CN112329260A - Multi-energy complementary micro-grid multi-element multi-target optimization configuration and optimization operation method - Google Patents
Multi-energy complementary micro-grid multi-element multi-target optimization configuration and optimization operation method Download PDFInfo
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Abstract
The invention discloses a multi-energy complementary micro-grid multi-element multi-target optimization configuration and optimization operation method. The invention relates to the technical field of multi-energy complementary micro-grid multi-element multi-objective optimization, and designs a micro-grid structure meeting energy supply requirements and establishes a model based on multi-element load requirements of a system. Firstly, planning and configuring the microgrid system, and determining the capacity of each distributed unit, so that the optimized operation has practical significance and is convenient for subsequent optimized operation. The planning configuration is configured with the lowest initial installation investment cost and the operation and maintenance cost of the equipment as the targets, and the optimal configuration result, namely the capacity of the equipment, is obtained. The capacity of the equipment influences the constraint condition of the optimized operation, so that the optimized operation can be performed after the planning and configuration of the microgrid system. The optimized operation is optimized by taking the lowest daily operation cost and the lowest environmental cost as targets to obtain an optimal daily operation scheme, namely the output power of each unit.
Description
Technical Field
The invention relates to the technical field of multi-energy complementary micro-grid multi-element multi-objective optimization, in particular to a multi-energy complementary micro-grid multi-element multi-objective optimization configuration and optimization operation method.
Background
The construction of the multi-energy complementary integration optimization demonstration project is one of important tasks of constructing an 'internet plus' intelligent energy system, is beneficial to improving the energy supply and demand coordination capacity, promoting the clean production and nearby consumption of energy, reducing the wind and light abandonment and water abandonment and electricity limitation, promoting the consumption of renewable energy, is an important hand grip for improving the comprehensive efficiency of the energy system, and has important practical significance and far-reaching strategic significance for the construction of a clean low-carbon, safe and efficient modern energy system.
The multi-energy complementary energy supply microgrid system has the advantages that the selectable system form, the main and auxiliary devices and the selectable range of the capacity of the system are large, no universally applicable technical scheme exists, the configuration of the system is closely related to the climate characteristics, load requirements, energy price and supply conditions and the like of the region where the user is located, and high requirements are provided for the configuration determination work of the system. For the optimal configuration of the multi-energy complementary energy supply microgrid system, the main task is to reasonably determine the structure and the form of the system before project implementation, optimally select the types, the capacities and the number of main equipment, obtain comprehensive performances of heat power, economy, environment and the like all the year around, provide decision reference for owners, provide model selection basis for design and provide guidance for operation strategy formulation. Improper configuration of a multi-energy complementary energy supply microgrid system can cause the problems of waste of equipment investment, incapability of fully exerting economic benefits, low system operation efficiency and the like of the system, even the system can not operate under extreme conditions, optimal operation of the microgrid can be influenced, and the economy of the microgrid can not be realized.
Disclosure of Invention
The method is used for scientifically configuring and planning the microgrid system by considering the load rate of the cooling, heating and power loads based on the multi-element load demand. The system operation optimization model is further solved by using a multi-objective particle swarm algorithm, the lowest multi-energy complementary microgrid operation cost and the lowest environmental pollution cost are realized, and the following technical scheme is provided:
a multi-energy complementary microgrid multi-element multi-target optimization configuration and optimization operation method comprises the following steps:
step 1: according to the multi-energy complementary microgrid, determining the annual operating efficiency index of the microgrid as the load rate of the cooling, heating and power loads, and expressing the load rate by the following formula:
among them, LRe、LRhAnd LRcRespectively representing the load rates of the electric heating and cooling of the system; pe(t)、Ph(t) and Pc(t) respectively representing the electric heat and cold power capacity of the system; peload(t)、Phload(t) and Pcload(t) respectively representing the power demand of the electric heating load at the moment t;
step 2: establishing a micro-grid structure meeting the energy supply requirement and establishing a system model based on the multi-element load requirement;
and step 3: planning and configuring a system model, optimizing the system, and determining daily operation energy consumption and environmental cost;
and 4, step 4: and according to the annual cost of different configurations, giving the optimized configuration to perform the optimized operation to obtain the optimal daily operation scheme.
Preferably, when the microgrid system is configured, the load rate of the cooling, heating and power loads is added in the configuration process as an efficiency index, and the total annual cost is taken as a configuration optimization target;
the total annual cost of the microgrid comprises two aspects: initial installation investment costs and operational maintenance costs of the equipment, the optimization objective F is represented by the following equation:
wherein N is the type number of units in the microgrid system, and NiThe number of the ith unit; cCPiAnd COMiIndividual equipment costs and annual fixed maintenance costs, m, for the different unitsiThe service life of the ith unit is r, and the bank interest rate is r.
Preferably, when the optimal planning configuration is solved, the equipment configuration schemes are listed and optimized respectively, and finally, the optimal configuration is given by analyzing annual cost of different configurations, so that the purpose of solving is achieved;
in the actual operation process, the power flow and the output distribution of each unit need to be optimized, the economic optimum is usually taken as an optimization target, the environmental protection property is considered, the environmental pollution cost is added, and the economic and environmental dual targets are considered.
Preferably, the microgrid operating cost target comprises three aspects: the natural gas cost, the maintenance cost of each micro source and the cost generated by the micro grid for purchasing and selling electricity from the large power grid are represented by the following formula:
wherein, FcTotal cost for 24 hours of system operation; n is the number of micro sources: cgasIs the natural gas price; piIs the power of the micro source i; ciThe maintenance unit cost of the micro source i; cpThe price for purchasing electricity from the large power grid; csFor selling electricity to a large power grid: pgridThe power is the interactive power of the micro-grid and the large grid, the electricity purchasing is positive, and the electricity selling is negative;
the method is characterized by comprising the following steps of (1) aiming at the cost of environmental pollution, wherein micro sources for generating pollution gas in a micro grid are mainly a micro gas turbine and a large power grid, the treatment cost of the pollution gas generated by the micro grid is optimized as the minimum target, and the treatment cost is expressed by the following formula:
wherein, FeThe total treatment cost of the pollution gas is generated for 24 hours of system operation; k represents the type of the pollution gas; wMT,kThe emission coefficient of the micro gas turbine producing the polluted gas k is represented as follows: wgrid,kRepresenting the emission coefficient of the pollution gas k generated by the large power grid; pgrid,kRepresents the power purchased from the large power grid (0 at the time of power sale); ckRepresents the unit abatement cost of the pollutant gas k.
Preferably, in the mode of 'fixing heat by electricity', the photovoltaic runs in the maximum power tracking mode, the combined cooling heating and power unit tracks the difference value between the electric load demand and the photovoltaic output power to generate electricity, and the surplus and shortage of the electricity at the moment are solved by the change of the charging and discharging states of the storage battery and the grid-connected electricity purchasing and selling;
the cold and heat loads are supplied by a combined cold and heat and power supply unit, the cold and heat loads which are not met are supplemented by a gas-fired boiler, a heat storage tank and an electric refrigerator, the waste of heat power and the penalty of shortage are added into the operation cost, and the adjustable quantity of the system operation is mainly micro-source electric power output at the moment.
Preferably, in the mode of 'electricity determination by heat', the combined cooling heating and power supply unit tracks the cooling and heating load of the microgrid, and the cold and heat which are not met are supplied by the gas-fired boiler, the heat storage tank and the electric refrigerator; the electric energy consumption of the electric refrigerator and the electric energy demand of a user form the electric load of the microgrid, the electric load is mainly met by the electric energy output by the combined cooling heating and power supply unit in the mode of 'fixing the power with heat', and the rest electric energy demand is supplied by photovoltaic power generation; when the electric energy in the micro-grid is excessive or insufficient, the problem is solved by adjusting the charging and discharging states of the storage battery, and grid connection electricity purchasing and electricity selling.
Preferably, three loads of cold, heat and electricity exist in the microgrid, the cold and heat loads have seasonality, and the load matching in different seasons has a large difference, so that during the optimization operation, the operation strategies are divided into a typical winter day, a typical summer day and a typical transition day, the optimization is performed by adopting different operation strategies, and the operation strategies suitable for different typical days are selected by comparing the optimization scheduling results obtained by different optimization strategies.
The invention has the following beneficial effects:
according to the invention, based on the multi-element load requirement of the system, a micro-grid structure meeting the energy supply requirement is designed and a model is established. Firstly, planning and configuring the microgrid system, and determining the capacity of each distributed unit, so that the optimized operation has practical significance and is convenient for subsequent optimized operation. The planning configuration is configured with the lowest initial installation investment cost and the operation and maintenance cost of the equipment as the targets, and the optimal configuration result, namely the capacity of the equipment, is obtained. The capacity of the equipment influences the constraint condition of the optimized operation, so that the optimized operation can be performed after the planning and configuration of the microgrid system. The optimized operation is optimized by taking the lowest daily operation cost and the lowest environmental cost as targets to obtain an optimal daily operation scheme, namely the output power of each unit.
Drawings
Fig. 1 is a flowchart of a multi-energy complementary microgrid multi-element multi-target optimization configuration and optimization operation method;
FIG. 2 is a diagram illustrating the effect of the electrical and thermal loading of the microgrid;
FIG. 3 is a simulation result of the thermal load unit optimization run.
Detailed Description
The present invention will be described in detail with reference to specific examples.
The first embodiment is as follows:
as shown in fig. 1 to fig. 3, the present invention provides a method for performing optimal configuration and optimal operation on multiple targets of a multi-energy complementary microgrid, which includes the following steps:
step 1: according to the multi-energy complementary microgrid, determining the annual operating efficiency index of the microgrid as the load rate of the cooling, heating and power loads, and expressing the load rate by the following formula:
among them, LRe、LRhAnd LRcRespectively representing the load rates of the electric heating and cooling of the system; pe(t)、Ph(t) and Pc(t) respectively representing the electric heat and cold power capacity of the system; peload(t)、Phload(t) and Pcload(t) respectively representing the power demand of the electric heating load at the moment t;
step 2: establishing a micro-grid structure meeting the energy supply requirement and establishing a system model based on the multi-element load requirement;
and step 3: planning and configuring a system model, optimizing the system, and determining daily operation energy consumption and environmental cost;
and 4, step 4: and according to the annual cost of different configurations, giving the optimized configuration to perform the optimized operation to obtain the optimal daily operation scheme.
When the micro-grid system is configured, the load rate of the cooling, heating and power loads is added in the configuration process as an efficiency index, and the total annual cost is taken as a configuration optimization target;
the total annual cost of the microgrid comprises two aspects: initial installation investment costs and operational maintenance costs of the equipment, the optimization objective F is represented by the following equation:
wherein N is the type number of units in the microgrid system, and NiThe number of the ith unit; cCPiAnd COMiIndividual equipment costs and annual fixed maintenance costs, m, for the different unitsiThe service life of the ith unit is r, and the bank interest rate is r.
When the optimal planning configuration is solved, the equipment configuration schemes are listed and optimized respectively, and finally, the optimal configuration is given by analyzing the annual cost of different configurations, so that the aim of solving is fulfilled;
in the actual operation process, the power flow and the output distribution of each unit need to be optimized, the economic optimum is usually taken as an optimization target, the environmental protection property is considered, the environmental pollution cost is added, and the economic and environmental dual targets are considered.
The microgrid operating cost target comprises three aspects: the natural gas cost, the maintenance cost of each micro source and the cost generated by the micro grid for purchasing and selling electricity from the large power grid are represented by the following formula:
wherein, FcTotal cost for 24 hours of system operation; n is the number of micro sources: cgasIs the natural gas price; piIs the power of the micro source i; ciThe maintenance unit cost of the micro source i; cpThe price for purchasing electricity from the large power grid; csFor selling electricity to a large power grid: pgridThe power is the interactive power of the micro-grid and the large grid, the electricity purchasing is positive, and the electricity selling is negative;
the method is characterized by comprising the following steps of (1) aiming at the cost of environmental pollution, wherein micro sources for generating pollution gas in a micro grid are mainly a micro gas turbine and a large power grid, the treatment cost of the pollution gas generated by the micro grid is optimized as the minimum target, and the treatment cost is expressed by the following formula:
wherein, FeThe total treatment cost of the pollution gas is generated for 24 hours of system operation; k represents the type of the pollution gas; wMT,kThe emission coefficient of the micro gas turbine producing the polluted gas k is represented as follows: wgrid,kRepresenting the emission coefficient of the pollution gas k generated by the large power grid; pgrid,kRepresents the power purchased from the large power grid (0 at the time of power sale); ckRepresents the unit abatement cost of the pollutant gas k.
Under the 'electricity-based heat setting' mode, the photovoltaic runs in a maximum power tracking mode, the combined cooling heating and power supply unit tracks the difference value between the electricity load demand and the photovoltaic output power to generate electricity, and the surplus and shortage of the electricity at the moment are solved by the change of the charge-discharge state of the storage battery and the grid-connected electricity purchasing and selling;
the cold and heat loads are supplied by a combined cold and heat and power supply unit, the cold and heat loads which are not met are supplemented by a gas-fired boiler, a heat storage tank and an electric refrigerator, the waste of heat power and the penalty of shortage are added into the operation cost, and the adjustable quantity of the system operation is mainly micro-source electric power output at the moment.
In the mode of 'electricity determination by heat', the combined cooling, heating and power supply unit tracks the cooling and heating load of the microgrid, and the cold and heat which are not met are supplied by the gas boiler, the heat storage tank and the electric refrigerator; the electric energy consumption of the electric refrigerator and the electric energy demand of a user form the electric load of the microgrid, the electric load is mainly met by the electric energy output by the combined cooling heating and power supply unit in the mode of 'fixing the power with heat', and the rest electric energy demand is supplied by photovoltaic power generation; when the electric energy in the micro-grid is excessive or insufficient, the problem is solved by adjusting the charging and discharging states of the storage battery, and grid connection electricity purchasing and electricity selling.
Because three loads of cold, heat and electricity exist in the micro-grid, the cold and heat loads have seasonality, and the load matching in different seasons has a great difference, during the optimization operation, the operation is divided into typical days in winter, typical days in summer and typical transitional days, different operation strategies are adopted for optimization, the optimization scheduling results obtained by comparing different optimization strategies are compared, and the operation strategies suitable for different typical days are selected.
The method is based on the multi-load demand, considers the load rate of the cooling, heating and power loads, and carries out scientific configuration planning on the microgrid system. And establishing an objective function of annual operation cost by combining the mathematical models of the devices, and establishing an optimal configuration planning model according to the device characteristic constraint and the energy balance constraint relation. Further constructing a daily operation optimization model for the multi-energy complementary microgrid, considering energy factors such as electricity price and gas price, constructing a target function according to operation of each distributed unit and environmental protection cost, and establishing constraint conditions according to characteristics and load requirements of each distributed unit; and solving the operation optimization model by using a multi-objective particle swarm algorithm.
Aiming at the invented multifunctional complementary microgrid, the optimized operation is carried out in consideration of typical days in winter, the economic optimized operation of a single target is carried out, and the designed parameters of the multifunctional complementary microgrid are shown in table 1.
Case analysis is carried out on typical days in winter, the load of the multi-energy complementary micro-grid is a thermoelectric load, the time scale of the optimized operation is 1 hour, the operation of the micro-grid is optimized based on the photovoltaic and load day-ahead prediction data to obtain an optimal day-ahead scheduling plan, the simulation result is shown in figure 2, due to the fact that the electric load is in a peak period and a low valley period, electricity is prevented from being directly purchased from the large power grid in the peak period, and the time-of-use electricity price is adopted in the optimized operation process and is shown in table 2.
TABLE 1 parameters of a multi-energy complementary microgrid
TABLE 2 time-of-use pricing scheme
The unit for supplying heat load is operated economically and optimally as shown in figure 3, the output of the waste heat boiler is relatively stable outside the electricity utilization peak period, the fluctuation of the heat load is absorbed by the gas-fired boiler and the heat storage tank, and the operation strategy of electricity-based heat setting is met.
In solving the multi-objective optimization problem, generally, the sub-objectives of the multi-objective optimization problem conflict with each other, and the improvement of one sub-objective may cause the reduction of another sub-objective, that is, it is impossible to make all the sub-objectives reach the optimal values at the same time, and only balance and coordinate among the sub-objectives, so as to make more sub-objectives reach the optimization as much as possible. The invention adopts a multi-target particle swarm optimization algorithm, and the algorithm has the characteristics of simple algorithm, high search efficiency, fast convergence and the like.
The above description is only a preferred embodiment of the multi-energy complementary microgrid multi-element multi-target optimization configuration and optimization operation method, and the protection range of the multi-energy complementary microgrid multi-element multi-target optimization configuration and optimization operation method is not limited to the above embodiments, and all technical solutions belonging to the idea belong to the protection range of the present invention. It should be noted that modifications and variations which do not depart from the gist of the invention will be those skilled in the art to which the invention pertains and which are intended to be within the scope of the invention.
Claims (7)
1. A multi-energy complementary micro-grid multi-element multi-target optimization configuration and optimization operation method is characterized by comprising the following steps: the method comprises the following steps:
step 1: according to the multi-energy complementary microgrid, determining the annual operating efficiency index of the microgrid as the load rate of the cooling, heating and power loads, and expressing the load rate by the following formula:
among them, LRe、LRhAnd LRcRespectively representing the load rates of the electric heating and cooling of the system; pe(t)、Ph(t) and Pc(t) respectively representing the electric heat and cold power capacity of the system; peload(t)、Phload(t) and Pcload(t) respectively representing the power demand of the electric heating load at the moment t;
step 2: establishing a micro-grid structure meeting the energy supply requirement and establishing a system model based on the multi-element load requirement;
and step 3: planning and configuring a system model, optimizing the system, and determining daily operation energy consumption and environmental cost;
and 4, step 4: and according to the annual cost of different configurations, giving the optimized configuration to perform the optimized operation to obtain the optimal daily operation scheme.
2. The multi-energy complementary microgrid multi-element multi-objective optimization configuration and optimization operation method according to claim 1, characterized in that: when the micro-grid system is configured, the load rate of the cooling, heating and power loads is added in the configuration process as an efficiency index, and the total annual cost is taken as a configuration optimization target;
the total annual cost of the microgrid comprises two aspects: initial installation investment costs and operational maintenance costs of the equipment, the optimization objective F is represented by the following equation:
wherein N is the type number of units in the microgrid system, and NiThe number of the ith unit; cCPiAnd COMiIndividual equipment costs and annual fixed maintenance costs, m, for the different unitsiThe service life of the ith unit is r, and the bank interest rate is r.
3. The multi-energy complementary microgrid multi-element multi-objective optimization configuration and optimization operation method according to claim 1, characterized in that: when the optimal planning configuration is solved, the equipment configuration schemes are listed and optimized respectively, and finally, the optimal configuration is given by analyzing the annual cost of different configurations, so that the aim of solving is fulfilled;
in the actual operation process, the power flow and the output distribution of each unit need to be optimized, the economic optimum is usually taken as an optimization target, the environmental protection property is considered, the environmental pollution cost is added, and the economic and environmental dual targets are considered.
4. The multi-energy complementary microgrid multi-element multi-objective optimization configuration and optimization operation method according to claim 1, characterized in that: the microgrid operating cost target comprises three aspects: the natural gas cost, the maintenance cost of each micro source and the cost generated by the micro grid for purchasing and selling electricity from the large power grid are represented by the following formula:
wherein, FcTotal cost for 24 hours of system operation; n is the number of micro sources: cgasIs the natural gas price; piIs the power of the micro source i; ciThe maintenance unit cost of the micro source i; cpThe price for purchasing electricity from the large power grid; csFor selling electricity to a large power grid: pgridThe power is the interactive power of the micro-grid and the large grid, the electricity purchasing is positive, and the electricity selling is negative;
the method is characterized by comprising the following steps of (1) aiming at the cost of environmental pollution, wherein micro sources for generating pollution gas in a micro grid are mainly a micro gas turbine and a large power grid, the treatment cost of the pollution gas generated by the micro grid is optimized as the minimum target, and the treatment cost is expressed by the following formula:
wherein, FeThe total treatment cost of the pollution gas is generated for 24 hours of system operation; k represents the type of the pollution gas; wMT,kThe emission coefficient of the micro gas turbine producing the polluted gas k is represented as follows: wgrid,kRepresenting the emission coefficient of the pollution gas k generated by the large power grid; pgrid,kRepresenting from large electric networksPower purchase (0 when selling electricity); ckRepresents the unit abatement cost of the pollutant gas k.
5. The multi-energy complementary microgrid multi-element multi-objective optimization configuration and optimization operation method according to claim 4, characterized in that: under the electricity heat-fixing mode, the photovoltaic runs in a maximum power tracking mode, the combined cooling heating and power supply unit tracks the difference value between the electricity load demand and the photovoltaic output power to generate electricity, and the surplus and the shortage of the electricity at the moment are solved by the change of the charge-discharge state of the storage battery and the grid-connected electricity purchasing and selling;
the cold and heat loads are supplied by a combined cold and heat and power supply unit, the cold and heat loads which are not met are supplemented by a gas-fired boiler, a heat storage tank and an electric refrigerator, the waste of heat power and the penalty of shortage are added into the operation cost, and the adjustable quantity of the system operation is mainly micro-source electric power output at the moment.
6. The multi-energy complementary microgrid multi-element multi-objective optimization configuration and optimization operation method according to claim 4, characterized in that: under the mode of electricity utilization by heat, the combined cooling heating and power supply unit tracks the cooling and heating load of the micro-grid, and the cold quantity and the heat quantity which are not met are supplied by the gas-fired boiler, the heat storage tank and the electric refrigerator; the electric energy consumption of the electric refrigerator and the electric energy demand of a user form the electric load of the microgrid, the electric load is mainly met by the electric energy output by the combined cooling heating and power supply unit in the mode of 'fixing the power with heat', and the rest electric energy demand is supplied by photovoltaic power generation; when the electric energy in the micro-grid is excessive or insufficient, the problem is solved by adjusting the charging and discharging states of the storage battery, and grid connection electricity purchasing and electricity selling.
7. The multi-energy complementary microgrid multi-element multi-objective optimization configuration and optimization operation method according to claim 1, characterized in that: because three loads of cold, heat and electricity exist in the micro-grid, the cold and heat loads have seasonality, and the load matching in different seasons has a great difference, during the optimization operation, the operation is divided into typical days in winter, typical days in summer and typical transitional days, different operation strategies are adopted for optimization, the optimization scheduling results obtained by comparing different optimization strategies are compared, and the operation strategies suitable for different typical days are selected.
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