A coastal multi-source and multi-load coordinated control system and method considering seawater desalination

Abstract

The present invention provides a coastal multi-source and multi-load coordinated control system and method considering seawater desalination, including: a control center, a new energy power station, an energy storage device, a seawater desalination facility, and a conventional load; the control center is used to formulate an optimal day-ahead plan and an optimal intra-day plan according to the acquired operation data and meteorological data, and control the new energy storage device and the seawater desalination facility to execute, so as to perform coordinated control, and can accurately give the optimized regulation path of the seawater desalination process under multi-source and multi-load, make full use of the characteristics of energy storage technology, and adjust the coastal controllable load and energy storage mainly by energy storage regulation and supplemented by controllable load regulation to track the renewable energy power generation curve, so as to meet the requirement of renewable energy consumption in coastal areas.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system control, and particularly relates to a coastal multi-source and multi-load coordinated control system and method considering seawater desalination. Background Art

[0002] Currently, the global population is rising sharply and society is developing rapidly, resulting in an increasingly scarce global fresh water resource. As an effective solution to the shortage of fresh water resources, seawater desalination needs to be developed on a large scale, and the demand for seawater desalination technology in coastal water-scarce areas is even more urgent. At the same time, coastal areas are rich in distributed renewable energy such as wind energy and solar energy for development. Traditional primary energy sources such as coal and oil are non-renewable and will surely run out. With the increasingly serious energy crisis and environmental pollution problems, countries are actively developing new renewable energy sources such as solar energy, wind energy, and ocean energy. Some renewable energy utilization technologies have achieved technological breakthroughs and formed a certain scale of renewable energy industries around the world. However, the related technologies of new energy are still immature at present. In addition, industries such as coastal seawater desalination and coastal aquaculture are developing strongly, and their load demands are becoming stronger and stronger. Especially in areas lacking fresh water resources, seawater desalination has become an important load in coastal areas. How to coordinate and control the power system in coastal areas to improve the power economic benefits in this area while taking into account other aspects such as suppressing load fluctuations remains to be studied. Summary of the Invention

[0003] To overcome the deficiencies of the above-mentioned prior art, the present invention proposes a coastal multi-source and multi-load coordinated control system and method considering seawater desalination. Aiming at the problem of insufficient renewable energy consumption capacity in existing coastal areas, the system and method utilize energy interconnection technology to realize the joint coordinated control of various loads including seawater desalination, coastal distributed renewable energy, and energy storage devices. This can not only enable the consumption of renewable energy in coastal areas to meet the demand for coordinated utilization of multiple energy sources, but also create huge social and economic benefits.

[0004] The solution adopted to achieve the above object is as follows:

[0005] A coastal multi-source and multi-load coordinated control system considering seawater desalination, which is improved in that it includes: a control center, a new energy power station, an energy storage device, a seawater desalination facility, and a conventional load;

[0006] The new energy power station, the energy storage device, the seawater desalination facility, and the conventional load are respectively communicatively connected to the control center, and are respectively used for collecting their own operation data and sending it to the control center, and receiving the control signals of the control center;

[0007] The new energy power station, energy storage device, seawater desalination facility, and conventional load are electrically connected to the bus respectively, and the bus is connected to the distribution network through a tie line;

[0008] The control center is used to formulate an optimal day-ahead plan and an optimal intra-day plan based on the obtained operation data and meteorological data, and control the new energy storage device and seawater desalination facility to execute, for coordinated control.

[0009] In the first preferred technical solution provided by the present invention, the improvement lies in that the control center further includes a database;

[0010] The database is used to receive and store operation data and meteorological data for the control center to call, and is also used to record the control signals sent by the control center.

[0011] In the second preferred technical solution provided by the present invention, the improvement lies in that the new energy power station, energy storage device, seawater desalination facility, and conventional load are respectively communicatively connected to the control center through wireless communication devices;

[0012] The wireless communication device includes a GPRS-DTU module.

[0013] An improved coordinated control method for multiple sources and multiple loads in a coastal area considering seawater desalination includes:

[0014] Predict the output of the new energy power station, the load power of the conventional load, and the desalinated water demand for the next day according to the data required for formulating the day-ahead plan;

[0015] Input the output of the new energy power station, the load power of the conventional load, and the desalinated water demand for the next day into a pre-established coordinated optimization model to obtain an optimal day-ahead plan;

[0016] When the next day arrives, based on the optimal day-ahead plan, formulate an optimal intra-day plan and control the energy storage device and seawater desalination facility to execute the optimal intra-day plan for coordinated control of multiple sources and multiple loads;

[0017] The coordinated optimization model is formulated based on minimizing the power fluctuations on the tie line between the distribution network;

[0018] The data required for formulating the day-ahead plan includes: fixed parameters, meteorological forecast parameters, operation data, and historical data; the fixed data includes: regional area, time-of-use electricity price, seawater desalination unit characteristics, and load type; the operation data includes: the power generation power of the new energy power station, the energy storage capacity and energy storage potential of the energy storage device, the desalinated water demand, desalinated water production, storage, and load power of each seawater desalination facility, and the load power of the conventional load, and the historical data includes the historical data of the operation data and meteorological data.

[0019] The third preferred technical solution provided by the present invention is improved in that, based on the optimal day-ahead plan, an optimal intra-day plan is formulated and the energy storage device and the seawater desalination facility are controlled to execute the optimal intra-day plan for multi-source and multi-load coordinated control, including:

[0020] Based on the day-ahead plan, within each hour of the next day, respectively according to the data for formulating the intra-day plan, predict the output of the new energy power station, the load power of the conventional load, and the desalinated water demand in the next hour;

[0021] Input the output of the new energy power station, the load power of the conventional load, and the desalinated water demand in the next hour into the coordinated optimization model to obtain the optimal intra-day plan for the next hour;

[0022] After reaching the next hour, control the energy storage device and the seawater desalination facility to execute the optimal intra-day plan for multi-source and multi-load coordinated control;

[0023] Among them, the data required for formulating the intra-day plan includes: the data required for formulating the day-ahead plan in the current hour, the updated weather forecast data, and the actual operation data of the current day.

[0024] The fourth preferred technical solution provided by the present invention is improved in that the establishment of the coordinated optimization model includes:

[0025] Establish an objective function, and establish a coordinated optimization model with the power constraint of the new energy unit, the seawater desalination constraint, the energy storage device constraint, and the power balance constraint as the constraint conditions.

[0026] The fifth preferred technical solution provided by the present invention is improved in that the objective function is as shown in the following formula:

[0027] f = min(k1C total + k2σ L )

[0028] Among them, f represents the objective function, C total represents the operating cost within the planned time period, k1 represents the weight coefficient of C total in the objective function, σ L represents the sum of variances of the power on the connection line with the distribution network within the planned time period, and k2 represents the weight coefficient of σ L in the objective function;

[0029] σ L is calculated as follows:

[0030]

[0031] Among them, N represents the number of operating time periods included in the planned time period, It represents the power on the connection line with the distribution network during the i-th operation period, and the subscript L represents the connection line;

[0032] C total It is calculated as follows:

[0033] C total = ∑C OM + ∑C PC + ∑C G - ∑B PV

[0034] Among them, ∑C OM represents the sum of operation and maintenance costs during the planned period, ∑C PC represents the sum of losses caused by wind and light curtailment of each new energy unit during the planned period, ∑C G represents the cost of purchasing electricity from the distribution network during the planned period, ∑B PV represents the sum of policy-based photovoltaic subsidies available due to power supply during the planned period. The new energy units include wind turbines and photovoltaic generators.

[0035] In the sixth preferred technical solution provided by the present invention, the improvement lies in that the ∑C OM is calculated as follows:

[0036]

[0037] Among them, is the operation and maintenance cost per unit power of the wind turbine during one operation period; is the operation and maintenance cost per unit power of the photovoltaic generator during one operation period; is the operation and maintenance cost per unit power of the seawater desalination unit during one operation period; is the operation and maintenance cost per unit power of the energy storage device during one operation period; N W is the number of wind turbines; N PV is the number of photovoltaic generators; N DE is the number of seawater desalination units; is the power of the j-th wind turbine during the i-th operation period; is the power of the k-th photovoltaic generator during the i-th operation period; is the power of the l-th seawater desalination unit during the i-th operation period; is the stored energy of the energy storage device during the i-th operation period;

[0038] The ∑C PC is calculated as follows:

[0039]

[0040] Among them, is the time-of-use electricity price for the i-th operation time period; is the curtailment wind power for the i-th operation time period; is the curtailment light power for the i-th operation time period;

[0041] The said ∑C G is calculated as follows:

[0042]

[0043] The said ∑B PV is calculated as follows:

[0044]

[0045] Among them, T PV is the photovoltaic subsidy amount per unit power.

[0046] For the seventh preferred technical solution provided by the present invention, its improvement lies in that after obtaining the optimal day-ahead plan and before reaching the next day, it further includes:

[0047] Issuing the day-ahead plan to the energy storage device and each distributed seawater desalination facility.

[0048] For the eighth preferred technical solution provided by the present invention, its improvement lies in that after obtaining the optimal intra-day plan for the next hour and before reaching the next hour, it further includes:

[0049] Issuing the intra-day plan to the energy storage device and each distributed seawater desalination facility.

[0050] For the ninth preferred technical solution provided by the present invention, its improvement lies in that after predicting the output of the new energy power station, the load power of the conventional load and the desalinated water demand for the next hour, and before inputting the output of the new energy power station, the load power of the conventional load and the desalinated water demand for the next hour into the coordinated optimization model, it further includes:

[0051] Judging whether the fresh water storage of any seawater desalination facility is lower than the fresh water demand corresponding to the next hour: if so, the next hour plan for the seawater desalination facility with the fresh water storage lower than the fresh water demand corresponding to the next hour is to start all units.

[0052] Compared with the closest prior art, the beneficial effects of the present invention are as follows:

[0053] A coastal multi-source and multi-load coordinated optimization control system and method considering seawater desalination provided by the present invention. The control center formulates an optimal day-ahead plan and an optimal intra-day plan according to the acquired operation data and meteorological data, and controls the new energy storage device and the seawater desalination facility to execute, so as to perform coordinated control. It can accurately give the optimized regulation path of the seawater desalination process under multi-source and multi-load, make full use of the characteristics of energy storage technology, and regulate the coastal controllable load and energy storage mainly by energy storage regulation and supplemented by controllable load regulation to track the renewable energy power generation curve, so as to meet the consumption requirements of renewable energy in coastal areas.

[0054] In addition, the proposed solution can promote the development of seawater desalination and coastal industries, is beneficial to power grid peak shaving, can improve the economic operation level of the coastal regional power grid, and the overall energy efficiency level of energy utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic structural diagram of a coastal multi-source and multi-load coordinated control system considering seawater desalination provided by the present invention;

[0056] Figure 2 It is a schematic diagram of the principle of a coastal multi-source and multi-load coordinated control system considering seawater desalination provided by the present invention;

[0057] Figure 3 It is a schematic diagram of the flow of a coastal multi-source and multi-load coordinated control method considering seawater desalination provided by the present invention;

[0058] Figure 4 It is a schematic diagram of the flow chart for the control center to formulate a day-ahead plan involved in the present invention;

[0059] Figure 5 It is a schematic diagram of the flow chart for the control center to formulate an intra-day plan involved in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0060] The following further elaborates on the specific embodiments of the present invention with reference to the drawings.

[0061] Embodiment 1:

[0062] A schematic structural diagram of a coastal multi-source and multi-load coordinated control system considering seawater desalination provided by the present invention is as Figure 1 shown, including:

[0063] A control center, a new energy power station, an energy storage device, a seawater desalination facility, and a conventional load;

[0064] The new energy power station, the energy storage device, the seawater desalination facility, and the conventional load are respectively communicatively connected to the control center, and are respectively used for collecting their own operation data and sending it to the control center, and receiving the control signals from the control center;

[0065] The new energy power station, energy storage device, seawater desalination facility, and conventional load are electrically connected to the bus respectively, and the bus is connected to the distribution network through a tie line;

[0066] A control center, which is used to formulate an optimal day-ahead plan and an optimal intra-day plan according to the obtained operation data and meteorological data, and control the new energy storage device and seawater desalination facility to execute, for coordinated control.

[0067] In this embodiment, taking a coastal area as an example, the coordinated optimization control method for coastal multi-source and multi-load considering seawater desalination of the present invention is used to perform coordinated optimization control on the energy facilities and load facilities in this area. The new energy power generation stations in this embodiment include a wind power station and a photovoltaic power station.

[0068] A coastal multi-source and multi-load coordinated control system considering seawater desalination, as Figure 2 shown, includes new energy generating units, specifically a wind power station, several distributed photovoltaic power stations, several distributed seawater desalination facilities, various coastal conventional loads, an energy storage device, a control center and its database, as well as other supporting facilities for the required lines; in the power topology structure, the wind power station, each distributed photovoltaic power station, each seawater desalination facility and each coastal conventional load are all connected to the coastal multi-source and multi-load system bus, and the bus is connected to the distribution network; in the control signal topology structure, the wind farm, each distributed photovoltaic power station, each seawater desalination facility and each coastal conventional load establish a communication connection with the control center in a wireless manner through their respective wireless communication devices. The function of the wind power station is to convert wind energy into alternating current electricity to provide power; the function of the distributed photovoltaic power station is to convert light energy into alternating current electricity to provide power; the function of the distributed seawater desalination facility is to desalinate seawater through a seawater desalination unit to convert it into fresh water to supply the fresh water demand in the coastal area; the function of the coastal conventional load is to consume electricity to undertake the normal operation of society in the coastal area; the function of the energy storage device is to consume new energy electricity according to the control signal received from the control center as planned, and supply electricity to each load under appropriate circumstances; the function of the control center is to formulate a day-ahead plan and an intra-day plan according to the data in the database, send instructions to each part of the system through wireless communication devices, and provide a man-machine interaction interface for relevant operators; the function of the database is to receive and store various data required to be collected by each part of the system for the control center to call, and record the control signals sent by the control center. Among them, the wind farm includes multiple wind turbine generators, the distributed photovoltaic power stations include multiple photovoltaic generator sets, and the seawater desalination facilities include multiple seawater desalination units.

[0069] Preferably, the wireless communication device can be a GPRS-DTU module.

[0070] Preferably, all data starts at 0:00 every day and is recorded and transmitted at 15-minute intervals.

[0071] Preferably, the control center and the database are geographically close for easy management, and data is transmitted between them using a local area network.

[0072] Preferably, the energy storage device should ensure a sufficiently large upper limit of electrical energy storage to ensure cooperation with each distributed seawater desalination facility to consume electrical energy.

[0073] Preferably, each distributed seawater desalination facility uses the RO reverse osmosis membrane method as the desalination method.

[0074] Preferably, when the control center formulates the day-ahead plan, according to the data provided by the database, using the prediction algorithms of all energy facilities or load facilities in the system, the predicted output data or load data for the next day is obtained; then using the obtained predicted data and the coordinated optimization algorithm, the optimal day-ahead plan is finally obtained.

[0075] Preferably, when the control center formulates the intra-day plan, according to the data provided by the database, ultra-short-term power predictions are made for each wind turbine, photovoltaic power generation unit, coastal conventional load, and fresh water demand, and the predicted output data or load data for the next hour is obtained; then according to the optimization algorithm, the optimal intra-day plan for the energy storage device and each seawater desalination facility in the next hour is calculated and issued to the energy storage device and each distributed seawater desalination facility.

[0076] Preferably, the control center formulates and issues the day-ahead plan from 23:45 to 0:00 the next day; and formulates and issues the intra-day plan in the last 15 minutes of each hour.

[0077] Preferably, the methods for formulating the day-ahead plan and the intra-day plan are multi-objective optimization, and the objective function can be selected and formulated according to requirements; the constraint conditions are established based on each component in the coastal multi-source and multi-load coordinated optimization control system.

[0078] Preferably, after obtaining the non-dominated solution set according to the optimization algorithm, each non-dominated solution is scored according to the weight coefficient determined by experience, and the solution with the highest score is selected as the optimal plan.

[0079] Embodiment 2:

[0080] Based on the same inventive concept, the present invention also provides a coastal multi-source and multi-load coordinated control method considering seawater desalination. This method controls the control system as shown in Embodiment 1.

[0081] The process of this method is as Figure 3 shown, including:

[0082] Step 1: According to the data required by the pre - formulated daily plan, predict the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next day;

[0083] Step 2: Input the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next day into the pre - established coordinated optimization model to obtain the optimal daily plan;

[0084] Step 3: When the next day arrives, based on the optimal daily plan, formulate the optimal intraday plan and control the energy storage device and the seawater desalination facility to execute the optimal intraday plan for multi - source and multi - load coordinated control;

[0085] The coordinated optimization model is formulated based on minimizing the power fluctuation on the connection line with the distribution network;

[0086] The data required for formulating the daily plan includes: fixed parameters, meteorological forecast parameters, operation data, and historical data; fixed data includes: regional area, time - of - use electricity price, characteristics of seawater desalination units, and load types; operation data includes: power generation power of new - energy power stations, energy storage capacity and energy storage potential of energy storage devices, desalinated water demand, desalinated water production, storage, and load power of each seawater desalination facility, and the load power of the conventional load; historical data includes historical data of operation data and meteorological data.

[0087] The following is a detailed description of this embodiment.

[0088] In this embodiment, at the current hour, the wind farm and each distributed photovoltaic power station measure and send the output data of the previous hour to the control center, each coastal conventional load measures and sends the load data of the previous hour to the control center, the energy storage device measures and sends the load data of the previous hour and its energy storage state to the control center, each distributed seawater desalination facility measures and sends the load data of the previous hour and its desalinated water reserve state to the control center, and the main power grid measures and sends the power on the connection line with the coastal multi - source and multi - load coordinated control system of the previous hour. The control center records the above data in the database.

[0089] In this embodiment, the control center issues the daily plan to the energy storage device and each distributed seawater desalination facility before 0:00 on the next day; and issues the intraday plan to the energy storage device and each distributed seawater desalination facility before the next hour.

[0090] In this embodiment, as Figure 4 shown, formulate the system daily plan for the next day according to the collected data within the current day. Assume that it is currently necessary to formulate the daily plan for the (t + 1) - th day, and its steps are as follows:

[0091] Step 11-1: The control center reads the required parameters from the database, including various fixed parameters, various meteorological forecast parameters, operation data, and historical data; the fixed parameters include parameters of the background nature such as the area of each facility region in the system, local time-of-use electricity price, characteristics of seawater desalination units, load types, etc.; the meteorological forecast parameters include meteorologically predictable parameters such as air temperature, surface temperature, humidity, lighting conditions, wind speed, etc. in the coastal area where the system is located from 0:00 to 23:45 on the (t + 1)-th day; the operation data includes various data required for the optimization algorithm in the recent 7 days, including: the actual power generation of the wind farm, the actual power generation of each distributed photovoltaic power station, the current stored energy and energy storage potential of the energy storage device, the fresh water demand, desalinated water production, storage, and load power of each seawater desalination facility, and the load power of each coastal conventional load, etc.; the historical data includes the average values of various meteorological forecast parameters and operation data in the current quarter and within the previous week.

[0092] Step 11-2: The control center uses the relevant parameters obtained in Step 11-1 to calculate the predicted output values of the wind farm from 0:00 to 23:45 on the (t + 1)-th day according to the wind power short-term prediction algorithm; calculates the predicted output values of each distributed photovoltaic power station from 0:00 to 23:45 on the (t + 1)-th day according to the photovoltaic short-term power prediction algorithm; calculates the predicted load values of each coastal conventional load from 0:00 to 23:45 on the (t + 1)-th day according to the conventional load short-term power prediction algorithm; calculates the predicted fresh water demand of each distributed seawater desalination facility from 0:00 to 23:45 on the (t + 1)-th day according to the fresh water demand short-term prediction algorithm.

[0093] Step 11-3: The control center uses the coordination optimization algorithm to find the optimal day-ahead plan based on the results in Step 11-2.

[0094] Step 11-4: The control center, based on the results obtained in Step 11-3, before 0:00 on the (t + 1)-th day, sends the day-ahead plan to the energy storage device and each distributed seawater desalination facility via wireless signals.

[0095] On the (t + 1)-th day, the day-ahead plan formulated on the t-th day is started to be executed. During the execution process, the deviation between the actual situation and the plan needs to be considered, and the day-ahead plan is revised. At other times except 23:00, the within-day plan for the next hour is formulated. Therefore, in fact, on the (t + 1)-th day, except for directly executing the day-ahead plan at 0:00, the within-day plan is actually executed for each hour at other times.

[0096] In this embodiment, as Figure 5 shown, the system within-day plan is formulated for the next hour according to the data collected on the same day. Assume that the within-day plan for the (r + 1)-th hour needs to be formulated currently, and its steps are as follows:

[0097] Step 21-1: The control center starts to read the required parameters from the database 15 minutes before the end of the r-th hour. In addition to the data required for the daily plan, it also includes the updated meteorological information and the actual operation data of each facility in the system on the same day.

[0098] Step 21-2: The control center uses the relevant parameters obtained in Step 21-1 to calculate the predicted output value of the wind farm at the (r + 1)-th hour according to the short-term wind power prediction algorithm; calculates the predicted output value of each distributed photovoltaic power generation station at the (r + 1)-th hour according to the ultra-short-term photovoltaic power prediction algorithm; calculates the predicted load value of each coastal conventional load at the (r + 1)-th hour according to the ultra-short-term conventional load power prediction algorithm; calculates the predicted desalinated water demand of each distributed seawater desalination facility at the (r + 1)-th hour according to the ultra-short-term fresh water demand prediction algorithm.

[0099] Step 21-3: The control center determines whether the fresh water storage of any distributed seawater desalination facility is lower than the corresponding fresh water demand at the (r + 1)-th hour. If so, the plan for the (r + 1)-th hour of this seawater desalination facility is to start all its units.

[0100] Step 21-4: The control center uses the optimization algorithm to find the optimal intraday plan according to the results in Step 21-2. For all distributed seawater desalination facilities determined to be "yes" in 21-3, set the power of all their units to the maximum value and substitute it into the algorithm for operation. Step 21-5: The control center issues the intraday plan to the energy storage device and each distributed seawater desalination facility via wireless signals before the (r + 1)-th hour according to the results obtained in 21-4.

[0101] In this embodiment, the method for formulating the day-ahead plan and the intraday plan is multi-objective optimization. For the day-ahead plan, when performing the multi-objective optimization algorithm, the planned time period is 24 hours from 0:00 to 23:00 of the next day; for the intraday plan, when performing the multi-objective optimization algorithm, assuming the current time is r, the planned time period is (23 - r) hours from the (r + 1)-th hour to 23:00 of the same day. In addition, according to the steps of formulating the day-ahead plan and the intraday plan, the operating time period in the optimization algorithm is set to 15 minutes.

[0102] The objective function selected in this embodiment is: the power fluctuation on the connection line between the coastal multi-source and multi-load coordinated optimization control system and the distribution network is minimized, and at the same time, the daily operating cost under the coastal multi-source and multi-load coordinated optimization control system is considered to be the lowest. The above two objectives can be expressed by formula (1).

[0103]

[0104] Where:

[0105] C totalis the operating cost of the coastal multi-source and multi-load coordinated optimization control system within the planned time period;

[0106] ∑C OM is the sum of the operation and maintenance costs of each component within the coastal multi-source and multi-load coordinated optimization control system within the planned time period;

[0107] ∑C PC is the sum of the losses caused by curtailment of wind and solar power of each new energy generating unit within the coastal multi-source and multi-load coordinated optimization control system within the planned time period;

[0108] ∑C G is the cost of purchasing electricity from the distribution network by the coastal multi-source and multi-load coordinated optimization control system within the planned time period;

[0109] ∑B PV is the sum of the policy-based photovoltaic subsidies obtained from power supply of each photovoltaic generating unit within the coastal multi-source and multi-load coordinated optimization control system within the planned time period;

[0110] σ L is the sum of the variances of the power on the connection line between the coastal multi-source and multi-load coordinated optimization control system and the distribution network within the planned time period;

[0111] N is the number of operating time periods included within the planned time period;

[0112] is the power on the connection line between the coastal multi-source and multi-load coordinated optimization control system and the distribution network at the i-th operating time period.

[0113] Specifically, ∑C OM can be expressed by formula (2):

[0114]

[0115] Where:

[0116] is the operation and maintenance cost per unit power of the wind turbine within one operating time period;

[0117] is the operation and maintenance cost per unit power of the photovoltaic generating unit within one operating time period;

[0118] is the operation and maintenance cost per unit power of the seawater desalination unit within one operating time period;

[0119] is the operation and maintenance cost per unit power of the energy storage device within one operating time period;

[0120] N Wis the number of wind turbines in the coastal multi-source and multi-load coordinated optimization control system;

[0121] N PV is the number of photovoltaic power generation units in the coastal multi-source and multi-load coordinated optimization control system;

[0122] N DE is the number of seawater desalination units in the coastal multi-source and multi-load coordinated optimization control system;

[0123] is the power of the j-th wind turbine in the i-th operation period, which is obtained by the wind power short-term power prediction algorithm according to the required data when formulating the day-ahead plan; and is obtained by the wind power ultra-short-term power prediction algorithm according to the required data when formulating the intra-day plan;

[0124] is the power of the k-th photovoltaic power generation unit in the i-th operation period, which is obtained by the photovoltaic short-term power prediction algorithm according to the required data when formulating the day-ahead plan; and is obtained by the photovoltaic ultra-short-term power prediction algorithm according to the required data when formulating the intra-day plan;

[0125] is the power of the l-th seawater desalination unit in the i-th operation period. If the fresh water storage of the distributed seawater desalination facility where a certain unit is located is less than the predicted demand, this parameter is directly set to its maximum value, that is

[0126] is the energy storage capacity of the energy storage device in the i-th operation period;

[0127] Δt is the operation period, taking 15 minutes.

[0128] Specifically, ∑C PC can be expressed by formula (3):

[0129]

[0130] Where:

[0131] is the time-of-use electricity price for the i-th operation period;

[0132] is the wind curtailment power for the i-th operation period;

[0133] is the PV curtailment power for the i-th operation period.

[0134] Furthermore, can be obtained by formula (4):

[0135]

[0136] Wherein: is the predicted maximum output value of the j-th wind turbine in the i-th operation period.

[0137] Furthermore, can be obtained from formula (5):

[0138]

[0139] Wherein: is the predicted maximum output value of the j-th photovoltaic power generation unit in the i-th operation period.

[0140] Specifically, ∑C G can be expressed by formula (6):

[0141]

[0142] Specifically, ∑B PV can be expressed by formula (7):

[0143]

[0144] Wherein:

[0145] T PV is the photovoltaic subsidy amount per unit power;

[0146] is the power of the k-th photovoltaic power generation unit in the i-th operation period.

[0147] According to the components within the coastal multi-source and multi-load coordinated optimization control system shown in the appendix Figure 2 the following multi-objective optimization constraint conditions can be established, including new energy unit power constraints, seawater desalination unit power constraints, desalinated water reservoir constraints, energy storage device constraints, and power balance constraints.

[0148] The new energy unit power constraints include the following (I) and (II).

[0149] (I) For all wind turbines, there are power constraint conditions as shown in formula (8):

[0150]

[0151] Wherein:

[0152] is the lower power limit of the j-th wind turbine;

[0153] is the power of the j-th wind turbine in the i-th operation period;

[0154] is the upper power limit of the j-th wind turbine generator, which is the installed capacity of this wind turbine generator.

[0155] (II) For all photovoltaic power generation units, there are power constraint conditions as shown in formula (9):

[0156]

[0157] where is the lower power limit of the k-th photovoltaic power generation unit;

[0158] is the power of the k-th photovoltaic power generation unit at the i-th operation time period

[0159] is the upper power limit of the j-th wind turbine generator, which is the installed capacity of this wind turbine generator.

[0160] The seawater desalination constraints include the following (III), (IV) and (V).

[0161] (III) For all seawater desalination units, there are power constraint conditions as shown in formula (10):

[0162]

[0163] where:

[0164] is the lower power limit of the l-th seawater desalination unit;

[0165] is the power of the l-th seawater desalination unit at the i-th operation time period;

[0166] is the upper power limit of the l-th seawater desalination unit, which is the installed capacity of this seawater desalination unit.

[0167] (IV) For all fresh water storage tanks of distributed seawater desalination facilities, there are volume constraint conditions as shown in formula (11):

[0168]

[0169] where:

[0170] is the lower volume limit of the fresh water storage tank of the m-th distributed seawater desalination facility;

[0171] is the water storage volume of the fresh water storage tank of the m-th distributed seawater desalination facility at the i-th operation time period;

[0172] is the upper limit of the volume of the fresh water storage tank for the m-th distributed seawater desalination facility.

[0173] (V) For all fresh water storage tanks of distributed seawater desalination facilities, there is a water storage balance constraint as shown in Equation (12):

[0174]

[0175] Where:

[0176] The operating characteristics of the n-th seawater desalination unit in the m-th distributed seawater desalination facility. The fresh water production of the l-th seawater desalination unit at the i-th operating time period can be obtained according to this characteristic curve;

[0177] is the efficiency of the n-th seawater desalination unit;

[0178] is the power of the n-th seawater desalination unit at the i-th operating time period;

[0179] is the head of the n-th seawater desalination unit at the i-th operating time period;

[0180] N DP,m is the total number of seawater desalination units in the m-th distributed seawater desalination facility;

[0181] is the fresh water demand of the m-th distributed seawater desalination facility at the i-th operating time period. It is obtained by the short-term fresh water demand prediction algorithm according to the required data when formulating the day-ahead plan; it is obtained by the ultra-short-term fresh water demand prediction algorithm according to the required data when formulating the intra-day plan.

[0182] The energy storage device constraints include the following (VI), (VII), and (IIX).

[0183] (VI) For the energy storage device, there is a power constraint as shown in Equation (13):

[0184]

[0185] Where:

[0186] P S is the lower power limit of the energy storage device;

[0187] is the power of the energy storage device at the i-th operating time period;

[0188] is the upper power limit of the energy storage device.

[0189] (VII) For the energy storage device, there are energy storage constraint conditions as shown in formula (14):

[0190]

[0191] Where:

[0192] Q S is the lower limit of the energy storage of the energy storage device;

[0193] is the energy storage of the energy storage device at the i-th operation time period;

[0194] is the upper limit of the energy storage of the energy storage device.

[0195] (IIX) For the energy storage device, there are charge and discharge constraint conditions as shown in formula (15):

[0196]

[0197] Where:

[0198] N S is the lower limit of the charge and discharge times of the energy storage device within the planned time period;

[0199] N S is the charge and discharge times of the energy storage device within the planned time period;

[0200] is the upper limit of the charge and discharge times of the energy storage device within the planned time period.

[0201] (IX) The power balance constraint is as shown in formula (16):

[0202]

[0203] Where:

[0204] N RL is the number of coastal conventional loads in the coastal multi-source and multi-load coordinated optimization control system;

[0205] is the load power of the u-th coastal conventional load at the i-th operation time period. It is obtained by the conventional load short-term prediction algorithm according to the required data when formulating the day-ahead plan; it is obtained by the conventional load ultra-short-term prediction algorithm according to the required data when formulating the intra-day plan.

[0206] After obtaining the non-dominated solution set according to the above objective function and constraint conditions, the method for selecting the optimal plan from this solution set is as shown in formula (17):

[0207] X = k1·C total + k2·σ L (17)

[0208] Where:

[0209] X is the non - dominated solution score;

[0210] k1 is the operating cost target coefficient, selected according to the importance degree of cost;

[0211] k2 is the power fluctuation target coefficient, selected according to the importance degree of power fluctuation;

[0212] All solutions in the non - dominated solution set are scored according to formula (17), and the solution with the highest score is selected as the optimal plan. That is, the objective function of coordinated optimization is:

[0213] f = min(k1C total + k2σ L )(18)

[0214] Where, f represents the objective function, k2 represents the weight coefficient of σ L in the objective function, k1 represents the weight coefficient of C total in the objective function

[0215] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer - usable storage media (including but not limited to disk memory, CD - ROM, optical memory, etc.) containing computer - usable program code.

[0216] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general - purpose computer, a special - purpose computer, an embedded processor, or other programmable data - processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data - processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks

[0217] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means that implement the functions specified in one or more of the procedures Figure 1 one or more procedures and / or blocks Figure 1 specified in the block or blocks.

[0218] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the procedures Figure 1 one or more procedures and / or blocks Figure 1 specified in the block or blocks.

[0219] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application rather than to limit the scope of its protection. Although the present application has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that after reading the present application, various changes, modifications or equivalent replacements can still be made to the specific implementation manners of the application. However, these changes, modifications or equivalent replacements are all within the scope of the claims of the application pending approval.

Claims

1. A coastal multi-source and multi-load coordinated control method considering seawater desalination, characterized in that Including: According to the data required by the pre - formulated daily plan, predicting the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next day; Inputting the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next day into a pre - established coordinated optimization model to obtain the optimal daily plan; When the next day arrives, based on the optimal daily plan, formulating an optimal intraday plan and controlling the energy storage device and the seawater desalination facility to execute the optimal intraday plan for multi - source and multi - load coordinated control; The coordinated optimization model is formulated based on minimizing the power fluctuation on the tie - line with the distribution network; The data required for formulating the daily plan includes: fixed parameters, meteorological forecast parameters, operation data, and historical data; the fixed parameters include: regional area, time - of - use electricity price, characteristics of seawater desalination units, and load types; the operation data includes: the power generation power of the new - energy power station, the stored energy and energy storage potential of the energy storage device, the desalinated water demand, desalinated water production, storage, and the load power of each seawater desalination facility, and the load power of the conventional load, and the historical data includes the historical data of the operation data and meteorological data; The establishment of the coordinated optimization model includes: Establishing an objective function and taking the power constraint of the new - energy unit, seawater desalination constraint, energy storage device constraint, and power balance constraint as constraint conditions to establish a coordinated optimization model; The objective function is shown as the following formula: f = min(k1C total + k2σ L ) Among them, f represents the objective function, C total represents the operating cost during the planned time period, and k1 represents C total the weight coefficient within the objective function, and σ L represents the sum of variances of the power on the connection line between the distribution network during the planned time period, and k2 represents σ L the weight coefficient within the objective function; σ L Calculated as follows: where N represents the number of operating time periods included in the planned time period, represents the power on the tie line between the distribution network and the tie line at the i-th operating time period, and the subscript L represents the tie line; C total Calculated as follows: C total = ∑C oM + ∑C PC + ∑C G - ∑B PV Among them, ∑C OM represents the sum of operation and maintenance costs during the planned time period, ∑C PC represents the sum of losses caused by curtailment of wind and solar power for each new energy unit during the planned time period, ∑C G represents the cost of purchasing electricity from the distribution network during the planned time period, ∑B PV represents the sum of policy-based photovoltaic subsidies available due to power supply during the planned time period. The new energy units include wind turbines and photovoltaic generators.

2. The method according to claim 1, wherein Based on the optimal daily plan, formulating an optimal intraday plan and controlling the energy storage device and the seawater desalination facility to execute the optimal intraday plan for multi - source and multi - load coordinated control, including: Based on the daily plan, within each hour of the next day, respectively predicting the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next hour according to the data for formulating the intraday plan; Inputting the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next hour into the coordinated optimization model to obtain the optimal intraday plan for the next hour; When the next hour arrives, controlling the energy storage device and the seawater desalination facility to execute the optimal intraday plan for multi - source and multi - load coordinated control; Among them, the data required for formulating the intraday plan includes: the data required for formulating the daily plan for the current hour, updated meteorological forecast data, and the actual operation data of the current day.

3. The method according to claim 1, wherein The ∑C OM is calculated as follows: Among them, is the operation and maintenance cost per unit power of the wind power generation unit within an operation time period; is the operation and maintenance cost per unit power of the photovoltaic power generation unit within an operation time period; is the operation and maintenance cost per unit power of the seawater desalination unit within an operation time period; is the operation and maintenance cost per unit power of the energy storage device within an operation time period; N W is the number of wind power generation units; N PV is the number of photovoltaic power generation units; N DE is the number of seawater desalination units; is the power of the j-th wind turbine at the i-th operation time period; is the power of the k-th photovoltaic power generation unit at the i-th operation time period; is the power of the l-th seawater desalination unit at the i-th operation time period; is the energy storage capacity of the energy storage device at the i-th operation time period; The ∑C PC is calculated as follows: Among them, is the time-of-use electricity price for the i-th operating time period; is the wind curtailment power for the i-th operating time period; is the PV curtailment power for the i-th operating time period; The ∑C G is calculated as follows: The ∑B PV is calculated as follows: Among them, T PV is the photovoltaic subsidy amount per unit power.

4. The method according to claim 1, characterized in that After obtaining the optimal daily plan and before the next day arrives, it further includes: Issuing the daily plan to the energy storage device and each distributed seawater desalination facility.

5. The method according to claim 2, wherein After obtaining the optimal intraday plan for the next hour and before the next hour arrives, it further includes: Issuing the intraday plan to the energy storage device and each distributed seawater desalination facility.

6. The method according to claim 2, wherein After predicting the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next hour and before inputting the output of the new - energy power station, the load power of the conventional load, and the desalinated water demand for the next hour into the coordinated optimization model, it further includes: Judging whether the fresh - water storage of any seawater desalination facility is lower than the fresh - water demand corresponding to the next hour: if so, the next - hour plan for the seawater desalination facility with the fresh - water storage lower than the fresh - water demand corresponding to the next hour is to start all units.

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