Novel energy system construction area planning method for high-temperature and high-humidity area

Abstract

The invention discloses a novel energy system construction area planning method for a high-temperature and high-humidity area, and the method comprises the steps: constructing an area division rule, dividing a target area into a plurality of unit areas, determining the installation number and position information of novel energy facilities based on the feature information of the unit areas, and obtaining the layout conditions of the unit areas, calculating a path failure rate in the target area, carrying out decoupling operation on adjacent unit areas based on the path failure rate, obtaining an energy scheduling path of the target planning area based on a decoupling result, constructing an energy complementation strategy set for the target area, carrying out optimization on the energy complementation strategy set, and obtaining an optimal energy complementation strategy. And planning the target area according to the layout condition of the unit area, the energy scheduling path and the optimal energy complementation strategy. The method not only can improve the regional planning efficiency and the energy synergistic effect, but also has good interpretability, and can be directly applied to a new energy system construction regional planning system.

Description

Technical Field

[0001] The present invention relates to the field of energy construction regional planning, and in particular to a new energy system construction regional planning method in high temperature and high humidity areas. Background Art

[0002] With the continuous growth of global energy demand and increasingly severe environmental problems, the development and utilization of new energy systems have become the key to addressing climate change and ensuring energy security.

[0003] Traditional regional planning methods for energy construction mainly rely on resource assessment and demand forecasting, but this method focuses more on increasing energy supply, pays less attention to improving the management of different energy types and basic demand sides, and lacks energy planning between different regions in the planning process. In recent years, with the rapid development of the Internet of Things, big data and artificial intelligence technologies, more and more regional planning methods for energy construction have begun to use intelligent algorithms or big data for monitoring to reduce costs and improve the efficiency and accuracy of monitoring.

[0004] At present, although there are some regional planning methods for the construction of new energy systems in high temperature and high humidity areas based on intelligent algorithms or big data, these methods often simply transform regional planning problems into facility site selection problems, and lack comprehensive consideration of cross-regional and energy scheduling. However, these methods are limited in real-time and accuracy, and lack risk assessment. In cross-regional scheduling planning, they often focus on energy transfer scheduling strategies, but lack consideration of scheduling paths. Summary of the invention

[0005] The purpose of the present invention is to provide a new energy system construction regional planning method for high temperature and high humidity areas.

[0006] To achieve the above object, the present invention is implemented according to the following technical solutions:

[0007] The present invention provides a method for regional planning of new energy system construction in high temperature and high humidity areas, comprising the following steps:

[0008] Step S1, constructing a region division rule, and dividing the target region into a plurality of unit regions based on the region division rule;

[0009] Step S2, acquiring characteristic information of the unit area, determining the installed capacity and location information of the new energy facilities based on the characteristic information, and obtaining the layout of the unit area; the characteristic information includes construction characteristics, load characteristics and resource characteristics;

[0010] Step S3, calculating the path failure rate in the target area, performing a decoupling operation on adjacent unit areas based on the path failure rate, and obtaining an energy scheduling path for the target planning area based on the decoupling result; the scheduling path includes a first energy scheduling path within the unit area and a second energy scheduling path across regions;

[0011] Step S4: constructing an energy conversion mechanism and an energy storage mechanism for the target area, and constructing an energy complementary strategy set for the target area based on the energy conversion mechanism and the energy storage mechanism;

[0012] Step S5: optimizing the energy complementary strategy set to obtain an optimal energy complementary strategy, and planning the target area according to the layout of the unit area, the energy scheduling path and the optimal energy complementary strategy.

[0013] Furthermore, the method for constructing the area division rule in step S1 includes:

[0014] Identify energy demand hotspots in the target planning area and divide existing energy facilities into controllable supply facilities and uncontrollable consumption facilities;

[0015] Energy demand hotspots, controllable supply facilities, and uncontrollable consumption facilities are used as nodes to construct partitioning constraints;

[0016] Based on the division constraints, a variety of regional division methods are obtained, the fitness of each regional division method is calculated, and the regional division method with the largest fitness is retained as the final regional division method.

[0017] Furthermore, the method for constructing partitioning constraints includes:

[0018] Balance constraint: Each unit area must contain at least one energy demand hotspot node, one controllable supply facility node, and one uncontrollable consumption facility node to ensure self-balance in the unit area;

[0019] Node distance constraint constrains the electrical distance between two existing energy facilities in a unit area. Two existing energy facilities with an electrical distance less than 0.1 are not allowed to be in the same unit area. The calculation formula for the electrical distance is:

[0020]

[0021] Where Δ(·) represents the calculated difference, ΔT n Q is the energy change of the existing energy facilities in the time interval n, n It is represented by the heat consumption value of the existing energy facilities in the time interval n, R is represented by the power attenuation coefficient of the existing energy facilities, T maxis the maximum allowable temperature of existing energy facilities, X k is the active power of existing energy facilities, C k is the reactive power of existing energy facilities, and D represents the Euclidean distance between existing energy facilities;

[0022] The new energy permeability constraint is that the divided unit area cannot be oversaturated with energy, that is, the new energy permeability should be greater than or equal to 90%, and the new energy permeability calculation formula is:

[0023]

[0024] Among them, η is the energy conversion efficiency in the unit area, ψ is the number of existing energy facilities in the unit area, and P L is the power that needs to be carried in the unit area, f N is the operating frequency of existing energy facilities, σ w is the area of ​​energy island in the unit area, ΔP w is the power to be compensated in the unit area, ρ is the distribution density of existing energy facilities, and Δv is the power increment of the new energy facilities compared to the existing energy facilities.

[0025] Furthermore, the method for calculating the fitness of each area division method includes:

[0026]

[0027] in, is the total number of regions after division, q i is the number of existing energy facilities in unit area i, μ i is the area of ​​unit region i, li is the width of unit region i, A i (x) represents the power defect value at position x in the unit area, It is expressed as the area-based integration of the power defect value in unit area i, A D is the power defect area ratio within unit area i, d max is the maximum distance between existing energy facilities in unit area i, is the average distance between adjacent existing energy facilities in unit area i, and m is the density adjustment index, which is 0.01.

[0028] Furthermore, the method for determining the installed capacity and location information of new energy facilities based on the characteristic information includes:

[0029] Use K-means clustering algorithm to cluster each unit area, determine the number of clusters based on the elbow rule according to the new energy penetration rate, and use the number of clusters as the number of new energy facilities in the unit area;

[0030] Construct a new energy site selection model, the expression is:

[0031]

[0032] Among them, f is the site selection objective function, n is the number of sites, u i It is expressed as the penetration rate of new energy facilities at the i-th site, A i It is represented as the power defect value of the i-th site, and is the construction cost and environmental restoration cost of the ith site.

[0033] Furthermore, the method of calculating the path failure rate within the unit area, performing a decoupling operation on adjacent unit areas based on the path failure rate, and obtaining an energy scheduling path of the target planning area based on the decoupling result includes:

[0034] Calculate the path failure rate between adjacent new energy facilities in the target area using the following formula:

[0035]

[0036] Among them, F max is the maximum possible value of the energy capacity transmitted, F ery is the transmission capacity limit of the path, and F is the flow value of the path;

[0037] The path with a failure rate higher than 0.07 is used as the decoupling standard. The adjacent unit areas that need to be decoupled are determined based on the failure rate. The adjacent unit areas are decoupled using the failure probability as the penalty function. After decoupling, a new energy scheduling path is replanned.

[0038] Determine a first energy dispatch path within the unit area to ensure energy supply and demand balance within the unit area, wherein the first dispatch path is: take a path with the best energy utilization rate among energy facilities of the same type within the unit area as the first dispatch path;

[0039] Determine the second energy dispatch path across regions to ensure the energy exchange balance between unit regions. The energy exchange balance expression of the second energy dispatch path is:

[0040]

[0041] Among them, P u Expressed as the net energy flow for energy exchange, P pre It is represented as the initial energy flow before crossing the region, is the maximum energy flow that the energy-providing region can provide, P is the minimum energy flow required by the energy-receiving region, and z + and z -They represent the direction of energy flow increase and energy flow decrease, respectively. + When it is greater than 0, it means from To P u Increase energy flow, when z - When it is greater than 0, it means that from P pre Reducing the energy flow to P, the objective function expression of the second energy scheduling path is:

[0042]

[0043] Where T represents the period of cross-regional energy exchange, I is the set of second energy scheduling paths, and a i,t is the energy loss of the ith scheduling path at time t, ⊙ represents the element-wise product operation, Expressed as the predicted energy dispatch quantity, x * Expressed as the actual energy dispatch amount, β i,t is the energy exchange cost of the i-th scheduling path at time t.

[0044] Furthermore, the method of constructing an energy conversion mechanism and an energy storage mechanism for the target area includes:

[0045] Construct an energy converter, the expression is:

[0046]

[0047] in, and For electrical load, gas load, thermal load, and are the charging power and discharging power of the storage device respectively, and are the charging power and releasing power of the heat storage device, respectively, m,ES is the number of installed new energy facilities, k is the number of unit areas, and are the electrical power transmitted between electrical devices, and are the thermal power transmitted between thermal energy devices, λ is the ratio of the electric energy demand of the electric boiler to the purchased electric energy, μ1 is the ratio of the natural gas demand of the gas turbine to the purchased natural gas, μ2 is the ratio of the natural gas demand of the gas boiler to the purchased natural gas, and are the power of electricity purchased and the power of gas purchased, P PV Produce power for photovoltaics;

[0048] Construct an energy storage, where the expression for energy storage is:

[0049]

[0050] Among them, Q m,HS is the amount of energy stored in the energy storage at the end of period m, Q m-1,HS is the amount of energy stored in the energy storage at the end of period m-1, Expressed as the ratio of actual stored energy to input energy, Expressed as the ratio of the amount of energy extracted from the energy storage to the actual output energy, and represents the charging power and discharging power of the energy storage in time period m.

[0051] Furthermore, the method for constructing a set of energy complementarity strategies for the target area based on the energy conversion mechanism and the energy storage mechanism includes:

[0052] Divide the facilities in the target area into three types of energy subsystems, including: energy conversion system, energy storage system and energy consumption facility system, and determine the operating status of each energy consumption facility, including: overload status and idle status;

[0053] Set a time window and perform load judgment regularly every time window. If the energy facility meets the load demand, continue normal operation. If the energy is overloaded, perform energy compensation:

[0054] Select the nearest energy facilities of the same type for energy compensation. When the compensation rate of the nearest energy facilities of the same type is insufficient, give priority to using the energy storage system for energy compensation. If the compensation rate of the energy storage system is insufficient, find the nearest energy conversion system and the different types of energy consumption facilities that are closest to the energy conversion system and in an idle state, and perform comprehensive compensation based on the energy conversion system and the energy storage system.

[0055] For each energy consumption facility in an overloaded state, all possible energy compensation sets are obtained, and based on all possible energy compensation sets, an energy complementary strategy set is obtained.

[0056] Furthermore, the method for optimizing the energy complementarity strategy set includes:

[0057] The energy benefit including the combination of carbon reduction gain and flexible regulation capacity gain is taken as the first objective function, and the expression is:

[0058]

[0059] Among them, I gr For carbon reduction gain, I fr is the flexible regulation capacity gain, Δψ is the annual carbon emission reduction, L is the dual carbon contribution, T ηis the carbon reduction capacity of green building facilities, Τ is the carbon reduction amount of green building facilities, and Υ η is the carbon reduction capacity of building photovoltaic facilities, Υ is the carbon reduction amount of building photovoltaic facilities, Φ η is the carbon reduction capacity of distributed photovoltaic facilities, Φ is the carbon reduction amount of distributed photovoltaic facilities, U * is the comprehensive voltage qualification rate,

[0060] **

[0061] ξ is the energy saving rate, P is the adjustable flexible load, α eq It is represented by the penetration rate of charging piles, Φ is represented by the power supply reliability, ΔQ is the amount of green electricity generated, Expressed as annual carbon emission reduction under maximum power supply reliability and maximum energy saving rate;

[0062] Taking the comprehensive cost of construction and operation as the second objective function, the expression is:

[0063]

[0064] Among them, f cs is the construction cost, f op is the maintenance cost, C fixeed The construction cost of new energy facilities, is the number of new energy facilities, C P and C E They are the unit power cost and unit capacity cost of new energy facilities, and are the rated power and rated capacity of the new energy facilities, r is the discount rate, T life is the service life of new energy facilities, k op The operation and maintenance cost coefficient for new energy facilities;

[0065] Maximize the first objective function and minimize the second objective function to obtain the optimal energy scheduling strategy.

[0066] Furthermore, the method of maximizing the first objective function and minimizing the second objective function includes:

[0067] The optimal solutions of the first objective function and the second objective function are solved separately, and the values ​​of the remaining objective functions are calculated while solving them separately to obtain the endpoints of the Pareto surface;

[0068] Divide the vector of the Pareto surface boundary into m equal parts, each of which has a length of ΔL = 1 / m, and construct a plane using the endpoints, vectors, and equal division points to obtain the Pareto surface;

[0069] Convert each point on the Pareto surface into a matrix form, determine the positive and negative ideal points, and calculate the relative closeness of each Pareto optimal solution. The calculation formula is:

[0070]

[0071] in, and are the Euclidean distances from the jth optimal solution to the positive ideal point and the negative ideal point respectively;

[0072] The Pareto optimal solution with the largest relative fit is selected as the final energy scheduling strategy.

[0073] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0074] (1) The present invention provides a regional planning method for the construction of a new energy system in a high-temperature and high-humidity area. By constructing regional division rules, the target area is divided into multiple unit areas. The installed capacity and location information of the new energy facilities are determined based on the characteristic information of the unit areas. The installed capacity and location of the new energy facilities are determined by considering the power defective areas, thereby optimizing resource allocation and improving energy utilization efficiency. By constructing regional division rules, a systematic and modular planning method is implemented, thereby improving planning efficiency.

[0075] (2) The present invention realizes multi-energy complementarity in the regional energy network by constructing an energy converter, constructs an energy storage device to realize energy conversion, balances supply and demand fluctuations, and improves the stability and flexibility of energy scheduling.

[0076] (3) The present invention adopts a first objective function to construct energy benefits and a second objective function to construct operation and maintenance costs. By maximizing the first objective function and minimizing the second objective function, multi-objective optimization is achieved, balancing the energy benefits and construction and operation costs, thereby improving the economy and environmental performance of the project area planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 This is a flow chart of the steps of a method for planning the construction of a new energy system in a high-temperature and high-humidity area according to the present invention. DETAILED DESCRIPTION

[0078] The technical solutions 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, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0079] Reference Figure 1As shown, the present invention provides a method for regional planning of new energy system construction in high temperature and high humidity areas, comprising:

[0080] Step S1, constructing a region division rule, and dividing the target region into a plurality of unit regions based on the region division rule;

[0081] In the actual evaluation, a regional division rule is constructed, and the target area is divided into A, B and C areas based on the regional division rule, which represent the transportation hub area in the north, the residential power consumption area in the south and the industrial power consumption area in the north respectively;

[0082] Step S2, acquiring characteristic information of the unit area, determining the installed capacity and location information of the new energy facilities based on the characteristic information, and obtaining the layout of the unit area; the characteristic information includes construction characteristics, load characteristics and resource characteristics;

[0083] In the actual evaluation, six integrated photovoltaic storage and charging supercharging stations with a combination of 480kW ultra-fast charging and 120kW fast charging terminals as basic units were built in area A, three distributed group cooling stations were set up in area B, and the cooling stations were interconnected to provide cooling reliability, and a joint power supply system was established in area C;

[0084] Step S3, calculating the path failure rate in the target area, performing a decoupling operation on adjacent unit areas based on the path failure rate, and obtaining an energy scheduling path for the target planning area based on the decoupling result; the scheduling path includes a first energy scheduling path within the unit area and a second energy scheduling path across regions;

[0085] In the actual evaluation, the path failure rate in the target area is calculated, and the North District Bus Station and the South District Residential Power Area are decoupled based on the failure rate. The cables with high failure rates are shut down and the energy flow is reconfigured. In the North District Bus Station, the path with the highest energy utilization rate is selected for each energy facility for scheduling to obtain the first energy scheduling path. Between the North District Bus Station and the South District Residential Power Area, the energy demand and supply are re-planned based on the decoupled energy demand and supply, and an energy exchange balance mechanism is constructed to minimize the energy exchange objective function and obtain the second cross-regional energy scheduling path.

[0086] Step S4: constructing an energy conversion mechanism and an energy storage mechanism for the target area, and constructing an energy complementary strategy set for the target area based on the energy conversion mechanism and the energy storage mechanism;

[0087] In the actual evaluation, an energy converter is constructed to realize mutual conversion of different types, and an energy storage device is constructed to realize the balance of energy supply and demand. The facilities in the target area are divided into three types of energy subsystems, including: energy conversion system, energy storage system and energy consumption facility system. The operating status of each energy consumption facility is determined, including: overload state, idle state, and time windows are set. Load judgment is performed regularly every time window. If the energy facility meets the load demand, normal operation continues. If the energy is overloaded, energy compensation is performed: select the nearest energy facilities of the same type for energy compensation. When the compensation rate of the nearest energy facilities of the same type is insufficient, the energy storage system is used for energy compensation first. If the compensation rate of the energy storage system is insufficient, the nearest energy conversion system and different types of energy consumption facilities in the idle state closest to the energy conversion system are found. Comprehensive compensation is performed based on the energy conversion system and the energy storage system. All possible energy compensation sets are obtained for each energy consumption facility in the overload state. Based on all possible energy compensation sets, a set of energy complementary strategies is obtained.

[0088] In the actual evaluation, area A converts photovoltaic power generation into electrical energy, part of which is used in charging stations, and the remaining electrical energy is stored in the energy storage system; area B uses electricity to drive refrigeration equipment through cold stations and converts it into cold energy; area C converts fuel into electrical energy through generator sets, and the energy storage system provides peak load support; in area A, electrical energy is stored in the battery energy storage system, in area B, cold energy is stored in cold storage facilities such as cold storage, and in area C, electrical energy is regulated by the battery energy storage system;

[0089] In the actual evaluation, area A provides nighttime energy storage power supply to area B, area B provides cooling energy to area A during peak hours, and area C provides power support to areas A and B during peak power demand or emergencies. When there is excess photovoltaic power generation in area A during the day, it is stored through the energy storage system and power is supplied to area B to drive refrigeration equipment. At night, area A uses the energy storage system to discharge power and provide power to area B, which releases cooling energy. When the power demand in areas A and B exceeds the local supply capacity, the joint power supply system in area C provides support.

[0090] Step S5: optimizing the energy complementary strategy set to obtain an optimal energy complementary strategy, and planning the target area according to the layout of the unit area, the energy scheduling path and the optimal energy complementary strategy.

[0091] In the actual evaluation, the energy gain data and construction operation and maintenance data obtained are:

[0092] Table 1 Carbon reduction effect in one area

[0093]

[0094] Table 2 Area flexibility potential indicators

[0095]

[0096] Table 3 Construction and operation indicators

[0097]

[0098] In the actual evaluation, the first objective function is constructed through the area carbon reduction effect and the area flexible potential indicators. By constructing the second objective function, the first objective function and the second objective function in the energy scheduling strategy set are calculated. By maximizing the first objective function and minimizing the second objective function, the optimal energy scheduling strategy is obtained. Construction planning for the target area is carried out based on the implementation layout of new energy in the northern bus station, the southern residential power consumption area and the northern industrial power consumption area, the energy scheduling path and the optimal energy scheduling strategy.

[0099] In this embodiment, the method for constructing area division rules in step S1 includes:

[0100] Identify energy demand hotspots in the target planning area and divide existing energy facilities into controllable supply facilities and uncontrollable consumption facilities;

[0101] Energy demand hotspots, controllable supply facilities, and uncontrollable consumption facilities are used as nodes to construct partitioning constraints;

[0102] Based on the division constraints, a variety of regional division methods are obtained, the fitness of each regional division method is calculated, and the regional division method with the largest fitness is retained as the final regional division method.

[0103] In this embodiment, the method for constructing the partition constraint condition includes:

[0104] Balance constraint: Each unit area must contain at least one energy demand hotspot node, one controllable supply facility node, and one uncontrollable consumption facility node to ensure self-balance in the unit area;

[0105] Node distance constraint constrains the electrical distance between two existing energy facilities in a unit area. Two existing energy facilities with an electrical distance less than 0.1 are not allowed to be in the same unit area. The calculation formula for the electrical distance is:

[0106]

[0107] Where Δ(·) represents the calculated difference, ΔT n Q is the energy change of the existing energy facilities within the time interval n, nIt is represented by the heat consumption value of the existing energy facilities in the time interval n, R is represented by the power attenuation coefficient of the existing energy facilities, T max is the maximum allowable temperature of existing energy facilities, X k is the active power of existing energy facilities, C k is the reactive power of existing energy facilities, and D is the Euclidean distance between existing energy facilities;

[0108] The new energy permeability constraint is that the divided unit area cannot be oversaturated with energy, that is, the new energy permeability should be greater than or equal to 90%, and the new energy permeability calculation formula is:

[0109]

[0110] Among them, η is the energy conversion efficiency in the unit area, ψ is the number of existing energy facilities in the unit area, and P L is the power that needs to be carried in the unit area, f N is the operating frequency of existing energy facilities, σ w is the area of ​​energy island in the unit area, ΔP w is the power to be compensated in the unit area, ρ is the distribution density of existing energy facilities, and Δv is the power increment of the new energy facilities compared to the existing energy facilities.

[0111] In this embodiment, the method for calculating the fitness of each area division method includes:

[0112]

[0113] in, is the total number of regions after division, q i is the number of existing energy facilities in unit area i, μ i is the area of ​​unit region i, li is the width of unit region i, A i (x) represents the power defect value at position x in the unit area, It is expressed as the area-based integration of the power defect value in unit area i, A D is the power defect area ratio within unit area i, d max is the maximum distance between existing energy facilities in unit area i, is the average distance between adjacent existing energy facilities in unit area i, and m is the density adjustment index, which is 0.01.

[0114] In this embodiment, the method for determining the installed capacity and location information of new energy facilities based on the characteristic information includes:

[0115] Use K-means clustering algorithm to cluster each unit area, determine the number of clusters based on the elbow rule according to the new energy penetration rate, and use the number of clusters as the number of new energy facilities in the unit area;

[0116] Construct a new energy site selection model, the expression is:

[0117]

[0118] Among them, f is the site selection objective function, n is the number of sites, u i It is expressed as the penetration rate of new energy facilities at the i-th site, A i It is represented as the power defect value of the i-th site, and is the construction cost and environmental restoration cost of the ith site.

[0119] In this embodiment, the method of calculating the path failure rate in the unit area, performing a decoupling operation on the adjacent unit areas based on the path failure rate, and obtaining the energy scheduling path of the target planning area based on the decoupling result includes:

[0120] Calculate the path failure rate between adjacent new energy facilities in the target area using the following formula:

[0121]

[0122] Among them, F max is the maximum possible value of the energy capacity transmitted, F ery is the transmission capacity limit of the path, and F is the flow value of the path;

[0123] The path with a failure rate higher than 0.07 is used as the decoupling standard. The adjacent unit areas that need to be decoupled are determined based on the failure rate. The adjacent unit areas are decoupled using the failure probability as the penalty function. After decoupling, a new energy scheduling path is replanned.

[0124] Determine a first energy dispatch path within the unit area to ensure energy supply and demand balance within the unit area, wherein the first dispatch path is: take a path with the best energy utilization rate among energy facilities of the same type within the unit area as the first dispatch path;

[0125] Determine the second energy dispatch path across regions to ensure the energy exchange balance between unit regions. The energy exchange balance expression of the second energy dispatch path is:

[0126]

[0127] Among them, P u Expressed as the net energy flow for energy exchange, P preIt is represented as the initial energy flow before crossing the region, is the maximum energy flow that the energy-providing region can provide, P is the minimum energy flow required by the energy-receiving region, and z + and z - They represent the direction of energy flow increase and energy flow decrease, respectively. + When it is greater than 0, it means from To P u Increase energy flow, when z - When it is greater than 0, it means that from P pre Reducing the energy flow to P, the objective function expression of the second energy scheduling path is:

[0128]

[0129] Where T represents the period of cross-regional energy exchange, I is the set of second energy scheduling paths, and a i,t is the energy loss of the ith scheduling path at time t, ⊙ represents the element-wise product operation, Expressed as the predicted energy dispatch quantity, x * Expressed as the actual energy dispatch amount, β i,t is the energy exchange cost of the i-th scheduling path at time t.

[0130] In this embodiment, the method of constructing an energy conversion mechanism and an energy storage mechanism for the target area includes:

[0131] Construct an energy converter, the expression is:

[0132]

[0133] in, and For electrical load, gas load, thermal load, and are the charging power and discharging power of the storage device respectively, and are the charging power and releasing power of the heat storage device, respectively, m,ES is the number of installed new energy facilities, k is the number of unit areas, and are the electrical power transmitted between electrical devices, and are the thermal power transmitted between thermal energy devices, θ is the ratio of the electric energy demand of the electric boiler to the purchased electric energy, μ1 is the ratio of the natural gas demand of the gas turbine to the purchased natural gas, and μ2 is the ratio of the natural gas demand of the gas boiler to the purchased natural gas. and are the power of electricity purchased and the power of gas purchased, PPV Produce power for photovoltaics;

[0134] Construct an energy storage, where the expression for energy storage is:

[0135]

[0136] Among them, Q m,HS is the amount of energy stored in the energy storage at the end of period m, Q m-1,HS is the amount of energy stored in the energy storage at the end of period m-1, Expressed as the ratio of actual stored energy to input energy, Expressed as the ratio of the amount of energy extracted from the energy storage to the actual output energy, and represents the charging power and discharging power of the energy storage in time period m.

[0137] In this embodiment, the method for constructing an energy complementation strategy set for the target area based on the energy conversion mechanism and the energy storage mechanism includes:

[0138] Divide the facilities in the target area into three types of energy subsystems, including: energy conversion system, energy storage system and energy consumption facility system, and determine the operating status of each energy consumption facility, including: overload status and idle status;

[0139] Set a time window and perform load judgment regularly every time window. If the energy facility meets the load demand, continue normal operation. If the energy is overloaded, perform energy compensation:

[0140] Select the nearest energy facilities of the same type for energy compensation. When the compensation rate of the nearest energy facilities of the same type is insufficient, give priority to using the energy storage system for energy compensation. If the compensation rate of the energy storage system is insufficient, find the nearest energy conversion system and the different types of energy consumption facilities that are closest to the energy conversion system and in an idle state, and perform comprehensive compensation based on the energy conversion system and the energy storage system.

[0141] For each energy consumption facility in an overloaded state, all possible energy compensation sets are obtained, and based on all possible energy compensation sets, an energy complementary strategy set is obtained.

[0142] In this embodiment, the method for optimizing the energy complementarity strategy set includes:

[0143] The energy benefit including the combination of carbon reduction gain and flexible regulation capacity gain is taken as the first objective function, and the expression is:

[0144]

[0145] Among them, I gr For carbon reduction gain, I fr is the flexible regulation capacity gain, Δψ is the annual carbon emission reduction, L is the dual carbon contribution, T η is the carbon reduction capacity of green building facilities, Τ is the carbon reduction amount of green building facilities, and Υ η is the carbon reduction capacity of building photovoltaic facilities, Υ is the carbon reduction amount of building photovoltaic facilities, Φ η is the carbon reduction capacity of distributed photovoltaic facilities, Φ is the carbon reduction amount of distributed photovoltaic facilities, U * is the comprehensive voltage qualification rate,

[0146] **

[0147] ξ is the energy saving rate, P is the adjustable flexible load, α eq It is represented by the penetration rate of charging piles, Φ is represented by the power supply reliability, ΔQ is the amount of green electricity generated, Expressed as annual carbon emission reduction under maximum power supply reliability and maximum energy saving rate;

[0148] Taking the comprehensive cost of construction and operation as the second objective function, the expression is:

[0149]

[0150] Among them, f cs is the construction cost, f op is the maintenance cost, C fixeed The construction cost of new energy facilities, is the number of new energy facilities, C P and C E They are the unit power cost and unit capacity cost of new energy facilities, and are the rated power and rated capacity of the new energy facilities, r is the discount rate, T life is the service life of new energy facilities, k op The operation and maintenance cost coefficient for new energy facilities;

[0151] Maximize the first objective function and minimize the second objective function to obtain the optimal energy scheduling strategy.

[0152] In this embodiment, the method of maximizing the first objective function and minimizing the second objective function includes:

[0153] The optimal solutions of the first objective function and the second objective function are solved separately, and the values ​​of the remaining objective functions are calculated while solving them separately to obtain the endpoints of the Pareto surface;

[0154] Divide the vector of the Pareto surface boundary into m equal parts, each of which has a length of ΔL = 1 / m, and construct a plane using the endpoints, vectors, and equal division points to obtain the Pareto surface;

[0155] Convert each point on the Pareto surface into a matrix form, determine the positive and negative ideal points, and calculate the relative closeness of each Pareto optimal solution. The calculation formula is:

[0156]

[0157] in, and are the Euclidean distances from the jth optimal solution to the positive ideal point and the negative ideal point respectively;

[0158] The Pareto optimal solution with the largest relative fit is selected as the final energy scheduling strategy.

[0159] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for regional planning of new energy system construction in high temperature and high humidity areas, characterized in that: The following steps are involved: Step S1, constructing a region division rule, and dividing the target region into a plurality of unit regions based on the region division rule; Step S2, acquiring characteristic information of the unit area, determining the installed capacity and location information of the new energy facilities based on the characteristic information, and obtaining the layout of the unit area; the characteristic information includes construction characteristics, load characteristics and resource characteristics; Step S3, calculating the path failure rate in the target area, performing a decoupling operation on adjacent unit areas based on the path failure rate, and obtaining an energy scheduling path in the target planning area based on the decoupling result; The energy scheduling path includes a first energy scheduling path within a unit area and a second energy scheduling path across regions; Step S4: constructing an energy conversion mechanism and an energy storage mechanism for the target area, and constructing an energy complementary strategy set for the target area based on the energy conversion mechanism and the energy storage mechanism; Step S5: optimizing the energy complementary strategy set to obtain an optimal energy complementary strategy, and planning the target area according to the layout of the unit area, the energy scheduling path and the optimal energy complementary strategy.

2. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 1, characterized in that: The method for constructing the area division rule in step S1 includes: Identify energy demand hotspots in the target planning area and divide existing energy facilities into controllable supply facilities and uncontrollable consumption facilities; Energy demand hotspots, controllable supply facilities, and uncontrollable consumption facilities are used as nodes to construct partitioning constraints; Based on the division constraints, a variety of regional division methods are obtained, the fitness of each regional division method is calculated, and the regional division method with the largest fitness is retained as the final regional division method.

3. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 2, characterized in that: The method for constructing partitioning constraints comprises: Balance constraint: Each unit area must contain at least one energy demand hotspot node, one controllable supply facility node, and one uncontrollable consumption facility node to ensure self-balance in the unit area; Node distance constraint constrains the electrical distance between two existing energy facilities in a unit area. Two existing energy facilities with an electrical distance less than 0.1 are not allowed to be in the same unit area. The calculation formula for the electrical distance is: Where Δ(·) represents the calculated difference, ΔT n Q is the energy change of the existing energy facilities within the time interval n, n It is represented by the heat consumption value of the existing energy facilities in the time interval n, R is represented by the power attenuation coefficient of the existing energy facilities, T max is the maximum allowable temperature of existing energy facilities, X k is the active power of existing energy facilities, C k is the reactive power of existing energy facilities, and D is the Euclidean distance between existing energy facilities; The new energy permeability constraint is that the divided unit area cannot be oversaturated with energy, that is, the new energy permeability should be greater than or equal to 90%, and the new energy permeability calculation formula is: Among them, η is the energy conversion efficiency in the unit area, ψ is the number of existing energy facilities in the unit area, P L is the power that needs to be carried in the unit area, f N is the operating frequency of existing energy facilities, σ w is the area of ​​energy island in the unit area, ΔP w is the power to be compensated in the unit area, ρ is the distribution density of existing energy facilities, and Δv is the power increment of the new energy facilities compared with the existing energy facilities.

4. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 2, characterized in that: The method for calculating the fitness of each area division method includes: in, is the total number of regions after division, q i is the number of existing energy facilities in unit area i, μ i is the area of ​​unit region i, li is the width of unit region i, A i (x) represents the power defect value at position x in the unit area, It is expressed as the area-based integration of the power defect value in unit area i, A D is the power defect area ratio within unit area i, d max is the maximum distance between existing energy facilities in unit area i, is the average distance between adjacent existing energy facilities in unit area i, and m is the density adjustment index, which is 0.

01.

5. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 1, characterized in that: The method for determining the installed capacity and location information of new energy facilities based on the characteristic information includes: Use K-means clustering algorithm to cluster each unit area, determine the number of clusters based on the elbow rule according to the new energy penetration rate, and use the number of clusters as the number of new energy facilities in the unit area; Construct a new energy site selection model, the expression is: Among them, f is the site selection objective function, n is the number of sites, u i It is expressed as the penetration rate of new energy facilities at the i-th site, A i It is represented as the power defect value of the i-th site, and is the construction cost and environmental restoration cost of the ith site.

6. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 1, characterized in that: The method of calculating the path failure rate in the unit area, performing a decoupling operation on adjacent unit areas based on the path failure rate, and obtaining an energy scheduling path for a target planning area based on the decoupling result includes: Calculate the path failure rate between adjacent new energy facilities in the target area using the following formula: Among them, F max is the maximum possible value of the energy capacity transmitted, F ery is the transmission capacity limit of the path, and F is the flow value of the path; The path with a failure rate higher than 0.07 is used as the decoupling standard. The adjacent unit areas that need to be decoupled are determined based on the failure rate. The adjacent unit areas are decoupled using the failure probability as the penalty function. After decoupling, a new energy scheduling path is replanned. Determine a first energy dispatch path within the unit area to ensure energy supply and demand balance within the unit area, wherein the first dispatch path is: take a path with the best energy utilization rate among energy facilities of the same type within the unit area as the first dispatch path; Determine the second energy dispatch path across regions to ensure the energy exchange balance between unit regions. The energy exchange balance expression of the second energy dispatch path is: Among them, P u Expressed as the net energy flow for energy exchange, P pre It is represented as the initial energy flow before crossing the region, is the maximum energy flow that the energy-providing region can provide, P is the minimum energy flow required by the energy-receiving region, and z + and z - They represent the direction of energy flow increase and energy flow decrease, respectively. + When it is greater than 0, it means from To P u Increase energy flow, when z - When it is greater than 0, it means that from P pre Reducing the energy flow to P, the objective function expression of the second energy scheduling path is: Where T represents the period of cross-regional energy exchange, I is the set of second energy scheduling paths, and a i,t is the energy loss of the ith scheduling path at time t, ⊙ represents the element-wise product operation, Expressed as the predicted energy dispatch quantity, x * Expressed as the actual energy dispatch amount, β i,t is the energy exchange cost of the i-th scheduling path at time t.

7. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 1, characterized in that: The method of constructing an energy conversion mechanism and an energy storage mechanism for the target area includes: Construct an energy converter, the expression is: in, and For electrical load, gas load, thermal load, and are the charging power and discharging power of the storage device respectively, and are the charging power and releasing power of the heat storage device, respectively, m,ES is the number of installed new energy facilities, k is the number of unit areas, and are the electrical power transmitted between electrical devices, and are the thermal power transmitted between thermal energy devices, λ is the ratio of the electric energy demand of the electric boiler to the purchased electric energy, μ1 is the ratio of the natural gas demand of the gas turbine to the purchased natural gas, μ2 is the ratio of the natural gas demand of the gas boiler to the purchased natural gas, and are the power of electricity purchased and the power of gas purchased, P PV Produce power for photovoltaics; Construct an energy storage, where the expression for energy storage is: Among them, Q m,HS is the amount of energy stored in the energy storage at the end of period m, Q m-1,HS is the amount of energy stored in the energy storage at the end of period m-1, Expressed as the ratio of actual stored energy to input energy, Expressed as the ratio of the amount of energy extracted from the energy storage to the actual output energy, and represents the charging power and discharging power of the energy storage in time period m.

8. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 1, characterized in that: The method for constructing a set of energy complementarity strategies for the target area based on the energy conversion mechanism and the energy storage mechanism includes: Divide the facilities in the target area into three types of energy subsystems, including: energy conversion system, energy storage system and energy consumption facility system, and determine the operating status of each energy consumption facility, including: overload status and idle status; Set a time window and perform load judgment regularly every time window. If the energy facility meets the load demand, continue normal operation. If the energy is overloaded, perform energy compensation: Select the nearest energy facilities of the same type for energy compensation. When the compensation rate of the nearest energy facilities of the same type is insufficient, give priority to using the energy storage system for energy compensation. If the compensation rate of the energy storage system is insufficient, find the nearest energy conversion system and the different types of energy consumption facilities that are closest to the energy conversion system and in an idle state, and perform comprehensive compensation based on the energy conversion system and the energy storage system. For each energy consumption facility in an overloaded state, all possible energy compensation sets are obtained, and based on all possible energy compensation sets, an energy complementary strategy set is obtained.

9. A method for planning the construction of a new energy system in a high temperature and high humidity area according to claim 1, characterized in that: The method for optimizing the energy complementation strategy set includes: The energy benefit including the combination of carbon reduction gain and flexible regulation capacity gain is taken as the first objective function, and the expression is: Among them, I gr For carbon reduction gain, I fr is the flexible regulation capacity gain, Δψ is the annual carbon emission reduction, L is the dual carbon contribution, T η is the carbon reduction capacity of green building facilities, Τ is the carbon reduction amount of green building facilities, and Υ η is the carbon reduction capacity of building photovoltaic facilities, Υ is the carbon reduction amount of building photovoltaic facilities, Φ η is the carbon reduction capacity of distributed photovoltaic facilities, Φ is the carbon reduction amount of distributed photovoltaic facilities, U * is the comprehensive voltage qualification rate, ** ξ is the energy saving rate, P is the adjustable flexible load, α eq It is represented by the penetration rate of charging piles, Φ is represented by the power supply reliability, ΔQ is the amount of green electricity generated, Expressed as annual carbon emission reduction under maximum power supply reliability and maximum energy saving rate; Taking the comprehensive cost of construction and operation as the second objective function, the expression is: Among them, f cs is the construction cost, f op is the maintenance cost, C fixeed The construction cost of new energy facilities, is the number of new energy facilities, C P and C E They are the unit power cost and unit capacity cost of new energy facilities, and are the rated power and rated capacity of the new energy facilities, r is the discount rate, T life is the service life of new energy facilities, k op The operation and maintenance cost coefficient for new energy facilities; Maximize the first objective function and minimize the second objective function to obtain the optimal energy scheduling strategy.

10. The urban underground space environment monitoring system based on the Internet of Things according to claim 9 is characterized in that: The method of maximizing the first objective function and minimizing the second objective function comprises: The optimal solutions of the first objective function and the second objective function are solved separately, and the values ​​of the remaining objective functions are calculated while solving them separately to obtain the endpoints of the Pareto surface; Divide the vector of the Pareto surface boundary into m equal parts, each of which has a length of ΔL = 1 / m, and construct a plane using the endpoints, vectors, and equal division points to obtain the Pareto surface; Convert each point on the Pareto surface into a matrix form, determine the positive and negative ideal points, and calculate the relative closeness of each Pareto optimal solution. The calculation formula is: in, and are the Euclidean distances from the jth optimal solution to the positive ideal point and the negative ideal point respectively; The Pareto optimal solution with the largest relative fit is selected as the final energy scheduling strategy.

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