CN-121235227-B - Collaborative optimization method, system, equipment and medium based on virtual power plant operators and producers and consumers

CN121235227BCN 121235227 BCN121235227 BCN 121235227BCN-121235227-B

Abstract

The invention belongs to the technical field of power grids, and discloses a collaborative optimization method, a system, equipment and a medium based on a virtual power plant operator and a producer and a consumer, which comprises the following steps that S1, an electric carbon collaborative management framework of the virtual power plant operator and the producer and the consumer is established; the method comprises the steps of S2, constructing a double-layer game model based on the electricity-carbon collaborative management framework, wherein an upper layer is an operator, a lower layer is a generator, the operator calculates node marginal electricity price and node carbon intensity through optimal power flow and sends the node marginal electricity price and the node carbon intensity to the generator, the generator optimizes and dispatches the node marginal electricity price and the node carbon intensity and submits an electricity purchasing and selling curve, and S3, solving the double-layer game model by using a distributed iteration algorithm of a penalty function, and realizing self-adaptive optimization of model solving by introducing penalty items to obtain an optimal electricity-carbon collaborative strategy.

Inventors

YAO LI
NI LINNA
CHEN YUHAO
CHENG YING
SUN GANG
HUANG RONGGUO
LU CHUNGUANG
YU JIALI
JIANG CHI

Assignees

国网浙江省电力有限公司营销服务中心

Dates

Publication Date: 20260505
Application Date: 20251203

Claims (9)

1. A collaborative optimization method based on virtual power plant operators and producers and consumers is characterized by comprising the following steps: S1, establishing an electric-carbon collaborative management framework of a virtual power plant operator and a producer and a consumer; S2, constructing a double-layer game model based on the electricity-carbon collaborative management framework, wherein the upper layer is an operator, the lower layer is a power producer and a power consumer, the operator calculates the node marginal electricity price and the node carbon intensity through the optimal power flow and issues the node marginal electricity price and the node carbon intensity to the power producer and the power consumer, and the power consumer optimizes and dispatches the node marginal electricity price and the node carbon intensity and submits an electricity purchasing and selling curve; S3, solving the double-layer game model by using a distributed iterative algorithm of a penalty function, and realizing self-adaptive optimization of model solving by introducing a penalty term to obtain an optimal electric carbon cooperative strategy; In step S3, a game problem solving algorithm based on a penalty function is constructed to accelerate the solving process, and a penalty term is added in the objective function of the producer and the consumer based on the penalty function method, as shown in the following formula: (20) Wherein, the The iteration times; The power purchasing power of the generator m at the time t and the kth iteration is used; the power selling of the generator m at the time t and the kth iteration is carried out; For producing and eliminating m in the first place Penalty term at the time of iteration; Is a first order and a second order penalty factor, wherein The calculation mode of (a) is defined as follows: (21) Wherein, the The method is an exponential decay function, and is used for enabling a second order penalty factor to be smoothly adjusted along with the reduction of iteration residual errors, and e is a natural constant; the residual scaling factor of the kth iteration is used for adjusting the magnitude of a residual index and controlling the variation amplitude of a penalty factor; As an intermediate variable, the number of the variables, The value of (2) is in the range of (0, 1), which means For the following The increase in (2) is very sensitive, and its value increases rapidly with the iteration residual, thus accelerating the convergence of the gaming process, and at the same time, Is defined as follows: (22) Wherein, the Representation of When the first layer game problem is in the iterative solving process Second iteration and first -When the residual at each moment between 1 iteration is smaller than the set threshold, it is considered to reach an equilibrium state, as follows: (23)。
2. The collaborative optimization method based on a virtual power plant operator and a generator and eliminator according to claim 1, wherein in the two-layer game model, objective functions of the virtual power plant operator comprise power generation cost, external electricity purchase cost, transaction cost with the generator and step-type carbon cost, and constraint conditions comprise node power balance, branch tidal current limit and generator output upper and lower limits.
3. The virtual power plant operator and consumer based collaborative optimization method according to claim 1, wherein the consumer resource scheduling optimization includes collaborative scheduling of photovoltaic, wind power, micro gas turbines, energy storage systems, electric vehicles and flexible loads with the goal of minimizing the sum of electricity costs and carbon trade costs.
4. The collaborative optimization method based on the virtual power plant operators and the generator and the eliminator according to claim 1, wherein the influence of the renewable energy DRG output and the load prediction error of the generator and the eliminator on the operation of the generator and the eliminator is dealt with by adopting an opportunity constraint method, and the opportunity constraint converts the original rigidity constraint into an elastic constraint, namely, the probability of setting the rigidity constraint to be satisfied is not less than a certain given confidence level And simultaneously performing opportunistic constraint conversion on the uncertainty of the source load, wherein the method is as follows: (16) (17) (18) Wherein, the Is the probability of an event occurring; Confidence level for producer m; Net required power at time t for producer m; An amount of power supplied to the interior of the consumer; Respectively generating photovoltaic output, wind power output and micro gas turbine output of the generator m at the time t; 、 the purchase and the selling power of the producer and the consumer m at the time t are respectively; respectively the ESS discharging power and the ESS charging power of the generator m at the time t; the discharge power and the charge power at time t are EVz respectively; 、 TL power transfer in and TL power transfer out at time t are respectively taken as power producer m; EV set for producer m; Reducing power for the IL of producer m at time t; base load power at time t for producer m.
5. The collaborative optimization method based on the virtual power plant operator and the production and elimination person according to claim 1, further comprising the following steps of S4, constructing a P2P secondary carbon trade market, wherein in the secondary carbon trade market, the carbon quota CEP report of the production and elimination person is constrained by the net difference between the initial free quota and the actual emission, and the quotation model integrates historical price, local supply and demand difference and carbon emission assessment performance pressure, wherein the performance pressure is exponentially increased along with the approaching of the assessment period.
6. The collaborative optimization method based on the virtual power plant operator and the producer and the consumer according to claim 5, wherein the secondary carbon trading market has a clearing rule that the virtual power plant operator matches carbon quota buyers and sellers with the aim of maximizing social benefit, and the trading price is an arithmetic average of winning bid price.
7. A virtual power plant operator and consumer based collaborative optimization system for implementing a virtual power plant operator and consumer based collaborative optimization method according to any of claims 1-6.
8. A computer device comprising a memory, a processor and a computer program, wherein the computer program when executed by the processor implements a virtual power plant operator and producer-consumer based co-optimization method according to any of claims 1-6.
9. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements a virtual power plant operator and consumer based co-optimization method according to any of claims 1-6.

Description

Collaborative optimization method, system, equipment and medium based on virtual power plant operators and producers and consumers Technical Field The invention belongs to the technical field of power grids, and particularly relates to a collaborative optimization method, a collaborative optimization system, collaborative optimization equipment and a collaborative optimization medium based on a virtual power plant operator and a producer. Background In the technical field of power grids, low-carbon transformation of a power system is achieved, the core development goal of the industry is achieved, the permeability of a distributed renewable energy DRG in a power distribution network is continuously improved, and the trend promotes traditional power users to gradually transform to producers and consumers with power production and consumption capabilities. The generator can effectively improve the energy utilization efficiency of the whole power system by integrating the self power generation resource, the energy storage system ESS, the flexible load and other factors. Under the background, the bidirectional energy exchange mode in the power distribution network is mature, a carbon transaction mechanism is also gradually integrated into the power distribution network to operate, and the occurrence of the virtual power plant provides an important carrier for hidden energy sharing among producers and consumers. However, a complete electric-carbon collaborative management scheme is still lacking in the existing distribution network operation management, and it is difficult to simultaneously meet the decarburization requirement of the local distribution network system and the efficient digestion and collaborative operation targets of a large number of DRGs. The traditional centralized management method is long in calculation time, and the requirements of producers and consumers of different benefit subjects on individual benefit maximization are not fully considered, and the highly distributed management method is easy to violate distribution network operation constraint, so that a scheduling result is in a suboptimal state. Under the layered management framework, the existing research mostly models double-layer games between a virtual power plant operator and a producer and a consumer as an equilibrium problem with equilibrium constraint, but the method needs to acquire detailed equipment operation information inside the producer and consumer, faces great difficulty in practical application, and does not effectively solve the influence caused by the operation uncertainty of the producer and consumer. Therefore, there is a need for an electric-carbon collaborative optimization scheme between virtual power plant operators and producers and consumers. Disclosure of Invention Aiming at the problems existing in the prior art, the application provides a collaborative optimization method, a system, equipment and a medium based on a virtual power plant operator and a producer and a consumer, by collaborative management of electricity and carbon between the virtual power plant operator and the producer and consumer, the operation uncertainty of the producer and consumer, the CEF model application of a distribution network layer and distribution network layer carbon emission factor model and a game equilibrium solution algorithm based on privacy protection are considered, and the self-adaptive optimization of model solution is realized by introducing penalty items, so that an optimal electricity and carbon collaborative strategy is obtained. In order to achieve the above object, the present application provides the following technical solutions: A collaborative optimization method, system, equipment and medium based on a virtual power plant operator and a producer and a consumer comprise the following steps of S1, establishing an electric carbon collaborative management framework of the virtual power plant operator and the producer and consumer, S2, constructing a double-layer game model based on the electric carbon collaborative management framework, wherein the upper layer is an operator, the lower layer is the producer and consumer, the operator calculates node marginal electricity price and node carbon intensity through optimal power flow and issues the node marginal electricity price and the node carbon intensity to the producer and consumer, the consumer optimizes scheduling based on the node marginal electricity price and the node carbon intensity and submits an electricity purchasing and selling curve, and S3, solving the double-layer game model through a distributed iteration algorithm of a penalty function, and realizing self-adaptive optimization of model solving through introducing penalty items to obtain an optimal electric carbon collaborative strategy. Optionally, in the double-layer game model, the objective function of the virtual power plant operator includes power generation cost, external power purchas