CN109919478B - Comprehensive energy microgrid planning method considering comprehensive energy supply reliability - Google Patents
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Abstract
A comprehensive energy microgrid planning method considering comprehensive energy supply reliability comprises the following steps: establishing a time sequence model of energy efficiency and economy of equipment in the comprehensive energy microgrid, wherein the time sequence model comprises a gas combined cooling heating and power system model, an energy conversion device model, an electricity storage equipment model and a heat storage equipment model; establishing an optimization planning model of the comprehensive energy microgrid, wherein the total cost of the comprehensive energy microgrid in the whole life cycle is taken as a target function, and the maximum load constraint, the power balance constraint, the self-sufficient probability constraint, the energy supply equipment operation constraint and the energy storage equipment operation constraint are also taken as the target function; and the comprehensive energy microgrid optimization planning comprises equipment configuration and operation scheduling. The method analyzes the energy supply reliability of the comprehensive energy microgrid, takes the energy supply reliability and the economic index of the comprehensive energy microgrid as the objective function, and further optimizes the capacity of the equipment in the comprehensive energy microgrid on the premise of meeting the energy consumption requirement of users in the comprehensive energy microgrid in a targeted manner, so that the planning economy is improved.
Description
Technical Field
The invention relates to a comprehensive energy microgrid planning method. In particular to a comprehensive energy micro-grid planning method which is suitable for the construction of urban energy stations of public institutions and takes the comprehensive energy supply reliability into consideration.
Background
The energy is the basis of human survival and development and is the source power of social and economic development. Improving the utilization efficiency of energy and guaranteeing the effective supply of energy become the inevitable choice for solving the conflict between the supply and demand of energy and the contradiction between social development and environmental protection. In recent years, with the continuous deepening of the construction of the energy internet, the existing mode that each original energy supply system is independently planned and independently operated is broken through, the cooperative supply of electricity/gas/heat (cold) multiple energy sources is realized, and the construction of an advanced energy supply system aiming at safety, reliability, economy, high efficiency, cleanness and environmental protection is a development trend in the future. As a key node of the energy internet, the comprehensive energy microgrid receives more and more attention due to a flexible operation mode, an effective energy utilization mode and strong constructability and practicability. Therefore, important problems to be solved are urgently needed to research key technologies such as planning methods and reliability evaluation of the comprehensive energy microgrid.
Aiming at the construction of the concept and the architecture of the comprehensive energy microgrid, researchers put forward an energy concentrator model at present, and analyze the complex relationship in the energy concentrator from the perspective of energy flow by establishing an energy conversion matrix, so as to highlight the relationship among energy subsystems in the energy concentrator. On the basis, researchers further put forward the concept of the comprehensive energy system, and analyze the characteristics of the comprehensive energy system in detail from two aspects of energy coupling elements and the synergistic effect between different energy networks. Meanwhile, with the proposal of the micro-grid concept, the distributed energy supply and storage devices are further integrated into the comprehensive energy system to form the comprehensive energy micro-grid with a more flexible operation mode, so as to provide guarantee for the effective consumption of renewable energy and the mutual support with the energy main grid.
As an important reference index of a planning link, the reliability is the basis for providing an ideal planning scheme. The enhancement of the coupling characteristics between the multiple energy systems also has a certain influence on the reliability: on one hand, due to the coupling relation among the energy sources, the requirement side is equivalent to have a plurality of energy source supply points, and the energy supply reliability is enhanced; on the other hand, due to the multi-energy coupling of the energy supply systems, a problem in one energy supply system may affect the energy supply of the whole system. As a key evaluation technology in the system operation and planning process, the research of the reliability evaluation method has been widely focused. Analytical methods and simulation methods are reliability assessment methods commonly used in power systems, and the calculation idea is also applied to the assessment of the reliability of the microgrid. However, there is currently less research on the evaluation of the reliability of the integrated energy supply. Therefore, an integrated energy microgrid planning method aiming at evaluating the energy supply reliability of the integrated energy microgrid and considering the integrated energy supply reliability needs to be researched urgently.
Although researchers have developed relevant research on the planning problem of the comprehensive energy microgrid at present, the following problems exist in the existing research: firstly, most research objects still focus on the single energy network level represented by electric energy, and the related methods have difficulty in meeting the requirements of comprehensive energy collaborative planning; secondly, a mathematical analysis method is mostly adopted in the aspect of reliability analysis, and the characteristics of the unit equipment and the user requirement time sequence cannot be embodied; thirdly, the current research fails to consider the energy grade differentiation between different energy sources and the resulting problems of supply/storage priority and load reduction strategy; fourth, although the conventional planning method considers the problem in operation, most of the conventional planning methods use the lowest comprehensive cost of the system operation cost, the starting cost, the fuel cost and the like as an optimization target, but do not consider the randomness of unit faults and the reliability problem of the power system, and the planning and configuration problem of the comprehensive energy microgrid not only needs to consider the economic problem under the normal operation condition, but also needs to consider the possible risk problem of the system.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a comprehensive energy microgrid planning method which optimizes and configures the capacity of equipment in a comprehensive energy microgrid and considers the reliability of comprehensive energy supply.
The technical scheme adopted by the invention is as follows: a comprehensive energy microgrid planning method considering comprehensive energy supply reliability comprises the following steps:
1) Establishing a time sequence model of energy efficiency and economy of equipment in the comprehensive energy microgrid, wherein the time sequence model comprises a gas combined cooling heating and power system model, an energy conversion device model, an electricity storage equipment model and a heat storage equipment model;
2) Establishing an optimization planning model of the comprehensive energy microgrid, wherein the total cost of the comprehensive energy microgrid in the whole life cycle is taken as a target function, and the maximum load constraint, the power balance constraint, the self-sufficient probability constraint, the energy supply equipment operation constraint and the energy storage equipment operation constraint are also taken as the target function;
3) And the comprehensive energy microgrid optimization planning comprises equipment configuration and operation scheduling.
The gas combined cooling heating and power system model in the step 1) comprises:
(1) The heating energy efficiency model of the gas combined cooling heating power system comprises the following steps:
(2) The refrigeration energy efficiency model of the gas combined cooling heating and power system is as follows:
in the formula (I), the compound is shown in the specification,
and &>
Respectively supplying natural gas quantity required by the gas combined cooling heating and power system during heating and refrigerating; q h And Q c The heat load and the cold load which need to be met by the gas combined cooling heating and power system are respectively; Δ t h And Δ t c The running time of the gas turbine for heating and refrigerating respectively; />
The operation efficiency of a gas combined cooling heating and power system is improved; l is the low heating value of natural gas; k is h0 And K c0 The heating coefficient and the refrigeration coefficient of the bromine refrigerator are respectively; q h0 And Q c0 Heating capacity and refrigerating capacity are respectively provided for the residual heat of the gas turbine;
(3) The fuel cost model of the gas combined cooling heating and power system is as follows:
in the formula (I), the compound is shown in the specification,
the fuel cost of a gas combined cooling heating and power system; w is a gas Is the price of the gas; />
For gas-fired cooling, heating and powerElectric power output by the combined supply system; l is the low heating value of natural gas; />
The operation efficiency of a gas combined cooling heating and power system is improved;
(4) The operation and maintenance cost calculation formula of the gas combined cooling heating and power system is as follows:
in the formula (I), the compound is shown in the specification,
the operation and maintenance cost of the gas combined cooling heating and power system is reduced; />
The proportional coefficient of the operation and maintenance cost of the gas combined cooling heating and power system is calculated; />
The electric power is output by the gas combined cooling heating and power system.
The energy conversion device model in the step 1) comprises:
(1) Energy efficiency output model of the energy conversion device:
P b ＝C ab P a (5)
in the formula, C ab Is the coupling conversion coefficient between the input energy a and the output energy b; p a Is the power of the input energy source a; p b Is the power of the input energy b;
(2) Maintenance cost model:
in the formula (I), the compound is shown in the specification,
the operation and maintenance cost of the energy conversion device at the moment t; n is a radical of Trans The total number of energy conversion devices; />
The maintenance cost coefficient of the mth type energy conversion device; p m (t) is the output power of the mth type energy conversion device at the moment t; Δ t is the scheduling interval.
The power storage equipment model in the step 1) comprises:
(1) Dynamic model:
wherein SOC (t) is the charge of the electricity storage unit at the time t; delta is the self-discharge rate of the electricity storage unit;
the charging and discharging powers of the electricity storage units are respectively; />
The charge and discharge efficiency of the electricity storage unit is respectively; e SOC Is the rated capacity of the power storage unit; Δ t is a scheduling time interval;
(2) Energy loss model:
in the formula (I), the compound is shown in the specification,
the transmission loss cost of the power storage device at the time t; />
Is the unit transmission loss cost of the electricity storage device; />
The charging and discharging powers of the electricity storage units are respectively; />
The charge and discharge efficiencies of the electricity storage units are respectively.
The heat storage equipment model in the step 1) comprises:
(1) Dynamic model:
in the formula, H HS (t) is the heat of the heat storage unit at the moment t; k is a radical of LOSS The heat dissipation rate of the heat storage unit;
the heat charging and discharging powers of the heat storage units are respectively; />
The heat storage units respectively have the charge-discharge efficiency; Δ t is a scheduling time interval;
(2) The loss cost model is:
in the formula (I), the compound is shown in the specification,
the transmission loss cost of the heat storage device at the moment t; />
The unit loss cost of the heat storage device; k is a radical of LOSS The heat dissipation rate of the heat storage unit; />
The heat charging and discharging powers of the heat storage units are respectively; />
The heat storage units respectively have the charge-discharge efficiency; Δ t is the scheduling interval.
The total cost of the comprehensive energy microgrid in the step 2) in the whole life cycle is taken as a target function formula as follows:
min{C IN +C OP +C RE } (11)
in the formula, C IN The cost of equipment construction; c OP The economic cost of the comprehensive energy microgrid under the normal operation condition is reflected as the system operation cost; c RE Cost is converted for reliability, economic loss caused by insufficient energy electricity/heat/cold sources due to outage of equipment in the comprehensive energy microgrid is shown, and the larger the numerical value is, the more serious the influence of unit failure on the energy supply reliability of the comprehensive energy microgrid is;
the calculation formula of the equipment construction cost is as follows:
in the formula, N m The construction quantity of the mth type equipment; c inst,i Investment and construction cost of the mth type equipment per unit capacity; m is a group of m The installation capacity of the m-th equipment; c scra,m The residual value of the m-th equipment; y is the planned life cycle; r is the actual interest rate;
the calculation formula of the system operation cost is as follows:
in the formula (I), the compound is shown in the specification,
fuel cost for class m devices; />
The operation and maintenance cost of the m-th equipment;
the calculation formula of the reliability conversion cost is as follows:
C RE ＝w elec LOEE elec +w heat LOEE heat +w cold LOEE cold (14)
in the formula, LOEE elec 、LOEE heat 、LOEE cold Respectively providing the energy shortage expectations of the electricity, heat and cold energy sources under the given planning configuration scheme; w is a elec 、w heat 、w cold The energy loss values of electric energy, heat energy and cold energy are respectively.
The step 3) comprises the following steps:
firstly, optimizing a device configuration layer, considering the constraints in the aspects of cost and load based on the overall load level of the comprehensive energy in the comprehensive energy microgrid, and giving the selection of energy supply and energy storage devices in the comprehensive energy microgrid by taking the type and the number of the devices as optimization variables in the alternative energy supply and storage devices according to an objective function; from the angle of the algorithm, the optimization problem of the planning layer belongs to the nonlinear integer programming problem, and is difficult to obtain an analytic solution, so the optimization problem of the planning layer model is solved by adopting a quantum particle swarm algorithm, the optimization variables of the planning layer are subjected to particle coding, a planning layer initial solution set is generated, namely, an initial particle swarm composed of different types of equipment capacity variables is randomly generated, the initial energy in an energy storage device is set, and parameters such as the population scale, the position, the speed, the iteration frequency and the like of the particles in the algorithm are set, so that the iteration frequency is 1;
secondly, optimizing an operation scheduling layer, considering comprehensive energy microgrid power balance constraint, energy supply equipment operation constraint and energy storage equipment operation constraint aiming at a time-by-time load demand curve in a planning time interval, combining an optimization result of an equipment configuration layer, and providing a time-by-time optimization scheduling scheme of each equipment by taking starting, stopping and output of the energy storage equipment as optimization variables; from the angle of the algorithm, the optimization problem of the scheduling level is a mixed nonlinear optimization problem, and the method adopts the quantum particle swarm algorithm to solve. And carrying out particle coding on the optimized variables of the planning layer to generate an initial solution set of the planning layer, and analyzing the output intervals of the unit and the energy storage device to be used as the particle optimization range. And returning the optimization result of the operation layer to the planning layer, and optimizing and calculating the planning layer model.
According to the comprehensive energy microgrid planning method considering comprehensive energy supply reliability, the comprehensive energy microgrid can be used as a research object, the energy supply reliability of the comprehensive energy microgrid is analyzed, the energy supply reliability and the economic index of the comprehensive energy microgrid are used as target functions, and further the capacity of equipment in the comprehensive energy microgrid is optimized and configured on the premise of meeting the energy consumption requirement of users in the comprehensive energy microgrid in a targeted manner, so that the planning economy is improved. The method can provide guidance for planning and construction of the urban comprehensive energy station, is beneficial to improving the management level of urban energy station planning, and promotes the reasonable development of urban energy Internet structure construction and planning technology.
Drawings
Fig. 1 is a flowchart of an integrated energy microgrid planning method considering integrated energy supply reliability according to the present invention.
Detailed Description
The comprehensive energy microgrid planning method considering comprehensive energy supply reliability is described in detail below with reference to the embodiments and the accompanying drawings.
As shown in fig. 1, the comprehensive energy microgrid planning method considering comprehensive energy supply reliability of the present invention includes the following steps.
1) Model for establishing energy efficiency and economy time sequence of equipment in comprehensive energy microgrid
The comprehensive energy microgrid is an energy system capable of operating autonomously and consists of energy management equipment, a distributed renewable energy device, an energy storage device, an energy conversion device and an energy load; the structure can be divided into energy input, conversion, storage, output and other links. The comprehensive energy microgrid is combined with an energy concentrator model to construct a comprehensive energy microgrid comprising a distributed combined cooling heating and power system, a gas heat pump, distributed photovoltaic power, an electric refrigerator, an electricity storage device, a heat storage device and the like, and various electric/gas/cold/heat energy sources. The time sequence model of the energy efficiency and the economy of the equipment in the comprehensive energy microgrid is as follows:
(1) Gas combined cooling heating and power system model
As a key unit in the comprehensive energy micro-grid, the gas combined cooling heating and power system supplies energy to self equipment such as an absorption chiller, a heat exchanger and the like and electricity/heat/cold loads in the comprehensive energy micro-grid. In the planning and configuration link of the comprehensive energy microgrid, characteristics such as output and fuel consumption of a gas combined cooling heating and power system are mainly concerned. The refrigeration and heating energy efficiency models of the gas combined cooling heating power system are respectively as follows:
in the formulas (1) and (2),
and &>
Respectively supplying natural gas quantity required by the gas combined cooling heating and power system during heating and refrigerating; q h And Q c The heat load and the cold load which need to be met by the gas combined cooling heating and power system are respectively; Δ t h And Δ t c The operating times of the gas turbine for heating and cooling respectively; />
The operation efficiency of a gas combined cooling heating and power system is improved; l is the low heating value of natural gas; k is h0 And K c0 The heating coefficient and the refrigeration coefficient of the bromine refrigerator are respectively; q h0 And Q c0 Respectively provides heating capacity and refrigerating capacity for the residual heat of the gas turbine smoke.
In terms of cost, besides the inherent installation cost, the fuel cost model of the gas combined cooling heating and power system is as follows:
in the formula (3), the reaction mixture is,
the fuel cost of a gas combined cooling heating and power system; w is a gas Is the price of the gas; />
Electric power output by the gas combined cooling heating and power system; l is the low heating value of natural gas; />
The operation efficiency of the gas combined cooling heating and power system is improved.
The operation and maintenance cost model of the gas combined cooling heating and power system is as follows:
in the formula (4), the reaction mixture is,
the operation and maintenance cost of the gas combined cooling heating and power system is reduced; />
The proportional coefficient of the operation and maintenance cost of the gas combined cooling heating and power system is calculated; />
The electric power is output by the gas combined cooling heating and power system.
(2) Energy conversion device model
The comprehensive energy microgrid comprises energy conversion devices such as a gas heat pump and an electric refrigerator, and is combined with an energy concentrator model, and the energy efficiency output model of the energy conversion devices is expressed as follows:
P b ＝C ab P a (5)
in formula (5), C ab For inputting energya and output energy b; p a Is the power of the input energy source a; p b Is the power of input energy b.
In the planning link, besides considering the installation cost of the equipment, the operation and maintenance cost also needs to be considered, and the operation and maintenance cost model of the energy conversion device is as follows:
in the formula (6), the reaction mixture is,
the operation and maintenance cost of the energy conversion device at the moment t; n is a radical of hydrogen Trans The total number of energy conversion devices; />
The maintenance cost coefficient of the mth type energy conversion device; p m (t) is the output power of the mth type energy conversion device at the moment t; Δ t is the scheduling interval.
(3) Electricity storage device
Compared with other energy storage technologies, the lead-acid battery is not limited by a place and has the characteristics of high charging efficiency and high energy density, so that the lead-acid battery is more suitable for being used in the comprehensive energy microgrid, and the dynamic model is as follows:
in the formula (7), SOC (t) is the charge amount of the electricity storage unit at time t; delta is the self-discharge rate of the electricity storage unit;
the charging and discharging powers of the electricity storage units are respectively; />
Are respectively an electricity storage sheetCharge-discharge efficiency of the cell; e SOC Is the rated capacity of the power storage unit; Δ t is the scheduling interval.
Besides the installation cost, the self-discharge rate of the lead-acid storage battery is low, so that the self-discharge loss is not taken into consideration; the cost loss of the electricity storage device in the operation process is mainly the electricity transmission loss
Cost, electric transmission loss of the electric storage device->
The energy loss is caused by the fact that the transmission efficiency does not reach 100%, and the energy loss model is expressed as follows:
in the formula (8), the reaction mixture is,
the transmission loss cost of the power storage device at the time t; />
Is the unit transmission loss cost of the electricity storage device; />
The charging and discharging powers of the electricity storage units are respectively; />
The charge and discharge efficiencies of the electricity storage units are respectively.
(4) Heat storage equipment model
The invention selects a heat accumulating type electric boiler as a heat accumulation device, can help to consume renewable energy sources while finishing the heat accumulation function, and has a dynamic model represented as:
in the formula (9), H HS (t) is the heat of the heat storage unit at time t; k is a radical of LOSS The heat dissipation rate of the heat storage unit;
the heat charging and discharging powers of the heat storage units are respectively; />
The heat storage units respectively have the charge and discharge efficiency; Δ t is the scheduling interval.
The cycle life loss of the heat storage device is small and is not considered temporarily. The cost of the heat storage device in operation mainly includes idle heat dissipation cost and heat transfer loss cost. The heat storage device loss cost model is as follows:
in the formula (10), the compound represented by the formula (10),
the transmission loss cost of the heat storage device at the moment t; />
The unit loss cost of the heat storage device; k is a radical of LOSS The heat dissipation rate of the heat storage unit; />
The heat charging and discharging powers of the heat storage units are respectively; />
The heat storage units respectively have the charge-discharge efficiency; Δ t is the scheduling interval.
2) Establishing comprehensive energy microgrid optimization planning model
The optimization planning model of the comprehensive energy microgrid comprises two layers. The first is optimization at the planning level, that is, the capacity and the number of supply and storage devices in the integrated energy microgrid are optimized. And secondly, optimization of a scheduling layer, namely optimization of output of energy supply equipment and operation of energy storage equipment in the comprehensive energy microgrid. Both aspects aim at economy and further consider energy supply reliability factors on this basis. The comprehensive energy microgrid optimization planning model comprises:
(1) The total cost of the comprehensive energy microgrid in the whole life cycle is taken as an objective function
The method takes the total cost of the comprehensive energy microgrid in the whole life cycle as an objective function. The total cost mainly relates to the purchase and installation cost, the operation cost, the reliability conversion cost and the like of the equipment. The specific expression taking the total cost of the comprehensive energy microgrid in the whole life cycle as a target function is as follows:
min{C IN +C OP +C RE } (11)
in formula (11), C IN The cost of equipment construction; c OP The economic cost of the comprehensive energy microgrid under the normal operation condition is reflected as the system operation cost; c RE And the cost is converted for reliability, and the economic cost under the condition of the fault of the comprehensive energy microgrid is reflected.
The calculation formula of the equipment construction cost of the system is as follows:
in the formula (12), C IN Cost of equipment construction for the system; n is a radical of m The construction quantity of the mth type equipment; c inst,i Investment construction cost per unit capacity for the mth type of equipment; m m The installation capacity of the m-th equipment; c scra,m The residual value of the m-th equipment; y is the planned life cycle; r is the actual interest rate.
The calculation formula of the system operation cost is as follows:
in formula (13), C OP The cost of maintaining the operation of the system;
fuel cost for class m devices; />
The operation and maintenance cost of the m-th equipment; the calculation formulas of the fuel cost and the operation and maintenance cost of different equipment are shown as a formula (4) and a formula (6).
The reliability conversion cost of the system can be calculated by combining the energy shortage expectation of different types of energy under the established planning and configuration scheme of the system and the corresponding energy price. And the system reliability conversion cost evaluates the loss of the failure of the unit equipment to the comprehensive energy microgrid from the economic point of view. The calculation formula of the system reliability conversion cost is as follows:
C RE ＝w elec LOEE elec +w heat LOEE heat +w cold LOEE cold (14)
in the formula (14), C RE The cost is reduced for the system reliability, the economic loss of insufficient energy electricity/heat/cold sources caused by the outage of equipment in the system is represented, and the larger the numerical value is, the more serious the influence of the unit failure on the energy supply reliability of the comprehensive energy microgrid is represented; LOEE elec 、LOEE heat 、LOEE cold Respectively providing the energy shortage expectation of the electric/heat/cold energy source under the given planning configuration scheme; w is a elec 、w heat 、w cold The energy loss values of electric energy/heat energy/cold energy, respectively.
(2) Constraint conditions
The constraint conditions of the comprehensive energy microgrid optimization planning model comprise:
the maximum load constraint, that is, the maximum output power of the energy supply equipment planned and configured by the comprehensive energy microgrid should meet the maximum demand of the loads of electricity, heat, cold and the like of the comprehensive energy microgrid, and the formula is as follows:
in the formula (15), the reaction mixture is,
the maximum output power of the mth type equipment at the time t; />
The maximum load demand at time t.
Power balance constraint, namely under the condition of considering the energy storage effect, ensuring that the supply and demand of the electricity/heat/cold energy in the comprehensive energy microgrid reach real-time balance, wherein the formula is as follows:
in the formula (16), the compound represented by the formula (I),
the output of the energy supply equipment m at the moment t is provided; />
The output of the energy storage device m at the moment t is obtained;
the demand of the load at the time t; />
The energy stored at time t for the energy storage device.
And self-sufficient probability constraint, namely guiding the planning configuration of the comprehensive energy microgrid through the probability that the comprehensive energy microgrid self-sufficiently meets the load requirement in a planning period, wherein the formula is as follows:
in the formula (17), the reaction mixture is,
the output of the energy supply equipment m at the moment t is provided; />
The output of the energy storage device m at the moment t is obtained;
the probability of self-sufficiency of a certain type of load in the microgrid system.
The operation constraint of the energy supply equipment, namely the rated power and the climbing constraint of the equipment need to be met in the operation process of the energy supply equipment configured by the comprehensive energy microgrid planning, and the formula is as follows:
in the formulae (19) and (20),
the output of the energy supply equipment m at the moment t is provided; />
Respectively the maximum/minimum output of the energy supply device m; />
The ramp speeds of the output reduction and the output increase for the energy supply device m, respectively.
The energy storage device operation constraint means that the energy storage device configured by the comprehensive energy microgrid planning needs to satisfy the charging and discharging energy power and capacity constraint of the device in the operation process, and the formula is as follows:
in the formulae (20), (21), M m (t) is the capacity of the energy storage device m at time t;
maximum/minimum capacity of the energy storage device m, respectively; />
The charging/discharging power of the energy storage device m at the moment t; />
The maximum charging/discharging power of the energy storage device m.
3) The comprehensive energy microgrid optimization planning comprises two layers of equipment configuration and operation scheduling
Firstly, optimizing a device configuration layer, considering constraints in the aspects of cost and load based on the overall load level of the comprehensive energy in the comprehensive energy microgrid, and giving the model selection of energy supply and storage devices in the comprehensive energy microgrid by taking the device types and the quantity as optimization variables aiming at target function formulas (11) and (12) in alternative energy supply and storage devices; from the angle of the algorithm, the optimization problem of the planning layer belongs to the nonlinear integer programming problem, and an analytic solution is difficult to obtain, so the method adopts the quantum particle swarm algorithm to solve the optimization problem of the planning layer model, carries out particle encoding on the optimization variable of the planning layer, generates an initial solution set of the planning layer, namely randomly generates an initial particle swarm composed of different types of equipment capacity variables, sets the initial energy in an energy storage device, and sets parameters such as the population scale, the position, the speed, the iteration frequency and the like of the particles in the algorithm to enable the iteration frequency to be 1.
Secondly, optimizing an operation scheduling layer, considering comprehensive energy microgrid power balance constraint, energy supply equipment operation constraint and energy storage equipment operation constraint aiming at a time-by-time load demand curve in a planning time interval, and giving a time-by-time optimization scheduling scheme of each equipment by taking the start-stop and output of the energy storage equipment as optimization variables by combining an optimization result of an equipment configuration layer; from the angle of the algorithm, the optimization problem of the scheduling level is a mixed nonlinear optimization problem, and the method adopts the quantum particle swarm algorithm to solve. And carrying out particle coding on the optimized variables of the planning layer to generate an initial solution set of the planning layer, and analyzing the output intervals of the unit and the energy storage device to be used as the particle optimization range. And returning the optimization result of the operation layer to the planning layer, and optimizing and calculating the planning layer model.
The optimization of the operation scheduling aspect shows the economy of the microgrid system under the normal operation condition, and in addition, the method further calculates the economy converted from the reliability of the energy supply of the microgrid system based on the formula (14) aiming at the result obtained by the double-layer optimization so as to reflect the possible economic loss of the microgrid system under the fault condition and perfect the formation of the planning economy index.
Specific examples are given below
(1) Basic overview of the implementation
The invention takes a typical industrial park in south China as an example, and takes 4-10 months as a cooling period in the aspects of energy supply and demand, which is reflected in that the demand of cooling load is large; the heat load mainly comprises the requirements of drying, fresh air, hot water in life and the like in the production process, and has certain seasonal characteristics although no clear supply period exists; electrical load demands are present throughout the year. By combining the energy demand, the types and economic operation parameters of selectable energy production/conversion equipment in the microgrid system are shown in table 1, and the types and economic operation parameters of selectable energy storage equipment are shown in table 2, wherein the initial capacity of the electricity storage device is 30% of the rated capacity, the initial capacity of the heat storage device is 50% of the rated capacity, and the maximum charge-discharge power is 80% of the rated capacity. The reliability parameters of various equipment units are shown in table 3, wherein the superior main power grid selects the failure rate and the repair time of a main transformer/bus at the power supply side; the upper-level gas network selects the failure rate and the repair time of the main gas transmission pipeline. In combination with the local actual step electricity price policy scheme, the power rates of the power sources are as follows, wherein the power rates are as follows, the power rates are as follows. The electric/heat/cooling loss load values in the micro-grid system are respectively 200 yuan/kW.h, 120 yuan/kW.h and 120 yuan/kW.h.
Table 1 examples alternative energy production/conversion equipment types and parameters
Table 2 example alternative energy storage device types and parameters
TABLE 3 Unit Equipment reliability parameters in the calculation example
TABLE 4 price of different types of energy in the example
(2) Optimized configuration analysis
In order to fully influence the selection of the planning scheme of the comprehensive energy microgrid system and the reliability by different configuration modes, 4 scenes are set for comparison.
Scene 0: no electricity storage and heat storage device is arranged in the microgrid system;
scene 1: a heat storage device can be configured in the microgrid system, and a power storage device is not configured;
scene 2: an electricity storage device can be configured in the microgrid system, and a heat storage device is not configured;
scene 3: an electricity storage and heat storage device can be configured in the microgrid system.
By solving the optimal configuration schemes of different scenes, the optimal configuration results and the cost of the comprehensive energy microgrid are respectively shown in tables 5 and 6.
Table 5 comprehensive energy microgrid system optimization configuration result in example
Table 6 comprehensive energy microgrid cost calculation result in calculation example
As can be seen from the calculation results in tables 5 and 6, the overall economy of the scenario 4 configuration scheme is optimal in the aspects of comprehensive consideration of the capacity configuration, the operation scheduling, the energy supply reliability, and the like of the microgrid system. Compared with other scenes, the scene 0 has no energy storage unit, so the investment cost of the comprehensive energy system is low; however, energy supply equipment in the microgrid system needs to meet the load requirement all the time, and the operating cost of the microgrid system is high due to the intermittent nature of distributed photovoltaic output; in addition, the energy storage unit is lacked as a backup resource after the fault, the reliability of the system is poor, and the loss caused by the poor reliability is expected to be large.
Different energy storage devices are added in the scene 1 and the scene 2, two energy storage devices are specifically compared, the heat storage device provided in the text belongs to a pure backup resource, only plays a role in improving the reliability of heat supply, the electricity storage device can stabilize the fluctuation of photovoltaic output, and meanwhile on the basis of improving the reliability of power supply of a micro-grid system, the energy supply reliability of other energy sources is further improved indirectly through an energy conversion device, so that the effect of the electricity storage device is more obvious.
Claims (6)
1. A comprehensive energy microgrid planning method considering comprehensive energy supply reliability is characterized by comprising the following steps:
1) Establishing a time sequence model of energy efficiency and economy of equipment in the comprehensive energy microgrid, wherein the time sequence model comprises a gas combined cooling heating and power supply system model, an energy conversion device model, an electricity storage equipment model and a heat storage equipment model; the gas combined cooling heating and power system model comprises:
(1) The heating energy efficiency model of the gas combined cooling heating power system comprises the following steps:
(2) The refrigeration energy efficiency model of the gas combined cooling heating and power system is as follows:
in the formula (I), the compound is shown in the specification,
and &>
Respectively supplying natural gas quantity required by the gas combined cooling heating and power system during heating and refrigerating; q h And Q c The heat load and the cold load which need to be met by the gas combined cooling heating and power system are respectively; Δ t h And Δ t c The running time of the gas turbine for heating and refrigerating respectively; />
The operation efficiency of a gas combined cooling heating and power system is improved; l is the low heating value of natural gas; k h0 And K c0 The heating coefficient and the refrigeration coefficient of the bromine refrigerator are respectively; q h0 And Q c0 Heating capacity and refrigerating capacity are respectively provided for the waste heat of the flue gas of the gas turbine;
(3) The fuel cost model of the gas combined cooling heating and power system is as follows:
in the formula (I), the compound is shown in the specification,
the fuel cost of a gas combined cooling heating and power system; w is a gas Is the price of the gas; />
Electric power output by the gas combined cooling heating and power system; l is the low heating value of natural gas; />
The operation efficiency of a gas combined cooling heating and power system is improved;
(4) The operation and maintenance cost calculation formula of the gas combined cooling heating and power system is as follows:
in the formula (I), the compound is shown in the specification,
the operation and maintenance cost of the gas combined cooling heating and power system is reduced; />
The proportional coefficient of the operation and maintenance cost of the gas combined cooling heating and power system is calculated; />
Electric power output by the gas combined cooling heating and power system;
2) Establishing an optimization planning model of the comprehensive energy microgrid, wherein the total cost of the comprehensive energy microgrid in the whole life cycle is taken as a target function, and the maximum load constraint, the power balance constraint, the self-sufficient probability constraint, the energy supply equipment operation constraint and the energy storage equipment operation constraint are also taken as the target function;
3) And the comprehensive energy microgrid optimization planning comprises equipment configuration and operation scheduling.
2. The method as claimed in claim 1, wherein the energy conversion device model in step 1) comprises:
(1) Energy efficiency output model of the energy conversion device:
P b ＝C ab P a (5)
in the formula, C ab Is the coupling conversion coefficient between the input energy a and the output energy b; p is a Is the power of the input energy source a; p is b Is the power of the input energy source b;
(2) Maintenance cost model:
in the formula (I), the compound is shown in the specification,
the operation and maintenance cost of the energy conversion device at the moment t; n is a radical of Trans The total number of energy conversion devices; />
The maintenance cost coefficient of the mth type energy conversion device; p is m (t) is the output power of the mth type energy conversion device at the moment t; Δ t is the scheduling interval.
3. The method for planning the comprehensive energy microgrid considering comprehensive energy supply reliability as claimed in claim 1, wherein the power storage equipment model in step 1) comprises:
(1) Dynamic model:
wherein SOC (t) is the charge of the electricity storage unit at the time t; delta is the self-discharge rate of the electricity storage unit;
the charging and discharging powers of the electricity storage units are respectively; />
The charge and discharge efficiency of the electricity storage units are respectively; e SOC Is the rated capacity of the power storage unit; Δ t is a scheduling time interval;
(2) Energy loss model:
in the formula (I), the compound is shown in the specification,
the transmission loss cost of the power storage device at the time t; />
Is the unit transmission loss cost of the electricity storage device;
the charging and discharging power of the electricity storage units respectively; />
The charge and discharge efficiencies of the electricity storage units are respectively.
4. The method as claimed in claim 1, wherein the heat storage equipment model in step 1) comprises:
(1) Dynamic model:
in the formula, H HS (t) is the heat of the heat storage unit at the moment t; k is a radical of formula LOSS The heat dissipation rate of the heat storage unit;
the heat charging and discharging powers of the heat storage units are respectively; />
The heat storage units respectively have the charge and discharge efficiency; delta t is a scheduling time interval;
(2) The loss cost model is:
in the formula (I), the compound is shown in the specification,
the transmission loss cost of the heat storage device at the moment t; />
The unit loss cost of the heat storage device; k is a radical of LOSS The heat dissipation rate of the heat storage unit; />
The heat charging and discharging powers of the heat storage units are respectively; />
The heat storage units respectively have the charge-discharge efficiency; Δ t is the scheduling interval.
5. The method as claimed in claim 1, wherein the function of the total cost of the integrated energy microgrid within the full life cycle in step 2) as an objective function is as follows:
min{C IN +C OP +C RE } (11)
in the formula, C IN The cost of equipment construction; c OP The economic cost of the comprehensive energy microgrid under the normal operation condition is reflected as the system operation cost; c RE Cost is converted for reliability, economic loss caused by insufficient energy electricity/heat/cold sources due to outage of equipment in the comprehensive energy microgrid is shown, and the larger the numerical value is, the more serious the influence of unit failure on the energy supply reliability of the comprehensive energy microgrid is;
the calculation formula of the equipment construction cost is as follows:
in the formula, N m The construction quantity of the mth type equipment; c inst,i Investment construction cost per unit capacity for the mth type of equipment; m m The installation capacity of the m-th equipment; c scra,m The residual value of the m-th equipment; y is the planned life cycle; r is the actual interest rate;
the calculation formula of the system operation cost is as follows:
in the formula (I), the compound is shown in the specification,
fuel cost for class m devices; />
For maintenance of operation of class m devicesUsing;
the calculation formula of the reliability conversion cost is as follows:
C RE ＝w elec LOEE elec +w heat LOEE heat +w cold LOEE cold (14)
in the formula, LOEE elec 、LOEE heat 、LOEE cold Respectively providing the energy shortage expectations of the electricity, heat and cold energy sources under the given planning configuration scheme; w is a elec 、w heat 、w cold The energy loss values of electric energy, heat energy and cold energy are respectively.
6. The comprehensive energy microgrid planning method considering comprehensive energy supply reliability as claimed in claim 1, wherein the step 3) comprises:
firstly, optimizing a device configuration layer, considering the constraints in the aspects of cost and load based on the overall load level of the comprehensive energy in the comprehensive energy microgrid, and giving the selection of energy supply and energy storage devices in the comprehensive energy microgrid by taking the type and the number of the devices as optimization variables in the alternative energy supply and storage devices according to an objective function; from the angle of the algorithm, the optimization problem of the planning layer belongs to the nonlinear integer programming problem, and is difficult to obtain an analytic solution, so the optimization problem of the planning layer model is solved by adopting a quantum particle swarm algorithm, the optimization variables of the planning layer are subjected to particle coding, a planning layer initial solution set is generated, namely, an initial particle swarm composed of different types of equipment capacity variables is randomly generated, the initial energy in an energy storage device is set, and parameters such as the population scale, the position, the speed, the iteration frequency and the like of the particles in the algorithm are set, so that the iteration frequency is 1;
secondly, optimizing an operation scheduling layer, considering comprehensive energy microgrid power balance constraint, energy supply equipment operation constraint and energy storage equipment operation constraint aiming at a time-by-time load demand curve in a planning time interval, combining an optimization result of an equipment configuration layer, and providing a time-by-time optimization scheduling scheme of each equipment by taking starting, stopping and output of the energy storage equipment as optimization variables; from the angle of the algorithm, the optimization problem of the scheduling layer is a mixed nonlinear optimization problem, the method adopts the quantum particle swarm algorithm to solve, carries out particle coding on the optimization variable of the planning layer, generates an initial solution set of the planning layer, analyzes the output intervals of the unit and the energy storage device, and returns the optimization result of the operation layer to the planning layer as the particle optimization range according to the output intervals, thereby optimizing and calculating the planning layer model.
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