Direct current transmission network planning method and device of offshore wind plant, terminal equipment and storage medium

Abstract

The invention discloses a DC power transmission network planning method and device for an offshore wind plant, terminal equipment and a storage medium, and the method comprises the steps: constructing an event occurrence probability function of a plurality of uncertain events affecting the power generation of the offshore wind plant, and generating a plurality of target events of the offshore wind plant in a plurality of preset operation scenes; the corresponding event occurrence probability is obtained; constructing a planning objective function according to the operation scene, the target event, the event occurrence probability and the initial planning scheme; and under a plurality of constraint conditions, taking the result minimization of the planning target function as a target, optimizing the initial planning scheme, and when the minimum value of the result of the planning target function is obtained, determining the corresponding planning scheme as the target planning scheme of the offshore wind plant. Therefore, the method specifically considers the power generation uncertainty of the offshore wind power plant to plan the offshore direct-current power transmission network, and the feasibility of a direct-current power transmission network planning scheme is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method, device, terminal equipment and storage medium for planning a direct current transmission network of an offshore wind farm. Background Art

[0002] The successful integration of wind power, especially offshore wind resources, relies heavily on transmission network planning. The purpose of offshore transmission network planning (TNP) is to identify an implementable and robust solution for the transmission network enhancements required to exploit remote wind energy, provide the necessary operational flexibility for changing the generation mix, and improve the resilience of the power system to unexpected events. To date, existing offshore wind energy has generally been exported through medium-voltage AC transmission networks, reflecting economic or technical limitations. But given the limited offshore wind resources and the constraints on long-distance transmission, the question arises whether AC transmission technology is still suitable for long-term use.

[0003] Many companies are now beginning to reevaluate previous decisions, especially since the limited capacity of AC submarine cables due to capacitive charging currents makes AC transmission the obvious choice for connecting remote offshore wind farms. The continued decline in the adequacy of AC power transmission has been clearly observed due to recent advances in the integration of remote non-dispatchable and non-fossil fuel generation, and DC power transmission systems are making a comeback on their own merits. However, when planning DC transmission networks, the uncertainty of offshore wind farm power generation is often ignored, which is extremely susceptible to uncertain factors such as the environment, which ultimately makes the planning scheme of the generated DC transmission network difficult to implement. Summary of the invention

[0004] The embodiments of the present invention provide a method, apparatus, terminal equipment and storage medium for planning a DC transmission network of an offshore wind farm. By constructing a distribution function of uncertain events that affect power generation of the offshore wind farm, target events that will occur in the offshore wind farm under several preset operating scenarios and the corresponding event occurrence probabilities are determined. The uncertainty of power generation of the offshore wind farm is specifically considered to plan the offshore DC transmission network, thereby improving the feasibility of the DC transmission network planning scheme.

[0005] An embodiment of the present invention provides a method for planning a DC transmission network of an offshore wind farm, comprising:

[0006] Obtain historical load data, historical wind data, historical fault data, and initial planning scheme of the offshore wind farm to be planned;

[0007] Constructing an event occurrence probability function of a plurality of uncertain events affecting power generation of the offshore wind farm according to the historical load data, the historical wind power data, and the historical fault data;

[0008] According to the event occurrence probability function, generating a plurality of target events occurring in the offshore wind farm under a plurality of preset operation scenarios, and the event occurrence probability of each target event;

[0009] Constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the direct current transmission network;

[0010] Under a number of preset constraints, with the goal of minimizing the result of the planning objective function, optimizing the initial planning scheme until the minimum value of the result of the planning objective function is obtained;

[0011] The planning scheme corresponding to the minimum value of the planning objective function result is determined as the target planning scheme of the direct current transmission network of the offshore wind farm.

[0012] Furthermore, the uncertain events include: load change events, wind power change events, and sudden failure events; the event occurrence probability function includes: a first probability distribution function, a second probability distribution function, and a third probability distribution function;

[0013] The constructing, based on the historical load data, the historical wind power data, and the historical fault data, an event occurrence probability function of a plurality of uncertain events that affect the power generation of the offshore wind farm comprises:

[0014] Using the Weibull distribution function to construct a first probability distribution function for characterizing the occurrence of a wind change event according to the historical wind data;

[0015] Using a Gaussian distribution function to construct a second probability distribution function for characterizing a load change event according to the historical load data;

[0016] A third probability distribution function for characterizing the occurrence of a sudden failure event is constructed based on the historical failure data using binomial distribution.

[0017] Further, the planning objective function includes: an investment cost sub-function, an operation cost sub-function, and an emergency cost sub-function;

[0018] The constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme includes:

[0019] According to the initial planning scheme, construct an investment cost sub-function for calculating the investment cost required to construct the DC transmission network;

[0020] According to the operation scenario, constructing an operation cost sub-function for calculating the operation cost required for the normal operation of the offshore wind farm in each operation scenario;

[0021] According to the operation scenarios, the target events, and the probability of occurrence of the events, an emergency cost sub-function is constructed for calculating the emergency cost required for the offshore wind farm to cope with each target event in each operation scenario.

[0022] Furthermore, the initial planning scheme includes: initial planning route, planning period, device cost, operation cost, and emergency cost;

[0023] The step of optimizing the initial planning scheme under a plurality of preset constraints with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained includes:

[0024] According to the initial planning scheme, the scheme optimization operation is repeatedly performed until the minimum value of the result of the planning objective function is generated;

[0025] The scheme optimization operation includes:

[0026] Obtaining a plan to be optimized; wherein the plan to be optimized includes: a planned route to be optimized, a planned period, a device cost, an operating cost, and an emergency cost; initially, the plan to be optimized is an initial planning plan, and the planned route to be optimized is an initial planning route;

[0027] According to the probability of occurrence of the event, the operation scenario, and the target event, several scheduling schemes for the offshore wind farm using the to-be-planned line to deal with each of the target events in each of the operation scenarios are generated; wherein the several scheduling schemes all satisfy the constraint conditions;

[0028] Calculate the result of the planning objective function according to the scheduling scheme, the planned route to be optimized, the planned period, the device cost, the operating cost, and the emergency cost;

[0029] When it is determined that the result is less than a preset threshold, determining a minimum value of the result of generating the planning objective function;

[0030] When it is determined that the result is not less than a preset threshold, a new planned route is regenerated as the route to be optimized required for the next round of scheme optimization operation; wherein the new planned route is different from the planned route to be optimized.

[0031] Further, the calculation of the result of the planning objective function according to the scheduling scheme, the planned route to be optimized, the planned period, the device cost, the operating cost, and the emergency cost includes:

[0032] Using the investment cost sub-function, according to the planned route to be optimized and the device cost, calculate the total investment cost to be evaluated;

[0033] Using an operating cost sub-function, according to the planned route to be optimized, the planned years, and the operating cost, the total operating cost to be evaluated is calculated;

[0034] Using the emergency cost sub-function, according to the scheduling scheme, the planned period, and the emergency cost, the total emergency cost to be evaluated is calculated;

[0035] The result of the planning objective function is generated according to the total investment cost to be evaluated, the total operating cost to be evaluated, and the total emergency cost to be evaluated.

[0036] Another embodiment of the present invention provides a DC transmission network planning device for an offshore wind farm, comprising:

[0037] A data acquisition module is used to obtain historical load data, historical wind data, historical fault data, and initial planning scheme of the offshore wind farm to be planned;

[0038] A first function construction module, configured to construct an event occurrence probability function of a plurality of uncertain events affecting power generation of the offshore wind farm according to the historical load data, the historical wind power data, and the historical fault data;

[0039] An event calculation module, used to generate a plurality of target events occurring in the offshore wind farm under a plurality of preset operation scenarios and an event occurrence probability of each target event according to the event occurrence probability function;

[0040] A second function construction module is used to construct a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the DC transmission network;

[0041] A scheme optimization module is used to optimize the initial planning scheme under a number of preset constraints with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained;

[0042] The scheme generating module determines, according to the planning scheme corresponding to the minimum value of the planning objective function result, the target planning scheme of the direct current transmission network of the offshore wind farm.

[0043] Furthermore, the uncertain events include: load change events, wind power change events, and sudden failure events; the event occurrence probability function includes: a first probability distribution function, a second probability distribution function, and a third probability distribution function;

[0044] The constructing, based on the historical load data, the historical wind power data, and the historical fault data, an event occurrence probability function of a plurality of uncertain events that affect the power generation of the offshore wind farm comprises:

[0045] Using the Weibull distribution function to construct a first probability distribution function for characterizing the occurrence of a wind change event according to the historical wind data;

[0046] Using a Gaussian distribution function to construct a second probability distribution function for characterizing a load change event according to the historical load data;

[0047] A third probability distribution function for characterizing the occurrence of a sudden failure event is constructed based on the historical failure data using binomial distribution.

[0048] Further, the planning objective function includes: an investment cost sub-function, an operation cost sub-function, and an emergency cost sub-function;

[0049] The constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme includes:

[0050] According to the initial planning scheme, construct an investment cost sub-function for calculating the investment cost required to construct the DC transmission network;

[0051] According to the operation scenario, constructing an operation cost sub-function for calculating the operation cost required for the normal operation of the offshore wind farm in each operation scenario;

[0052] According to the operation scenarios, the target events, and the probability of occurrence of the events, an emergency cost sub-function is constructed for calculating the emergency cost required for the offshore wind farm to cope with each target event in each operation scenario.

[0053] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a method for planning a DC transmission network for an offshore wind farm as described in any one of the embodiments is implemented.

[0054] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a DC transmission network planning method for an offshore wind farm as described in any one of the above embodiments.

[0055] The following beneficial effects are achieved by implementing the present invention:

[0056] The present invention discloses a direct current transmission network planning method, device, terminal equipment and storage medium for an offshore wind farm. The method comprises the following steps: constructing an event occurrence probability function of several uncertain events that affect the power generation of the offshore wind farm according to historical load data, historical wind power data and historical fault data of the offshore wind farm to be planned; generating several target events that occur in the offshore wind farm under several preset operation scenarios according to the event occurrence probability function, and the event occurrence probability of each target event; constructing a planning objective function according to the operation scenario, the target event, the event occurrence probability and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the direct current transmission network; optimizing the initial planning scheme with the goal of minimizing the result of the planning objective function under several preset constraint conditions until the minimum value of the result of the planning objective function is obtained; and determining the planning scheme corresponding to the minimum value of the result of the planning objective function as the target planning scheme of the offshore wind farm. Therefore, the present invention determines the target events that will occur in the offshore wind farm under several preset operating scenarios and the corresponding probability of occurrence of the events by constructing a distribution function of uncertain events that affect the power generation of the offshore wind farm. The uncertainty of the power generation of the offshore wind farm is specifically considered to plan the offshore DC transmission network, thereby improving the feasibility of the DC transmission network planning scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a flow chart of a method for planning a direct current transmission network for an offshore wind farm provided in one embodiment of the present invention.

[0058] Figure 2 It is a structural schematic diagram of a DC transmission network planning device for an offshore wind farm provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0061] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0062] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0063] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0064] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0065] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0066] See also Figure 1 , is a flow chart of a method for planning a DC transmission network for an offshore wind farm provided by an embodiment of the present invention, comprising:

[0067] S1. Obtain historical load data, historical wind power data, historical fault data, and initial planning scheme of the offshore wind farm to be planned;

[0068] S2. constructing an event occurrence probability function of a number of uncertain events that affect power generation at the offshore wind farm based on the historical load data, the historical wind power data, and the historical fault data;

[0069] Preferably, the uncertain events include: load change events, wind power change events, and sudden failure events; the event occurrence probability function includes: a first probability distribution function, a second probability distribution function, and a third probability distribution function;

[0070] The constructing, based on the historical load data, the historical wind power data, and the historical fault data, an event occurrence probability function of a plurality of uncertain events that affect the power generation of the offshore wind farm comprises:

[0071] S21, constructing a first probability distribution function for characterizing a wind change event according to the historical wind data using a Weibull distribution function;

[0072] S22, using a Gaussian distribution function to construct a second probability distribution function for characterizing a load change event according to the historical load data;

[0073] S23: constructing a third probability distribution function for characterizing the occurrence of a sudden failure event according to the historical failure data using binomial distribution.

[0074] In a preferred embodiment of the present invention, one of the key challenges of transmission planning is how to explicitly represent the extensive uncertainties associated with power system operation, which adds complexity to the development of existing planning models. In the scope of transmission planning, the main sources of uncertainty faced by decision makers are system demand, variable generation, component outages, demand-side control, government policies, etc. This embodiment takes into account load change events, intermittent generation events, i.e. wind change events, generator forced shutdown events, and transmission line outage emergencies, i.e. fault emergencies.

[0075] Probabilistic methods usually use a probability distribution function (PDF) of one or some or all parameters in the simulation. This embodiment performs uncertainty modeling and probability distribution of system load and renewable generation based on the characteristics of the system load and renewable generation profile. Both load and wind speed are modeled using Gaussian distribution and Weibull distribution. The generation of random loads is based on the assumption that all loads follow a Gaussian distribution independently from a long-term perspective, where a given demand level is used as an average. The corresponding probability distribution function is given in the following formula. The wind power generation pattern generates uncertainty about the flow of electricity, and subsequently, parts of the network will be restricted. Weibull distribution is used to model wind speed uncertainty.

[0076] The following equations provide the probability distribution functions for Gaussian and Weibull distributions, respectively.

[0077]

[0078] Where: represents the probability distribution function based on Gaussian distribution of random load, i.e., the second probability distribution function; f(x|λ i ,δ i ) represents the probability distribution function of wind speed uncertainty based on Weibull distribution, i.e., the first probability distribution function; μ i ,σ i is the parameter in Gaussian distribution; i ,ζ i is the parameter of the Weibull distribution.

[0079] The power flow will also vary greatly with planned or unplanned outages of system components. The present invention considers multiple levels of contingencies, and a variety of contingencies can be selected based on the operating criteria. The present invention uses a binomial distribution to model generator forced outages and transmission line outages:

[0080]

[0081] Where: f(x|θ i ,τ i ) represents the probability distribution function of generator forced shutdown and transmission line shutdown based on binomial distribution, i.e., the third probability distribution function; θ i ,τ i is the parameter of the binomial distribution.

[0082] S3. generating, according to the event occurrence probability function, a number of target events occurring in the offshore wind farm under a number of preset operation scenarios, and the event occurrence probability of each target event;

[0083] In a preferred embodiment of the present invention, current transmission planning standards use an 'N-1' or 'N-2' criterion that checks for all credible single or multiple unit outages and ensures sufficient redundancy so that supply is not interrupted even if an element in the network fails. Unexpected events that cause network load or bus voltage to exceed their limits should be identified, and corrective control measures should be determined under a wide range of scenarios. To improve computational efficiency, the present invention uses a fast screening method to identify possible limitations under different configurations and introduces a hierarchical contingency list. It provides a very fast approximation of fault severity without the need for runtime domain simulation, greatly reducing the computational time of planning studies.

[0084] The method quickly scans for potential component failures under heavy load conditions and identifies the most severe component failures. The main goal of the contingency analysis is to screen a selected set of contingencies and identify any that would result in: potential steady-state voltage instability, meet cascade trip criteria, and exceed any emergency or normal thermal overvoltage limits.

[0085] S4. Constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the DC transmission network;

[0086] Preferably, the planning objective function includes: an investment cost sub-function, an operation cost sub-function, and an emergency cost sub-function;

[0087] The constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme includes:

[0088] S41. constructing an investment cost sub-function for calculating the investment cost required for constructing a DC transmission network according to the initial planning scheme;

[0089] S42. Constructing, according to the operation scenario, an operation cost sub-function for calculating the operation cost required for the normal operation of the offshore wind farm in each operation scenario;

[0090] S43. Constructing an emergency cost sub-function for calculating the emergency cost required for the offshore wind farm to cope with each target event in each of the operation scenarios according to the operation scenarios, the target events, and the probability of occurrence of the events.

[0091] In a preferred embodiment of the present invention, the objective function: The formulated objective is given in the following formula, which can be decomposed into two layers, an upper layer investment problem and a lower layer operation problem.

[0092]

[0093] Where: d is the discount rate; N T N is the planning years; S is the number of scenes; N G is the number of controllable generators; N K is the number of unexpected events; N L is the compressible load quantity; ρ s represents the accidental probability of scene s; ρ k,s,t represents the probability of contingency of scenario s in planning year t when in state k; represents the investment cost of bus ij, including transmission lines, transformers, converter stations and compensation devices; represents the estimated operating cost of the controllable generator g in the planning year t under scenario s, including the fuel cost of the controllable generator and the wind turbine; represents the estimated generator redispatch cost of controllable generator g in planning year t under state k and scenario s; represents the expected load reduction cost of the compressible load l in the planning year t under state k and scenario s; is the fuel cost coefficient of generator g; represents the active power output of controllable generator g in planning year t under scenario s; It represents the fluctuation of controllable generator g in the planning period t under state k and scenario s; is the decision variable of the candidate DC transmission line between busbars i and j (1 for the planned line, 0 otherwise); VSC is the voltage source converter coefficient; It represents the load reduction of compressible load l in the planned year t under state k and scenario s.

[0094] The objective function contains three cost-related terms: (1) The first term is the investment cost sub-function, which gives the total investment cost of the offshore transmission system network solution. The investment includes DC submarine cables, transformers, reactive compensation devices or converter stations. The cost of each component depends on its voltage level and capacity. (2) The second term is the operating cost sub-function, which is the sum of the fuel costs of the generators under each operating scenario. (3) The third term is the emergency cost sub-function, which is the total expected cost of control measures in emergency situations, including generation redispatch and load reduction. Although a large amount of additional renewable energy capacity has been committed, there is still a risk of load reduction after an unexpected event. During the planning process, the customer reliability value (unit: $ / MWh) is used to evaluate the economic benefits of network development projects. It represents a range of customers' willingness to pay for reliable electricity supply. All these costs in the objective function are discounted to present value.

[0095] S5. Under a plurality of preset constraints, with the goal of minimizing the result of the planning objective function, optimizing the initial planning scheme until the minimum value of the result of the planning objective function is obtained;

[0096] Preferably, the initial planning scheme includes: initial planning route, planning period, device cost, operation cost, and emergency cost;

[0097] The step of optimizing the initial planning scheme under a plurality of preset constraints with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained includes:

[0098] S51, repeating the scheme optimization operation according to the initial planning scheme until the minimum value of the result of the planning objective function is generated;

[0099] The scheme optimization operation includes:

[0100] S511, obtaining a plan to be optimized; wherein the plan to be optimized includes: a planned route to be optimized, a planned period, a device cost, an operating cost, and an emergency cost; initially, the plan to be optimized is an initial planning plan, and the planned route to be optimized is an initial planning route;

[0101] S512, generating, according to the probability of occurrence of the event, the operation scenario, and the target event, several scheduling schemes for the offshore wind farm using the to-be-planned line to deal with each of the target events in each of the operation scenarios; wherein the several scheduling schemes all satisfy the constraint condition;

[0102] S513, calculating the result of the planning objective function according to the scheduling scheme, the planned route to be optimized, the planned period, the device cost, the operating cost, and the emergency cost;

[0103] Preferably, the calculation of the result of the planning objective function according to the scheduling scheme, the planned route to be optimized, the planned period, the device cost, the operating cost, and the emergency cost includes:

[0104] S5131, using the investment cost sub-function, according to the planned line to be optimized and the device cost, calculating the total investment cost to be evaluated;

[0105] S5132, using the operating cost sub-function, according to the planned route to be optimized, the planned years, and the operating cost, calculating the total operating cost to be evaluated;

[0106] S5133, using the emergency cost sub-function, according to the scheduling plan, the planned years, and the emergency cost, calculate the total emergency cost to be evaluated;

[0107] S5134. Generate a result of the planning objective function according to the total investment cost to be evaluated, the total operating cost to be evaluated, and the total emergency cost to be evaluated.

[0108] S514, when it is determined that the result is less than a preset threshold, determining a minimum value of the result of generating the planning objective function;

[0109] S515. When it is determined that the result is not less than a preset threshold, a new planned route is regenerated as the route to be optimized required for the next round of scheme optimization operation; wherein the new planned route is different from the planned route to be optimized.

[0110] In a preferred embodiment of the present invention, the constraints include transmission construction constraints, power flow constraints, generation scheduling constraints and power balance. In order to consider the planning horizon and sub-period, the variables in all constraints accept superscripts t and h.

[0111] ① Power balance constraints:

[0112]

[0113] Where: They are the active power output of bus i of DC grid and wind power generation in state k respectively; are the voltage amplitudes of DC bus i and j in state k respectively; is the conductance between DC bus i and DC bus j in state k; is the number of DC lines.

[0114] ②Generator capacity constraints:

[0115]

[0116] Where: They are the lower limit and upper limit of the active power output of the controllable generator g respectively.

[0117] ③Bus voltage constraints:

[0118]

[0119] Where: v i dc , are the lower and upper limits of the DC bus voltage amplitude respectively.

[0120] ④ Generator ramp limit and load reduction constraints:

[0121]

[0122] Where: and They are the output change and active load reduction before and after the accident respectively; are the lower and upper bounds of the output change before and after the accident respectively; are the lower and upper limits of the active load reduction before and after the accident respectively; Ω G is the controllable generator set in the power grid; Ω L is the set of curtailable loads in the grid; each contingency must satisfy all constraints.

[0123] ⑤ Line flow constraints:

[0124]

[0125] Where: are the lower and upper limits of the DC line power flow connecting DC busbars i and j, respectively.

[0126] It should be noted that this embodiment uses a remedial action plan to generate several scheduling schemes for the offshore wind farm using the planned line to deal with each of the target events in each of the operation scenarios. Specifically, by detecting abnormal power system conditions and taking predetermined or designed actions to prevent these conditions from escalating into system-wide disturbances. After any element outage, such as during maintenance or after a forced outage, the ISO will apply stricter constraints within a short adjustment period to predict the impact of further emergencies. This requires rescheduling generators and dispatchable loads, and reducing loads in the absence of other alternatives.

[0127] Due to the rapid controllability of VSCs, the DC power system can be controlled to affect the power flow in a shorter time. As the DC grid continues to develop, remedial action planning becomes a key tool because it controls the power flow to provide acceptable control actions. In fact, the ability to control the power flow is one of the advantages of DC transmission. In the present invention, power flow control, generator re-dispatch and load shedding are considered as potential remedial action plan actions, which can help balance demand and supply after one or more system components are out of service.

[0128] S6. Determine the planning scheme corresponding to the minimum value of the planning objective function result as the target planning scheme of the direct current transmission network of the offshore wind farm.

[0129] The present embodiment provides a method for planning a DC transmission network of an offshore wind farm, which constructs an event occurrence probability function of several uncertain events that affect the power generation of the offshore wind farm according to historical load data, historical wind power data, and historical fault data of the offshore wind farm to be planned; generates several target events that occur in the offshore wind farm under several preset operating scenarios and the event occurrence probability of each target event according to the event occurrence probability function; constructs a planning objective function according to the operating scenario, the target event, the event occurrence probability, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the DC transmission network; under several preset constraint conditions, the initial planning scheme is optimized with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained; and the planning scheme corresponding to the minimum value of the result of the planning objective function is determined as the target planning scheme of the offshore wind farm. Therefore, the present invention determines the target events that will occur in the offshore wind farm under several preset operating scenarios and the corresponding probability of occurrence of the events by constructing a distribution function of uncertain events that affect the power generation of the offshore wind farm. The uncertainty of the power generation of the offshore wind farm is specifically considered to plan the offshore DC transmission network, thereby improving the feasibility of the DC transmission network planning scheme.

[0130] See also Figure 2 , is a schematic diagram of the structure of a DC transmission network planning device for an offshore wind farm provided by an embodiment of the present invention, comprising:

[0131] A data acquisition module is used to obtain historical load data, historical wind data, historical fault data, and initial planning scheme of the offshore wind farm to be planned;

[0132] A first function construction module, configured to construct an event occurrence probability function of a plurality of uncertain events affecting power generation of the offshore wind farm according to the historical load data, the historical wind power data, and the historical fault data;

[0133] An event calculation module, used to generate a plurality of target events occurring in the offshore wind farm under a plurality of preset operation scenarios and an event occurrence probability of each target event according to the event occurrence probability function;

[0134] A second function construction module is used to construct a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the DC transmission network;

[0135] A scheme optimization module is used to optimize the initial planning scheme under a number of preset constraints with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained;

[0136] The scheme generating module determines, according to the planning scheme corresponding to the minimum value of the planning objective function result, the target planning scheme of the direct current transmission network of the offshore wind farm.

[0137] Further, the uncertain events include: load change events, wind power change events, generator forced shutdown events, and transmission line outage emergencies; the event occurrence probability function includes: a first probability distribution function, a second probability distribution function, a third probability distribution function, and a fourth probability distribution function;

[0138] The constructing, based on the historical load data, the historical wind power data, and the historical fault data, an event occurrence probability function of a plurality of uncertain events that affect the power generation of the offshore wind farm comprises:

[0139] Using the Weibull distribution function to construct a first probability distribution function for characterizing the occurrence of a wind change event according to the historical wind data;

[0140] Using a Gaussian distribution function to construct a second probability distribution function for characterizing a load change event according to the historical load data;

[0141] A third probability distribution function for characterizing the occurrence of a generator forced shutdown event and a fourth probability distribution function for characterizing the occurrence of a transmission line outage emergency event are constructed based on the historical fault data using binomial distribution.

[0142] Further, the planning objective function includes: an investment cost sub-function, an operation cost sub-function, and an emergency cost sub-function;

[0143] The constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme includes:

[0144] According to the initial planning scheme, construct an investment cost sub-function for calculating the investment cost required to construct the DC transmission network;

[0145] According to the operation scenario, constructing an operation cost sub-function for calculating the operation cost required for the normal operation of the offshore wind farm in each operation scenario;

[0146] According to the operation scenarios, the target events, and the probability of occurrence of the events, an emergency cost sub-function is constructed for calculating the emergency cost required for the offshore wind farm to cope with each target event in each operation scenario.

[0147] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0148] Those skilled in the art can clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0149] Another preferred embodiment of the present invention provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a method for planning a DC transmission network for an offshore wind farm as described in any one of the above embodiments is implemented.

[0150] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0151] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0152] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Med i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0153] Another preferred embodiment of the present invention provides a storage medium, the storage medium is a computer-readable storage medium, the computer program is stored in the computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0154] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for planning a DC transmission network for an offshore wind farm, characterized in that: include: Obtain historical load data, historical wind data, historical fault data, and initial planning scheme of the offshore wind farm to be planned; Constructing an event occurrence probability function of a plurality of uncertain events affecting power generation of the offshore wind farm according to the historical load data, the historical wind power data, and the historical fault data; According to the event occurrence probability function, generating a plurality of target events occurring in the offshore wind farm under a plurality of preset operation scenarios, and the event occurrence probability of each target event; Constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the direct current transmission network; Under a number of preset constraints, with the goal of minimizing the result of the planning objective function, optimizing the initial planning scheme until the minimum value of the result of the planning objective function is obtained; The planning scheme corresponding to the minimum value of the planning objective function result is determined as the target planning scheme of the direct current transmission network of the offshore wind farm.

2. A method for planning a DC transmission network for an offshore wind farm according to claim 1, characterized in that: The uncertain events include: load change events, wind power change events, and sudden failure events; the event occurrence probability function includes: a first probability distribution function, a second probability distribution function, and a third probability distribution function; The constructing, based on the historical load data, the historical wind power data, and the historical fault data, an event occurrence probability function of a plurality of uncertain events that affect the power generation of the offshore wind farm comprises: Using the Weibull distribution function to construct a first probability distribution function for characterizing the occurrence of a wind change event according to the historical wind data; Using a Gaussian distribution function to construct a second probability distribution function for characterizing a load change event according to the historical load data; A third probability distribution function for characterizing the occurrence of a sudden failure event is constructed based on the historical failure data using binomial distribution.

3. A method for planning a DC transmission network for an offshore wind farm as claimed in claim 2, characterized in that: The planning objective function includes: an investment cost sub-function, an operation cost sub-function, and an emergency cost sub-function; The constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme includes: According to the initial planning scheme, construct an investment cost sub-function for calculating the investment cost required to construct the DC transmission network; According to the operation scenario, constructing an operation cost sub-function for calculating the operation cost required for the normal operation of the offshore wind farm in each operation scenario; According to the operation scenarios, the target events, and the probability of occurrence of the events, an emergency cost sub-function is constructed for calculating the emergency cost required for the offshore wind farm to cope with each target event in each operation scenario.

4. A method for planning a DC transmission network for an offshore wind farm as claimed in claim 3, characterized in that: The initial planning scheme includes: initial planning route, planning period, device cost, operation cost, and emergency cost; The step of optimizing the initial planning scheme under a plurality of preset constraints with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained includes: According to the initial planning scheme, the scheme optimization operation is repeatedly performed until the minimum value of the result of the planning objective function is generated; The scheme optimization operation includes: Obtaining a plan to be optimized; wherein the plan to be optimized includes: a planned route to be optimized, a planned period, a device cost, an operating cost, and an emergency cost; initially, the plan to be optimized is an initial planning plan, and the planned route to be optimized is an initial planning route; According to the probability of occurrence of the event, the operation scenario, and the target event, several scheduling schemes for the offshore wind farm using the to-be-planned line to deal with each of the target events in each of the operation scenarios are generated; wherein the several scheduling schemes all satisfy the constraint conditions; Calculate the result of the planning objective function according to the scheduling scheme, the planned route to be optimized, the planned period, the device cost, the operating cost, and the emergency cost; When it is determined that the result is less than a preset threshold, determining a minimum value of the result of generating the planning objective function; When it is determined that the result is not less than a preset threshold, a new planned route is regenerated as the route to be optimized required for the next round of scheme optimization operation; wherein the new planned route is different from the planned route to be optimized.

5. A method for planning a DC transmission network for an offshore wind farm as claimed in claim 4, characterized in that: The result of calculating the planning objective function according to the scheduling scheme, the planned route to be optimized, the planned period, the device cost, the operating cost, and the emergency cost includes: Using the investment cost sub-function, according to the planned route to be optimized and the device cost, calculate the total investment cost to be evaluated; Using an operating cost sub-function, according to the planned route to be optimized, the planned years, and the operating cost, the total operating cost to be evaluated is calculated; Using the emergency cost sub-function, according to the scheduling scheme, the planned period, and the emergency cost, the total emergency cost to be evaluated is calculated; The result of the planning objective function is generated according to the total investment cost to be evaluated, the total operating cost to be evaluated, and the total emergency cost to be evaluated.

6. A DC transmission network planning device for an offshore wind farm, characterized in that: include: A data acquisition module is used to obtain historical load data, historical wind data, historical fault data, and initial planning scheme of the offshore wind farm to be planned; A first function construction module, configured to construct an event occurrence probability function of a plurality of uncertain events affecting power generation of the offshore wind farm according to the historical load data, the historical wind power data, and the historical fault data; An event calculation module, used to generate a plurality of target events occurring in the offshore wind farm under a plurality of preset operation scenarios and an event occurrence probability of each target event according to the event occurrence probability function; A second function construction module is used to construct a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme; wherein the result of the planning objective function is the total planning cost of the DC transmission network; A scheme optimization module is used to optimize the initial planning scheme under a number of preset constraints with the goal of minimizing the result of the planning objective function until the minimum value of the result of the planning objective function is obtained; The scheme generating module determines, according to the planning scheme corresponding to the minimum value of the planning objective function result, the target planning scheme of the direct current transmission network of the offshore wind farm.

7. A DC transmission network planning device for an offshore wind farm as claimed in claim 6, characterized in that: The uncertain events include: load change events, wind power change events, and sudden failure events; the event occurrence probability function includes: a first probability distribution function, a second probability distribution function, and a third probability distribution function; The constructing, based on the historical load data, the historical wind power data, and the historical fault data, an event occurrence probability function of a plurality of uncertain events that affect the power generation of the offshore wind farm comprises: Using the Weibull distribution function to construct a first probability distribution function for characterizing the occurrence of a wind change event according to the historical wind data; Using a Gaussian distribution function to construct a second probability distribution function for characterizing a load change event according to the historical load data; A third probability distribution function for characterizing the occurrence of a sudden failure event is constructed based on the historical failure data using binomial distribution.

8. A DC transmission network planning device for an offshore wind farm as claimed in claim 7, characterized in that: The planning objective function includes: an investment cost sub-function, an operation cost sub-function, and an emergency cost sub-function; The constructing a planning objective function according to the operation scenario, the target event, the probability of occurrence of the event, and the initial planning scheme includes: According to the initial planning scheme, construct an investment cost sub-function for calculating the investment cost required to construct the DC transmission network; According to the operation scenario, constructing an operation cost sub-function for calculating the operation cost required for the normal operation of the offshore wind farm in each operation scenario; According to the operation scenarios, the target events, and the probability of occurrence of the events, an emergency cost sub-function is constructed for calculating the emergency cost required for the offshore wind farm to cope with each target event in each operation scenario.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, a method for planning a direct current transmission network for an offshore wind farm as claimed in any one of claims 1 to 5 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the method for planning a direct current transmission network for an offshore wind farm as claimed in any one of claims 1 to 5.

Images