Multi-microgrid integrated energy system scheduling method, device and equipment

Abstract

The invention discloses a multi-microgrid integrated energy system scheduling method, device and equipment. The method comprises the following steps: acquiring micro-grid basic data corresponding to the multi-micro-grid integrated energy system; according to the micro-grid basic data, a minimum cost model corresponding to the multi-micro-grid integrated energy system is constructed, and the minimum cost model at least comprises an energy purchase cost algorithm, a carbon transaction cost algorithm, a carbon sequestration income algorithm, a wind curtailment and light curtailment cost algorithm, an electric energy interaction cost algorithm and an operation and maintenance cost algorithm. Determining micro-grid scheduling data corresponding to the multi-micro-grid integrated energy system based on a segmented linear algorithm according to the minimum cost model, and performing scheduling processing on the multi-micro-grid integrated energy system based on the micro-grid scheduling data to determine dynamic scheduling data of the multi-micro-grid integrated energy system, and scheduling the multi-microgrid integrated energy system according to the dynamic scheduling data so as to ensure efficient, safe, economical and environment-friendly operation of the system.

Description

Technical Field

[0001] The present invention relates to the field of energy regulation technology, and in particular to a multi-microgrid integrated energy system scheduling method, device and equipment. Background Art

[0002] The mutual assistance of electric energy between multiple integrated energy microgrids forms a multi-microgrid integrated energy system. This system can promote the complementary energy advantages between different integrated energy microgrids to improve the full utilization of energy. In the multi-microgrid integrated energy system, the Carbon Capture System (CCS) can realize carbon circulation, and the two-stage Power to Gas (P2G) can absorb excess renewable energy and produce natural gas through the process of electric hydrogen production and methanation.

[0003] The traditional hydrogen-blended gas process uses a fixed hydrogen blending ratio, which cannot flexibly adjust the ratio of hydrogen to natural gas according to actual needs or system operating conditions. This may lead to low efficiency in hydrogen use in some cases, or inability to fully utilize the extra electricity generated to produce more hydrogen when there is an excess of renewable energy. At the same time, with changes in hydrogen prices and different hydrogen demands in different application scenarios, fixed hydrogen blending ratios are prone to increase costs and cannot meet the actual microgrid scheduling needs. Summary of the invention

[0004] The present invention provides a multi-microgrid integrated energy system scheduling method, device and equipment to determine the dynamic scheduling data of the multi-microgrid integrated energy system, and schedule the multi-microgrid integrated energy system according to the dynamic scheduling data to ensure efficient, safe, economical and environmentally friendly operation of the system.

[0005] According to one aspect of the present invention, a multi-microgrid integrated energy system scheduling method is provided. The method comprises:

[0006] Acquire microgrid basic data corresponding to the multi-microgrid integrated energy system, wherein the microgrid basic data at least includes microgrid wind and solar data, load forecast data, electric energy data and gas energy data;

[0007] According to the microgrid basic data, a minimum cost model corresponding to the multi-microgrid integrated energy system is constructed, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar abandonment cost algorithm, an electric energy interaction cost algorithm, and an operation and maintenance cost algorithm;

[0008] Based on the segmented linear algorithm and according to the minimum cost model, the microgrid scheduling data corresponding to the multi-microgrid integrated energy system is determined, and the multi-microgrid integrated energy system is scheduled based on the microgrid scheduling data.

[0009] According to another aspect of the present invention, a multi-microgrid integrated energy system scheduling device is provided. The device comprises:

[0010] A microgrid basic data acquisition module is used to acquire microgrid basic data corresponding to a multi-microgrid integrated energy system, wherein the microgrid basic data at least includes microgrid wind and solar data, load forecast data, electric energy data, and gas energy data;

[0011] A minimum cost model construction module is used to construct a minimum cost model corresponding to the multi-microgrid integrated energy system according to the microgrid basic data, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar abandonment cost algorithm, an electric energy interaction cost algorithm, and an operation and maintenance cost algorithm;

[0012] The microgrid scheduling data determination module is used to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system based on a segmented linear algorithm and according to the minimum cost model, and schedule the multi-microgrid integrated energy system based on the microgrid scheduling data.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-microgrid integrated energy system scheduling method described in any embodiment of the present invention.

[0017] The technical solution of the embodiment of the present invention obtains the microgrid basic data corresponding to the multi-microgrid integrated energy system, and constructs the minimum cost model corresponding to the multi-microgrid integrated energy system according to the microgrid basic data, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar power abandonment cost algorithm, an electric energy interaction cost algorithm and an operation and maintenance cost algorithm. Based on a piecewise linear algorithm, according to the minimum cost model, the microgrid scheduling data corresponding to the multi-microgrid integrated energy system is determined, and the multi-microgrid integrated energy system is scheduled based on the microgrid scheduling data, which solves the technical problem of high cost caused by traditional fixed scheduling values ​​and achieves the beneficial effect of scheduling the multi-microgrid integrated energy system according to dynamic scheduling data to ensure efficient, safe, economical and environmentally friendly operation of the system.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a multi-microgrid integrated energy system scheduling method provided according to the first embodiment of the present invention;

[0021] Figure 2 is a schematic diagram of the structure of a typical integrated energy microgrid provided according to the first embodiment of the present invention;

[0022] Figure 3 This is a structural diagram of a multi-microgrid integrated energy system scheduling device provided according to Embodiment 2 of the present invention;

[0023] Figure 4 It is a structural schematic diagram of an electronic device for implementing the multi-microgrid integrated energy system scheduling method of an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] Embodiment 1

[0027] Figure 1 A flowchart of a multi-microgrid integrated energy system scheduling method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of dynamic scheduling of a multi-microgrid integrated energy system. The method can be executed by a multi-microgrid integrated energy system scheduling device. The multi-microgrid integrated energy system scheduling device can be implemented in the form of hardware and / or software. The multi-microgrid integrated energy system scheduling device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0028] S101. Obtain basic microgrid data corresponding to the multi-microgrid integrated energy system.

[0029] Figure 2 Schematic diagram of the structure of a typical integrated energy microgrid provided by the present invention. Figure 2 As shown, the energy input link includes power interaction with adjacent microgrids, photovoltaic (PV), wind turbine (WT), thermal power unit and natural gas source. In the energy conversion link, the equipment includes combined heat and power (CHP) units, electric boilers (EB), CCS and two-stage P2G, where the two-stage P2G consists of an electrolyzer (EL) and a methane reactor (MR). In addition, in the energy storage link, the system is equipped with an electrical energy storage (EES) as an electrical energy storage device. In terms of load, the electricity, heat and gas load requirements are considered. At the same time, the present invention uses the hydrogen generated by EL to mix with natural gas to construct a dynamic hydrogen-blended energy flow network in the gas grid.

[0030] Exemplarily, microgrid basic data may include but are not limited to microgrid wind and solar data, load forecast data, electric energy data, and gas energy data, etc. Microgrid wind and solar data may include wind and solar power data and wind and solar abandonment data, etc. Load forecast data may include load data of various energy exchange devices in various time periods, etc. Electric energy data may include electric energy consumption data, generation data, and electricity price data, and gas energy data may include gas energy consumption data, generation data, and gas price data, etc.

[0031] It should be noted that there is no specific limitation on the means of obtaining microgrid basic data, such as manual on-site collection or automatic collection by intelligent devices.

[0032] S102. Constructing a minimum cost model corresponding to the multi-microgrid integrated energy system based on the microgrid basic data.

[0033] Among them, the minimum cost model takes minimizing the total operating cost of the multi-microgrid integrated energy system within the dispatch period T as the objective function. The minimum cost model at least includes energy purchase cost algorithm, carbon trading cost algorithm, carbon fixation benefit algorithm, wind and solar curtailment cost algorithm, electricity interaction cost algorithm and operation and maintenance cost algorithm.

[0034] Exemplarily, the minimum cost model is as follows:

[0035]

[0036] Where: F is the total operating cost algorithm within a scheduling cycle; f buy,i is the energy purchase cost algorithm for the i-th microgrid; is the carbon-green certificate transaction cost algorithm for the i-th microgrid; is the carbon sequestration benefit algorithm of the i-th microgrid; is the wind and solar power abandonment cost algorithm of the i-th microgrid; f mg,i is the inter-microgrid electricity interaction cost algorithm of the i-th microgrid; f em,i It is the operation and maintenance cost algorithm of the i-th microgrid.

[0037] S103. Based on a segmented linear algorithm and according to the minimum cost model, determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system, and schedule the multi-microgrid integrated energy system based on the microgrid scheduling data.

[0038] Among them, the microgrid dispatching data may at least include carbon emissions, various cost data, processing status of each unit, etc.

[0039] It should be noted that the constructed minimum cost model belongs to a mixed integer nonlinear programming problem, and its solution process is relatively complex. In order to simplify the solution process, the piecewise linearization method is used to convert the original optimization model into a mixed integer linear programming problem. The minimum cost model is linearized by a piecewise linear algorithm to simplify the solution process to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system. The multi-microgrid integrated energy system is dispatched using the microgrid scheduling data. For example, after obtaining the microgrid scheduling data, optimized electricity, heat, gas, hydrogen power balance diagrams and carbon emission distribution diagrams can also be formed.

[0040] Exemplarily, the method of determining the microgrid dispatching data corresponding to the multi-microgrid integrated energy system based on the segmented linear algorithm and the minimum cost model includes: based on the segmented linear algorithm, segmenting the nonlinear relationship in the minimum cost model to obtain a linear cost model; inputting the linear cost model into a preset operation solver to determine the microgrid dispatching data corresponding to the multi-microgrid integrated energy system.

[0041] In the present invention, the preset operation solver can be any solver. Preferably, the present invention uses the CPLEX solver in the MATLAB environment as the preset operation solver.

[0042] Specifically, the present invention uses a segmented linear algorithm to segment the nonlinear relationship in the minimum cost model to obtain a linear cost model, and then inputs the linear cost model into a preset operation solver to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system.

[0043] For example, the specific piecewise linearization process of calculating actual carbon emissions is as follows:

[0044] Step 1: According to the accuracy requirement of piecewise linearization, select k+1 segmentation points q1,q2,…,q k+1 , the independent variable of the actual carbon emission calculation method in the minimum cost model is divided into k segmented intervals within the power range.

[0045] Step 2: Set k+1 continuous auxiliary variables w1, w2, …, w k+1 and k 0-1 auxiliary variables d1, d2, ..., d k , and the following relationship is satisfied.

[0046]

[0047] Step 3: Linearize the calculation method of actual carbon emissions as follows.

[0048]

[0049] According to the above linearization process, the optimization model can be solved using the CPLEX solver in the MATLAB environment to obtain the microgrid scheduling data.

[0050] The technical solution of the embodiment of the present invention obtains the microgrid basic data corresponding to the multi-microgrid integrated energy system, and constructs the minimum cost model corresponding to the multi-microgrid integrated energy system according to the microgrid basic data, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar power abandonment cost algorithm, an electric energy interaction cost algorithm and an operation and maintenance cost algorithm. Based on a piecewise linear algorithm, according to the minimum cost model, the microgrid scheduling data corresponding to the multi-microgrid integrated energy system is determined, and the multi-microgrid integrated energy system is scheduled based on the microgrid scheduling data, which solves the technical problem of high cost caused by traditional fixed scheduling values ​​and achieves the beneficial effect of scheduling the multi-microgrid integrated energy system according to dynamic scheduling data to ensure efficient, safe, economical and environmentally friendly operation of the system.

[0051] Exemplarily, the energy purchase cost algorithm determination process includes: determining the electricity purchase amount, gas purchase amount, electricity price information and gas price information corresponding to each time period within a preset cycle based on the microgrid basic data; and constructing the energy purchase cost algorithm based on the electricity purchase amount, gas purchase amount, electricity price information and gas price information.

[0052] Specifically, the energy purchase cost algorithm can be as follows:

[0053]

[0054] Where: P buy,t G is the amount of electricity purchased from thermal power units during period t; buy,t is the gas purchase volume in period t; α t and β t They are respectively the electricity price information and gas price information in period t.

[0055] Exemplarily, the carbon trading cost algorithm determination process includes:

[0056] According to the microgrid basic data, determine the electric load data, wind and solar power output, and abandoned wind and solar power corresponding to each time period within a preset period;

[0057] Determine the green certificate quota and green certificate ownership corresponding to the multi-microgrid integrated energy system according to the electric load data, the wind and solar power output and the abandoned wind and solar power;

[0058] According to the green certificate quota quantity and the green certificate ownership quantity, determine the mutually recognized actual carbon emissions of the multi-microgrid integrated energy system after the carbon-green certificate mutual recognition mechanism, and according to the mutually recognized actual carbon emissions, determine the mutually recognized static carbon emissions of the multi-microgrid integrated energy system after the carbon-green certificate mutual recognition mechanism;

[0059] According to the mutually recognized static carbon emissions, the carbon-green certificate mutual recognition transaction cost is determined, and according to the carbon-green certificate mutual recognition transaction cost, a carbon transaction cost algorithm is constructed.

[0060] Specifically, the carbon trading cost algorithm can be as follows:

[0061]

[0062] Where: It refers to the transaction cost of mutual recognition of carbon-green certificates within the period t.

[0063] For example, the calculation formula for the transaction cost of carbon-green certificate mutual recognition is as follows:

[0064]

[0065] Where: is the carbon-green certificate transaction cost in period t; λ is the carbon trading base price; l is the length of the carbon emission interval; ω and α are the reward coefficient and penalty coefficient respectively; is the mutually recognized net carbon emissions after considering the carbon-green certificate mutual recognition mechanism in period t; C out,t is the target net carbon emissions in period t.

[0066] For example, the target net carbon emissions calculation formula is as follows:

[0067] C out,t =C a,t -C CCS,t -C quota,t ;

[0068] Where: C out,t is the net carbon emissions in period t; C a,t is the actual carbon emissions generated during period t.

[0069]

[0070] Where: C a,t is the actual carbon emissions generated during period t; C buy,a,t , C CHP,a,t and C Lg,a,t are the carbon emissions actually generated by purchasing electricity from thermal power units, CHP units and gas loads during period t; a1, b1 and c1 are the actual carbon emission calculation parameters for purchasing electricity from thermal power units; a2, b2 and c2 are the actual carbon emission calculation parameters for CHP units; ε Lg P is the carbon emission corresponding to the unit of natural gas added to the CHP unit and gas load; buy,t is the amount of electricity purchased from thermal power units during period t; CHP,t is the electric power generated by the CHP unit during period t; H CHP,tis the thermal power generated by the CHP unit during period t.

[0071] The electric power and thermal power generated by the CHP unit can be obtained by the CHP unit combustion dynamic hydrogen-blended gas model. For example, the CHP unit combustion dynamic hydrogen-blended gas model is as follows:

[0072]

[0073] Where: G CHP,t 、M CHP,t are the power consumed by the CHP unit for natural gas and hydrogen during period t, respectively; and are the electricity and heat production efficiencies of natural gas in the CHP unit during period t, respectively; and are the electricity and heat production efficiencies of hydrogen in the CHP unit during period t; P CHP,t and H CHP,t are the electrical and thermal powers generated by the CHP unit during period t, respectively; and are the calorific values ​​of natural gas and hydrogen respectively (kW / m3); δ CHP,t is the fuel gas hydrogen blending ratio of the CHP unit during period t; and are the lower and upper limits of the thermal power generated by the CHP unit, respectively; and They are the lower and upper limits of the ramping of the thermal power generated by the CHP unit; and They are respectively the lower and upper limits of the hydrogen blending ratio of fuel gas for CHP units.

[0074] For example, the calculation formula for mutual recognition of net carbon emissions is as follows:

[0075]

[0076] Where: is the mutually recognized net carbon emissions after considering the carbon-green certificate mutual recognition mechanism in period t; To consider the actual carbon emissions after the mutual recognition mechanism of carbon-green certificates; C CCS,t is the mass of CO2 captured by CCS during period t; C quota,t is the carbon emission quota for period t.

[0077] For example, the calculation formula for the mass of CO2 captured by CCS is as follows:

[0078]

[0079] Where: P CCS,t is the electric power consumed by CCS during period t; C CCS,tis the mass of CO2 captured by CCS during period t; η CCS is the power conversion efficiency of CCS; and They are the lower and upper limits of CCS power consumption respectively.

[0080] The present invention takes thermal power units, CHP units and gas load as the main carbon emission sources. Since the gas load needs to consume hydrogen-blended fuel gas during operation, its carbon emissions are affected by the use of hydrogen-blended fuel gas. Therefore, the initial carbon emission quota calculation method is as follows:

[0081] C quota,t = x buy P buy,t +χ CHP P CHP,t +χ Lg G L,t ;

[0082] Where: C quota,t is the carbon emission quota for period t; buy , χ CHP and χ Lg They are the carbon emission quotas for purchasing unit electricity load from thermal power units, unit electricity power generated by CHP units, and unit natural gas power mixed with gas load; P buy,t G is the amount of electricity purchased from thermal power units during period t; L,t It is the power of natural gas mixed into the gas load during period t.

[0083] The calculation method of the power of natural gas mixed into the gas load is as follows:

[0084]

[0085] Where: G L,t and M L,t are the power of natural gas and hydrogen added to the gas load during period t; δ L,t is the fuel gas hydrogen blending ratio of the gas load during period t; and are the lower and upper limits of the hydrogen blending ratio of the gas load respectively; M MR,t is the hydrogen power consumed by MR during period t; G MR,t is the natural gas power generated by MR during period t.

[0086] For example, the calculation method of natural gas power generated by MR is as follows:

[0087]

[0088] Where: M MR,t is the hydrogen power consumed by MR during period t; G MR,tis the natural gas power generated by MR during period t; and are the efficiency of MR consumption of hydrogen and conversion of CO2 to natural gas, respectively.

[0089] For example, the calculation formula for mutual recognition of actual carbon emissions is as follows:

[0090]

[0091] Where: is the actual carbon emissions recognized after considering the carbon-green certificate mutual recognition mechanism; ΔC t The amount of carbon emissions offset by redundant green certificates; γ g -γ re is the difference between the carbon emission intensity of the main carbon emitters and that of renewable energy power generation; N green,t -N quota,t N is the number of redundant green certificates; quota,t 、N green,t They are the number of green certificate quotas and the number of green certificates generated by renewable energy power generation.

[0092] For example, the calculation formula for the green certificate quota and the green certificate ownership is as follows:

[0093]

[0094] Where: N quota,t 、N green,t are the number of green certificate quotas and the number of green certificates generated by renewable energy power generation; GCT,quota , ε green are the green certificate quota coefficient per unit electric load power and the green certificate coefficient per unit renewable energy consumption; P Load,t is the electrical load demand; P RE,t , are the sum of wind and solar power output and abandoned wind and solar power in period t respectively; is the transaction cost of green certificates; green Green certificate transaction unit price.

[0095] For example, the calculation formula of the electric load demand is as follows:

[0096]

[0097] Where: P RE,t The output power of renewable energy; P ch,t and P dis,t is the EES storage and discharge power; P buy,t is the amount of electricity purchased from thermal power units during period t; is the abandoned wind and solar power in period t; P CHP,tis the electric power generated by the CHP unit during period t; P EL,t P is the electric power consumed by EL during period t; CCS,t P is the electric power consumed by CCS during period t; EB,t is the electric power consumed by EB during period t.

[0098] Exemplarily, the carbon sequestration benefit algorithm determination process includes: determining the carbon consumption quality and unit carbon consumption benefit corresponding to each time period within a preset period based on the microgrid basic data; and constructing the carbon sequestration benefit algorithm based on the carbon consumption quality and the unit carbon consumption benefit.

[0099] Specifically, the carbon sequestration benefit algorithm can be as follows:

[0100]

[0101] Where: fix C is the unit carbon consumption benefit obtained by consuming unit mass of CO2 of the MR unit; MR,t It refers to the carbon consumption mass of CO2 consumed by the MR unit during period t.

[0102] Exemplarily, the process of determining the wind and solar power abandonment cost algorithm includes:

[0103] According to the microgrid basic data, the wind and light abandonment power and the unit wind and light abandonment penalty coefficient corresponding to each time period in a preset cycle are determined; according to the wind and light abandonment power and the unit wind and light abandonment penalty coefficient, the wind and light abandonment cost algorithm is constructed.

[0104] Specifically, the cost algorithm for curtailing wind and solar power can be as follows:

[0105]

[0106] Where: RE is the penalty coefficient for unit wind and solar power abandonment; is the abandoned wind and solar power in period t.

[0107] Exemplarily, the electric energy interaction cost algorithm determination process includes:

[0108] According to the microgrid basic data, the microgrid interactive electric power and the unit electric energy interactive cost corresponding to each time period within a preset cycle are determined; according to the microgrid interactive electric power and the unit electric energy interactive cost, the electric energy interactive cost algorithm is constructed.

[0109] Specifically, the electric energy interaction cost algorithm can be as follows:

[0110]

[0111] Where: r mgP is the unit electric energy interaction cost between microgrids; mg,j,t is the microgrid interaction electric power between microgrid i and microgrid j in period t.

[0112] Exemplarily, the operation and maintenance cost algorithm determination process includes: determining, based on the microgrid basic data, the corresponding equipment operating power of each energy conversion equipment in the multi-microgrid integrated energy system corresponding to each time period within a preset cycle, and the corresponding unit power operation and maintenance cost of each energy conversion equipment; constructing the operation and maintenance cost algorithm based on the equipment operating power and the unit power operation and maintenance cost.

[0113] Specifically, the operation and maintenance cost algorithm can be as follows:

[0114]

[0115] Where: k CHP , k EB , k EL , k MR , k CCS and k EES are the unit power operation and maintenance costs per unit time period for CHP units, EB units, EL units, MR units, CCS units and batteries respectively; P CHP,t is the power generation of the CHP unit during period t; P EB,t is the electric power consumed by the EB unit during period t; F MR,t is the operating power of the MR unit during period t; P CCS,t P is the electric power consumed by the CCS unit during period t; ch,t P is the charging power of the battery in period t; dis,t are the discharge power of the battery in period t respectively.

[0116] Embodiment 2

[0117] Figure 3 This is a schematic diagram of the structure of a multi-microgrid integrated energy system dispatching device provided in Embodiment 2 of the present invention. Figure 3 As shown, the device comprises:

[0118] The microgrid basic data acquisition module 301 is used to acquire microgrid basic data corresponding to the multi-microgrid integrated energy system, wherein the microgrid basic data at least includes microgrid wind and solar data, load forecast data, electric energy data and gas energy data.

[0119] The minimum cost model construction module 302 is used to construct the minimum cost model corresponding to the multi-microgrid integrated energy system based on the microgrid basic data, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar power abandonment cost algorithm, an electricity interaction cost algorithm and an operation and maintenance cost algorithm.

[0120] The microgrid scheduling data determination module 303 is used to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system based on a segmented linear algorithm and according to the minimum cost model, and schedule the multi-microgrid integrated energy system based on the microgrid scheduling data.

[0121] The technical solution of the embodiment of the present invention obtains the microgrid basic data corresponding to the multi-microgrid integrated energy system, and constructs the minimum cost model corresponding to the multi-microgrid integrated energy system according to the microgrid basic data, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar power abandonment cost algorithm, an electric energy interaction cost algorithm and an operation and maintenance cost algorithm. Based on a piecewise linear algorithm, according to the minimum cost model, the microgrid scheduling data corresponding to the multi-microgrid integrated energy system is determined, and the multi-microgrid integrated energy system is scheduled based on the microgrid scheduling data, which solves the technical problem of high cost caused by traditional fixed scheduling values ​​and achieves the beneficial effect of scheduling the multi-microgrid integrated energy system according to dynamic scheduling data to ensure efficient, safe, economical and environmentally friendly operation of the system.

[0122] Optionally, the minimum cost model building module 302 includes an energy purchase cost algorithm building unit.

[0123] Among them, the energy purchase cost algorithm building unit is used to:

[0124] Determine the electricity purchase amount, gas purchase amount, electricity price information and gas price information corresponding to each time period within a preset period according to the microgrid basic data;

[0125] The energy purchase cost algorithm is constructed according to the electricity purchase amount, the gas purchase amount, the electricity price information and the gas price information.

[0126] Optionally, the minimum cost model building module 302 includes a carbon trading cost algorithm building unit.

[0127] Among them, the carbon trading cost algorithm building unit is used to:

[0128] According to the microgrid basic data, determine the electric load data, wind and solar power output, and abandoned wind and solar power corresponding to each time period within a preset period;

[0129] Determine the green certificate quota and green certificate ownership corresponding to the multi-microgrid integrated energy system according to the electric load data, the wind and solar power output and the abandoned wind and solar power;

[0130] According to the green certificate quota quantity and the green certificate ownership quantity, determine the mutually recognized actual carbon emissions of the multi-microgrid integrated energy system after the carbon-green certificate mutual recognition mechanism, and according to the mutually recognized actual carbon emissions, determine the mutually recognized static carbon emissions of the multi-microgrid integrated energy system after the carbon-green certificate mutual recognition mechanism;

[0131] According to the mutually recognized static carbon emissions, the carbon-green certificate mutual recognition transaction cost is determined, and according to the carbon-green certificate mutual recognition transaction cost, a carbon transaction cost algorithm is constructed.

[0132] Optionally, the minimum cost model construction module 302 includes a carbon sequestration benefit algorithm construction unit.

[0133] Among them, the carbon sequestration benefit algorithm construction unit is used to:

[0134] Determine the carbon consumption quality and unit carbon consumption benefit corresponding to each time period within a preset period according to the microgrid basic data;

[0135] The carbon sequestration benefit algorithm is constructed according to the carbon consumption quality and the unit carbon consumption benefit.

[0136] Optionally, the minimum cost model construction module 302 includes a wind and solar power abandonment cost algorithm construction unit. The wind and solar power abandonment cost algorithm construction unit is used to:

[0137] Determine the wind and solar power abandonment and the unit wind and solar power abandonment penalty coefficient corresponding to each time period in a preset period according to the microgrid basic data;

[0138] The wind and light abandonment cost algorithm is constructed according to the abandoned wind and light abandonment power and the unit wind and light abandonment penalty coefficient.

[0139] Optionally, the minimum cost model construction module 302 includes an electric energy interaction cost algorithm construction unit. The electric energy interaction cost algorithm construction unit is used to:

[0140] Determine the microgrid interactive power and unit electric energy interactive cost corresponding to each time period within a preset period according to the microgrid basic data;

[0141] The electric energy interaction cost algorithm is constructed according to the microgrid interaction electric power and the unit electric energy interaction cost.

[0142] Optionally, the minimum cost model construction module 302 includes an operation and maintenance cost algorithm construction unit. The operation and maintenance cost algorithm construction unit is used to:

[0143] Determine, according to the microgrid basic data, the corresponding equipment operating power of each energy conversion device in the multi-microgrid integrated energy system corresponding to each time period within a preset period, and the corresponding unit power operation and maintenance cost of each energy conversion device;

[0144] The operation and maintenance cost algorithm is constructed according to the equipment operation power and the unit power operation and maintenance fee.

[0145] Optionally, the microgrid scheduling data determination module 303 is specifically configured to:

[0146] Based on a piecewise linear algorithm, the nonlinear relationship in the minimum cost model is processed piecewise to obtain a linear cost model;

[0147] The linear cost model is input into a preset operation solver to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system.

[0148] The multi-microgrid integrated energy system scheduling device provided in the embodiment of the present invention can execute the multi-microgrid integrated energy system scheduling method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0149] Embodiment 3

[0150] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0151] like Figure 4As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0152] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0153] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as the method for multi-microgrid integrated energy system scheduling.

[0154] In some embodiments, the method for multi-microgrid integrated energy system scheduling can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for multi-microgrid integrated energy system scheduling described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the method for multi-microgrid integrated energy system scheduling in any other appropriate manner (for example, by means of firmware).

[0155] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0156] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0157] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0158] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0159] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0160] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0161] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0162] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-microgrid integrated energy system scheduling method, characterized in that: include: Acquire microgrid basic data corresponding to the multi-microgrid integrated energy system, wherein the microgrid basic data at least includes microgrid wind and solar data, load forecast data, electric energy data and gas energy data; According to the microgrid basic data, a minimum cost model corresponding to the multi-microgrid integrated energy system is constructed, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar abandonment cost algorithm, an electric energy interaction cost algorithm, and an operation and maintenance cost algorithm; Based on the segmented linear algorithm and according to the minimum cost model, the microgrid scheduling data corresponding to the multi-microgrid integrated energy system is determined, and the multi-microgrid integrated energy system is scheduled based on the microgrid scheduling data.

2. The method according to claim 1, characterized in that: The process of determining the energy purchase cost algorithm includes: Determine the electricity purchase amount, gas purchase amount, electricity price information and gas price information corresponding to each time period within a preset period according to the microgrid basic data; The energy purchase cost algorithm is constructed according to the electricity purchase amount, the gas purchase amount, the electricity price information and the gas price information.

3. The method according to claim 1, characterized in that The carbon trading cost algorithm determination process includes: According to the microgrid basic data, determine the electric load data, wind and solar power output, and abandoned wind and solar power corresponding to each time period within a preset period; Determine the green certificate quota and green certificate ownership corresponding to the multi-microgrid integrated energy system according to the electric load data, the wind and solar power output and the abandoned wind and solar power; According to the green certificate quota quantity and the green certificate ownership quantity, determine the mutually recognized actual carbon emissions of the multi-microgrid integrated energy system after the carbon-green certificate mutual recognition mechanism, and according to the mutually recognized actual carbon emissions, determine the mutually recognized static carbon emissions of the multi-microgrid integrated energy system after the carbon-green certificate mutual recognition mechanism; According to the mutually recognized static carbon emissions, the carbon-green certificate mutual recognition transaction cost is determined, and according to the carbon-green certificate mutual recognition transaction cost, a carbon transaction cost algorithm is constructed.

4. The method according to claim 1, characterized in that: The carbon sequestration benefit algorithm determination process includes: Determine the carbon consumption quality and unit carbon consumption benefit corresponding to each time period within a preset period according to the microgrid basic data; The carbon sequestration benefit algorithm is constructed according to the carbon consumption quality and the unit carbon consumption benefit.

5. The method according to claim 1, characterized in that The process of determining the wind and solar power abandonment cost algorithm includes: Determine the wind and solar power abandonment and the unit wind and solar power abandonment penalty coefficient corresponding to each time period in a preset period according to the microgrid basic data; The wind and light abandonment cost algorithm is constructed according to the abandoned wind and light abandonment power and the unit wind and light abandonment penalty coefficient.

6. The method according to claim 1, characterized in that The electric energy interaction cost algorithm determination process includes: Determine the microgrid interactive power and unit electric energy interactive cost corresponding to each time period within a preset period according to the microgrid basic data; The electric energy interaction cost algorithm is constructed according to the microgrid interaction electric power and the unit electric energy interaction cost.

7. The method according to claim 1, characterized in that The operation and maintenance cost algorithm determination process includes: Determine, according to the microgrid basic data, the corresponding equipment operating power of each energy conversion device in the multi-microgrid integrated energy system corresponding to each time period within a preset period, and the corresponding unit power operation and maintenance cost of each energy conversion device; The operation and maintenance cost algorithm is constructed according to the equipment operation power and the unit power operation and maintenance fee.

8. The method according to claim 1, characterized in that: The step of determining the microgrid dispatching data corresponding to the multi-microgrid integrated energy system based on the piecewise linear algorithm and the minimum cost model includes: Based on a piecewise linear algorithm, the nonlinear relationship in the minimum cost model is processed piecewise to obtain a linear cost model; The linear cost model is input into a preset operation solver to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system.

9. A multi-microgrid integrated energy system dispatching device, characterized in that: include: A microgrid basic data acquisition module is used to acquire microgrid basic data corresponding to a multi-microgrid integrated energy system, wherein the microgrid basic data at least includes microgrid wind and solar data, load forecast data, electric energy data, and gas energy data; A minimum cost model construction module is used to construct a minimum cost model corresponding to the multi-microgrid integrated energy system according to the microgrid basic data, wherein the minimum cost model at least includes an energy purchase cost algorithm, a carbon trading cost algorithm, a carbon fixation benefit algorithm, a wind and solar abandonment cost algorithm, an electric energy interaction cost algorithm, and an operation and maintenance cost algorithm; The microgrid scheduling data determination module is used to determine the microgrid scheduling data corresponding to the multi-microgrid integrated energy system based on a segmented linear algorithm and according to the minimum cost model, and schedule the multi-microgrid integrated energy system based on the microgrid scheduling data.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-microgrid integrated energy system scheduling method described in any one of claims 1-8.

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