.

[0034] 2) Based on the price elasticity theory, considering the output power of each power supply equipment, a differentiated bidding model for each power generation and consumption equipment is constructed; The lower-level power generation and consumption equipment quotes to the upper-level power market through a bidding model. Since the operating costs of different power supply equipment are different, a differentiated pricing method is used to price each device. For example, the costs of wind and solar power generation are different from those of pumped storage power generation. It is not appropriate to price according to the costs of wind and solar power generation or according to the costs of pumped storage power generation. Based on this, this paper proposes that different power generation and consumption equipment adopt different pricing methods. For example, wind farms and photovoltaic power stations have lower power generation costs and quote lower prices to the upper-level power market; conversely, pumped storage power stations have higher power generation costs and quote higher prices to the upper-level power market. This differentiated pricing method can guide the upper-level power market to effectively absorb low-cost power sources, while ensuring economic operation, and improving the level of wind and solar power generation absorption. The differentiated pricing model is as follows.

[0035] A. Price model for power generation from wind farms and photovoltaic power stations In addition to the demand price elasticity factor, the formulation of the bidding for wind farms and photovoltaic power stations should also consider the issue of energy rights. For the party selling energy rights, it means that the cost of generating electricity for the unit is high at this time, and it is not economical to participate in the electricity market more, so some energy rights are sold to other equipment for profit. This indirectly reflects that the bidding price of this equipment is low, and the electricity market allocates more energy rights to this equipment based on price information. Therefore, in the next iteration, the energy rights sale factor should be considered to increase the bidding price of this equipment. Based on this, the price of wind and solar power generation can be described as: ; In the formula, Bidding prices for wind and solar; is the wind and solar price adjustment coefficient; The cost of wind and solar electricity; It is the upper limit of wind and solar prices; and They are respectively the energy right interaction power and energy right price adjustment coefficient between wind and solar power generation and other equipment. It should be noted that the energy right interaction power between the equipment has positive and negative values. The selling energy right is a positive value and the purchasing energy right is a negative value. The selling energy right will increase the bidding price of the equipment in the next iteration. On the contrary, purchasing energy right will reduce the bidding price of the equipment in the next iteration.

[0036] B. Pumped Storage Power Station Power Generation Price Model Pumped storage power stations are energy storage devices that participate in the electricity market only during the discharge period. Based on this, the power generation price model of pumped storage power stations can be described as: ; In the formula, bidding prices for pumped storage power stations; It is the price adjustment coefficient of power generation of pumped storage power station; The cost of generating electricity for pumped storage power stations; capping the price of electricity generated by pumped storage plants; and They are the energy rights interaction power and energy rights price adjustment coefficient between the pumped storage power station and other equipment; It is the discharge state of the pumped-storage power station, which is a 0-1 variable. When the discharge state is 1, the pumped-storage power station quotes to the electricity market; when the discharge state is 0, the pumped-storage power station does not quote to the electricity market.

[0037] Furthermore, the energy weight price model of each power generation and consumption equipment constructed in step 3 can be described as: ; In the formula, It is the price of energy rights exchange between various devices. It should be noted that the price of energy rights should meet the operating characteristics of each power supply equipment, and the price of energy rights exchange cannot be higher than the price quoted by the equipment with the lowest power generation cost to the power market. For example, in the process of power generation and consumption equipment quoting to the power market, wind and solar power generation have the lowest price, and the price of energy rights exchange cannot be higher than the price quoted by wind and solar power generation to the power market. The purpose is to prevent wind and solar power generation from selling all energy rights for profit, forming vicious price competition.

[0038] 4) Construct a two-layer optimization model for a multi-source joint system, where the lower layer is the power generation operator, i.e. wind farms, photovoltaic power stations, pumped storage power stations and other equipment, and the upper layer is the power market. The lower layer provides the upper layer with the clearing price and power of each device. The upper layer updates the clearing power according to the power market demand and transmits it to the lower layer, and the upper and lower layers iterate to solve the problem; A. Upper-level electricity market optimization model 1) Objective function The upper-level electricity market operation cost is the electricity purchase cost for the lower-level multi-source joint system, which is described as follows: ; 2) Constraints In addition, load satisfaction constraints are set to ensure that the electric load demand response operates within a reasonable range.

[0039] ; In the formula, for t The lower limit of power shift of electric load during the period; is the interruptible load ratio of the electrical load.

[0040] B. Lower-level multi-source joint system optimization model 1) Objective function The operating costs of the lower-level power generation operators include: the cost of wind and solar power abandonment and the income from selling electricity to the upper level. Combining the above costs, the operating costs of the upper-level power generation operators in a dispatch cycle are It can be expressed as: ; In the formula, is the cost of wind and solar power abandonment. The cost of wind and solar power abandonment can be expressed as: ; In the formula, is the penalty coefficient for wind and solar power abandonment, is the abandoned wind power; is the abandoned light power.

[0041] 2) Constraints At the same time, the lower-level multi-source joint system needs to meet the electricity demand of the upper-level power market, and the balance constraint is the electric power balance constraint, as follows.

[0042] ; In the formula, , and They are the initial electric load demand in the power market, the time-shiftable load power, and the interruptible load power.

[0043] For a certain node, the sum of the injected node power, the inflow node power, the outflow node power and the corresponding line network loss is 0. Based on this, the node power balance constraint can be expressed as: ; In the formula, and They are t Time j Node active and reactive power, and They are t Time jk Branch active and reactive power, for t Time jk Branch current, and They are ij Branch resistance and reactance.

[0044] The node voltage constraint can be described as: ; In the formula, For the distribution network branch, and are the voltage values ​​at nodes i and j respectively.

[0045] To facilitate the solution, this section converts the multi-source joint system power flow model into a second-order cone optimization model, which is compatible with CPELX efficient solution. The second-order cone model after the conversion is as follows: ; In the formula, is the two-norm.

[0046] The static VAR compensation (SVC) has the ability to absorb and generate inductive reactive power. The SVC operation constraints can be described as: ; In the formula, for t Time j Node SVC output reactive power, and They are the upper and lower limits of SVC output reactive power respectively.

[0047] Other constraints include three-phase distribution network current constraints, node voltage constraints, etc., as follows: ; In the formula, and They are t Time i Node generator active and reactive power, and They are i The upper and lower limits of the active output of the node generator, and They are i The upper and lower limits of the node generator reactive output.

[0048] 5) The CPLEX solver is used to iteratively solve the two-level optimization model of the multi-source joint system. The solution ends when the upper and lower layer costs no longer change.

[0049] The solution process of CPLEX in MATLAB is as follows Figure 3 As shown, the CPELX solver is used to minimize any objective function F The main steps can be described as: Step 1: Use heuristics to find a solution to the problem X . Stored Value Y = F ( X ). X will be marked as the best solution found so far and will be used as an upper bound for the candidate solutions.

[0050] Step 2: Initialize a queue to hold the partial solutions that do not contain problem variables.

[0051] Step 3: Loop until the queue is empty: (1) Get node NN from the queue; (2) If NN represents a single candidate solution X and F ( X )< Y ,but X This is the best solution so far. X And set Y ← F ( X ).

[0052] (3) Otherwise, branch on the NN node to generate a new node NN i , for each newly generated node, if, F ( NN i )> Y , keep the previous solution, otherwise, NN i Stored in a queue.

[0053] In the above method, a differentiated bidding model is proposed to set a separate price for each power generation and consumption equipment; at the same time, considering that energy rights can be traded between different equipment, equipment with sufficient energy rights can be sold to other equipment for profit, thus achieving mutual benefit and win-win results between power generation operators and power market operators.

[0054] The bidding mechanism, energy trading method and joint system two-tier dispatch method can achieve mutual benefit and win-win results between multi-source equipment and the power market through coordinated operation among various devices, and further improve energy utilization and the level of wind and solar power generation consumption.

[0055] The above-mentioned embodiments are only preferred technical solutions of the present invention and should not be regarded as limitations of the present invention. The embodiments and features in the embodiments of the present application can be arbitrarily combined with each other without conflict. The protection scope of the present invention shall be the technical solutions recorded in the claims, including the equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading, characterized in that: The steps include: S1, construct the operating characteristic models of the above equipment, including wind farm, photovoltaic power station and pumped storage power station models; S2, based on the price elasticity theory, considering the output power of each power supply equipment, constructs a differentiated bidding model for each power generation and consumption equipment; S3, based on the initial allocation plan of energy rights, build an energy rights trading mechanism between devices to realize the interaction of energy rights between multiple power generation and power consumption devices; S4, construct a two-layer optimization model for a multi-source joint system, where the upper layer is the power market and the lower layer is the power generation operator. The lower layer provides the clearing price and power of each device to the upper layer. The upper layer updates the clearing power according to the power market demand and transmits it to the lower layer, and the upper and lower layers iterate to solve the problem. S5, using CPLEX solver to iteratively solve the two-level optimization model of the multi-source joint system. When the upper and lower layer costs no longer change, the solution is completed.

2. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: exist In S1, in the wind farm model, the wind turbine output power and wind speed present a piecewise function relationship. P WT The actual wind speed v The functional relationship between them can be described as: ； Where: , and Respectively represent the cut-in wind speed, cut-out wind speed and rated wind speed; is the rated output power of the fan.

3. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: In S1, the Hay model is introduced into the photovoltaic power station model to consider the impact of different hemispheres on the sky diffuse radiation. The sky diffuse radiation of this model can be expressed as: ； Where: is the amount of scattered radiation in the air; is the scattered radiation on the horizontal surface; is the direct scattering amount on the horizontal plane; Direct radiation on the inclined surface / direct radiation on the horizontal surface; is the solar radiation at the horizontal surface outside the atmosphere; is the inclination angle; combined with the above formula, the formula for solar radiation on the inclined surface can be derived: ； Where: is the total radiation on the horizontal plane; is the reflectivity of the ground surface; In addition to the amount of solar radiation, the output power of photovoltaic power generation is also related to the power conversion efficiency of the solar panel and the area of ​​the solar panel exposed to radiation, as follows: ； Where: is the output power of photovoltaic power generation; is the energy conversion efficiency; is the radiation area.

4. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: In S1, in the pumped storage power station model, without considering the factors of water loss during the operation of the pumped storage power station, the operating constraints of the pumped storage power station and the pumping conditions can be specifically described as: the relationship between pumping, power generation, efficiency and head of the pumped storage power station under the pump-turbine power generation condition and pumping condition: ； Where: Electricity consumption for water pumping; is the amount of electricity generated; To regulate water volume; is the average pumping head; is the average water head for power generation; It is the pumping efficiency of the water turbine; is the power generation efficiency of the pump turbine; 367.2 is the conversion factor; the primary cycle efficiency of the pumped storage power station can be expressed as: ； Under power generation and pumping conditions, the output of the pumped storage power station is related to the flow rate, which can be described specifically as: ； Where: for t Power generation during the period; for t Power generation flow during the period; for t Water head under power generation status during the period; for t Power generation efficiency during the period; for t Pumping power during the period; for t Pumping flow rate during the period; for t Head under period pumping state; for t Pumping efficiency during the period; In addition, starting from the operation constraints of the pumped storage power station itself, the constraints of the pumped storage power station include state constraints, power constraints and extraction balance constraints, as follows: ； In the formula, and They are the upper and lower limits of the reservoir capacity of the pumped storage power station, respectively; is the initial capacity of the pumped storage power station; and They are the power generation and pumping power of the pumped storage power station; and They are the power generation and pumping status of the pumped storage power station, which are 0-1 variables; and They are the power generation and pumping efficiency of pumped storage power plants, respectively; and They are the upper limits of power generation and pumping power of pumped-storage power stations respectively.

5. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: In S2, the differentiated bidding models for various power generation and consumption equipment are constructed, including price models for wind farms, photovoltaic power stations, and pumped storage power stations. In the price models for wind farms and photovoltaic power stations, the prices for wind and photovoltaic power generation can be described as: ； In the formula, Bidding prices for wind and solar; is the wind and solar price adjustment coefficient; The cost of wind and solar electricity; It is the upper limit of wind and solar prices; and They are respectively the energy right interaction power and energy right price adjustment coefficient between wind and solar power generation and other equipment. It should be noted that the energy right interaction power between the equipment has positive and negative values. The selling energy right is a positive value and the purchasing energy right is a negative value. The selling energy right will increase the bidding price of the equipment in the next iteration. On the contrary, purchasing energy right will reduce the bidding price of the equipment in the next iteration.

6. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 5 is characterized by: In S2, the electricity price model of the hydropower station can be described as: ； In the formula, bidding prices for pumped storage power stations; It is the price adjustment coefficient of power generation of pumped storage power station; The cost of generating electricity for pumped storage power stations; capping the price of electricity generated by pumped storage plants; and They are the energy rights interaction power and energy rights price adjustment coefficient between the pumped storage power station and other equipment; It is the discharge state of the pumped-storage power station, which is a 0-1 variable. When the discharge state is 1, the pumped-storage power station quotes to the electricity market; when the discharge state is 0, the pumped-storage power station does not quote to the electricity market.

7. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: In S3, the energy price model of each power generation and consumption equipment can be described as: ； In the formula, It is the price of energy rights interaction between various devices; among which, the energy rights price should meet the operating characteristics of each power supply equipment, and the energy rights interaction price cannot be higher than the price quoted by the device with the lowest power generation cost to the power market.

8. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: In S4, the proposed multi-source joint system optimization scheduling model includes: A. Upper-level electricity market optimization model: 1) Objective function, The upper-level electricity market operation cost is the electricity purchase cost for the lower-level multi-source joint system, which is described as follows: ； 2) Constraints, In addition, load satisfaction constraints are set to ensure that the electric load demand response operates within a reasonable range; ； In the formula, for t The lower limit of power shift of electric load during the period; The interruptible load ratio of the electric load; B. Lower-level multi-source joint system optimization model, 1) Objective function, The operating costs of the lower-level power generation operators include: the cost of wind and solar power abandonment and the income from selling electricity to the upper level. Combining the above costs, the operating costs of the lower-level power generation operators in a dispatch cycle are It can be expressed as: ； In the formula, is the cost of wind and solar power abandonment; the cost of wind and solar power abandonment can be expressed as: ； In the formula, is the penalty coefficient for wind and solar power abandonment, is the abandoned wind power; is the abandoned optical power; 2) Constraints, At the same time, the lower-level multi-source joint system needs to meet the electricity demand of the upper-level power market, and the balance constraint is the electric power balance constraint, which is as follows: ； In the formula, , and They are the initial electric load demand, time-shiftable load power and interruptible load power in the power market; For a certain node, the sum of the injected node power, the inflow node power, the outflow node power and the corresponding line network loss is 0. Based on this, the node power balance constraint can be expressed as: ； In the formula, and They are t Time j Node active and reactive power, and They are t Time jk Branch active and reactive power, for t Time jk Branch current, and They are ij Branch resistance and reactance; The node voltage constraint can be described as: ； In the formula, For the distribution network branch, and are the voltage values ​​at nodes i and j respectively.

9. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 8 is characterized by: In S4, in order to facilitate the solution, the multi-source joint system power flow model is converted into a second-order cone optimization model, which is compatible with CPELX efficient solution; the second-order cone model after the conversion is as follows: ； In the formula, is the two-norm; The static VAR compensation (SVC) has the ability to absorb and generate inductive reactive power. The SVC operation constraints can be described as: ； In the formula, for t Time j Node SVC output reactive power, and They are the upper and lower limits of SVC output reactive power respectively; Other constraints include three-phase distribution network current constraints and node voltage constraints, as follows: ； In the formula, and They are t Time i Node generator active and reactive power, and They are i The upper and lower limits of the active output of the node generator, and They are i The upper and lower limits of reactive power output of node generators.

10. The method for operating a wind-solar-pumped-storage multi-source dual-layer joint system based on differentiated pricing and energy rights trading according to claim 1 is characterized by: In S5, the constructed optimization model is solved to obtain the optimal operation result, including the CPLEX solver solution steps, as follows: CPELX solver for minimizing arbitrary objective functions F The main steps are as follows: Step 1: Use heuristics to find a solution to the problem X ; Store value Y = F ( X ); X will be marked as the best solution found so far and used as an upper bound for the candidate solutions; Step 2: Initialize a queue to hold partial solutions that do not contain problem variables; Step 3: Loop until the queue is empty: Step 3-1, obtain node NN from the queue; Step 3-2, if NN represents a single candidate solution X and F ( X ) < Y ,but X This is the best solution so far. X And set Y ← F ( X ); Step 3-3, otherwise, branch on the NN node to generate a new node NN i , for each newly generated node, if, F ( NN i ) > Y , keep the previous solution, otherwise, NN i Stored in a queue.

Images