CN110768303A - Optimization configuration method for equipment capacity of island-type energy system - Google Patents

Optimization configuration method for equipment capacity of island-type energy system Download PDF

Info

Publication number
CN110768303A
CN110768303A CN201910992406.5A CN201910992406A CN110768303A CN 110768303 A CN110768303 A CN 110768303A CN 201910992406 A CN201910992406 A CN 201910992406A CN 110768303 A CN110768303 A CN 110768303A
Authority
CN
China
Prior art keywords
output
unit
constructing
power
island
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201910992406.5A
Other languages
Chinese (zh)
Inventor
王佳伟
谷志红
刘卓
李楠楠
张�荣
温伟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Economic and Technological Research Institute of State Grid Shanxi Electric Power Co Ltd
Original Assignee
Economic and Technological Research Institute of State Grid Shanxi Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Economic and Technological Research Institute of State Grid Shanxi Electric Power Co Ltd filed Critical Economic and Technological Research Institute of State Grid Shanxi Electric Power Co Ltd
Priority to CN201910992406.5A priority Critical patent/CN110768303A/en
Publication of CN110768303A publication Critical patent/CN110768303A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/10—Photovoltaic [PV]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00—Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention provides an optimized configuration method for equipment capacity of an island type energy system, which comprises the following steps: (1) constructing a unit output model; (2) constructing an island type energy system equipment capacity optimization scheduling model; (3) and calculating the capacity optimization configuration result of each device of the island energy system. The method of the invention can provide an optimization method for the capacity configuration of each device of the island energy system, and reduce the energy consumption of the system.

Description

Optimization configuration method for equipment capacity of island-type energy system
Technical Field
The invention belongs to the technical field of island type energy system configuration, and particularly relates to the technical field of equipment capacity configuration.
Background
China is long in coastline and numerous in islands, and the development of a multi-energy complementary energy supply system is the basic guarantee of island development construction and daily life of residents. The island type energy system mainly comprises a solar cell photovoltaic array, a wind driven generator, a storage battery pack, a diesel generator and a load. The sea island energy utilization system mainly comprises the electric load requirements of a sea water desalination system and the illumination loads of residents, wherein the sea water desalination system has lower requirements on the electric energy reliability, the illumination loads in the system continuously provide electric energy for the energy storage system, the wind power generation output, the photovoltaic power station and the diesel generator set to realize balance with the load requirements, and the stable and safe operation of the system is met. For the problem of optimal scheduling of an island-type energy system, the capacity of a wind-light complementary power generation system in the system is excessive by a traditional optimization method, and the waste of resources is caused. The optimization configuration of the microgrid mainly depends on mathematical programming methods, but the methods have certain limitations. Such as: the correlation between wind speed and illumination is not considered, the problem that the local optimum is caused by improper parameter setting is solved, and the like.
How to realize the lowest system operation cost and the carbon emission cost is a problem which needs to be solved urgently.
Disclosure of Invention
The invention provides an optimized configuration method of equipment capacity of an island type energy system, which comprises the following steps: (1) constructing a unit output model; (2) constructing an island type energy system equipment capacity optimization scheduling model; (3) and calculating the capacity optimization configuration result of each device of the island energy system.
Further, the constructing of the unit output model includes: constructing an output power model of the wind power system; constructing a photovoltaic system output power model; constructing an output power model of the energy storage power station; and constructing an uncertainty set of the wind and light machine set.
Further, the calculating of the optimal configuration result of the capacity of each device of the island-type energy system includes calculating the minimum operating cost condition of the system and calculating the optimal capacity allocation value of each unit.
Further, the minimum operating cost condition of the computing system is specifically as follows: according to
Figure BDA0002238676890000021
Minimum operating cost condition of computing system, wherein
Figure BDA0002238676890000022
The difference value of the combined output of the wind power and the photovoltaic is obtained; delta represents the penalty factor (unit: yuan/kW) in the risk penalty term.
Further, the calculating of the optimal capacity ratio of each unit specifically includes: according to
Figure BDA0002238676890000023
Calculating the optimal capacity allocation ratio of each unit, wherein giRepresenting the active output of the diesel generator set i; gj,wRepresenting the active power output of the fan j; gm,pvRepresenting the active output of the photovoltaic unit; d represents the power system load demand value.
The method of the invention can provide an optimization method for the capacity configuration of each device of the island energy system, and reduce the energy consumption of the system.
Drawings
Fig. 1 is a logic diagram of the optimized configuration of equipment capacity of the island type energy system.
Detailed Description
Example 1
1. Establishing unit output model
(1) Construction of wind power system output power model
The wind power is limited by the incoming wind speed, but when the incoming wind speed is lower than the cut-in wind speed or higher than the cut-out wind speed, the wind power plant does not generate electricity, and the relationship between the wind power and the wind speed is as follows:
Figure BDA0002238676890000024
in the formula: gj,w(t) is the available output of the wind turbine generator w at the moment t;grthe rated output power of the wind turbine generator is set; v. ofi,w、vo,wThe cutting is respectively the cut-in wind speed and the cut-out wind speed; v. ofr,wRated wind speed; v (t) is the actual wind speed at time t.
(2) Building photovoltaic system output power model
The output curve of a photovoltaic system generally satisfies the β distribution
Figure BDA0002238676890000031
α and β are shape parameters of Beta distribution respectively, theta is a radiance correlation coefficient, and the Beta parameters are calculated by introducing the average value and the standard deviation value of irradiance.
Figure BDA0002238676890000033
In the formula: μ and σ are the mean value and normal distribution value of solar radiation, and the probability of the solar radiation state can be calculated by the following formula.
Figure BDA0002238676890000034
In the formula: thetac、θdThe solar radiation degree theta is the upper limit and the lower limit of the solar radiation degree theta, the solar radiation energy is calculated and converted into electric energy, and the photovoltaic output is obtained through a formula.
gm,pv(t)＝ηPV×SPV×θt
In the formula ηpvFor photovoltaic efficiency of work, SpvIs the total area of the photovoltaic module, thetatThe time when the photovoltaic is exposed to sunlight.
(3) Construction of output power model of energy storage power station
The energy storage power station is charged at the night valley, and is discharged at the daytime peak, so that the peak-valley difference of the load curve can be effectively reduced, the stability of a power grid is improved, and wind power and photovoltaic grid connection is promoted. The energy storage controller controls the energy storage power station to stop discharging.
Figure BDA0002238676890000035
In the formula:
Figure BDA0002238676890000036
respectively representing the upper limit and the lower limit of the storage capacity of the energy storage power station; gk,sAnd (t) is the charge and discharge amount of the energy storage power station at the moment t. When the energy storage power station is in a discharge state, the following formula is shown:
Figure BDA0002238676890000041
when the energy storage power station is in a charging state, the following formula is shown:
Figure BDA0002238676890000042
in the formula:
Figure BDA0002238676890000043
and
Figure BDA0002238676890000044
respectively representing the charging and discharging power of the energy storage power station k at the moment t; gk,s(t +1) represents the charge amount of the energy storage power station k at the time t + 1;
Figure BDA0002238676890000045
andrespectively representing the discharge and charge losses of the energy storage power station.
(4) Constructing uncertainty set of wind and light machine set
Calculating the wind power g of the jth wind field at the time tj,w(t) minimum and maximum values of the variation range. Calculating the photovoltaic power g of the mth photovoltaic at the time tm,pvThe range of variation of (t) may be closed.
Figure BDA0002238676890000047
In the formula: gj,w(t)、gm,pv(t) actual values of wind power output and photovoltaic output in a time period t respectively;
Figure BDA0002238676890000049
Figure BDA00022386768900000410
the maximum fluctuation quantity of the wind power station in the t period;
Figure BDA00022386768900000411
the maximum fluctuation amount of the photovoltaic power station in the t period.
The photovoltaic power generation robust deviation coefficient is generally set to
Figure BDA00022386768900000412
It controls the photovoltaic power generation fluctuation range in each period, i.e. the worst boundary of uncertainty, follows an unknown but symmetrical distribution and is in [ -1,1]And (6) taking the value. Taking into account that wind, photovoltaic and load demands do not occur in the worst case at every time interval, i.e. the coefficients
Figure BDA00022386768900000417
The boundary of-1 or 1 is not reached, and the uncertainty factor can be further described as:
Figure BDA00022386768900000413
in the formula:
Figure BDA00022386768900000415
the real values of the wind power and the photovoltaic output power in the t time period are as follows: gw(t)、gpv(t) is the nominal value of the wind power and photovoltaic output power in the time period t:
Figure BDA00022386768900000416
the maximum fluctuation amounts of the wind power and the photovoltaic output power in the t period are respectively. T isw＝[1,2,…,Tw]Is a time period set of wind power generation. Gamma-shapedw、ΓpvRobust measurement of wind power generation and photovoltaic power generation, wherein gamma is an integer or a non-integerw∈[0,Γw]、Γpv∈[0,Γpv]. In a limited time period, the robust measure gamma represents the maximum amount of deviation of uncertain factors from a nominal value, and the wind power and photovoltaic power generation have worst random fluctuation in all time periods simultaneously. If gamma is 0, the randomness fluctuation of the wind power and the photovoltaic power generation is not generated, and the corresponding true value is equal to the nominal value, namely the certainty condition. The real description of the random scene is realized by controlling the value of the robust measure, and the cost and the conservation of the robust optimization are adjusted.
2. Building optimized dispatching model of island type energy system
(1) System operation objective function
Due to the fluctuation and randomness of system voltage and wind turbine generator output force. There is a need for a system that optimizes the capacity configuration of the unit. For a multi-energy complementary power generation system, the optimization design target is to minimize the comprehensive cost of system environment management cost, wind power and photovoltaic output deviation and the like on the premise of meeting the performance index of the system. Considering from the perspective of maximizing social benefits, reducing the consumption of fossil energy is the most direct means for realizing social benefits, so that a power generation scheduling model with the minimum energy consumption as the guide is constructed. In order to obtain the fuel consumption of the diesel generator and further obtain the operating cost of the diesel generator, it is necessary to establish a diesel generator power cost model.
The mathematical model of a diesel generator is represented as a quadratic function of power, as shown in the following equation:
Figure BDA0002238676890000051
in the formula: u. ofi(t) is a start-stop state variable of the diesel generating set i at the moment t, and u is a start-up state variable when the diesel generating set is in a start-up statei(t) takes a value of 1, u being in a shutdown statei(t) takes the value 0; SUiThe coal consumption for starting the diesel generator set i (unit: g/kW ∙ h); gi(gi(t)) is the generated output g of the diesel generating set ii(t) fuel consumption function. a, b and c are coefficients of a cost function and can be obtained by fitting according to an energy consumption characteristic curve of the diesel engine, giAnd (t) is the generated power of the diesel engine set i, wherein a is 0.0071, b is 0.2333, and c is 0.4333.
(2) System operation constraints
Under the objective function, the following constraints must be satisfied:
and (3) system power balance:
Figure BDA0002238676890000052
in the formula: giRepresenting the active output of the diesel generator set i; gj,wRepresenting the active power output of the fan j; gm,pvRepresenting the active output of the photovoltaic unit; d represents the power system load demand value.
(2) Diesel generator set operating condition constraints
1) Unit output restraint:
Figure BDA0002238676890000061
in the formula:
Figure BDA0002238676890000062
representing the maximum schedulable output of the unit i;
Figure BDA0002238676890000063
representing the minimum dispatchable capacity of unit i.
2) Unit climbing restraint:
Figure BDA0002238676890000064
3) and (3) constraint of start and stop of the unit:
Figure BDA0002238676890000066
in the formula:
Figure BDA0002238676890000067
the power lifting constraint of the diesel generator set i is defined;
Figure BDA0002238676890000068
the running time of the diesel generating set i at the moment t-1 is represented;the shortest running time of the diesel generating set;
Figure BDA00022386768900000610
the shutdown time of the diesel generating set i at the time t-1 is represented;
Figure BDA00022386768900000611
the shortest stop time of the diesel generating set i.
(3) Wind power output constraint
Figure BDA00022386768900000612
In the formula:representing the maximum schedulable output of the wind turbine generator j;
Figure BDA00022386768900000614
representing the minimum dispatchable capacity of unit j.
(4) Photovoltaic output constraint
Figure BDA00022386768900000615
In the formula:
Figure BDA00022386768900000616
representing the maximum schedulable output of the photovoltaic unit m;
Figure BDA00022386768900000617
representing the minimum dispatchable output of the photovoltaic module m.
(5) Calculating the maximum output of the unit
Figure BDA00022386768900000618
In the formula: d (t) is the load demand of the system at the moment t; r (t) is the standby requirement of the system at the time t; l is the line loss rate of the system; theta is the self-power consumption rate of the unit; gmaxAnd (t) is the maximum unit output of the unit at the moment t.
3. Calculating capacity optimization configuration result of each device of island type energy system
(1) Minimum operating cost condition of computing system
Comprehensively considering the unit operation risk condition of the wind power and the photovoltaic unit, the obtained expression is as follows:
Figure BDA0002238676890000071
in the formula:
Figure BDA0002238676890000072
the difference value of the combined output of the wind power and the photovoltaic is obtained; delta represents the penalty factor in the risk penalty term (singleton)Bit: yuan/kW).
(2) Calculating the optimal capacity allocation ratio of each unit according to the system power balance:
Figure BDA0002238676890000073
in the formula: giRepresenting the active output of the diesel generator set i; gj,wRepresenting the active power output of the fan j; gm,pvRepresenting the active output of the photovoltaic unit; d represents the power system load demand value.
The above is a specific calculation mode of the present invention. While there has been shown and described the fundamental principles of the invention and with the details thereof, it will be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (5)

1. An optimal configuration method for equipment capacity of an island-in-sea type energy system is characterized by comprising the following steps:
(1) constructing a unit output model;
(2) constructing an island type energy system equipment capacity optimization scheduling model;
(3) and calculating the capacity optimization configuration result of each device of the island energy system.
2. The method of claim 1, wherein constructing the unit contribution model comprises:
constructing an output power model of the wind power system;
constructing a photovoltaic system output power model;
constructing an output power model of the energy storage power station;
and constructing an uncertainty set of the wind and light machine set.
3. The method of claim 1, wherein the calculating of the optimal configuration result of the capacities of the equipments of the island-type energy system comprises calculating a minimum operating cost condition of the system and calculating an optimal capacity allocation value of each unit.
4. The method of claim 1, wherein the minimum operating cost condition of the computing system is: according to
Figure FDA0002238676880000011
Minimum operating cost condition of computing system, wherein
Figure FDA0002238676880000012
The difference value of the combined output of the wind power and the photovoltaic is obtained; delta represents the penalty factor (unit: yuan/kW) in the risk penalty term.
5. The method according to claim 1, wherein the calculating of the optimal capacity allocation value of each unit specifically comprises: according to
Figure FDA0002238676880000013
Calculating the optimal capacity allocation ratio of each unit, wherein giRepresenting the active output of the diesel generator set i; gj,wRepresenting the active power output of the fan j; gm,pvRepresenting the active output of the photovoltaic unit; d represents the power system load demand value.
CN201910992406.5A 2019-10-18 2019-10-18 Optimization configuration method for equipment capacity of island-type energy system Pending CN110768303A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910992406.5A CN110768303A (en) 2019-10-18 2019-10-18 Optimization configuration method for equipment capacity of island-type energy system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910992406.5A CN110768303A (en) 2019-10-18 2019-10-18 Optimization configuration method for equipment capacity of island-type energy system

Publications (1)

Publication Number Publication Date
CN110768303A true CN110768303A (en) 2020-02-07

Family

ID=69332397

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910992406.5A Pending CN110768303A (en) 2019-10-18 2019-10-18 Optimization configuration method for equipment capacity of island-type energy system

Country Status (1)

Country Link
CN (1) CN110768303A (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113013904A (en) * 2021-03-23 2021-06-22 中国能源建设集团广东省电力设计研究院有限公司 Optimization method and device for offshore wind power energy storage capacity configuration
CN116689464A (en) * 2023-07-27 2023-09-05 广州汇锦能效科技有限公司 Distributed garbage treatment and energy supply system suitable for islands
CN117375106A (en) * 2023-10-11 2024-01-09 揭阳前詹风电有限公司 Offshore wind power construction management method and system based on Internet of things

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113013904A (en) * 2021-03-23 2021-06-22 中国能源建设集团广东省电力设计研究院有限公司 Optimization method and device for offshore wind power energy storage capacity configuration
CN116689464A (en) * 2023-07-27 2023-09-05 广州汇锦能效科技有限公司 Distributed garbage treatment and energy supply system suitable for islands
CN117375106A (en) * 2023-10-11 2024-01-09 揭阳前詹风电有限公司 Offshore wind power construction management method and system based on Internet of things
CN117375106B (en) * 2023-10-11 2024-04-09 揭阳前詹风电有限公司 Offshore wind power construction management method and system based on Internet of Things

Similar Documents

Publication Publication Date Title
CN108711892B (en) Optimal scheduling method of multi-energy complementary power generation system
CN107425534B (en) Micro-grid scheduling method based on optimization of storage battery charging and discharging strategy
CN109742796B (en) Multi-time scale coordinated scheduling method of wind, light, water, fire and storage combined system
CN110768303A (en) Optimization configuration method for equipment capacity of island-type energy system
CN110783959B (en) New forms of energy power generation system's steady state control system
CN111355270B (en) Island micro-grid group capacity optimization configuration method
CN112600209A (en) Multi-objective capacity optimization configuration method for island independent micro-grid containing tidal current energy
JP2010259303A (en) Distributed power generation system
CN112366684A (en) Island micro-grid system
CN116979578A (en) Electric and thermal triple generation optimal scheduling method and system for wind, light, water and fire storage
CN115333161A (en) Capacity optimization configuration method for power supply system of green water plant
CN115882460A (en) Two-stage new energy micro-grid optimization scheduling method considering demand side management
Shaikh et al. Performance analysis of wind-photovoltaic-battery based DC microgrid setup for off-grid applications
CN117829470A (en) Electric power production simulation method for regular wind-avoiding photoelectric output uncertainty scheduling risk
CN110571868B (en) Optimal configuration method of micro-grid
Zidane et al. A new fuzzy logic solution for energy management of hybrid photovoltaic/battery/hydrogen system
Quan et al. Optimal Energy Management of Vanadium Redox Flow Batteries Energy Storage System for Frequency Regulation and Peak Shaving in an Islanded Microgrid
Bhol et al. Performance Analysis and Cost Calculation of Standalone PV-DG Generation System Without Storage
CN206894253U (en) A kind of power network intelligent control system based on the energy storage of photovoltaic DC side
Huang et al. A multi-time scale scheduling method for wind-PV-pumped storage-electrochemical energy storage integrated generation system
El-Hendawi et al. Enhanced MG with optimum operational cost of pumping water distribution systems
CN110417002B (en) Optimization method of island micro-grid energy model
Sathyan et al. Hybrid wind/PV/fuel cell generation system
Gholami et al. Establishment of a Virtual Power Plant in Grid for Maximizing Producers’ Profits and Minimizing Pollutant Emissions and Investment Costs
CN111062532A (en) Incremental distribution park power grid capacity configuration optimization method considering V2G

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20200207

WD01 Invention patent application deemed withdrawn after publication