Independent micro-grid energy storage optimization method considering lithium ore load regulation potential improvement

Abstract

The invention discloses an independent micro-grid energy storage optimization method considering lithium ore load regulation potential improvement, and the method comprises the steps: S1, considering the lithium ore load regulation potential and a micro-grid operation scene, and constructing a lithium ore load and energy storage coordination optimization model; s2, outputting a result of the lithium ore load and energy storage coordinated optimization model by taking the optimal operation cost benefit of the micro-grid as a target function; and S3, according to an output result of the lithium ore load and energy storage coordinated optimization model, completing independent micro-grid energy storage optimization, the lithium ore load regulation potential is excavated, the bidirectional flexible interaction capability with the micro-grid is improved, the micro-grid system operation cost is reduced, and the new energy consumption capability and the lithium ore load power supply reliability are improved in the technical aspect.

Description

Technical Field

[0001] The present invention relates to the field of microgrid configuration, and in particular to an independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential. Background Art

[0002] With the continuous development of new energy power batteries and energy storage equipment, and the continuous advancement of the task of consolidating and developing border areas, the demand for the development of salt lake lithium mine resources in remote border areas is growing, and energy-intensive lithium mining companies are gradually emerging. However, the "long-chain, weakly interconnected" grid structure is difficult to extend to remote areas, the power grid in the surrounding areas is weak, and the level of grid mutual assistance is insufficient. It is necessary to develop clean energy independent microgrids according to local conditions to meet the substantial increase in the power demand of high-energy-consuming lithium mine loads. The high proportion of clean energy access to the grid with strong randomness and volatility will frequently lead to power imbalance problems in independent microgrids. The lack of support from large power grids will further aggravate the phenomenon of clean energy abandonment and load power shortage. Under the above background, energy storage systems that can realize power support and energy transfer are regarded as high-quality regulation resources to meet the power balance of microgrids. At the same time, there is still a large gap in the response of large-scale, highly flexible, and multi-process lithium mine loads, and it is necessary to further tap its regulation potential, improve its demand response mechanism, and enhance the two-way interaction ability of independent microgrids. Therefore, the study of the optimization configuration strategy of independent microgrids considering the improvement of lithium mine load regulation potential is helpful to meet the power demand of independent lithium mine microgrid loads and improve the clean energy consumption capacity.

[0003] The flexibility of considering production processes and production behavior constraints is a typical feature of industrial loads that is different from other loads. Its flexibility modeling and quantification is an important part of participating in demand response and realizing multi-resource coordinated optimization operation. At present, relevant research has been carried out at home and abroad on the participation of high-energy-consuming industrial loads in the optimization operation of power grids. Existing technologies include:

[0004] 1. Based on the high energy consumption load industrial production process of electrolytic copper, a power control strategy is proposed to maximize the load response benefit while meeting the production safety and effective response constraints;

[0005] 2. Establish an economic dispatch model of the power system that takes into account the emission characteristics of typical cement plant industrial loads, and use a stepped time-of-use electricity price to increase the enthusiasm of industrial loads to participate in demand response;

[0006] 3. Based on the production characteristics of different types of industrial loads, the flexibility potential is explored, and the effective escaping of industrial load resources is achieved through a multi-time scale rolling optimization scheduling model;

[0007] 4. Treat industrial loads as transferable loads and include them in virtual power plants to participate in grid demand response to optimize power system operation and regulation;

[0008] 5. Taking the electrolytic aluminum load as a representative of typical high-energy-consuming industrial loads, the demand response regulation capability boundary was constructed by analyzing its production characteristics and regulation constraints, thereby enhancing the ability of large-capacity electrolytic aluminum loads to flexibly participate in the two-way interaction of the power grid.

[0009] The above studies have considered the industrial production process and have widely explored the flexible regulation potential of high-energy-consuming industrial loads such as electrolytic copper, cement plants, and electrolytic aluminum, effectively improving the economic benefits of industrial enterprises and the stable operation capacity of the power grid. However, compared with the power supply of industrial loads in the large power grid, the electricity demand of high-energy-consuming lithium mines has brought more severe power supply pressure to the clean energy independent microgrids that lack the support of the large power grid. It is particularly urgent to quantify the flexibility of lithium mine loads participating in the grid demand response, but research in this area is still rarely reported. Summary of the invention

[0010] In view of the above-mentioned deficiencies in the prior art, the present invention provides an independent microgrid energy storage optimization method that takes into account the improvement of lithium mine load regulation potential, focuses on independent industrial and mining microgrid scenarios in remote areas, and proposes an independent microgrid energy storage optimization configuration and operation strategy that takes into account the improvement of industrial and mining load regulation potential, which solves the problems of insufficient lithium mine load demand response capability, difficulty in improving new energy consumption capacity, and insufficient operation reliability of independent industrial and mining microgrids.

[0011] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: an independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential, comprising:

[0012] S1. Considering the lithium mine load regulation potential and microgrid operation scenarios, a coordinated optimization model of lithium mine load and energy storage is constructed;

[0013] S2. Taking the optimal cost-effectiveness of microgrid operation as the objective function, output the results of the coordinated optimization model of lithium mine load and energy storage;

[0014] S3. Complete the independent microgrid energy storage optimization based on the output results of the lithium mine load and energy storage coordination optimization model.

[0015] Further: In S1, the expression of the coordinated optimization model of lithium ore load and energy storage is:

[0016] Q=mC P ΔT (1)

[0017] Q loss,t =hA(T lu,t -T env,t ) (2)

[0018] T min ≤T lu,t ≤T max (3)

[0019]

[0020] mxD P (T lu,t+1 -T lu,t )=ηP Li (t)-Q loss,t (7)

[0021]

[0022] Among them, Q represents the heat required in the process of heating brine, m represents the mass of brine, C p represents the specific heat capacity of brine, ΔT represents the temperature change of brine Q loss,t represents the amount of heat loss per unit time; h represents the heat transfer coefficient between the outside world and the heat storage tank; A represents the surface area of ​​the heat storage tank in contact with the outside world; T lu,t Represents brine temperature; T env,t Represents the ambient temperature, T max Represents the upper limit of brine temperature; T min Represents the lower limit of brine temperature, P Li (t) is the lithium mine load operating power; and They represent the upper and lower limits of thermal inertia load power at time t; λ represents the thermal efficiency coefficient of heating, C Li Economic compensation for lithium mine load temperature control; c Li Economic compensation cost per unit power for lithium mine load temperature control; The planned power consumption curve for lithium mine load is: and P tr (t) are the transferable load powers before and after dispatch, respectively; T is the dispatch period, and are the upper and lower limits of the power after load transfer, K tr The compensation price for unit power load transfer.

[0023] Further: In S2, the objective function is the cost of renewable energy abandonment obj PV , gas turbine power generation and carbon reduction costs GT 、Operation cost of CSP unit obj PT , energy storage construction and operation costs ES And the lithium mine load adjustment cost obj load The comprehensive operation cost of the microgrid obj obtained by linear weighting is expressed as:

[0024] min obj=obj PV +obj GT +obj PT +obj ES +objload (12)

[0025] Among them, min represents the minimization operation;

[0026] New energy abandoned electricity cost PV The expression is:

[0027]

[0028] Among them, c PV is the penalty cost per unit abandoned optical power, is the predicted photovoltaic output power on a typical day, P PV (t) is the actual operating power of photovoltaic power;

[0029] Gas turbine power generation and carbon reduction costs GT The expression is:

[0030] obj GT =∑ t (c GT +c ca ) GT (t) (14)

[0031] Among them, c GT and c ca are the power generation cost per unit power of gas turbine and the penalty cost of carbon emission; P GT (t) is the operating power of the gas turbine;

[0032] CSP unit operating cost obj PT The expression is:

[0033] obj PT =∑ t c PT |P PT (t) (15)

[0034] Among them, c PT is the unit operating cost of the CSP unit; P PT (t) is the output of the CSP unit at time t;

[0035] Energy storage construction and operation costs ES The expression is:

[0036]

[0037]

[0038] C op =∑ t c op |P ES (t)| (19)

[0039] in, is the one-time investment and construction cost; C op is the energy storage operation cost; R ES is the annual investment recovery factor of energy storage; T ES is the life of energy storage; r is the discount rate; c E The construction cost of the entire life cycle of energy storage; E N is the rated capacity of energy storage; P ES (t) is the operating power of the energy storage at time t; c op is the operation and maintenance cost coefficient of energy storage;

[0040] Lithium ore load adjustment cost obj load The expression is:

[0041] obj laod =C Li +C tr (20).

[0042] Furthermore: the constraints of the lithium mine load and energy storage coordinated optimization model include power supply constraints, grid constraints, energy storage constraints and load constraints.

[0043] Further: the power supply constraints include photovoltaic unit output constraints, gas turbine output constraints and solar thermal unit output constraints;

[0044] The output constraint of photovoltaic units is:

[0045]

[0046] The gas turbine output constraint is:

[0047]

[0048] Among them, μ GT is the minimum technical output coefficient of the gas turbine; is the rated power of the gas turbine;

[0049] The output constraints of CSP units include power generation output constraints, minimum on / off time cycle constraints, instantaneous thermal power constraints, charge and thermal state constraints, and thermal storage system boundary constraints;

[0050] The expression of power generation output constraint is:

[0051] P s,min *I CSP (t)≤P CSP (t)≤P s,max *I CSP (t)

[0052] I CSP(t)∈{0,1} (23)

[0053] Among them, I CSP (t) is the on / off state of the CSP device at time period t; P CSP (t) is the dispatching output of the CSP plant in time period t; P s,min and P s,max They are the lower and upper limits of the output power of a CSP plant respectively;

[0054] The expression for the minimum on / off time period constraint is:

[0055]

[0056] Among them, T s,off is the period during which the CSP unit is shut down, T s,on The period during which the CSP unit is turned on;

[0057] The expression of instantaneous thermal power constraint is:

[0058]

[0059] λ cha +λ dis ≤1 (27)

[0060] Among them, η PB,s is the power efficiency of the CSP device; is the thermal storage power of CSP in time period t; is the heat release power of CSP in time period t; is the solar thermal power available during period t; is the rated value of the CSP output system; η N,dis is the efficiency of converting heat release power into electrical power; cha and λ dis are 0-1 state variables that characterize heat storage and heat release of the CSP thermal storage system;

[0061] The expression of the charge thermal state constraint is:

[0062]

[0063] Among them, E CSP (t) is the heat storage capacity of the heat storage system in the CSP device at time period t; η CSP is the efficiency coefficient of the heat storage system.

[0064] The expression of the boundary constraint of the thermal storage system is:

[0065] E s,min ≤E CSP (t)≤E s,max (29)

[0066] Among them, E s,min and E s,max They are respectively the lower and upper limits of the heat storage capacity of the heat storage system in the CSP device.

[0067] Further: The expression of the power grid constraint is:

[0068]

[0069] Among them, P Net,t It is because the microgrid cannot completely absorb the unbalanced power at time t.

[0070] Further: energy storage constraints include energy storage capacity configuration and operation constraints, grid energy storage response potential constraints, and grid energy storage charge state constraints;

[0071] The expressions of energy storage capacity configuration and operation constraints are:

[0072]

[0073] Among them, P ES,N is the rated capacity of energy storage, P ES,max is the maximum rated capacity of energy storage, P ES,min is the minimum rated capacity of energy storage, λ ES is the energy storage configuration variable, P ES (t) is the operating power of the microgrid in which the energy storage participates at time t; α ch and α dis are the maximum charging efficiency and the maximum discharging efficiency respectively;

[0074] The expression of grid energy storage response potential constraint is:

[0075]

[0076] in, and They are the upward and downward response rates of the grid energy storage participating in the multi-link regulation of the grid during period t; Δt is the time period during which the grid energy storage actually participates in the regulation of the microgrid;

[0077] The expression of the grid energy storage charge state constraint is:

[0078]

[0079] Among them, S0 and S max are the initial state and total capacity of energy storage, respectively, and their ratio is the state of charge before energy storage participates in multi-link regulation of the power grid; P ES (t) is the charging and discharging power of the grid energy storage during period t; t0 and t endare the start time and end time of the grid energy storage participating in the multi-link regulation of the grid; t1 is any period between the start time and end time of the grid energy storage participating in the multi-link regulation of the grid.

[0080] Further: The expression of load response rate constraint is:

[0081]

[0082] in, and They are the lower and upper limits of lithium ore load regulation rate respectively; and are the lower and upper limits of the transferable load regulation rate respectively.

[0083] Further: S3 includes:

[0084] S31. Determine whether the output result of the lithium mine load and energy storage coordination optimization model satisfies the power balance:

[0085] If so, the energy storage optimization of the independent microgrid is completed;

[0086] If not, enter S32;

[0087] S32, calculating the unbalanced power of the microgrid, and calculating the unbalanced power penalty of the microgrid according to the unbalanced power of the microgrid;

[0088] S33. Complete the energy storage optimization of the independent microgrid according to the unbalanced power penalty of the microgrid.

[0089] The beneficial effects of the present invention are:

[0090] 1. Establish a coordinated optimization model for lithium mine load and energy storage, tap the potential for lithium mine load regulation, and enhance the two-way flexible interaction capability with the microgrid;

[0091] 2. It involves designing photovoltaic units, solar thermal units, energy storage, and lithium mine load constraints, and constructing an independent microgrid energy storage optimization configuration model with the best system comprehensive construction and operation costs. It reduces the operating costs of the microgrid system economically and improves the new energy absorption capacity and lithium mine load power supply reliability technically. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] Figure 1 Flowchart of the energy storage optimization method for a standalone microgrid considering the enhanced load regulation potential of lithium mines.

[0093] Figure 2 Optimize the operation diagram for microgrids without energy storage.

[0094] Figure 3 This is a diagram of the heat storage and release of the solar thermal unit.

[0095] Figure 4 Optimize the operation diagram for microgrids with energy storage participation.

[0096] Figure 5 This is a diagram of the heat storage and release of the solar thermal unit.

[0097] Figure 6 Schematic diagram of system unbalanced power with and without energy storage participation.

[0098] Figure 7 Schematic diagram comparing the system curtailment with and without energy storage.

[0099] Figure 8 Schematic diagram of heat storage and release comparison between CSP units with and without energy storage. DETAILED DESCRIPTION

[0100] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0101] like Figure 1 As shown, in one embodiment of the present invention, an independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential is provided, including:

[0102] S1. Considering the lithium mine load regulation potential and microgrid operation scenarios, a coordinated optimization model of lithium mine load and energy storage is constructed;

[0103] S2. Taking the optimal cost-effectiveness of microgrid operation as the objective function, output the results of the coordinated optimization model of lithium mine load and energy storage;

[0104] S3. Complete the independent microgrid energy storage optimization based on the output results of the lithium mine load and energy storage coordination optimization model.

[0105] Furthermore, in S1, the expression of the coordinated optimization model of lithium ore load and energy storage is:

[0106] Q=mC P ΔT (1)

[0107] Q loss,t =hA(T lu,t -T env,t ) (2)

[0108] T min ≤T lu,t ≤T max (3)

[0109]

[0110] mxD P (T lu,t+1 -T lu,t )=ηP Li (t)-Q loss,t (7)

[0111]

[0112] Among them, Q represents the heat required in the process of heating brine, m represents the mass of brine, C p represents the specific heat capacity of brine, ΔT represents the temperature change of brine Q loss,t represents the amount of heat loss per unit time; h represents the heat transfer coefficient between the outside world and the heat storage tank; A represents the surface area of ​​the heat storage tank in contact with the outside world; T lu,t Represents brine temperature; T env,t Represents the ambient temperature, T max Represents the upper limit of brine temperature; T min represents the lower limit of brine temperature, P Li (t) is the lithium mine load operating power; and They represent the upper and lower limits of thermal inertia load power at time t; λ represents the thermal efficiency coefficient of heating, C Li Economic compensation for lithium mine load temperature control; c Li Economic compensation cost per unit power for lithium mine load temperature control; The planned power consumption curve for lithium mine load is: and P tr (t) are the transferable load powers before and after dispatch, respectively; T is the dispatch period, and are the upper and lower limits of the power after load transfer, K tr The compensation price for unit power load transfer.

[0113] Among them, formula (1) is the heat consumption model of brine, formula (2) is used to characterize the heat loss caused by the interaction with environmental heat energy, formula (3) is used to characterize the temperature regulation potential of brine, formula (4)-formula (6) are used to characterize the power regulation potential of electricity, formula (7) is used to characterize the thermal power balance of the heat storage tank, formula (8) is used to characterize the economic compensation of industrial and mining load temperature regulation, formula (9) is used to characterize the load transferability characteristics of time series production, formula (10) is used to characterize the transferable load regulation potential of time series production, and formula (11) is used to characterize the compensation that should be made when the electricity load is transferred.

[0114] In S2, the objective function is the cost of renewable energy abandonment obj PV , gas turbine power generation and carbon reduction costsGT 、Operation cost of CSP unit obj PT , energy storage construction and operation costs ES And the lithium mine load adjustment cost obj load The comprehensive operation cost of the microgrid obj obtained by linear weighting is expressed as:

[0115] min obj=obj PV +obj GT +obj PT +obj ES +obj load (12)

[0116] Among them, min represents the minimization operation.

[0117] The output power of photovoltaic units supplies the load demand. In order to improve the photovoltaic absorption rate, the abandonment rate is included in the optimization target. In order to facilitate multi-objective linear weighting, it is converted into an economic target of the abandonment cost. The new energy abandonment cost obj PV The expression is:

[0118]

[0119] Among them, c PV is the penalty cost per unit abandoned optical power, is the predicted photovoltaic output power on a typical day, P PV (t) is the actual operating power of photovoltaic power;

[0120] Gas turbine power generation and carbon reduction costs GT The expression is:

[0121] obj GT =∑ t (c GT +c ca ) GT (t) (14)

[0122] Among them, c GT and c ca are the power generation cost per unit power of gas turbine and the penalty cost of carbon emission; P GT (t) is the operating power of the gas turbine;

[0123] CSP unit operating cost obj PT The expression is:

[0124] obj PT =∑ t c PT |P PT (t)| (15)

[0125] Among them, c PT is the unit operating cost of the CSP unit; P PT (t) is the output of the CSP unit at time t;

[0126] Energy storage costs include energy storage construction costs and operation and maintenance costs. The primary investment and construction costs of energy storage refer to the total construction costs of various types of energy storage divided by the operating life, converted to daily fixed costs. The energy storage operation and maintenance costs are the costs required to maintain the energy storage power station in a good standby state. The energy storage construction and operation costs are ES The expression is:

[0127]

[0128] C op =∑ t c op |P ES (t)| (19)

[0129] in, is the one-time investment and construction cost; C op is the energy storage operation cost; R ES is the annual investment recovery factor of energy storage; T ES is the life of energy storage; r is the discount rate; c E The construction cost of the entire life cycle of energy storage; E N is the rated capacity of energy storage; P ES (t) is the operating power of the energy storage at time t; c op is the operation and maintenance cost coefficient of energy storage;

[0130] Lithium ore load adjustment cost obj load The expression is:

[0131] obj laod =C Li +C tr (20).

[0132] Specifically, the lithium mine load and energy storage coordinated optimization model also includes constraints based on the optimized operating conditions of the industrial and mining microgrid. The constraints of the lithium mine load and energy storage coordinated optimization model include power supply constraints, grid constraints, energy storage constraints and load constraints.

[0133] Power supply constraints include photovoltaic unit output constraints, gas turbine output constraints, and solar thermal unit output constraints;

[0134] The output constraint of photovoltaic units is:

[0135]

[0136] The gas turbine output constraint is:

[0137]

[0138] Among them, μ GT is the minimum technical output coefficient of the gas turbine; is the rated power of the gas turbine;

[0139] The output constraints of the CSP unit include power generation output constraints, minimum on / off time cycle constraints, instantaneous thermal power constraints, charge and thermal state constraints, and thermal storage system boundary constraints;

[0140] The expression of power generation output constraint is:

[0141] P s,min *I CSP (t)≤P CSP (t)≤P s,max *I CSP (t)

[0142] I CSP (t)∈{0,1} (23)

[0143] Among them, I CSP (t) is the on / off state of the CSP device at time period t; P CSP (t) is the dispatching output of the CSP plant in time period t; P s,min and P s,max They are the lower and upper limits of the output power of a CSP plant respectively;

[0144] The expression for the minimum on / off time period constraint is:

[0145]

[0146] Among them, T s,off is the period during which the CSP unit is shut down, T s,on The period during which the CSP unit is turned on;

[0147] The expression of instantaneous thermal power constraint is:

[0148]

[0149] λ cha +λ dis ≤1 (27)

[0150] Among them, η PB,s is the power efficiency of the CSP device; is the thermal storage power of CSP in time period t; is the heat release power of CSP in time period t; is the solar thermal power available during period t; is the rated value of the CSP output system; η N,dis is the efficiency of converting heat release power into electrical power; cha and λ dis are 0-1 state variables that characterize heat storage and heat release of the CSP thermal storage system;

[0151] The expression of the charge thermal state constraint is:

[0152]

[0153] Among them, E CSP (t) is the heat storage capacity of the heat storage system in the CSP device at time period t; η CSP is the efficiency coefficient of the heat storage system.

[0154] The expression of the boundary constraint of the thermal storage system is:

[0155] E s,min ≤E CSP (t)≤E s,max (29)

[0156] Among them, E s,min and E s,max They are respectively the lower and upper limits of the heat storage capacity of the heat storage system in the CSP device.

[0157] Since the microgrid needs to maintain system power balance and guarantee load power demand, including the load power, power generation power, energy storage power and unbalanced power of the entire power system, the expression of the grid constraint is:

[0158]

[0159] Among them, P Net,t It is because the microgrid cannot completely absorb the unbalanced power at time t.

[0160] Energy storage constraints include energy storage capacity configuration and operation constraints, grid energy storage response potential constraints, and grid energy storage charge state constraints;

[0161] The expressions of energy storage capacity configuration and operation constraints are:

[0162]

[0163] Among them, P ES,N is the rated capacity of energy storage, P ES,max is the maximum rated capacity of energy storage, P ES,min is the minimum rated capacity of energy storage, λ ES is the energy storage configuration variable, P ES (t) is the operating power of the microgrid in which the energy storage participates at time t; α ch and α disare the maximum charging efficiency and the maximum discharging efficiency respectively;

[0164] Since the multiplication of 0-1 variables and continuous variables is nonlinear, the Big-M method is used to linearize equation (31) as follows:

[0165]

[0166] Among them, P MV An intermediate variable introduced to characterize the energy storage configuration, M is an infinite coefficient.

[0167] The expression of grid energy storage response potential constraint is:

[0168]

[0169] in, and They are the upward and downward response rates of the grid energy storage participating in the multi-link regulation of the grid during period t; Δt is the time period during which the grid energy storage actually participates in the regulation of the microgrid;

[0170] The grid energy storage charge state constraint is used to indicate the ratio of the remaining capacity of the grid energy storage in a certain period of time to its fully charged capacity. It is usually expressed as a percentage with a value range of 0 to 1. When SOC = 0, it means that the energy storage is fully discharged, and when SOC = 1, it means that the energy storage is fully charged. The expression of the grid energy storage charge state constraint is:

[0171]

[0172] Among them, S0 and S max are the initial state and total capacity of energy storage, respectively, and their ratio is the state of charge before energy storage participates in multi-link regulation of the power grid; P ES (t) is the charging and discharging power of the grid energy storage during period t; t0 and t end are the start time and end time of the grid energy storage participating in the multi-link regulation of the grid; t1 is any period between the start time and end time of the grid energy storage participating in the multi-link regulation of the grid.

[0173] The expression of load response rate constraint is:

[0174]

[0175] in, and They are the lower and upper limits of lithium ore load regulation rate respectively; and are the lower and upper limits of the transferable load regulation rate respectively.

[0176] In addition to the load response rate constraint, other constraints on the load side are shown in equations (1) to (7), (9) and (10).

[0177] Furthermore, in this embodiment, S3 includes:

[0178] S31. According to the power balance equation constraint of formula (30), determine whether the output result of the lithium mine load and energy storage coordination optimization model satisfies the power balance:

[0179] If so, the energy storage optimization of the independent microgrid is completed;

[0180] If not, enter S32;

[0181] S32, calculate the unbalanced power of the microgrid, and calculate the unbalanced power P of the microgrid according to the unbalanced power P of the microgrid. Net,t , the unbalanced power P of the microgrid Net,t Multiplying by an infinite unit cost coefficient gives the microgrid unbalanced power penalty;

[0182] S33, completing energy storage optimization of the independent microgrid according to the unbalanced power penalty of the microgrid;

[0183] The specific method is: incorporate the penalty for unbalanced power of the microgrid into the comprehensive cost of the optimization target, and the power grid dispatching center then adopts backup measures to make up for the unbalanced power, thereby completing the optimized dispatching operation of the microgrid.

[0184] To demonstrate the feasibility and beneficial effects of the present application, in one example of the invention, an analysis of the optimized operation of a microgrid without the participation of energy storage, an analysis of the optimized operation of a microgrid with the participation of energy storage, and a comparative analysis of the optimized operation of a microgrid with and without the participation of energy storage were conducted.

[0185] Analysis of microgrid optimization operation without energy storage:

[0186] Since the CSP power station is equipped with a heat storage system, it has overcome the randomness and uncertainty of solar energy resources, so it can maintain a stable output. It can be used as the main unit in the power system to bear the basic load, or as the peak-shaving unit in the power system to bear the peak load. Compared with coal-fired units, CSP power generation units have better regulation characteristics, can quickly respond to grid load requirements, and quickly adjust the output of the units. By integrating it into the grid together with photovoltaic power, and utilizing the regulation characteristics of CSP output, the volatility of wind and solar output can be smoothed, and the uncertainty brought to the grid when photovoltaic power is connected to the grid on a large scale can be reduced, thereby increasing the absorption of photovoltaic resources.

[0187] like Figure 1As shown in the figure, when there is no energy storage involved in the operation, the operating resources of the microgrid are photovoltaic units, solar thermal units and loads. When photovoltaic power generation is large, the photovoltaic output is much higher than the load power demand. Part of the photovoltaic output will be directly stored in the heat storage device in the solar thermal unit through the molten salt heater. When there is no light at night, it will release heat to heat the water vapor, drive the steam turbine to rotate and finally convert it into electrical power output. When the photovoltaic output is 0 at night, the load is powered. However, due to the limitation of the rated power of the steam turbine, the maximum power is only 12MW, which is still unable to effectively meet the load power demand at night, and there is still a large proportion of power shortage.

[0188] In addition, the heat storage and heat release of the solar thermal unit are further analyzed. Since there is no solar collector field in this example, the heat source of the heat storage system and the steam turbine unit comes from photovoltaic power generation heating. Therefore, part of the photovoltaic system actually outputs power directly, and the other part converts electrical energy into thermal energy for storage through the molten salt heater. Figure 2 As shown in the figure, the CSP unit stores heat at 15:00 and 16:00, and releases heat at 1:00-8:00 and 17:00-24:00. Considering the influence of factors such as heat loss, the thermoelectric conversion efficiency in this paper is considered to be 0.95, that is, 95% of the heat released by the CSP unit will be converted into electrical power output to meet the power demand of photovoltaic small power generation and night load, which is consistent with Figure 3 The output of the CSP units shown remains consistent.

[0189] Analysis of energy storage participating in microgrid optimization operation:

[0190] When energy storage participates in the optimization operation of the microgrid, the resources included in the microgrid are photovoltaic units, solar thermal units, energy storage and loads. The photovoltaic units, solar thermal units and energy storage work together to meet the power demand of the loads. Figure 4 As shown, similarly, when photovoltaic power is high, in addition to supplying load demand, the system surplus power is absorbed by energy storage for charging. At the same time, there is no abandoned photovoltaic power at this time, and the surplus power is completely absorbed by energy storage. In addition, since the actual configuration of energy storage capacity is greater than the optimized configuration capacity, the actual configuration of energy storage can also absorb the system surplus power. However, since the model in this article is relatively ideal, the system is bound to abandon light under the influence of uncertain factors in the actual operation process. When the photovoltaic output is 0 at night, the load demand is met by the output of energy storage and solar thermal units. Considering factors such as energy storage capacity, the proportion of energy storage power supply is relatively high. When the photovoltaic output is small, such as 8:00 and 17:00, the photovoltaic unit, solar thermal unit, and energy storage all output power to ensure load power consumption.

[0191] Similarly, further analysis of the heat storage and heat release of the CSP unit, such as Figure 5As shown in the figure, the CSP unit heats the molten salt for heat storage through photovoltaic power generation at 7:00, 16:00, and 18:00, releases heat at 1:00-3:00, 8:00, 17:00, 19:00-20:00, and 24:00, and drives the steam turbine to output electrical power through heated steam. The heat-to-electricity efficiency is still 95%. Compared with the optimized operation of the microgrid without energy storage, the frequency of heat release of the CSP unit decreases, and the storage and release capacity are reduced. The main reason is that the advantages of energy storage itself can support a higher proportion of the system's stable operation needs.

[0192] Comparative analysis of microgrid optimization operation with and without energy storage:

[0193] Based on the optimized operation of the microgrid with and without the participation of energy storage and the heat storage and release of the solar thermal unit mentioned above, a further comparative analysis is conducted on the stable operation of the microgrid with and without the participation of energy storage, mainly including comparative analysis of unbalanced power, comparative analysis of system abandonment of light, and comparative analysis of solar thermal units.

[0194] First, analyze the unbalanced power operation, such as Figure 6 As shown in the figure, the difference between the planned load power and the planned photovoltaic output is regarded as the net load power of the system. It can be seen that the net load power is positive from 1:00 to 8:00 and 17:00 to 24:00, that is, there is a power shortage at the current moment, and the load power demand is difficult to be met, while the net load power is negative from 9:00 to 16:00, that is, there is a power surplus at the current moment, and the power supply is greater than the power consumption. When the CSP unit participates in the system optimization operation but the energy storage does not participate, the heat release and output power of the CSP unit at night can alleviate a certain power shortage, but due to its output power limitation, there is still unbalanced power, and the surplus power can only be maintained by abandoning light to maintain power balance. When the CSP unit and energy storage participate in the system optimization operation, based on the characteristics of energy storage energy transfer, the energy storage absorbs surplus power for charging during the day and releases power to supplement the power shortage at night, and the unbalanced power of the system is completely absorbed.

[0195] like Figure 7 Comparison of the system abandonment with and without energy storage shows that when there is no energy storage, the system abandonment is serious, reaching 488.0793MWh, while the photovoltaic output is 857.2111MWh. By calculating the new energy consumption rate, it is only 43.07%, which means there is a large waste of energy. After configuring energy storage, the abandonment of the system has been greatly improved. In an ideal situation, the abandonment of the system is almost zero. After considering actual factors, the abandonment of the system will also be greatly reduced.

[0196] Finally, the heat storage and heat release of the CSP units with and without energy storage are compared and analyzed. Figure 8As shown in the figure, when there is no energy storage involved in the system optimization operation, the heat storage capacity of the CSP unit is 88.4211MWht, and the heat release capacity is 202.1053MWht; in contrast, when energy storage participates in the system optimization operation, the heat storage capacity of the CSP unit is 34.9838MWht, and the heat release capacity is 81.7680MWht. It can be seen that the participation of energy storage has a great impact on the heat storage and heat release of the CSP unit. The participation of energy storage can greatly reduce the heat storage capacity and heat release capacity of the CSP unit, among which the heat storage capacity is reduced by 60.44% and the heat release capacity is reduced by 59.54%. The main reason is that the advantages of fast charging and discharging of energy storage and energy transfer have effectively alleviated the regulation pressure of the CSP unit and improved the stability of microgrid operation.

[0197] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential, characterized in that: include: S1. Considering the lithium mine load regulation potential and microgrid operation scenarios, a coordinated optimization model of lithium mine load and energy storage is constructed; S2. Taking the optimal cost-effectiveness of microgrid operation as the objective function, output the results of the coordinated optimization model of lithium mine load and energy storage; S3. Complete the independent microgrid energy storage optimization based on the output results of the lithium mine load and energy storage coordination optimization model.

2. The independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential according to claim 1 is characterized in that: In S1, the expression of the coordinated optimization model of lithium mine load and energy storage is: Q=mC P ΔT (1) Q loss,t =hA(T lu,t -T env,t ) (2) T min ≤T lu,t ≤T max (3) mC P (T lu,t+1 -T lu,t )=ηP Li (t)-Q loss,t (7) Among them, Q represents the heat required in the process of heating brine, m represents the mass of brine, C p represents the specific heat capacity of brine, ΔT represents the temperature change of brine Q loss,t represents the amount of heat loss per unit time; h represents the heat transfer coefficient between the outside world and the heat storage tank; A represents the surface area of ​​the heat storage tank in contact with the outside world; T lu,t Represents brine temperature; T env,t Represents the ambient temperature, T max Represents the upper limit of brine temperature; T min Represents the lower limit of brine temperature, P Li (t) is the lithium mine load operating power; and They represent the upper and lower limits of thermal inertia load power at time t; λ represents the thermal efficiency coefficient of heating, C Li Economic compensation for lithium mine load temperature control; c Li Economic compensation cost per unit power for lithium mine load temperature control; The planned power consumption curve for lithium mine load is: and P tr (t) are the transferable load powers before and after dispatch, respectively; T is the dispatch period, and are the upper and lower limits of the power after load transfer, K tr The compensation price for unit power load transfer.

3. The independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential according to claim 1 is characterized in that: In S2, the objective function is the cost of renewable energy abandonment obj PV , gas turbine power generation and carbon reduction costs GT 、Operation cost of CSP unit obj PT , energy storage construction and operation costs ES And the lithium ore load adjustment cost obj load The comprehensive operation cost of the microgrid obj obtained by linear weighting is expressed as: myobj=obj PV +obj GT +obj PT +obj ES +obj load (12) Among them, min represents the minimization operation; New energy abandoned electricity cost PV The expression is: Among them, c PV is the penalty cost per unit abandoned optical power, is the predicted photovoltaic output power on a typical day, P PV (t) is the actual operating power of photovoltaic power; Gas turbine power generation and carbon reduction costs GT The expression is: obj GT =∑ t (c GT +c ca )P GT (t) (14) Among them, c GT and c ca are the power generation cost per unit power of gas turbine and the penalty cost of carbon emission; P GT (t) is the operating power of the gas turbine; CSP unit operating cost obj PT The expression is: obj PT =∑ t c PT |P PT (t)| (15) Among them, c PT is the unit operating cost of the CSP unit; P PT (t) is the output of the CSP unit at time t; Energy storage construction and operation costs ES The expression is: C op =∑ t c op |P ES (t)| (19) in, is the one-time investment and construction cost; C op is the energy storage operation cost; R ES is the annual investment recovery factor of energy storage; T ES is the life of energy storage; r is the discount rate; c E The construction cost of the entire life cycle of energy storage; E N is the rated capacity of energy storage; P ES (t) is the operating power of the energy storage at time t; c op is the operation and maintenance cost coefficient of energy storage; Lithium ore load adjustment cost obj load The expression is: obj laod =C Li +C tr (20)。 4. The independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential according to claim 3 is characterized in that: The constraints of the lithium mine load and energy storage coordinated optimization model include power supply constraints, grid constraints, energy storage constraints and load constraints.

5. The independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential according to claim 4 is characterized in that: Power supply constraints include photovoltaic unit output constraints, gas turbine output constraints, and solar thermal unit output constraints; The output constraint of photovoltaic units is: The gas turbine output constraint is: Among them, μ GT is the minimum technical output coefficient of the gas turbine; is the rated power of the gas turbine; The output constraints of the CSP unit include power generation output constraints, minimum on / off time cycle constraints, instantaneous thermal power constraints, charge and thermal state constraints, and thermal storage system boundary constraints; The expression of power generation output constraint is: Among them, I CSP (t) is the on / off state of the CSP device at time period t; P CSP (t) is the dispatching output of the CSP plant in time period t; P s,min and P s,max They are the lower and upper limits of the output power of a CSP plant respectively; The expression for the minimum on / off time period constraint is: Among them, T s,off is the period during which the CSP unit is shut down, T s,on The period during which the CSP unit is turned on; The expression of instantaneous thermal power constraint is: l cha +λ dis ≤1 (27) Among them, η PB,s is the power efficiency of the CSP device; is the thermal storage power of CSP in time period t; is the heat release power of CSP in time period t; is the solar thermal power available during period t; is the rated value of the CSP output system; η N,dis is the efficiency of converting heat release power into electrical power; cha and λ dis are 0-1 state variables that characterize heat storage and heat release of the CSP thermal storage system; The expression of the charge thermal state constraint is: Among them, E CSP (t) is the heat storage capacity of the heat storage system in the CSP device at time period t; η CSP is the efficiency coefficient of the heat storage system. The expression of the boundary constraint of the thermal storage system is: E s,min ≤E CSP (t)≤E s,max (29) Among them, E s,min and E s,max They are respectively the lower and upper limits of the heat storage capacity of the heat storage system in the CSP device.

6. The independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential according to claim 5 is characterized in that: The expression of the power grid constraint is: Among them, P Net,t It is because the microgrid cannot completely absorb the unbalanced power at time t.

7. According to the independent microgrid energy storage optimization method considering the improvement of lithium mine load regulation potential as described in claim 5, the energy storage constraints include energy storage capacity configuration and operation constraints, grid energy storage response potential constraints and grid energy storage charge state constraints; The expressions of energy storage capacity configuration and operation constraints are: in, P ESN is the rated capacity of energy storage, P ESmax is the maximum rated capacity of energy storage, P ESmin is the minimum rated capacity of energy storage, λ ES is the energy storage configuration variable, P ES (t) is the operating power of the microgrid in which the energy storage participates at time t; α ch and α dis are the maximum charging efficiency and the maximum discharging efficiency respectively; The expression of grid energy storage response potential constraint is: in, and They are the upward and downward response rates of the grid energy storage participating in the multi-link regulation of the grid during period t; Δt is the time period during which the grid energy storage actually participates in the regulation of the microgrid; The expression of the grid energy storage charge state constraint is: Among them, S0 and S max are the initial state and total capacity of energy storage, respectively, and their ratio is the state of charge before energy storage participates in multi-link regulation of the power grid; P ES (t) is the charging and discharging power of the grid energy storage during period t; t0 and t end are the start time and end time of the grid energy storage participating in the multi-link regulation of the grid; t1 is any period between the start time and end time of the grid energy storage participating in the multi-link regulation of the grid.

8. The independent microgrid energy storage optimization method considering the lithium mine load regulation potential improvement according to the load constraint of claim 2 is characterized in that: The expression of load response rate constraint is: in, and They are the lower and upper limits of lithium ore load regulation rate respectively; and are the lower and upper limits of the transferable load regulation rate respectively.

9. The independent microgrid energy storage optimization method considering the lithium mine load regulation potential improvement according to the load constraint of claim 1 is characterized in that S3 include: S31. Determine whether the output result of the lithium mine load and energy storage coordination optimization model satisfies the power balance: If so, the energy storage optimization of the independent microgrid is completed; If not, enter S32; S32, calculating the unbalanced power of the microgrid, and calculating the unbalanced power penalty of the microgrid according to the unbalanced power of the microgrid; S33. Complete the energy storage optimization of the independent microgrid according to the unbalanced power penalty of the microgrid.

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