CN113902309A - Optimization method and system for green port energy interconnection system - Google Patents
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Abstract
The invention provides an optimization method and system of a green port energy interconnection system, which comprises the following steps: randomly generating a population of particles, each particle representing a solution; initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle; evaluating the fitness of each particle to determine the individual optimum and the global optimum; updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not meet the constraint condition; and updating the individual optimum and the global optimum, and judging whether a stopping condition is met. According to the invention, a port shore power and wind power generation system are combined, a particle swarm optimization algorithm is utilized, and the peak clipping and valley filling can be realized through the integrated scheduling of the shore flexible load, the domestic power and the ship load, and the operation cost and pollutant discharge of a port power grid can be reduced.
Description
Technical Field
The invention relates to the technical field of power system operation and port energy optimization scheduling, in particular to an optimization method and system of a green port energy interconnection system, and particularly relates to an optimization method of a green port energy interconnection system based on a particle swarm optimization algorithm.
Background
In today's global society, transportation is of paramount importance, with shipping taking over 80% of the volume of cargo. Under the trend that the port scale is increasingly huge and the loads of the port and the ship are continuously increased, the traditional ship auxiliary generator cannot meet the increasing power utilization requirement and has the problem of pollutant emission. With the intellectualization of a port power system and the continuous development of new energy power generation, the economical efficiency of a power grid can be effectively improved by renewable energy utilization and port energy scheduling optimization, and carbon emission is reduced.
For a large-scale electrified port, a unidirectional distribution mode of a traditional power grid is replaced by the distributed power generation implementation demand response system, so that the traditional port power grid is converted into an intelligent energy hub, and the resource consumption can be obviously reduced. At present, the improvement of the port efficiency by using the complete electrification and the intelligent energy scheduling is mainly based on the economic standard, although the cost can be reduced and the energy utilization rate can be reflected by optimization, the consideration on the environmental influence is lacked, and the demand response management is still insufficient under the carbon neutralization development target.
In document 2, an ocean island group integrated energy supply system (the report of the Chinese electro-mechanical engineering, 2017,07(1):98-109) has special geodesic strategic significance as an important fulcrum and platform for maintaining the national sea defense and ocean interests in the overall national safety strategy, and reliable energy supply is an artery for the development and construction of the ocean island group. The document firstly explores the current situation of island power grid research and analyzes the limitation and defect of the island (group) applied to ocean; further, an ocean island group comprehensive energy supply system which fully utilizes rich renewable energy resources of the island and realizes the optimal configuration and sustainable development of the whole resources of the island group is provided, the structure of isolated development of the island power grid is broken, and the island group is taken as a whole to be interconnected through an original electricity storage (electricity conversion) ship; then analyzing the connotation and the characteristics of the system; the key technology required for constructing the ocean island comprehensive energy supply system is provided, and an electricity storage ship design and operation analysis example is provided so as to provide reference for development and construction of ocean islands (groups) in China. However, the document proposes a comprehensive energy supply system for realizing the optimized configuration and sustainable development of the overall resources of the ocean island group for the island grid. The scheme fully utilizes renewable energy sources, but research objects are island power grids and power storage ships, the method has no universality, and the influence of flexible load on port operation cost and carbon emission is not considered.
Patent document with publication number CN102130455B discloses a port shore-based variable frequency power supply system, which comprises a variable frequency power supply, a port high-voltage transformer substation and a ship power system, wherein the input end of the variable frequency power supply is connected with the port high-voltage transformer substation, and the output end of the variable frequency power supply is connected with the ship power system; the power supply system can continuously output three-phase alternating current with the voltage regulation range of 0-6.6 kV or 0-10 kV and the frequency regulation range of 0-60 Hz. The output side of the variable frequency power supply is connected with a distribution line through a cable reel, high-voltage output directly distributes power for the ship power system through the distribution line, and low-voltage output distributes power for the ship power system after passing through the step-down transformer. However, the patent document still has the defects of serious carbon emission and environmental pollution.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an optimization method and system for an energy interconnection system of a green port.
The invention provides an optimization method of a green port energy interconnection system, which comprises the following steps:
step 1: randomly generating a particle swarm by using the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system of the green port energy interconnection system, wherein each particle represents a solution, and each solution comprises the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system;
step 2: initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle;
and step 3: evaluating the fitness of each particle to determine the individual optimum and the global optimum;
and 4, step 4: updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not meet the constraint condition;
and 5: updating the individual optimum and the global optimum, judging whether the stopping condition is met, returning to the step 3 if the stopping condition is not met, and outputting the global optimum solution as a final result of the optimized scheduling if the stopping condition is met.
Preferably, in step 2, the port total cost objective function is:
wherein T is the total scheduling time of the scheme; costshoreThe electricity cost is the electricity cost of the port bank side; costshipThe cost of generating electricity for the ship; pSPSIs shore power; EP is real-time electricity price; pgenOutputting power for a marine diesel engine power generation system; a, b and c are cost coefficients of the generator;
the green port energy interconnection system comprises a port key load, a renewable energy power generation system and a mobile ship power station;
the key loads of the port comprise ship loads, shore fixed loads and shore flexible loads; the onshore flexible load comprises an onshore heat load and an onshore cold load;
the renewable energy power generation system is an onshore wind power generation system.
Preferably, the electricity consumption power of the shore fixed load is:
wherein, PlThe port fixed load power; prRated power for the motor; kzThe coefficients are required for synthesis; epsilonrIs its rated load duration.
Preferably, the power required by the onshore thermal load is as follows:
PACH＝qVD(Th-To)
wherein, PACHIs the thermal load power; q. q.sVIs a heating heat index per unit volume; d is the building volume calculated from the outside dimensions; t ishThe indoor heating temperature is set; t isoIs the outdoor temperature.
Preferably, the power required by the onshore cooling load is as follows:
PACC＝qSS(To-Tc)
wherein q isSIs a cooling index of a unit area; s is the area of the building calculated according to the external dimension; t isoIs the outdoor temperature; t iscIs the indoor refrigeration temperature.
Preferably, the solution represented by all particles satisfies the following formula:
preferably, in step 3, the fitness of each particle is evaluated, an optimal solution of each particle is found, the position and the fitness of the particle corresponding to the optimal solution are stored in the individual optimal, and a global optimal is selected from all the individual optimal.
Preferably, the evaluation fitness specifically includes: and substituting each solution into a port total cost objective function, and comparing the port total cost of each particle.
Preferably, in the step 5, the updating the individual optimal and the global optimal specifically includes: and if the newly generated solution is lower than the port total cost objective function value of the solution of the previous generation, updating the individual optimum, wherein the optimal value of all the solutions in each iteration is the global optimum.
The invention also provides an optimization system of the green port energy interconnection system, which comprises the following modules:
a particle generation module: randomly generating a particle swarm by using the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system of the green port energy interconnection system, wherein each particle represents a solution, and each solution comprises the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system;
an initialization module: initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle;
an evaluation module: evaluating the fitness of each particle to determine the individual optimum and the global optimum;
a detection module: updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not meet the constraint condition;
a judging module: updating the individual optimum and the global optimum, judging whether the stopping condition is met, returning to the step 3 if the stopping condition is not met, and outputting the global optimum solution as a final result of the optimized scheduling if the stopping condition is met.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention combines a new energy power generation technology, can replace part of the traditional power grid for power supply, reduces the environmental pollution and simultaneously improves the system economy;
2. according to the invention, a port power day-ahead scheduling scheme is set through a particle swarm optimization algorithm, shore power and heat load are flexibly controlled, power distribution is comprehensively planned, the use and fuel consumption of a diesel generator are reduced while the port power demand is ensured, and the pollutant emission and operation cost are reduced;
3. according to the invention, through economic dispatching, the potential of local power generation by port flexible loads and renewable energy sources is considered, and all parts of the system are effectively integrated, so that the new energy system and the traditional power grid are mutually matched, peak clipping and valley filling in the double meanings of economic benefit and wind energy resource are realized, and the rapid power change caused by a wind power plant is eliminated while the port operation cost is reduced;
4. the invention has universality, is not limited to a fixed port model, can comprise different renewable energy systems and various loads, is suitable for port or island group scheduling of various scales, and has short time-consuming scheme and high efficiency;
5. according to the invention, the port power dispatching scheme is established based on the particle swarm optimization algorithm, so that the power consumption and charging requirements of a ship at a berth can be ensured, power supply parts and loads can be more flexibly controlled, and the overall arrangement of a port power grid is realized;
6. the method considers the daily operation curve trend of the port flexible load and the power price change of the land power grid, and utilizes an optimization system to carry out day-ahead scheduling;
7. the invention combines the renewable energy power generation technology, and the renewable energy power generation technology and the traditional power grid are operated in a coordinated mode to establish a port comprehensive power system;
8. according to the invention, the wind power generation assembly is adopted, so that the economy of the port can be improved, the environment friendliness can be enhanced, and the particle swarm optimization algorithm is adopted, so that the model is more concise and efficient.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a flow chart of the optimization method of the green port energy interconnection system of the invention;
FIG. 2 is a system diagram of the green port energy interconnection system of the present invention;
FIG. 3 is a schematic view of an embodiment 4 of cost calculation;
FIG. 4 is a schematic view of an example of the discharge in example 4.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Example 1:
as shown in fig. 1 and fig. 2, the embodiment provides an optimization method of a green port energy interconnection system, including the following steps:
step 1: randomly generating a particle swarm by the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system of the green port energy interconnection system, wherein each particle represents a solution, and each solution comprises the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system.
Step 2: initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle;
the port total cost objective function is:
wherein T is the total scheduling time of the scheme; costshoreThe electricity cost is the electricity cost of the port bank side; costshipThe cost of generating electricity for the ship; pSPSIs shore power; EP is real-time electricity price; pgenOutputting power for a marine diesel engine power generation system; a, b and c are cost coefficients of the generator;
the green port energy interconnection system comprises a port key load, a renewable energy power generation system and a movable ship power station, wherein the port key load comprises a ship load, an onshore fixed load and an onshore flexible load; the shore flexible load comprises a shore heat load and a shore cold load, and the renewable energy power generation system is a shore wind power generation system.
The power consumption of the shore fixed load is as follows:
wherein, PlThe port fixed load power; prRated power for the motor; kzThe coefficients are required for synthesis; epsilonrIs its rated load duration.
The power required by the onshore thermal load is as follows:
PACH＝qVD(Th-To)
wherein, PACHIs the thermal load power; q. q.sVIs a heating heat index per unit volume; d is the building volume calculated from the outside dimensions; t ishThe indoor heating temperature is set; t isoIs the outdoor temperature.
The power required by the onshore cold load is as follows:
PACC＝qSS(To-Tc)
wherein q isSIs a cooling index of a unit area; s is the area of the building calculated according to the external dimension; t isoIs the outdoor temperature; t iscIs the indoor refrigeration temperature.
The solutions represented by all particles satisfy the following formula:
and step 3: evaluating the fitness of each particle, determining the individual optimum and the global optimum, evaluating the fitness of each particle, finding out the optimum solution of each particle, storing the position and the fitness of the particle corresponding to the optimum solution in the individual optimum, and selecting the global optimum from all the individual optimum; the evaluation fitness specifically comprises the following steps: and substituting each solution into a port total cost objective function, and comparing the port total cost of each particle.
And 4, step 4: and updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not accord with the constraint condition.
And 5: updating the individual optimum and the global optimum, judging whether a stopping condition is met, returning to the step 3 if the stopping condition is not met, and outputting a global optimum solution as a final result of the optimized scheduling if the stopping condition is met; in step 5, updating the individual optimum and the global optimum specifically comprises: and if the newly generated solution is lower than the port total cost objective function value of the solution of the previous generation, updating the individual optimum, wherein the optimal value of all the solutions in each iteration is the global optimum.
Example 2:
the embodiment provides an optimizing system of green harbour energy interconnected system, includes following module:
a particle generation module: randomly generating a particle swarm by using the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system of the green port energy interconnection system, wherein each particle represents a solution, and each solution comprises the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system;
an initialization module: initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle;
an evaluation module: evaluating the fitness of each particle to determine the individual optimum and the global optimum;
a detection module: updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not meet the constraint condition;
a judging module: updating the individual optimum and the global optimum, judging whether the stopping condition is met, returning to the step 3 if the stopping condition is not met, and outputting the global optimum solution as a final result of the optimized scheduling if the stopping condition is met.
Example 3:
those skilled in the art will understand this embodiment as a more specific description of embodiments 1 and 2.
As shown in fig. 1-2, the embodiment provides a green harbour energy interconnection system, and the energy structure of the green harbour energy interconnection system is as shown in fig. 1, and comprises a harbour key load component, a renewable energy power generation component and a mobile ship power station. Economic dispatch mainly aims at the minimum operation cost of a port and takes the improvement of the overall energy efficiency as a criterion.
The concrete implementation means is as follows:
the key load subassembly in harbour, key load subassembly in harbour include boats and ships load subassembly, the fixed load subassembly on the bank and the flexible load subassembly on the bank. The ship load of the ship load component comprises the power consumption demand and the charging demand when the ship stops at a port, and P is usedshipThe specific values are shown to be determined by the type of vessel and the size of the vessel.
The shore fixed load assembly mainly comprises mechanical equipment such as a crane and an anchor machine, and the power consumption of the shore fixed load assembly is specifically calculated as follows:
wherein, PlThe port fixed load power; prRated power for the motor; kzThe coefficients are required for synthesis; epsilonrIs its rated load duration.
The flexible load components on the shore refer to heat load components and cold load components of air conditioners, heating containers, refrigerated containers and the like. The cold load component and the heat load component can adjust the load power by adjusting the temperature on the premise of meeting the comfort level of a user, wherein the heat load component is mainly used for a heating system, and the required power adopts a single-bit heat accumulation index estimation method, which specifically comprises the following steps:
PACH＝qVD(Th-To) (2)
wherein, PACHIs the thermal load power; q. q.sVIs a heating heat index per unit volume; d is the building volume calculated from the outside dimensions; t ishThe indoor heating temperature is set; t isoIs the outdoor temperature.
The power required by the cold load component adopts a cold load coefficient method, which comprises the following steps:
PACC＝qSS(To-Tc) (3)
wherein q isSIs a cooling index of a unit area; s is according to the external ruleCalculating the area of the building; t isoIs the outdoor temperature; t iscIs the indoor refrigeration temperature.
The renewable energy power generation assembly is a shore wind power generation assembly, and the renewable energy power generation form of the green port mainly takes wind energy as a main component in the scheme. The shore wind power generation power is wind energy flowing through a section area perpendicular to a wind speed in unit time, is related to air density and the section area of power generation equipment, and is in a nonlinear relation with the wind speed, and specifically comprises the following steps:
wherein, WPGenerating power for the wind power; ρ is the air density; cpThe conversion rate of wind energy; v is the wind speed; u is the wind speed sectional area.
The sea, land and wind resources of the port are rich, but wind power is not uniformly distributed day and night, and the wind power field can cause rapid power change. Aiming at the wind energy characteristics, the influence of the wind power change on the system can be eliminated by adjusting the load and the power supply of each part in real time. In the embodiment, when the wind energy resource is rich, the onshore air conditioning load and the ship charging power can be increased, and the shore power supply and the ship auxiliary power generation are reduced; when the wind energy resource is insufficient, the set temperature of the air conditioner can be properly adjusted to reduce the heat load of the heat load component. The whole load is changed by adjusting the temperature and supplying power to the ship, and peak clipping and valley filling of wind power energy are realized.
Green port energy interconnection optimization model: the purpose of green harbour energy interconnection optimization is to meet various load requirements of ships and shore sides and reduce the operation cost of the harbour as much as possible by reasonably allocating energy. Therefore, the minimum operation cost of the green port is set as an objective function, and the minimum operation cost is composed of two parts, namely port shore side electricity utilization cost and ship electricity generation cost, and is specifically expressed as follows:
whereinT is the total scheduling time of the scheme, for example, T is 24 in the day-ahead scheduling; costshoreCost for electricity consumption on port shore side, CostshipThe cost of generating electricity for the ship; pSPSShore power, EP real-time electricity prices; pgenOutputting power for a marine diesel engine power generation system; and a, b and c are cost coefficients of the generator.
According to the model, the port electricity utilization cost is influenced by the real-time electricity price. In order to reduce the overall cost, the shore power supply can be reduced in the peak time period, the auxiliary power supply of the ship is increased, and the valley time period is opposite. Economic dispatch in the optimization model is matched with wind power resources, and peak clipping and valley filling in double meanings can be achieved. It should be noted that in order to ensure the balance of the power supply and demand, the optimization model considers the power balance constraint, the limit of the ship diesel generator and the ramp rate, the flexible load and the shore power constraint, etc.
The embodiment also provides a green port energy interconnection optimization method based on the particle swarm optimization algorithm, which comprises the following steps:
the particle swarm optimization algorithm is an intelligent heuristic optimization method, originates from the research on the behavior of bird swarm predation, has concise operation principle and high convergence speed, and is widely applied to numerous fields such as function optimization, image processing, geodetic survey and the like.
For the optimization problem, its solution can be seen as a bird in the search space, abstracted as a particle without mass and volume, and extended to an N-dimensional space. All particles have an adaptation value determined by the optimized function, and position and velocity in the N-dimensional space. In each iteration process, each particle summarizes own experience to obtain the individual optimum, and simultaneously shares experience with the group to obtain the global extreme value, and the next step of movement is determined according to the two experiences. The iterative process of the algorithm comprises updating of speed and position, wherein the speed updating comprises inertia, individual cognition and social cognition, and the new position depends on the historical position and the current speed and is specifically represented as follows:
wherein v isiIs the flight velocity of the ith particle; x is the number ofiIs the position of the ith particle; w is the inertial weight; c. C1,c2Is a positive learning factor, r1,r2Is represented by [0,1 ]]Random numbers uniformly distributed in the interval; p is a radical ofiAn individual optimal position; giRepresenting a global optimal position.
In the scheme, a solution is provided for green port energy interconnection optimization based on a single-target particle swarm optimization algorithm. The optimization process is summarized as follows:
s1, randomly generating an initial particle swarm P with the particle number N;
s2, initializing particle swarm optimization variables including set temperatures of cold and heat loads on the shore and power output of the ship auxiliary generator system per hour;
s3, initializing a particle swarm, and randomly endowing the position and the speed of each particle; setting the fitness, namely the port total cost objective function;
s4, calculating the adaptive value of each particle according to the objective function and evaluating the adaptive value;
s5, starting iteration, finding out the optimal solution of each particle to the current, storing the position and fitness of each particle in the individual optimal solution, and selecting the global optimal solution from all the individual optimal solutions;
s6, updating the speed and position of the particle swarm according to the individual and global optima, checking according to the constraint condition, and adjusting if the speed and position of the particle swarm do not meet the constraint condition;
s7, updating the individual and global optima, and judging whether the stop condition is met;
and S8, outputting the global optimal solution as a final result of the optimized scheduling.
Aiming at the port emission problem, the use of shore power and renewable energy is the key to realize the energy conservation and emission reduction of green ports. The emission depends on the berth state and the power generation constitution of the onshore energy, and the centralized system and the clean energy can reduce the environmental pollution and simultaneously contribute to increasing the flexibility of the seaport system.
The scheme of this embodiment combines harbour bank electricity and wind power generation system, utilizes the particle swarm optimization algorithm, through flexible load on the bank, the overall scheduling of domestic power consumption and boats and ships load not only can cut the peak and fill the valley, can also reduce harbour electric wire netting running cost and pollutant discharge. In order to realize the energy interconnection optimization of the green port, a new energy power generation technology is combined, shore power, ship power supply and various load constraints are comprehensively considered, and a novel optimization scheduling scheme suitable for the comprehensive port is provided based on a particle swarm optimization algorithm.
In the embodiment, when a ship stops at a port, a ship power grid and a port energy network are interconnected through high-voltage shore power, so that bidirectional energy flow between the ship and the port is realized, and for the energy interconnection system, an energy regulation and control method mainly based on economy is provided in the embodiment, so that the running cost of the port and the ship can be reduced. When the ship is parked at a port, the ship load mainly refers to lighting equipment and pump loads on the ship; the shore fixed load mainly comprises a crane for loading and unloading articles, a crane and a port lighting load; flexible loads on shore mainly refer to cold and hot loads (air conditioners, refrigerated containers and the like) of ports; the land power grid is a port power grid which is connected with a large power grid on the land through a transformer, and when the power supply capacity of a port is insufficient, the land power grid is required to supply power to the port.
When the ship stops at the port, the energy interaction between the ship and the port is considered, and the economical operation of the port energy interconnection system is realized by optimizing and adjusting the temperature of cold and hot loads and the diesel engine power generation system on the ship. Therefore, in the embodiment, the particle group generates cold and heat load temperature and output power of the marine diesel generator per hour.
The optimization method of the embodiment is characterized in that the electricity purchasing cost of the port and the power supply cost of the ship are considered, and the operation cost of the port and the ship can be reduced simultaneously through the optimization method.
Example 4:
those skilled in the art will understand this embodiment as a more specific description of embodiments 1 and 2.
With the rapid increase of the port load, the single energy supply mode of the port power grid cannot meet the increasing ship power demand, and the random access of the large-scale ship load brings a serious challenge to the optimal operation and the coordination control of the port power grid. The embodiment designs a green port energy interconnection system and an optimization method of a particle swarm optimization algorithm by relying on the national natural fund project ' multivariate coupled mobile microgrid optimization configuration research ' and ' Pujiang talent plan ' advanced energy management basic theory and key technology of all-electric ships ' in Shanghai city.
Through the interconnection optimization scheme that this embodiment provided, can reduce green harbour electric power system cost, rationally allocate boats and ships auxiliary generator, indirectly reduce carbon emission, reduce environmental pollution. Taking 24-hour day-ahead scheduling of a port with rated power of 5MW wind power generation equipment, 10 ship berths, shore-side living and industrial loads with rated capacity of 15MW as an example, if the electricity price of a land grid adopts a time-of-use electricity price standard, the peak-to-valley time periods are 1.033, 0.601 and 0.301 (yuan/kilowatt hour), the 24-hour running cost is 577784 yuan, and the carbon emission is 266058 kilograms. As shown in table 1, fig. 3 and fig. 4, the interconnection optimization method provided by the scheme can fully utilize renewable resources of the port, more reasonably distribute electric energy of each part, ensure that the load of the ship and the shore side is met, improve the overall economy and energy efficiency of the port, reduce the cost and carbon emission by 14.03% and 74.56%, and further solve the problems of large fuel consumption and much pollution emission when the ship stops at the port.
TABLE 1 results of green harbor interconnection optimization
| Non-interconnection optimization example | Calculation example of the scheme | |
| Running cost (Yuan) | 577784 | 496736 |
| Carbon emission (kilogram) | 266058 | 67680 |
According to the invention, by utilizing a particle swarm optimization algorithm, the peak clipping and valley filling can be realized through the on-shore flexible load, the domestic power utilization and the overall scheduling of the ship load, and the operation cost and the pollutant discharge of a port power grid can be reduced.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. An optimization method of a green port energy interconnection system is characterized by comprising the following steps:
step 1: randomly generating a particle swarm by using the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system of the green port energy interconnection system, wherein each particle represents a solution, and each solution comprises the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system;
step 2: initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle;
and step 3: evaluating the fitness of each particle to determine the individual optimum and the global optimum;
and 4, step 4: updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not meet the constraint condition;
and 5: updating the individual optimum and the global optimum, judging whether the stopping condition is met, returning to the step 3 if the stopping condition is not met, and outputting the global optimum solution as a final result of the optimized scheduling if the stopping condition is met.
2. The method for optimizing green port energy interconnection system according to claim 1, wherein in the step 2, the port total cost objective function is:
wherein T is the total scheduling time of the scheme; costshoreThe electricity cost is the electricity cost of the port bank side; costshipThe cost of generating electricity for the ship; pSPSIs shore power; EP is real-time electricity price; pgenOutputting power for a marine diesel engine power generation system; a, b and c are cost coefficients of the generator;
the green port energy interconnection system comprises a port key load, a renewable energy power generation system and a mobile ship power station;
the key loads of the port comprise ship loads, shore fixed loads and shore flexible loads; the onshore flexible load comprises an onshore heat load and an onshore cold load;
the renewable energy power generation system is an onshore wind power generation system.
3. The optimization method of the green port energy interconnection system according to claim 2, wherein the electricity power of the onshore fixed load is as follows:
wherein, PlThe port fixed load power; prRated power for the motor; kzThe coefficients are required for synthesis; epsilonrIs its rated load duration.
4. The optimization method of the green port energy interconnection system according to claim 3, wherein the power required by the onshore thermal load is as follows:
PACH＝qVD(Th-To)
wherein, PACHIs the thermal load power; q. q.sVIs a heating heat index per unit volume; d is the building volume calculated from the outside dimensions; t ishThe indoor heating temperature is set; t isoIs the outdoor temperature.
5. The optimization method of the green port energy interconnection system according to claim 4, wherein the power required by the onshore cooling load is as follows:
PACC＝qSS(To-Tc)
wherein q isSIs a cooling index of a unit area; s is the area of the building calculated according to the external dimension; t isoIs the outdoor temperature; t iscIs the indoor refrigeration temperature.
6. The method for optimizing green port energy interconnected system according to claim 5, wherein the solution represented by all the particles satisfies the following formula:
7. the method for optimizing the green port energy interconnection system according to claim 2, wherein in the step 3, the fitness of each particle is evaluated, an optimal solution of each particle is found, the position and the fitness of the particle corresponding to the optimal solution are stored in the individual optimal, and a global optimal is selected from all the individual optimal.
8. The optimization method of the green port energy interconnection system according to claim 7, wherein the evaluation fitness specifically comprises: and substituting each solution into a port total cost objective function, and comparing the port total cost of each particle.
9. The method for optimizing the green port energy interconnection system according to claim 2, wherein in the step 5, the updating of the individual optimal and the global optimal specifically comprises: and if the newly generated solution is lower than the port total cost objective function value of the solution of the previous generation, updating the individual optimum, wherein the optimal value of all the solutions in each iteration is the global optimum.
10. The utility model provides an optimization system of green harbour energy interconnected system which characterized in that includes following module:
a particle generation module: randomly generating a particle swarm by using the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system of the green port energy interconnection system, wherein each particle represents a solution, and each solution comprises the set temperature of the onshore cold load, the set temperature of the onshore heat load and the hourly power output of the ship auxiliary generator system;
an initialization module: initializing a particle swarm, randomly giving the position and the speed value of each particle, setting a port total cost objective function, and substituting each solution into the port total cost objective function to calculate the fitness of each particle;
an evaluation module: evaluating the fitness of each particle to determine the individual optimum and the global optimum;
a detection module: updating the speed and the position of the particle swarm according to the individual optimum and the global optimum, checking according to the constraint condition, and adjusting if the speed and the position of the particle swarm do not meet the constraint condition;
a judging module: updating the individual optimum and the global optimum, judging whether the stopping condition is met, returning to the step 3 if the stopping condition is not met, and outputting the global optimum solution as a final result of the optimized scheduling if the stopping condition is met.
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