CN111445107B - Multi-objective optimal configuration method for combined cooling heating power type micro-grid - Google Patents
Multi-objective optimal configuration method for combined cooling heating power type micro-grid Download PDFInfo
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Abstract
The invention relates to a multi-target optimal configuration method of a combined cooling, heating and power type micro-grid, which comprises the steps of constructing an energy supply equipment model of a CCHP system and an energy flow chart thereof, uniformly converting cold energy and heat energy into electric energy for scheduling, analyzing the energy cost of each kilowatt-hour generated by various equipment in different time periods from the aspects of the running cost and the maintenance cost of the equipment, and determining a scheduling flow chart of the output energy of each equipment in the CCHP system according to the size relation of the energy cost; constructing an objective function configured by the CCHP system, solving constraint conditions of the function, and determining an evaluation index for solving an objective function value of the system; the best configuration scheme is found by improving the PSO algorithm under the condition that the evaluation index is met. The power supply reliability of the CCHP system after the optimal configuration of the invention reaches more than 99 percent, the investment in the service period of the CCHP system is small, the pollution to the environment is also minimum, and the cost of the CCHP system in the operation period is effectively reduced.
Description
Technical Field
The invention belongs to the technical field of micro-grids, relates to a combined cooling, heating and power type micro-grid technology, and particularly relates to a multi-target optimal configuration method for a combined cooling, heating and power type micro-grid.
Background
The combined cooling heating power type micro-grid is mainly provided by a solar photovoltaic power generation system, a wind power generation system and other equipment with low operation cost as a first output unit when the island operation is performed, and by a gas turbine and other output units with relatively low operation cost when the electric energy is not supplied enough. The cold load and the heat load related in the traditional micro-grid system are generated by a separate supply device compression test refrigerator and an electric boiler, the whole energy supply process is accompanied by low energy use efficiency, for example, the natural gas utilization rate of a gas turbine is only thirty percent, and sixty percent of energy contained in the flue gas is directly discharged into the atmosphere, so that the pollution to the atmosphere is caused, and huge resource waste is generated.
The gas turbine is used as an output device in a combined cooling heating and power (English: combined cooling heating and power, abbreviated as CCHP) system, and waste gas generated in the power generation process of the gas turbine is reused in the CCHP system and converted into heat energy in a heating season and cold energy in a cooling season, so that the pollution-free natural gas is utilized under the condition of combustion by different levels of heat, and the graded utilization of energy is realized. Compared with a split supply (English: separation production, SP for short) system formed by a distributed power supply, the CCHP system not only improves the utilization rate of energy sources, but also reduces the pollution to the environment, and is an energy supply mode advocating great development at present.
The CCHP system has the characteristics of high energy utilization rate and small environmental pollution compared with the SP system, but the key to solving the configuration research of the whole CCHP system is to configure the whole CCHP system from the aspects of improving the energy utilization rate, reducing the environmental pollution and enhancing the robustness of the system. The literature (Hu, r.; ma, j.; li, z.k.; lu, q.; zhang, d.h.; qian, x.; optimal allocation and applicability analysis of distributed combined cooling-heating-power system, dianwang jisha 2017,41,418-425) sets the multiple benefits generated by the CCHP system as a solution target for the entire model, giving the CCHP system configuration pattern under different load structure requirements, and the entire CCHP system failed to verify system robustness against multiple years of data and against future years of data. In literature (Ma, X.Y.; wu, Y.W.; fang, H.L.; sun, Y.Z. optimal sizing of hybrid solar-wind distributed generation in an islanded microgrid using improved bacterial foraging algorithm.Zhongguo Dianji Gongcheng Xuebao 2011,31,17-25.) the output devices comprising the wind/light/storage hybrid microgrid are optimally configured by improving the bacterial foraging algorithm, and the whole configuration process does not consider the load differentiation in actual engineering, especially the use in heating seasons and peak load periods in summer, nor the relationship between the energy storage devices and the primary load in the CCHP system. The configuration of CCHP systems in the literature (Li, m.; mu, h.l.; li, n.; ma, b.y.optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system. Energy 2016,99,202-220.) was optimized in terms of energy analysis, economic operation, and environmental impact, and two algorithms were employed to compare the economic benefits generated by CCHP systems in different scenarios to arrive at the most suitable use scenario, where gas price fluctuations and uncontrollable factors were not taken into account in the CCHP system, thus making the reliability of the overall CCHP system too much dependent on experimental data.
In summary, the existing CCHP system configuration method has the following problems: (1) The system construction cost considered during the system configuration is not comprehensive, for example, the land cost and the grid-connected inverter equipment cost are not considered in the system configuration, and the construction operation cost is not comprehensive and cannot be close to the actual engineering application. (2) In the system optimization configuration, the built system is not fully combined with the actual engineering application, for example, a system model is built only under fixed data, the reliability of the system model is not verified, and the power supply reliability is poor. (3) The advantage of the accumulated investment cost of the system in the running period is not reflected in the initial stage of the system construction. Therefore, how to improve the power supply reliability of the CCHP system and reduce the construction and operation costs, and simultaneously reduce the environmental pollution is a problem to be solved in order to optimize the CCHP system.
Disclosure of Invention
Aiming at the problems of poor reliability, high running cost and the like in the conventional combined cooling heating power type micro-grid optimal configuration, the invention provides a multi-target optimal configuration method for the combined cooling heating power type micro-grid, which can improve the power supply reliability of a CCHP system, reduce the construction running cost and reduce the environmental pollution.
In order to achieve the above purpose, the invention provides a multi-objective optimal configuration method for a combined cooling heating power type micro-grid, which comprises the following steps:
constructing an energy supply equipment model and an energy flow chart of the CCHP system;
calculating the cost of each distributed power supply in the CCHP system for generating each kilowatt-hour of electric energy;
the cost of cold energy and heat energy generated by refrigerating and heating equipment in the CCHP system is calculated, and the cost is converted into the cost of electric energy per kilowatt hour;
determining a scheduling flow chart of energy supply equipment of the CCHP system according to the calculated cost of the electric energy;
targeting minimum capital investment for CCHP systems by solving an objective function C total Constructing a CCHP system configuration model by the minimum value on the premise of meeting constraint conditions and evaluation indexes, wherein the objective function C total Expressed as:
C total ＝C fi +C gas +C ma +C in +C e +C su (1)
wherein C is fi Representing equipment purchase cost, C gas Indicating fuel consumption cost, C ma Representing equipment maintenance cost, C in Indicating equipment installation cost, C e Representing environmental cost, C su Representing CCHP system revenue costs;
objective function C by solving CCHP system configuration model total And obtaining the optimal configuration of the CCHP system.
Preferably, the energy supply equipment model comprises a solar photovoltaic battery pack, a wind generating set, a gas turbine, a storage battery energy storage device, a direct-fired lithium bromide absorption type water chilling unit, a direct-fired lithium bromide absorption type warm water machine set, an energy storage device, an electric refrigerator and an electric boiler.
Preferably, the running cost, maintenance cost and power generation subsidy cost of each distributed power supply are calculated according to the historical meteorological conditions and the material price level of the region where the CCHP system is located, and then the cost of each distributed power supply for generating electric energy per kilowatt-hour is obtained.
Preferably, the equipment purchase cost C fi The method comprises the following steps:
where n is the total number of distributed power sources,
for the unit price of the ith device, +.>
The power output of the ith distributed power source; />
As a function of the number of i-th distributed power sources; />
The unit price of the ith grid-connected inverter equipment; />
Solving the number function of the ith grid-connected inverter equipment;
the fuel consumption cost C gas The method comprises the following steps:
wherein, T is the time point of equipment operation in the CCHP system;
is a gas turbinePower output quantity at the t-th moment of the machine; η (eta) MT Generating efficiency for the gas turbine; LHV is the heating value of natural gas, and the value is 9.7kW.h/m 3 ；Δt MT The gas turbine operation time is the gas turbine operation time; />
The method comprises the steps that cold energy generated by natural gas is consumed by a lithium bromide water chilling unit at a time t; />
The heat energy generated by natural gas is consumed by a lithium bromide hot water unit at the time t; η (eta) BT_cool The efficiency of generating cold energy for the consumption of natural gas at the time t of the lithium bromide water chilling unit; η (eta) BT_hot The efficiency of generating heat energy for consuming natural gas at the time t of the lithium bromide water heater unit; Δt (delta t) BT_gas_cool The working time for generating cold energy for consuming natural gas for the lithium bromide water chiller; Δt (delta t) BT_gas_hot The working time for generating heat energy for consuming natural gas by the lithium bromide hot water unit; />
Is the unit price of natural gas at time t;
the equipment maintenance cost C ma The method comprises the following steps:
in the method, in the process of the invention,
generating operation maintenance costs for the device per kilowatt-hour of electrical energy for the ith distributed power source; />
The output of the distributed power supply at the t moment is the output of the distributed power supply; Δt is the run time of the distributed power supply; />
Determination for ith deviceThe maintenance cost is reduced;
the equipment installation cost C in The method comprises the following steps:
in the method, in the process of the invention,
the installation cost for each of the ith distributed power supply; />
The floor space required by the ith distributed power supply; c (C) land The circulation price of the land under the unit area is set;
the environmental cost C e The method comprises the following steps:
wherein M is the number of species that produce contaminants in the CCHP system; alpha j A unit treatment cost for treating the jth polluted gas in accordance with international standards; beta ij Generating a scaling factor for the j-th pollutant gas per unit output power for the i-th plant; p (P) i (t) is the force output of the ith device at t; q is the kind of harmful gas which can be purified in the occupied land; l is the total cost type of the occupied land purified air; l is the cost type of the occupied land purified air; alpha lq The cost of purifying q gases for the land occupied by the CCHP system; alpha q Purifying the proportionality coefficient of q gases for the land occupied by the CCHP system;
the CCHP system benefit cost C su The method comprises the following steps:
wherein K is the number of types of new energy power generation patches;
the output of the distributed power supply at the ith moment; c (C) k The price of the power generation subsidy for the kth new energy; />
The electricity quantity purchased from the power grid at the moment t; />
The price of electricity purchasing to the power grid at the moment t; />
The electricity quantity is the electricity quantity for selling electricity to the power grid at the moment t; />
And selling electricity price to the power grid at the moment t.
Preferably, the objective function C total The constraint conditions met include an energy balance constraint condition, an energy supply unit output constraint condition and an energy storage unit energy storage constraint condition, wherein:
the energy balance constraint is expressed as:
in the method, in the process of the invention,
the electric quantity output in unit time of the ith distributed power supply is used as the electric quantity output in unit time of the ith distributed power supply; />
The demand for electrical load at time t in the system; />
The cooling energy output in unit time of the ith cooling energy output device; />
The demand for the cooling load at time t in the system; />
The heat energy output in the unit time of the ith heat energy output equipment;
the demand for the thermal load of the system at time t;
the energy supply unit output constraint condition is expressed as:
in the method, in the process of the invention,
lower limit of the output force for the ith electric energy output device,/->
Upper limit of the output force for the ith electric energy output device,/-for the electric energy output device>
For the lower limit of the output force of the ith cold energy output unit,/->
For the upper limit of the output force of the ith cold energy output unit,/->
Lower limit of the output force for the ith heat energy output unit,/->
An upper limit for the output of the ith thermal energy output unit;
the energy storage constraint condition of the energy storage unit is expressed as:
(1-DOD)Q R ≤Q BAT (t)≤Q BAT_max (t) (14)
0≤Q cool (t)≤Q cool_max (15)
0≤Q hot (t)≤Q hot_max (16)
in which Q BAT_max (t) is the rated capacity of the storage battery system at the moment t; q (Q) BAT (t) is the capacity of the storage battery system at the moment t; q (Q) R Is the rated capacity of the battery system; DOD (%) is the maximum allowable depth of discharge of the battery pack; q (Q) cool_max Rated cold storage capacity for the cold storage tank; q (Q) cool (t) is the cold storage capacity of the cold storage tank at the t moment; q (Q) hot_max Rated heat storage capacity of the heat storage tank; q (Q) hot And (t) is the heat storage quantity of the heat storage tank at the t moment.
Preferably, the evaluation index includes a reliability evaluation index, an economical efficiency evaluation index and an environmental protection evaluation index, wherein:
the objective function of the reliability evaluation index is expressed as:
η sys ＝η eq η gird η power (17)
wherein eta is sys Stability for CCHP system; η (eta) eq For device stability in CCHP systems, high reliability devices are selected during system configuration and spare devices are added to enable eta eq Hundred percent; η (eta) gird Adding C when configuring CCHP system for load node stability fi The selective output electric energy has high quality and stable operation, and meanwhile, emergency equipment is additionally arranged, so that eta gird Hundred percent; η (eta) power The energy supply and demand reliability in the CCHP system is realized; n is the CCHP system planning construction period;
the power output by the CCHP system according to the load at the moment t; />
Total load for the CCHP system of year i;
the economic evaluation index is expressed as the accumulated investment cost of the CCHP system:
wherein Y is the service life of the CCHP system;
benefit cost for the ith CCHP system, < +.>
For the fuel consumption of the ith CCHP system, < > for the year i->
Maintenance costs for the ith CCHP system equipment, < >>
For the cost of the CCHP system environment in the i th year,>
the electric energy cost of the power grid is purchased for the ith CCHP system;
the environmental protection evaluation index refers to the emission reduction rate eta of the polluted gas after the CCHP system replaces the traditional functional system and after the SP system e Expressed as:
wherein P is sys Is the total load of the CCHP system.
Preferably, the objective function C is optimized by adopting a modified particle swarm optimization algorithm total Solving, and in the improved particle swarm optimization algorithm, the population particle speed and position updating formula is as follows:
in the method, in the process of the invention,
is the population particle speed at the k+1th iteration; omega is the inertia weight coefficient, +.>
The particle velocity of the population at the kth iteration; c 1 The acceleration constant is an individual extremum; r is (r) 1 Is [0,1]Random numbers transformed in range; />
Is the individual extremum at the kth iteration; />
The search area position at the kth iteration; c 2 Adding to population extremumA speed constant; r is (r) 2 Is [0,1]Random numbers transformed in range; />
Is the population extremum at the kth iteration; />
Search region position at the k+1st iteration;
the inertia weight coefficient ω satisfies a condition that decreases with an increase in the number of iterations, the inertia weight coefficient ω satisfying the above condition is determined by the formula (23), and the formula (23) is expressed as:
ω(k)＝ω star +(ω star -ω end )(2k/T max -(k/T max ) 2 ) (23)
wherein ω (k) is a weight coefficient at the kth iteration; k is the current iteration number; omega star Is an initial inertial weight; omega end Inertial weights for iterating to a maximum number of times; t (T) max Is the maximum point in time for the operation of the devices in the CCHP system.
Compared with the prior art, the invention has the advantages and positive effects that:
the invention converts cold energy and heat energy into electric energy to schedule by constructing energy supply equipment and an energy flow chart of the CCHP system, analyzes the energy cost of each kilowatt-hour generated by various equipment in different time periods from the angles of the running cost and the maintenance cost of the equipment, and determines a scheduling flow chart of the energy output by each equipment in the CCHP system according to the size relation of the energy cost; constructing an objective function configured by the CCHP system, solving constraint conditions of the function, and determining an evaluation index for solving an objective function value of the system; the best configuration scheme is found by improving the PSO algorithm under the condition that the evaluation index is met. The CCHP system configuration scheme obtained by the configuration method provided by the invention has the advantages that the power supply reliability of the CCHP system reaches more than 99%, the investment in the service period of the CCHP system is small, the pollution to the environment is also minimum, and the cost of the CCHP system in the operation period is effectively reduced.
Drawings
FIG. 1 is an energy flow diagram of a CCHP system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the cost per kilowatt-hour of power generated by a distributed power source according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of the cost per kilowatt-hour of electric energy generated by the cooling and heating device according to an embodiment of the present invention;
FIG. 4 is a flow chart of energy scheduling for an energy supply device according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of typical solar, cold and heat load demands under different load structures according to an embodiment of the present invention;
FIG. 6 is a graph of typical solar power generation of fans and photovoltaic in different load structure time periods according to an embodiment of the invention;
FIG. 7 is a schematic diagram of a CCHP system configuration model constructed in accordance with an embodiment of the present invention;
FIG. 8 is a statistical graph of daily missing load data according to an embodiment of the present invention;
FIG. 9 is a diagram of the reliability of the system and the amount of load loss according to the embodiment of the present invention;
FIG. 10 is a schematic diagram of accumulated usage costs during usage time of the CCHP system, the SP system, and the conventional energy supply system according to an embodiment of the present invention;
FIG. 11 is an environmental cost schematic diagram of different energy consumption devices of each system in different energy supply modes according to an embodiment of the present invention.
Detailed Description
The present invention will be specifically described below by way of exemplary embodiments. It is to be understood that elements, structures, and features of one embodiment may be beneficially incorporated in other embodiments without further recitation.
The embodiment of the invention provides a multi-objective optimal configuration method for a combined cooling heating power type micro-grid, which comprises the following steps:
s1, constructing an energy supply equipment model of the CCHP system and an energy flow chart of the energy supply equipment model. The energy supply equipment model comprises a solar photovoltaic battery pack, a wind generating set, a gas turbine, a storage battery energy storage device, a direct-fired lithium bromide absorption type water chilling unit, a direct-fired lithium bromide absorption type warm water unit, an energy storage device, an electric refrigerator and an electric boiler; the energy flow diagram of the CCHP system is shown in fig. 1.
S2, calculating the cost of each distributed power supply in the CCHP system for generating each kilowatt-hour of electric energy.
In this embodiment, the CCHP system operates in a grid-tie mode or island mode, and the gas turbine power generation system uses natural gas as fuel, and the generated electrical energy is used for the supply of electrical energy in the system. The running cost, maintenance cost and power generation subsidy cost of each distributed power supply are calculated according to the historical meteorological conditions and the price level of the CCHP system in the region, and then the cost of each distributed power supply for generating electric energy per kilowatt-hour is obtained (see fig. 2).
Specifically, the calculation formula of the power generation cost of the photovoltaic cell per kilowatt-hour is as follows:
wherein C is PV Generating cost for each kilowatt-hour of photovoltaic cells; p (P) PV Annual energy production for a single photovoltaic cell; c (C) buy_PV Purchase cost for a single photovoltaic cell; c (C) land_PV The land use cost is reduced for a single photovoltaic cell every year; c (C) ma_PV The maintenance cost of each year for a single photovoltaic cell; c (C) in_PV The installation cost of folding a single photovoltaic cell; c (C) be_PV And subsidy for photovoltaic power generation per kilowatt hour.
The calculation formula of the power generation cost of the wind driven generator per kilowatt hour is as follows:
wherein C is WT The power generation cost of the wind driven generator is per kilowatt hour; p (P) WT Annual energy production of a single wind power generator; c (C) buy_WT The electric purchase cost of a single wind power generator is realized; c (C) land_WT The land use cost is reduced for a single wind power generator each year; c (C) ma_WT The maintenance cost is reduced for a single wind power generator every year; c (C) in_WT The installation cost is reduced for a single wind power generator; cbe_WT is the power generation patch of the wind driven generator per kilowatt hour.
The power generation cost of the gas turbine per kilowatt-hour is calculated as follows:
wherein C is MT The power generation cost of the gas turbine per kilowatt hour; p (P) MT Generating power for consuming 1 cubic meter of natural gas for the gas turbine; c (C) gas Price per cubic meter of natural gas; c (C) ma_MT Maintenance costs per kilowatt-hour of electrical energy are generated for the gas turbine.
The price of the electric energy is determined according to the price of the electric energy in the region where the CCHP system is located.
S3, calculating the cost of cold energy and heat energy generated by the refrigerating and heating equipment in the CCHP system (see FIG. 3), and converting the cost into the cost of electric energy per kilowatt-hour.
S4, determining the dispatching flow chart of the energy supply equipment energy of the CCHP system according to the calculated cost of the electric energy (see FIG. 4). Since the CCHP system distinguishes between peak and valley functional time periods, the device with the smallest processing cost is preferentially selected at a specific time according to the device output costs calculated in fig. 2 and 3.
S5, taking the minimum investment funds of the CCHP system as a target, and solving an objective function C total Constructing a CCHP system configuration model by the minimum value on the premise of meeting constraint conditions and evaluation indexes, wherein the objective function C total Expressed as:
C total ＝C fi +C gas +C ma +C in +C e +C su (1)
wherein C is fi Representing equipment purchase cost, C gas Indicating fuel consumption cost, C ma Representing equipment maintenance cost, C in Indicating equipment installation cost, C e Representing environmental cost, C su Representing CCHP system revenue costs.
Specifically, the device purchase cost C fi The method comprises the following steps:
where n is the total number of distributed power sources,
for the unit price of the ith device, +.>
The power output of the ith distributed power source; />
As a function of the number of i-th distributed power sources; />
The unit price of the ith grid-connected inverter equipment;
the method is used for solving the number function of the ith grid-connected inverter equipment.
The fuel consumption cost C gas The method comprises the following steps:
wherein, T is the time point of equipment operation in the CCHP system;
the power output quantity is the t moment of the gas turbine; η (eta) MT Generating efficiency for the gas turbine; LHV is the heating value of natural gas, and the value is 9.7kW.h/m 3 ；Δt MT The gas turbine operation time is the gas turbine operation time; />
The method comprises the steps that cold energy generated by natural gas is consumed by a lithium bromide water chilling unit at a time t; />
The heat energy generated by natural gas is consumed by a lithium bromide hot water unit at the time t; η (eta) BT_cool The efficiency of generating cold energy for the consumption of natural gas by the lithium bromide water chiller; η (eta) BT_hot The efficiency of generating heat energy for consuming natural gas by the lithium bromide hot water unit; Δt (delta t) BT_gas_cool The working time for generating cold energy for consuming natural gas for the lithium bromide water chiller; Δt (delta t) BT_gas_hot The working time for generating heat energy for consuming natural gas by the lithium bromide hot water unit; />
Is the unit price of natural gas at time t.
The equipment maintenance cost C ma The method comprises the following steps:
in the method, in the process of the invention,
generating operation maintenance costs for the device per kilowatt-hour of electrical energy for the ith distributed power source; />
The output of the distributed power supply at the t moment is the output of the distributed power supply; Δt is the run time of the distributed power supply; />
Is the periodic maintenance cost of the ith equipment.
The equipment installation cost C in The method comprises the following steps:
in the method, in the process of the invention,
the installation cost for each of the ith distributed power supply; />
The required floor space for the ith distributed power source; c (C) land The circulation price of the land under the unit area is set;
the environmental cost C e The method comprises the following steps:
wherein M is the type of contaminant generated in the CCHP system; alpha j A unit treatment cost for treating the jth polluted gas in accordance with international standards; beta ij Generating a scaling factor for the j-th pollutant gas per unit output power for the i-th plant; p (P) i (t) is the force output of the ith device at t; q is the kind of harmful gas which can be purified in the occupied land; l is the total cost type of the occupied land purified air; l is the cost type of the occupied land purified air; alpha lq The cost of purifying q gases for the land occupied by the CCHP system; alpha q The scaling factor of q gases is purified for the land occupied by the CCHP system.
The CCHP system benefit cost C su The method comprises the following steps:
wherein K is the number of types of new energy power generation patches;
the output of the distributed power supply at the ith moment; c (C) k The price of the power generation subsidy for the kth new energy; />
Is t time directionThe electric quantity of electricity purchased by the power grid; />
The price of electricity purchasing to the power grid at the moment t; />
The electricity quantity is the electricity quantity for selling electricity to the power grid at the moment t; />
And selling electricity price to the power grid at the moment t.
The constraint condition in the CCHP system is to make the whole CCHP system possess higher operation reliability, economy and environmental protection, and according to the IEEE Std 1366-2003 standard and the china DLT836-2012 power supply reliability index standard of the power distribution network, the reliability standard of the power distribution network is divided into three layers. The whole CCHP system must satisfy the total energy balance of electric energy demand balance, cold energy demand balance and heat energy demand balance in the operation process, the CCHP system distributes the total energy demand to each energy output unit, and the output units in the CCHP system also satisfy respective output constraint. The storage battery system and the whole energy storage system play a role in peak clipping and valley filling in the energy dispatching process in the whole process.
Specifically, the objective function C total The constraint conditions met include an energy balance constraint condition, an energy supply unit output constraint condition and an energy storage unit energy storage constraint condition.
The energy supply of the whole CCHP system needs to meet the load demand of the CCHP system at any moment so as to ensure the stable operation of the whole CCHP system. Thus, the energy balance constraint is expressed as:
in the method, in the process of the invention,
the electric quantity output in unit time of the ith distributed power supply is used as the electric quantity output in unit time of the ith distributed power supply; />
The demand for electrical load at time t in the system; />
The cooling energy output in unit time of the ith cooling energy output device; />
The demand for the cooling load at time t in the system; />
The heat energy output in the unit time of the ith heat energy output equipment;
is the demand for the thermal load of the system at time t.
The stability of the CCHP system is mainly ensured by cold energy, heat energy and electric energy output by the energy output units, and the energy output of the energy output units in the system has own range. Determining the output constraint of each energy output unit is critical to solving the number of each output unit in the model. In order to achieve the energy supply unit output constraint, the energy supply unit output constraint condition is expressed as:
in the method, in the process of the invention,
lower limit of the output force for the ith electric energy output device,/->
Upper limit of the output force for the ith electric energy output device,/-for the electric energy output device>
For the lower limit of the output force of the ith cold energy output unit,/->
For the upper limit of the output force of the ith cold energy output unit,/->
Lower limit of the output force for the ith heat energy output unit,/->
An upper limit for the output of the ith thermal energy output unit.
The energy storage unit in the CCHP system can meet the energy storage constraint condition of the energy storage unit at any time, and the energy storage constraint condition of the energy storage unit is expressed as:
(1-DOD)Q R ≤Q BAT (t)≤Q BAT_max (t) (14)
0≤Q cool (t)≤Q cool_max (15)
0≤Q hot (t)≤Q hot_max (16)
in the method, in the process of the invention,Q BAT_max (t) is the rated capacity of the storage battery system at the moment t; q (Q) BAT (t) is the capacity of the storage battery system at the moment t; q (Q) R Is the rated capacity of the battery system; DOD (%) is the maximum allowable depth of discharge of the battery pack; q (Q) cool_max Rated cold storage capacity for the cold storage tank; q (Q) cool (t) is the cold storage capacity of the cold storage tank at the t moment; q (Q) hot_max Rated heat storage capacity of the heat storage tank; q (Q) hot And (t) is the heat storage quantity of the heat storage tank at the t moment.
Specifically, the evaluation indexes include reliability evaluation indexes, economical efficiency evaluation indexes and environmental protection evaluation indexes, wherein:
the objective function of the reliability evaluation index is expressed as:
η sys ＝η eq η gird η power (17)
wherein eta is sys Stability for CCHP system; η (eta) eq For device stability in CCHP systems, high reliability devices are selected during system configuration and spare devices are added to enable eta eq Hundred percent; η (eta) gird Adding C when configuring CCHP system for load node stability fi The selective output electric energy has high quality and stable operation, and meanwhile, emergency equipment is additionally arranged, so that eta gird Hundred percent; η (eta) power The energy supply and demand reliability in the CCHP system is realized; n is the CCHP system planning construction period;
the power output by the CCHP system according to the load at the moment t; />
Total load for the CCHP system of the i-th year.
Compared with an SP system, the CCHP system has the advantages that: most of heat energy and cold energy are obtained by recycling the flue gas of the gas turbine, so that the running cost of the whole system is reduced, and the China government has a certain limit patch and an electric energy recycling policy for solar energy and wind energy power generation, so that the whole CCHP system is a system capable of gradually recycling the cost. The economic evaluation index is expressed as the accumulated investment cost of the CCHP system:
wherein Y is the service life of the CCHP system;
benefit cost for the ith CCHP system, < +.>
For the fuel consumption of the ith CCHP system, < > for the year i->
Maintenance costs for the ith CCHP system equipment, < >>
For the cost of the CCHP system environment in the i th year,>
and purchasing the electric energy cost of the electric network for the ith CCHP system.
The main output units in the micro-grid of the CCHP system are photovoltaic battery packs, wind generating sets and gas turbine generating units, and the power interaction unit of the grid is used as an auxiliary unit for energy output. The electric energy in China is 60% generated by a thermal generator using coal as fuel. The coal burns and generates a large amount of NO x 、SO x 、CO x Etc., and thus the energy usage behind it when using grid electricity is also equivalent to the additional cost of operating the CCHP system when discharging these contaminants, with reference to the capital costs of currently handling these contaminants. The environmental protection evaluation index refers to the CCHP system after replacing the traditional functional system and the SP systemReduction rate eta of exhaust of unified polluted gas e Expressed as:
wherein P is sys Is the total load of the CCHP system.
S6, solving an objective function C of the CCHP system configuration model total And obtaining the optimal configuration of the CCHP system.
Particle Swarm Optimization (PSO) algorithm is commonly used for solving an objective function because of the advantages of random global search, fast convergence, high efficiency and the like. But at the same time its drawbacks are also evident, for example: in the optimizing process, the situation that the particles miss the global optimal solution in the diving process exists. When applying the PSO algorithm to deal with multi-dimensional complexity problems, the algorithm may sink into the locally optimal solution, known as premature convergence.
Specifically, in order to avoid the occurrence of the above problem in solving the objective function, in the embodiment of the present invention, an improved particle swarm optimization algorithm is used for the objective function C total Solving, and in the improved particle swarm optimization algorithm, the population particle speed and position updating formula is as follows:
in the method, in the process of the invention,
is the population particle speed at the k+1th iteration; omega is the inertia weight coefficient, +.>
The particle velocity of the population at the kth iteration; c 1 The acceleration constant is an individual extremum; r is (r) 1 Is [0,1]Random numbers transformed in range; />
Is the individual extremum at the kth iteration; />
The search area position at the kth iteration; c 2 Acceleration constants are population extremum; r is (r) 2 Is [0,1]Random numbers transformed in range; />
Is the population extremum at the kth iteration; />
Is the search area location at the k+1st iteration.
The inertia weight coefficient ω satisfies a condition that decreases with an increase in the number of iterations, the inertia weight coefficient ω satisfying the above condition is determined by the formula (23), and the formula (23) is expressed as:
ω(k)＝ω star +(ω star -ω end )(2k/T max -(k/T max ) 2 ) (23)
wherein ω (k) is a weight coefficient at the kth iteration; k is the current iteration number; omega star Is an initial inertial weight; omega end Inertial weights for iterating to a maximum number of times; t (T) max Is the maximum point in time for the operation of the devices in the CCHP system.
According to the method, when the optimal configuration of the CCHP system is carried out, three targets of economy, reliability and environment in the CCHP system are all converted into the same system investment target, the economy objective function is expressed as fixed cost investment, system operation and investment of the system, the reliability target of the system is converted into the system investment to increase the quality stability of energy output equipment and the reliability of energy output, and the energy supply is ensured to reach more than 99% under the load demand; the environmental objectives of the system are expressed as the pollutant remediation costs incurred by the system itself,and after the system obtains the electric energy through the electric network, because 60% of the electric energy of the electric network is generated by the traditional thermal power generation, the environmental cost converted in the system when the electric energy of the electric network is used is expressed as NO generated by the thermal power plant for producing electric energy per kilowatt-hour x 、SO x 、CO x And (5) pollutant treatment cost. The CCHP system after the optimal configuration has small investment in the service period and minimal environmental pollution, and effectively reduces the cost of the CCHP system in the operation period.
In order to illustrate the effectiveness of the above method, the above method is further described below in connection with specific examples.
The CCHP system energy supply/demand was analyzed.
(1) Load analysis
Taking the 2016 year load requirement of an industrial park as an example, the total area of the industrial park is 2.05 x 10 5 m 2 The average annual average electric load amount per hour is about 350KWh, the load demand amount per hour in the heating season (11.16-3.31) is about 115KWh according to the conversion into electric energy amount, the load demand amount per hour in the cooling season (5.15-9.15) is about 218KWh according to the conversion into electric energy amount, the energy supply of the whole system is divided into the electric load used in the heating season, the cooling season and the excessive season (seasons which are neither heated nor cooled), the heat load in the heating season, the cooling load in the cooling season and various loads are shown in figure 5. The different loads are distinguished, so that the optimization in configuration is facilitated, and unreasonable equipment capacity planning is avoided.
(2) Analysis of solar power generation and wind power generation output
The system construction site is selected in a certain region of a smoke desk, the photoelectric conversion efficiency of the region is calculated to be 16.15% and 26.5% according to meteorological data such as wind speed, temperature and the like with hour as a scale in a local year through a solar photovoltaic cell and wind driven generator power output mathematical model, and the energy output of a solar photovoltaic cell group and the wind driven generator set of the whole system is distinguished according to the intervals of different load structures, as shown in fig. 6.
Obtaining CCHP meeting constraint conditions according to objective function and constraint conditionsA system configuration model, see fig. 7, in which 4000000 points all meet constraint conditions of the system and allow the system to run reliably, but each point corresponds to a C total The costs involved in equation (1) are different from each other.
Solving an objective function of a CCHP system configuration model according to an improved particle swarm optimization algorithm, and calculating the cost of CCHP system construction to be 3.385 x 10 according to an evaluation index under the condition that constraint conditions are met 5 The capacity of each energy supply device is shown in table 1.
TABLE 1
| Energy output device name | Capacity per KW of installation |
| Solar power generating set | 1140.4 |
| Wind driven generator set | 980 |
| Gas turbine generator set | 325 |
| Direct-fired lithium bromide cold water (hot water) machine set | 260 |
| Electric refrigerator unit | 283 |
| Electric boiler unit | 268.7 |
| Storage battery pack | 1200 |
| |
2000 |
| Cold accumulation tank | 4500 |
And (3) evaluating the reliability of the CCHP system according to a formula (17) and a formula (18), counting the difference between the load cold-hot load demand data of the system and the energy provided by the system, evaluating the reliability of the system, and counting the load quantity missing every day in the CCHP system in the embodiment, and calculating the reliability of the system. Wind-light data and energy demand data of a system in 2017, 2018 and 2019 are input, the statistical system operation data are mined out to obtain the annual statistical load loss, and the daily load loss, various annual load loss and system reliability are calculated, and particularly, reference is made to fig. 8 and 9.
According to the economic evaluation index of the CCHP system, wind and light data and load data within twenty years of system construction and operation are estimated by taking an average value according to wind and light data of the place where the system is located in the last four years and load data of a park. Calculating the annual CCHP system from the formula (19)
Calculating the annual +.of SP system from equation (24)>
The conventional industrial park uses only electric energy to meet the load demand in the industrial park, so that the energy running cost thereof is calculated as the electric energy cost of use, and the conventional energy supply system +.>
Calculated from equation (25). Equation (24) and equation (25) are expressed as:
in the method, in the process of the invention,
cumulative investment cost for SP systems; c (C) SP_fi Purchase cost for SP system equipment; c (C) SP_in Installation cost for SP system equipment; />
Cost of revenue for the SP system of the ith year; />
Fuel consumption cost for SP system of the i-th year; />
Maintenance costs for the i-th SP system equipment; />
The cost of the SP system environment is the ith year; />
Purchasing the electric energy cost of the electric network for the SP system of the ith year; />
Cumulative investment costs for conventional energy supply systems; />
Environmental cost for the traditional energy supply system of the ith year; />
And purchasing the electric energy cost of the electric network for the traditional energy supply system in the ith year.
As shown in FIG. 10, the image shows that the CCHP has the highest construction cost, the SP system is inferior and the traditional energy supply system is the lowest, but from the long-term development of the system, the accumulated investment in the service time is gradually reduced along with the increase of the service time because the CCHP system and the SP system have benefits, the accumulated investment cost of the CCHP system after the optimal configuration in the embodiment is lower than that of the traditional energy supply system from 13 th year of the service time of the system, and the total investment of the system only accounts for 50% of the traditional energy supply system in 20 years of planned use. Compared with an SP system, the CCHP system after optimal configuration of the embodiment has the advantages that the cost is larger due to the fact that related equipment such as energy secondary utilization is added, but most of heat energy and cold energy are obtained through recycling of tail gas of a gas turbine, so that the system operation cost is lower, the total investment cost of the CCHP system after optimal configuration of the embodiment is lower than that of the SP system when the system investment is used for the eleventh year, and the CCHP system has the most obvious economic advantage.
According to the formula (6), the annual environmental cost generated by the system when the industrial park meets the annual load supply of the whole industrial park under the SP system, the traditional electric energy supply and the CCHP system after the optimal configuration of the embodiment is 102606.98 yuan, 148979.6 yuan and 584923 yuan respectively. In fig. 11, detailed data of environmental costs generated by each system of the industrial park each year under three energy supply modes are shown, and the environmental costs generated by the CCHP system are mainly divided into environmental costs generated by equipment consuming electric energy of the power grid and environmental costs generated by equipment consuming natural gas according to the energy scheduling flow chart of fig. 4. The SP system and the traditional electric energy supply system calculate corresponding environmental cost generated by equipment consuming electric energy of a power grid and environmental cost generated by equipment consuming natural gas according to the demand of the cold and hot electric loads. The environmental protection index of the CCHP system after the optimal configuration of the embodiment is about 31.26% relative to the SP system and 82.45% relative to the traditional power supply system, which is obtained by the formula (20), so that the CCHP after the optimal configuration of the embodiment has a great advantage in terms of environmental protection.
The above-described embodiments are intended to illustrate the present invention, not to limit it, and any modifications and variations made thereto are within the spirit of the invention and the scope of the appended claims.
Claims (6)
1. The multi-objective optimal configuration method for the combined cooling heating power type micro-grid is characterized by comprising the following steps of:
constructing an energy supply equipment model and an energy flow chart of the CCHP system;
calculating the cost of each distributed power supply in the CCHP system for generating each kilowatt-hour of electric energy;
the cost of cold energy and heat energy generated by refrigerating and heating equipment in the CCHP system is calculated, and the cost is converted into the cost of electric energy per kilowatt hour;
determining a scheduling flow chart of energy supply equipment of the CCHP system according to the calculated cost of the electric energy; targeting minimum capital investment for CCHP systems by solving an objective function C total Constructing a CCHP system configuration model by the minimum value on the premise of meeting constraint conditions and evaluation indexes, wherein the objective function C total Expressed as:
C total ＝C fi +C gas +C ma +C in +C e +C su (1)
wherein C is fi Representing equipment purchase cost, C gas Indicating fuel consumption cost, C ma Representing equipment maintenance cost, C in Indicating equipment installation cost, C e Representing environmental cost, C su Representing CCHP system revenue costs;
the equipment purchase cost C fi The method comprises the following steps:
where n is the total number of distributed power sources,
for the unit price of the ith device, +.>
The power output of the ith distributed power source; />
As a function of the number of i-th distributed power sources; />
The unit price of the ith grid-connected inverter equipment; />
Solving the number function of the ith grid-connected inverter equipment;
the fuel consumption cost C gas The method comprises the following steps:
wherein, T is the time point of equipment operation in the CCHP system;
the power output quantity is the t moment of the gas turbine; η (eta) MT Generating efficiency for the gas turbine; LHV is the heating value of natural gas, and the value is 9.7kW.h/m 3 ；Δt MT The gas turbine operation time is the gas turbine operation time; />
The method comprises the steps that cold energy generated by natural gas is consumed by a lithium bromide water chilling unit at a time t; />
The heat energy generated by natural gas is consumed by a lithium bromide hot water unit at the time t;η BT_cool the efficiency of generating cold energy for the consumption of natural gas by the lithium bromide water chiller; η (eta) BT_hot The efficiency of generating heat energy for consuming natural gas by the lithium bromide hot water unit; Δt (delta t) BT_gas_cool The working time for generating cold energy for consuming natural gas for the lithium bromide water chiller; Δt (delta t) BT_gas_hot The working time for generating heat energy for consuming natural gas by the lithium bromide hot water unit; />
Is the unit price of natural gas at time t;
the equipment maintenance cost C ma The method comprises the following steps:
in the method, in the process of the invention,
generating operation maintenance costs for the device per kilowatt-hour of electrical energy for the ith distributed power source; />
The output of the distributed power supply at the t moment is the output of the distributed power supply; Δt is the run time of the distributed power supply; />
Periodic maintenance costs for the ith equipment;
the equipment installation cost C in The method comprises the following steps:
in the method, in the process of the invention,
the installation cost for each of the ith distributed power supply; />
The floor space required by the ith distributed power supply; c (C) land The circulation price of the land under the unit area is set;
the environmental cost C e The method comprises the following steps:
wherein M is the number of species that produce contaminants in the CCHP system; alpha j A unit treatment cost for treating the jth polluted gas in accordance with international standards; beta ij Generating a scaling factor for the j-th pollutant gas per unit output power for the i-th plant; p (P) i (t) is the force output of the ith device at t; q is the kind of harmful gas which can be purified in the occupied land; l is the total cost type of the occupied land purified air; l is the cost type of the occupied land purified air; alpha lq The cost of purifying q gases for the land occupied by the CCHP system; alpha q Purifying the proportionality coefficient of q gases for the land occupied by the CCHP system;
the CCHP system benefit cost C su The method comprises the following steps:
wherein K is the number of types of new energy power generation patches;
the output of the distributed power supply at the ith moment; c (C) k The price of the power generation subsidy for the kth new energy; />
The electricity quantity purchased from the power grid at the moment t; />
The price of electricity purchasing to the power grid at the moment t;
the electricity quantity is the electricity quantity for selling electricity to the power grid at the moment t; />
Electricity price for selling electricity to the power grid at t moment;
objective function C by solving CCHP system configuration model total And obtaining the optimal configuration of the CCHP system.
2. The method for optimizing configuration of a combined cooling, heating and power type micro-grid according to claim 1, wherein the energy supply equipment model comprises a solar photovoltaic battery pack, a wind generating set, a gas turbine, a storage battery energy storage device, a direct-fired lithium bromide absorption type water chilling unit, a direct-fired lithium bromide absorption type warm water unit, an energy storage device, an electric refrigerator and an electric boiler.
3. The method for optimizing configuration of a cogeneration type micro grid according to claim 2, wherein the running cost, maintenance cost and power generation subsidy cost of each distributed power supply are calculated according to the historical meteorological conditions and the price level of the region where the CCHP system is located, so as to obtain the cost of each distributed power supply for generating electric energy per kilowatt hour.
4. The combined cooling heating power type micro grid multi-objective optimal configuration method as set forth in claim 1, wherein an objective function C total The constraint conditions met include an energy balance constraint condition, an energy supply unit output constraint condition and an energy storage unit energy storage constraint condition, wherein:
the energy balance constraint is expressed as:
in the method, in the process of the invention,
the electric quantity output in unit time of the ith distributed power supply is used as the electric quantity output in unit time of the ith distributed power supply; />
The demand for electrical load at time t in the CCHP system; />
The cooling energy output in unit time of the ith cooling energy output device; />
The demand for the cooling load at time t in the CCHP system; />
The heat energy output in the unit time of the ith heat energy output equipment; />
The demand for the thermal load of the system at time t;
the energy supply unit output constraint condition is expressed as:
in the method, in the process of the invention,
a lower limit for the output of the ith electrical energy output device; />
An upper limit for the output of the ith electrical energy output device; />
The lower limit of the output force of the ith cold energy output unit; />
The upper limit of the output force of the ith cold energy output unit; />
A lower limit for the output of the ith thermal energy output unit; />
An upper limit for the output of the ith thermal energy output unit;
the energy storage constraint condition of the energy storage unit is expressed as:
(1-DOD)Q R ≤Q BAT (t)≤Q BAT_max (t) (14)
0≤Q cool (t)≤Q cool_max (15)
0≤Q hot (t)≤Q hot_max (16)
in which Q BAT_max (t) is the time t of the storage battery systemRated capacity; q (Q) BAT (t) is the capacity of the storage battery system at the moment t; q (Q) R Is the rated capacity of the battery system; DOD (%) is the maximum allowable depth of discharge of the battery pack; q (Q) cool_max Rated cold storage capacity for the cold storage tank; q (Q) cool (t) is the cold storage capacity of the cold storage tank at the t moment; q (Q) hot_max Rated heat storage capacity of the heat storage tank; q (Q) hot And (t) is the heat storage quantity of the heat storage tank at the t moment.
5. The method for optimizing configuration of a combined cooling, heating and power micro grid according to claim 1, wherein the evaluation indexes comprise reliability evaluation indexes, economical evaluation indexes and environmental protection evaluation indexes, wherein:
the objective function of the reliability evaluation index is expressed as:
η sys ＝η eq η gird η power (17)
wherein eta is sys Stability for CCHP system; η (eta) eq For device stability in CCHP systems, high reliability devices are selected during system configuration and spare devices are added to enable eta eq Hundred percent; η (eta) gird Adding C when configuring CCHP system for load node stability fi The selective output electric energy has high quality and stable operation, and meanwhile, emergency equipment is additionally arranged, so that eta gird Hundred percent; η (eta) power The energy supply and demand reliability in the CCHP system is realized; n is the CCHP system planning construction period;
the power output by the CCHP system according to the load at the moment t; />
Total load for the CCHP system of year i;
the economic evaluation index is expressed as the accumulated investment cost of the CCHP system:
wherein Y is the service life of the CCHP system;
benefit cost for the ith CCHP system, < +.>
For the fuel consumption of the ith CCHP system, < > for the year i->
Maintenance costs for the ith CCHP system equipment, < >>
For the cost of the CCHP system environment in the i th year,>
the electric energy cost of the power grid is purchased for the ith CCHP system; />
The environmental protection evaluation index refers to the emission reduction rate eta of the polluted gas after the CCHP system replaces the traditional electric energy supply system and the SP system e Expressed as:
wherein P is sys Is the total load of the CCHP system.
6. The method for optimizing and configuring a plurality of targets of a combined cooling, heating and power micro grid according to claim 1, wherein an improved particle swarm optimization algorithm is adopted for the target function C total Improved particle swarm optimization by solvingIn the chemosynthesis algorithm, the population particle speed and position updating formula is as follows:
in the method, in the process of the invention,
is the population particle speed at the k+1th iteration; omega is the inertia weight coefficient, +.>
The particle velocity of the population at the kth iteration; c 1 The acceleration constant is an individual extremum; r is (r) 1 Is [0,1]Random numbers transformed in range; />
Is the individual extremum at the kth iteration; />
The search area position at the kth iteration; c 2 Acceleration constants are population extremum; r is (r) 2 Is [0,1]Random numbers transformed in range; />
Is the population extremum at the kth iteration; />
Search region position at the k+1st iteration;
the inertia weight coefficient ω satisfies a condition that decreases with an increase in the number of iterations, the inertia weight coefficient ω satisfying the above condition is determined by the formula (23), and the formula (23) is expressed as:
ω(k)＝ω star +(ω star -ω end )(2k/T max -(k/T max ) 2 ) (23)
wherein ω (k) is a weight coefficient at the kth iteration; k is the current iteration number; omega star Is an initial inertial weight; omega end Inertial weights for iterating to a maximum number of times; t (T) max Is the maximum point in time for the operation of the devices in the CCHP system.
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| CN112713590B (en) * | 2020-12-22 | 2022-11-08 | 南昌大学 | Combined optimization scheduling method for combined cooling, heating and power supply microgrid and active power distribution network considering IDR (Integrated data Rate) |
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