CN113078689A - Load tracking management operation strategy for comprehensive energy optimization configuration - Google Patents
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Abstract
The invention discloses a load tracking management operation strategy for comprehensive energy optimization configuration, which comprises the steps of firstly determining the reference heat transfer power of a thermodynamic system layer under the current capacity configuration by using heat to determine power, and calculating the corresponding reference electric power; then, an electric load tracking link is carried out, the actual electric power of each link of the electric power system layer is calculated, a heat load tracking link is further carried out, and the actual heat transfer power of the thermal power system layer is calculated; and (4) iteration, entering the next calculation period, and calculating each optimization target and fitness function under the current capacity configuration when the termination time is reached. The load tracking management operation strategy provides a specific execution process during the solution of the optimal configuration, is beneficial to enabling the comprehensive energy network to efficiently operate under a certain optimization purpose, tracks the load change and provides the working condition of each unit under the current capacity configuration, and is beneficial to reasonably adjusting the comprehensive energy network to enable the comprehensive energy network to economically and efficiently operate.
Description
Technical Field
The invention belongs to the technical field of comprehensive energy supply, and particularly relates to a load tracking management operation strategy for comprehensive energy optimal configuration.
Background
Aiming at the power supply problem of remote areas, the power supply of the remote areas is generally realized at home and abroad by building a micro-grid; meanwhile, in order to solve the problem of heat supply in remote areas, the realization of combined heat and power is generally considered on the basis of the original micro-grid. The concept of combined heat and power has been long, and in the early days, it mainly means that a thermal power plant delivers heat energy to users while delivering electric energy to users, but with the development and utilization of renewable energy sources such as solar energy, wind energy and the like, combined heat and power has once again received great attention as a typical and efficient energy supply mode. The combined heat and power technology has the advantages of energy conservation, environmental protection, high efficiency, peak clipping and valley filling, high energy utilization rate and the like, can provide various energies such as electric power, heating power and the like for users at the same time, can absorb clean energy such as solar energy and the like on the spot, and realizes the environmental protection and economic utilization of the energy. By taking Qinghai province as an example, the Qinghai province has remarkable advantages of light resources and land resources, strong light radiation and wide area of unused land, establishes a novel light, storage and heat integrated energy supply system which mainly uses photovoltaic power generation and comprehensively utilizes the advanced technologies of distributed power generation, energy storage and heat storage, and becomes an effective way for solving the problem of power supply and heat supply in remote areas of the Qinghai province.
In order to ensure the safe operation of the novel energy supply system and meet the stability requirement of power supply and heat supply, reasonable capacity configuration needs to be carried out on the system composition. The existing optimal configuration method for the alternating current (direct current) microgrid system usually takes the operation cost or the energy utilization rate as an optimization target or carries out multi-objective optimization; however, most of the existing patents on optimization configuration of the integrated energy network are on the optimization method level, and the adjustment starts from an objective function or a fitness function, so that fewer patents are involved in the specific operation process of the system. When the external environment changes and the electrical load or the thermal load correspondingly changes, the working state of the system may change, and the working state of a thermodynamic system layer or an electrical system layer needs to be confirmed and the operation method needs to be adjusted; therefore, in order to maintain stable operation of the integrated energy system under a certain capacity configuration, the specific operation process of the system is very important.
However, the existing integrated energy network has less research on the operation process, and the influence on the integrated energy system and the needed adjustment method when the thermal load or the electrical load changes are slightly insufficient. The Chinese patent with the publication number of CN108510404A provides a multi-microgrid ordered grid-connected optimization scheduling method, device and system, and the main content is to construct an optimization objective function and a limiting condition, and decompose a multi-microgrid optimization model into a main problem and a sub-problem according to the discreteness and continuity of variables; and solving the main problem and the sub-problem according to the parameters of each microgrid and the electricity price information to obtain a scheduling plan. The technology is mainly used for a centralized multi-microgrid energy management system to coordinate multi-microgrid energy transactions, overcome disturbance of uncertain factors, improve operation economy and energy utilization efficiency and help system operators to make optimal operation decisions; however, the optimized operation only considers a single influence factor, global closed-loop management is not formed, and the patent technology does not make output power of each unit track load change and make adjustment, and can not ensure that the system can stably operate under various conditions.
Disclosure of Invention
In view of the above, the present invention provides a load tracking management operation strategy of integrated energy optimization configuration, so as to realize that the new energy supply system tracks and stably operates the load under any capacity optimization configuration scheme.
A load tracking management operation strategy of comprehensive energy optimization configuration is applied to an iterative operation process of a new energy supply system under any capacity optimization configuration scheme, wherein the new energy supply system comprises a photovoltaic power generation unit, a converter unit, an electricity storage unit, a heat storage unit and an electric heat conversion unit, the photovoltaic power generation unit, the electricity storage unit and the converter unit form an electric power system layer for supplying power to an electric load, the electric heat conversion unit and the heat storage unit form a thermal power system layer for supplying heat to the electric load, and the electric heat conversion unit comprises a heat pump and an electric boiler;
the load tracking management operation strategy specifically comprises the following steps:
(1) determining the power by heat, and calculating and determining the reference heat transfer power and the reference electric power of the thermodynamic system layer under the current capacity configuration scheme;
(2) calculating the actual electric power of the electricity storage unit through an electric load tracking link, and judging the energy supply condition;
(3) calculating the actual heat transfer power of a thermodynamic system layer through a thermal load tracking link;
(4) and (4) performing an iterative calculation process at the next moment according to the steps (1) to (3), when the iterative time reaches a set length, solving an optimized objective function or fitness function of the system under the current capacity allocation scheme according to the iterative calculation result, and further determining the optimal capacity allocation scheme of the system according to the function.
Further, the specific implementation process of the step (1) is as follows: firstly, defining the heat production power H of the photovoltaic-heat pump device at the moment t* pvt-pum(t)＝min{Hpvt(t),Hpum-maxIn which H ispvt(t) the heat collection power of the photovoltaic power generation unit at the time t, Hpum-maxThe maximum heat production power of the heat pump;
then, the reference thermal power H of the heat storage unit at the time t is determined* sto(t), calculating the reference heat transfer power and the reference electric power of the heat pump and the electric boiler, and concretely dividing the reference heat transfer power and the reference electric power into the following four conditions:
the following conditions are: when H is present* pvt-pum(t)≥Hload(t)+Hloss1(t) and Q (t) ≧ QrateWhen the heat storage unit is full, H* sto(t)＝0，H* pum(t)＝Hload(t)+Hloss1(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝0，H* boi(t)＝0；
Case two: when H is present* pvt-pum(t)≥Hload(t)+Hloss1(t) and Q (t) < QrateWhen the heat storage unit stores heat, H* pum(t)＝Hload(t)+Hloss1(t)+H* sto(t)+Hloss2(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝0，H* boi(t)＝0；
If H is* pvt-pum(t)-Hload(t)-Hloss1(t)≥Hin-max+Hloss2(t)，
Then H* sto(t)＝min{Hin-max,(Qrate-Q(t))/Δt}；
If H is* pvt-pum(t)-Hload(t)-Hloss1(t)＜Hin-max+Hloss2(t)，
Then H* sto(t)＝min{H* pvt-pum(t)-Hload(t)-Hloss1(t)-Hloss2(t),(Qrate-Q(t))/Δt}；
Case (c): when H is present* pvt-pum(t)＜Hload(t)+Hloss1(t) and Q (t) is not less than 0, when the heat storage unit releases heat, H* boi(t)＝min{Hload(t)+Hloss1(t)-H* pvt-pum(t)-H* sto(t),Hboi-max}，H* pum(t)＝H* pvt-pum(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝H* boi(t)/COPboi；
If H is* pvt-pum(t)+Hout-max≥Hloss1(t)+Hload(t)，
Then H* sto(t)＝-min{Hloss1(t)+Hload(t)-H* pvt-pum(t),Q(t)/Δt}；
If H is* pvt-pum(t)+Hout-max＜Hloss1(t)+Hload(t)，
Then H* sto(t)＝-min{Hout-max,Q(t)/Δt}；
Case four: when H is present* pvt-pum(t)＜Hload(t)+Hloss1(t) and Q (t) < 0, when the heat storage unit is completely discharged, then H* sto(t)＝0，H* pum(t)＝H* pvt-pum(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝H* boi(t)/COPboi，H* boi(t)＝min{Hloss1(t)+Hload(t)-H* pvt-pum(t),Hboi-max}；
Wherein: hload(t) is the magnitude of the thermal load at time t, Hloss1(t) the heat loss power of the system when supplying heat to the heat load at time t, Q (t) the heat storage capacity of the heat storage unit at time t, QrateFor the rated heat storage capacity of the heat storage unit, H* sto(t) reference Heat transfer Power of the Heat storage Unit at time t, H* pum(t) and P* pum(t) reference heat transfer power and reference electric power of the heat pump at time t, H* boi(t) and P* boi(t) reference heat transfer power and reference electric power, H, of the electric boiler at time t, respectivelyloss2(t) the heat loss power H when the system supplies heat to the heat storage unit at time tin-maxIs the maximum heat absorption power of the heat storage unit, Hout-maxIs the maximum heat release power of the heat storage unit, Δ t is the iteration step length, Hboi-maxIs the maximum heat production power, COP, of the electric boilerpumIs the average energy efficiency ratio, COP, of the heat pumpboiIs the average energy efficiency ratio of the electric boiler.
Further, the actual electric power of the electricity storage unit is calculated through an electric load tracking link in the step (2), and the following four conditions are specifically divided:
case 1: when P is presentpvt(t)≥Pload(t)+P* pum(t)+P* boi(t) and SOC (t) ≧ SOCmaxWhen the power storage unit is full, Pbat(t)＝0；
Case 2: when P is presentpvt(t)≥Pload(t)+P* pum(t)+P* boi(t) and SOC (t) < SOCmaxWhen the power storage unit is charged;
if Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t)≥Pbat-max，
Then P isbat(t)＝min{Pbat-max,(SOCmax-SOC(t))/Δt}；
If Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t)＜Pbat-max，
Then P isbat(t)＝min{Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t),(SOCmax-SOC(t))/Δt}；
Case 3: when P is presentpvt(t)＜Pload(t)+P* pum(t)+P* boi(t) and SOC (t) ≧ SOCminAt this time, the electricity storage unit discharges, and the following three conditions are specifically subdivided:
case 3.1: when- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]＜Pbat-max，
And- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]＜(SOC(t)-SOCmin) At the time of/at, the time of the,
then P isbat(t)＝Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t)；
Case 3.2: when- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]＜Pbat-max，
And- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]≥(SOC(t)-SOCmin) At the time of/at, the time of the,
then P isbat(t)＝-(SOC(t)-SOCmin)/Δt；
Case 3.3: when- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]≥Pbat-maxWhen the temperature of the water is higher than the set temperature,
then P isbat(t)＝-min{Pbat-max,(SOC(t)-SOCmin)/Δt}；
Case 4: when P is presentpvt(t)＜Pload(t)+P* pum(t)+P* boi(t) and SOC (t) < SOCminWhen the electricity storage unit is completely discharged, Pbat(t)＝0；
Wherein: ppvt(t) the generated power of the photovoltaic power generation unit at time t, Pload(t) is the magnitude of the electrical load at time t, P* pum(t) is the reference electric power of the heat pump at time t, P* boi(t) is reference electric power of the electric boiler at time t, SOC (t) is electric charge of the electric storage unit at time t, SOCmaxIs the maximum charge capacity, SOC, of the electricity storage unitminIs the minimum charge of the electricity storage unit, Pbat(t) actual electric power of the storage unit at time t, Pbat-maxAnd delta t is the maximum charge-discharge power of the electricity storage unit and is the iteration step length.
Further, when the actual electric power of the electricity storage unit is calculated from case 1, case 2 or case 3.1 in the step (2), the actual electric power P of the heat pump is calculated at time tpum(t)＝P* pum(t), the actual electric power P of the electric boiler at time tboi(t)＝P* boi(t), the actual heat transfer power H of the heat storage unit at time tsto(t)＝H* sto(t), under the conditions, the reference power of the thermodynamic system layer can be met, the electric load requirement can be met, and the whole system at the moment of tPower supply Psue(t)＝Pload(t)。
Further, when the actual electric power of the electricity storage unit is calculated in the step (2) according to the case 3.2, the case 3.3 or the case 4, the thermodynamic system layer reference power is preferably satisfied in these cases, specifically:
when P is presentpvt(t)≥Pbat(t)+P* pum(t)+P* boi(t), the actual electric power P of the heat pump is obtained at the time tpum(t)＝P* pum(t), the actual electric power P of the electric boiler at time tboi(t)＝P* boi(t), the actual heat transfer power H of the heat storage unit at time tsto(t)＝H* sto(t), in this case, the reference power of the thermodynamic system layer can be met, but the electric load demand cannot be met, and the power supply power P of the whole system at the moment tsue(t)＝Ppvt(t)-Pbat(t)-Ppum(t)-Pboi(t)；
When P is presentpvt(t)＜Pbat(t)+P* pum(t)+P* boi(t), under the condition, the reference power of the thermodynamic system layer cannot be met, the electric load requirement cannot be met, and the power supply power P of the whole system at the time of tsueWhen t is 0, the process proceeds to step (3).
Further, the actual heat transfer power of the thermodynamic system layer is calculated through a heat load tracking link in the step (3), and the following three conditions are specifically adopted:
case a: when P is present* boi(t) > 0 and Ppvt(t)≥Pbat(t)+P* pumWhen (t) is greater than Ppum(t)＝P* pum(t)，Pboi(t)＜P* boi(t) and Pboi(t)＝Ppvt(t)-Pbat(t)-P* pum(t)，Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)，Hboi(t)＝COPboi×Pboi(t)，Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)；
Case B: when P is present* boi(t) > 0 and Ppvt(t)＜Pbat(t)+P* pumWhen (t) is greater than Ppum(t)＜P* pum(t) and Ppum(t)＝Ppvt(t)-Pbat(t)，Hboi(t)＝Pboi(t)＝0，Hsuh(t)＝Hpum(t)-Hsto(t)-Hloss1(t)，Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)；
Case C: when P is present* boiWhen (t) is less than or equal to 0, Ppum(t)＜P* pum(t)，Hboi(t)＝Pboi(t) ═ 0, specifically, the following three cases are subdivided:
case C1: when H is present* stoWhen (t) > 0, Ppum(t)＝Ppvt(t)-Pbat(t)，Hpum(t)＝COPpum×Ppum(t)，
Hsto(t)＝max{0,Hpum(t)-Hload(t)-Hloss1(t)-Hloss2(t)}，
Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)-Hloss2(t)；
Case C2: when H is present* sto(t) is less than or equal to 0 and-H* sto(t)≥min{Hout-maxQ (t)/Δ t },
Ppum(t)＝Ppvt(t)-Pbat(t)，Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)，
Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)；
case C3: when H is present* sto(t) is less than or equal to 0 and-H* sto(t)＜min{Hout-maxQ (t)/Δ t },
H* sto2(t)＝-min{Hout-max,Q(t)/Δt}，P* pum2(t)＝Ppvt(t)-Pbat(t)，
H* pum2(t)＝COPpum×P* pum2(t)；
in this case, if H* pum2(t)-H* sto2(t)≤Hload(t)+Hloss1(t) then Ppum(t)＝P* pum2(t)，
Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)，
Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)
In this case, if H* pum2(t)-H* sto2(t)＞Hload(t)+Hloss1(t) then Ppum(t)＝P* pum2(t)，
Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* pum2(t)-Hload(t)-Hloss1(t)，Hsuh(t)＝Hload(t)；
Wherein: p* boi(t) is the reference electric power of the electric boiler at time t, Ppvt(t) the generated power of the photovoltaic power generation unit at time t, Pbat(t) actual electric power of the storage unit at time t, P* pum(t) is the reference electric power of the heat pump at time t, Ppum(t) actual electric power of the heat pump at time t, Pboi(t) actual electric power of the electric boiler at time t, Hsuh(t) heating power of the whole system at time t, Hpum(t) actual heat transfer power of the heat pump at time t, Hboi(t) actual heat transfer power of the electric boiler at time t, Hsto(t) actual heat transfer power of the heat storage unit at time t, Hload(t) is the magnitude of the thermal load at time t, Hloss1(t) heat loss power, COP, when the system supplies heat to the thermal load at time tboiAverage energy efficiency ratio, COP, of electric boilerpumIs the average energy efficiency ratio of the heat pump, H* sto(t) reference Heat transfer Power of the Heat storage Unit at time t, Hloss2(t) the heat loss power H when the system supplies heat to the heat storage unit at time tout-maxThe maximum heat release power of the heat storage unit is Q (t), the heat storage amount of the heat storage unit at the moment t is Q (t), delta t is iteration step length, H* sto2(t)、H* pum2(t) and P* pum2(t) are all intermediate variables.
Further, when the iterative calculation process at the next moment is performed in the step (4), the heat storage amount of the heat storage unit and the electric charge amount of the electricity storage unit are calculated and determined by the following formulas;
Q(t+1)＝Q(t)+Hsto(t)×Δt
SOC(t+1)＝SOC(t)+Pbat(t)×Δt
wherein: q (t +1) and Q (t) are the heat storage amount of the heat storage unit at the time t +1 and the time t respectively, SOC (t +1) and SOC (t) are the charge amount of the electricity storage unit at the time t +1 and the time t respectively, delta t is iteration step length, P is the voltage of the electricity storage unitbat(t) actual electric power of the storage unit at time t, HstoAnd (t) is the actual heat transfer power of the heat storage unit at the moment t.
The load tracking management operation strategy provides a specific operation mode of the novel light, storage and heat energy supply system based on any optimal configuration scheme, provides a specific execution process during optimal configuration solving, is beneficial to enabling the comprehensive energy network to operate efficiently under a certain optimization purpose, tracks load changes and provides working conditions of each unit under current capacity configuration, and is beneficial to reasonably adjusting the comprehensive energy network to enable the comprehensive energy network to operate economically and efficiently.
Drawings
FIG. 1 is a schematic flow chart of the step of determining the electric power by heat according to the present invention.
Fig. 2 is a schematic flow chart of an electrical load tracking procedure according to the present invention.
FIG. 3 is a schematic flow chart of an electric heat charge tracking link according to the present invention.
FIG. 4(a) is a graph showing the predicted changes of the generated power, the electrical load and the thermal load of a typical summer day 1MW PV/T unit in a remote area.
FIG. 4(b) is a graph of predicted changes in power generation, electrical load, and thermal load of a typical winter daily 1MW PV/T unit in a remote area.
FIG. 5 is a graph of power and energy changes of a typical summer solar power system layer of the region under the multi-objective optimization configuration.
FIG. 6 is a graph of power and energy changes of a typical thermal system layer in summer in the region under the multi-objective optimization configuration.
FIG. 7 is a graph of power and energy changes of a typical daily power system layer in winter in the region under the multi-objective optimization configuration.
FIG. 8 is a graph of power and energy changes of a typical thermal system layer in winter in the area under the multi-objective optimization configuration.
Fig. 9 is a graph of power and energy variation of a typical daily power system layer in winter in the area under the LPSP minimization target.
Fig. 10 is a graph of power and energy variation of a typical thermal system layer in winter in the area under the LPSP minimization objective.
Detailed Description
In order to more specifically describe the present invention, the following detailed description is provided for the technical solution of the present invention with reference to the accompanying drawings and the specific embodiments.
Considering that the combined heat and power type microgrid system is in an island working condition and adopts a load tracking management strategy to operate in order to ensure the stable supply of electric heat for users, the invention simultaneously regulates and controls the power and energy states of a power system layer and a thermal system layer of the microgrid system according to the change rule of loads, wherein:
1) heating priority of a thermodynamic system layer: PV/T-heat pump unit > heat storage unit > electric boiler;
2) thermodynamic system layer load priority: thermal load > heat storage unit;
3) power supply priority of the power system: PV/T cell > storage cell;
4) electric power system layer load priority: the heat pump, the electric boiler, the electric load and the electricity storage unit.
In the present embodiment, the maximum electric load on a typical day in summer of the remote village is 720kW, the maximum heat load is 564kW, the maximum electric load on a typical day in winter is 746kW, and the maximum heat load is 1128 kW. Fig. 4 shows predicted variation curves of the generated power, the electrical load and the thermal load of the 1MW PV/T unit in the typical summer and the typical winter days of the remote village, wherein the photovoltaic conversion efficiency and the photothermal conversion efficiency of the PV/T unit are set to 15% and 22% respectively according to an example, the electricity storage unit adopts a lithium storage battery, and the heat storage unit adopts molten salt phase change heat storage.
Example one, example analysis is performed under the multi-objective optimization configuration.
According to the prediction data of the PV/T power generation power and load in the typical summer of the remote village, the optimal configuration result of the cogeneration-type microgrid system is obtained under the multi-objective optimal configuration as follows: the rated power generation power of the PV/T unit is 2.762MW, the power storage unit is 10010 groups, the rated electric power of the converter unit is 1040kW, the rated electric power of the heat pump is 280.0kW, the rated electric power of the electric boiler is 573.9kW, and the rated heat storage capacity of the heat storage unit is 10172 kWh. Based on the capacity configuration scheme and the summer typical day 1MW PV/T unit generated power, electrical load and thermal load data of the region, the load tracking management operation strategy of the invention is adopted to obtain the power and energy change curve of the summer typical day power system layer as shown in FIG. 5 and the power and energy change curve of the summer typical day thermodynamic system layer as shown in FIG. 6.
Firstly, as shown in fig. 1, the thermodynamic system layer reference heat transfer power under the current capacity configuration is determined by using heat to fix the electricity, and then the corresponding reference electric power is calculated.
Then, the following is obtained through the electrical load tracking link shown in fig. 2: in a 1-10 h period, the generated power of the PV/T unit is difficult to meet the load requirement, at the moment, the electricity storage unit is in a discharging state, and the charge quantity is reduced; in a period of 10-17 h, the power generation power of the PV/T unit is obviously increased, the residual electric quantity exists while the load requirement is met, the electricity storage unit is in a charging state, and the electric charge quantity is increased; in a 17-24 h period, the generated power of the PV/T unit is reduced to 0, the electricity storage unit discharges electricity, and the charge quantity is reduced.
Further, the following is obtained through the thermal load tracking link shown in fig. 3: the electric power of the electric boiler is constant 0, namely, the heat load is only supplied by the heat pump and the heat storage unit, and under the capacity configuration, the phenomenon of light abandon does not occur; in the 1-6 h period, the PV/T unit does not generate heat, and at the moment, the heat storage unit only supplies heat for the heat load, so that the heat storage amount is reduced; in a period of 6-8 h, the PV/T-heat pump device generates insufficient heat, at the moment, the heat load is still mainly supplied by the heat storage unit, and the heat storage amount is reduced; in the 8-18 h period, the heat production of the PV/T unit is increased, the heat load is supplied by the heat pump, the heat storage of the redundant heat is performed by the heat storage unit, and the heat storage amount is increased; in a period of 18-24 h, the heat production of the PV/T-heat pump device is gradually reduced to 0, the heat load is supplied by the heat storage unit, and the heat storage amount is reduced.
According to the forecast data of the PV/T power generation power and load of the remote village in winter typical days, the optimal configuration result of the cogeneration type microgrid system is obtained under the multi-objective optimal configuration as follows: the rated power generation power of the PV/T unit is 4.381MW, the group of the power storage units is 14317, the rated electric power of the converter unit is 1821kW, the rated electric power of the heat pump is 1634kW, the rated electric power of the electric boiler is 1377kW, and the rated heat storage capacity of the heat storage unit is 10016 kWh. Compared with the optimal configuration result in the typical day in summer, the PV/T unit capacity is obviously reduced and the heat load is obviously increased in the typical day in winter, so that the capacity of each unit is obviously increased. Based on the capacity allocation scheme and the winter typical daily 1MW PV/T unit generated power, electrical load and thermal load data of the area, the load tracking management operation strategy of the invention is adopted to obtain the power and energy change curve of the winter typical daily power system layer as shown in FIG. 7 and the power and energy change curve of the winter typical daily thermodynamic system layer as shown in FIG. 8.
And (3) through an electric load tracking link: in a period of 1-9 h, the generated power of the PV/T unit is difficult to meet the load requirement, at the moment, the electricity storage unit is in a discharging state, and the charge quantity is reduced; in a period of 10-17 h, the generated power of the PV/T unit is obviously increased, and residual electric quantity exists while the load requirement is met, so that the electricity storage unit is in a charging state, and the electric charge quantity is increased; note that certain light abandoning phenomenon exists in the period of 13-17 h, but the maximum light abandoning power is less than 40 kW.
And (3) tracking the link through thermal load: in a 1-7 h period, the PV/T unit does not generate heat, the electric boiler and the heat storage unit supply heat for heat load, wherein in the 1-3 h period, the electric boiler and the heat storage unit generate heat simultaneously; in a period of 3-8 h, the heat storage unit completely releases heat, and only the electric boiler supplies heat for the heat load; in the period of 8-18 h, the heat production of the PV/T unit is increased, the heat pump starts to work, the electric boiler basically does not work, and at the moment, when the heat produced by the PV/T-heat pump device meets the heat load requirement, the residual heat is still used for storing the heat; in a 19-24 h period, the PV/T unit does not generate heat any more, the heat pump stops working, and the heat load is supplied mainly by heat released by the heat storage unit.
And example two, performing example analysis under the condition of single-target capacity optimization configuration.
In order to guarantee the annual electric heating supply of remote areas, only the example analysis of the load tracking management operation strategy under the single target capacity optimization configuration in typical days in winter is given.
With LPSP minimization as the optimal configuration target, a certain set of capacity configuration schemes is obtained as follows: the rated power generation power of the PV/T unit is 8MW, the power storage units are 12724 groups, the rated electric power of the converter unit is 1931kW, the rated electric power of the heat pump is 871.0kW, the rated electric power of the electric boiler is 372.4kW, and the rated heat storage amount of the heat storage units is 24686 kWh. Based on the capacity configuration scheme, the load tracking management operation strategy is adopted, and the power and energy change situation of the power system layer of the winter typical daily microgrid system is shown in fig. 9, and the power and energy change situation of the thermodynamic system layer of the winter typical daily microgrid system is shown in fig. 10.
Under the various capacity configuration schemes, the load tracking management operation strategy is applied to finally obtain corresponding power and energy curve graphs of the power system layer and the thermal system layer of the microgrid system, and the load tracking management operation strategy can meet the requirements of power supply and heat supply stability in remote areas under any optimal configuration scheme.
The foregoing description of the embodiments is provided to enable one of ordinary skill in the art to make and use the invention, and it is to be understood that other modifications of the embodiments, and the generic principles defined herein may be applied to other embodiments without the use of inventive faculty, as will be readily apparent to those skilled in the art. Therefore, the present invention is not limited to the above embodiments, and those skilled in the art should make improvements and modifications to the present invention based on the disclosure of the present invention within the protection scope of the present invention.
Claims (8)
1. A load tracking management operation strategy of comprehensive energy optimization configuration is applied to an iterative operation process of a new energy supply system under any capacity optimization configuration scheme, wherein the new energy supply system comprises a photovoltaic power generation unit, a converter unit, an electricity storage unit, a heat storage unit and an electric heat conversion unit, the photovoltaic power generation unit, the electricity storage unit and the converter unit form an electric power system layer for supplying power to an electric load, the electric heat conversion unit and the heat storage unit form a thermal power system layer for supplying heat to the electric load, and the electric heat conversion unit comprises a heat pump and an electric boiler; the method is characterized in that the load tracking management operation strategy specifically comprises the following steps:
(1) determining the power by heat, and calculating and determining the reference heat transfer power and the reference electric power of the thermodynamic system layer under the current capacity configuration scheme;
(2) calculating the actual electric power of the electricity storage unit through an electric load tracking link, and judging the energy supply condition;
(3) calculating the actual heat transfer power of a thermodynamic system layer through a thermal load tracking link;
(4) and (4) performing an iterative calculation process at the next moment according to the steps (1) to (3), when the iterative time reaches a set length, solving an optimized objective function or fitness function of the system under the current capacity allocation scheme according to the iterative calculation result, and further determining the optimal capacity allocation scheme of the system according to the function.
2. The load tracking management operation policy of claim 1, wherein: the specific implementation process of the step (1) is as follows: firstly, defining the heat production power H of the photovoltaic-heat pump device at the moment t* pvt-pum(t)＝min{Hpvt(t),Hpum-maxIn which H ispvt(t) the heat collection power of the photovoltaic power generation unit at the time t, Hpum-maxFor maximum heat production of heat pumpPower;
then, the reference thermal power H of the heat storage unit at the time t is determined* sto(t), calculating the reference heat transfer power and the reference electric power of the heat pump and the electric boiler, and concretely dividing the reference heat transfer power and the reference electric power into the following four conditions:
the following conditions are: when H is present* pvt-pum(t)≥Hload(t)+Hloss1(t) and Q (t) ≧ QrateWhen the heat storage unit is full, H* sto(t)＝0，H* pum(t)＝Hload(t)+Hloss1(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝0，H* boi(t)＝0；
Case two: when H is present* pvt-pum(t)≥Hload(t)+Hloss1(t) and Q (t) < QrateWhen the heat storage unit stores heat, H* pum(t)＝Hload(t)+Hloss1(t)+H* sto(t)+Hloss2(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝0，H* boi(t)＝0；
If H is* pvt-pum(t)-Hload(t)-Hloss1(t)≥Hin-max+Hloss2(t)，
Then H* sto(t)＝min{Hin-max,(Qrate-Q(t))/Δt}；
If H is* pvt-pum(t)-Hload(t)-Hloss1(t)＜Hin-max+Hloss2(t)，
Then H* sto(t)＝min{H* pvt-pum(t)-Hload(t)-Hloss1(t)-Hloss2(t),(Qrate-Q(t))/Δt}；
Case (c): when H is present* pvt-pum(t)＜Hload(t)+Hloss1(t) and Q (t) is not less than 0, when the heat storage unit releases heat, H* boi(t)＝min{Hload(t)+Hloss1(t)-H* pvt-pum(t)-H* sto(t),Hboi-max}，H* pum(t)＝H* pvt-pum(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝H* boi(t)/COPboi；
If H is* pvt-pum(t)+Hout-max≥Hloss1(t)+Hload(t)，
Then H* sto(t)＝-min{Hloss1(t)+Hload(t)-H* pvt-pum(t),Q(t)/Δt}；
If H is* pvt-pum(t)+Hout-max＜Hloss1(t)+Hload(t)，
Then H* sto(t)＝-min{Hout-max,Q(t)/Δt}；
Case four: when H is present* pvt-pum(t)＜Hload(t)+Hloss1(t) and Q (t) < 0, when the heat storage unit is completely discharged, then H* sto(t)＝0，H* pum(t)＝H* pvt-pum(t)，P* pum(t)＝H* pum(t)/COPpum，P* boi(t)＝H* boi(t)/COPboi，H* boi(t)＝min{Hloss1(t)+Hload(t)-H* pvt-pum(t),Hboi-max}；
Wherein: hload(t) is the magnitude of the thermal load at time t, Hloss1(t) the heat loss power of the system when supplying heat to the heat load at time t, Q (t) the heat storage capacity of the heat storage unit at time t, QrateFor the rated heat storage capacity of the heat storage unit, H* sto(t) reference Heat transfer Power of the Heat storage Unit at time t, H* pum(t) and P* pum(t) reference heat transfer power and reference electric power of the heat pump at time t, H* boi(t) and P* boi(t) reference heat transfer powers of the electric boiler at times t, respectivelyReference electric power, Hloss2(t) the heat loss power H when the system supplies heat to the heat storage unit at time tin-maxIs the maximum heat absorption power of the heat storage unit, Hout-maxIs the maximum heat release power of the heat storage unit, Δ t is the iteration step length, Hboi-maxIs the maximum heat production power, COP, of the electric boilerpumIs the average energy efficiency ratio, COP, of the heat pumpboiIs the average energy efficiency ratio of the electric boiler.
3. The load tracking management operation policy of claim 1, wherein: in the step (2), the actual electric power of the electricity storage unit is calculated through an electric load tracking link, and the following four conditions are specifically adopted:
case 1: when P is presentpvt(t)≥Pload(t)+P* pum(t)+P* boi(t) and SOC (t) ≧ SOCmaxWhen the power storage unit is full, Pbat(t)＝0；
Case 2: when P is presentpvt(t)≥Pload(t)+P* pum(t)+P* boi(t) and SOC (t) < SOCmaxWhen the power storage unit is charged;
if Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t)≥Pbat-max，
Then P isbat(t)＝min{Pbat-max,(SOCmax-SOC(t))/Δt}；
If Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t)＜Pbat-max，
Then P isbat(t)＝min{Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t),(SOCmax-SOC(t))/Δt}；
Case 3: when P is presentpvt(t)＜Pload(t)+P* pum(t)+P* boi(t) and SOC (t) ≧ SOCminAt this time, the electricity storage unit discharges, and the following three conditions are specifically subdivided:
case 3.1: when- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]＜Pbat-max，
And- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]＜(SOC(t)-SOCmin) At the time of/at, the time of the,
then P isbat(t)＝Ppvt(t)-Pload(t)-P* pum(t)-P* boi(t)；
Case 3.2: when- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]＜Pbat-max，
And- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]≥(SOC(t)-SOCmin) At the time of/at, the time of the,
then P isbat(t)＝-(SOC(t)-SOCmin)/Δt；
Case 3.3: when- [ P ]pvt(t)-Pload(t)-P* pum(t)-P* boi(t)]≥Pbat-maxWhen the temperature of the water is higher than the set temperature,
then P isbat(t)＝-min{Pbat-max,(SOC(t)-SOCmin)/Δt}；
Case 4: when P is presentpvt(t)＜Pload(t)+P* pum(t)+P* boi(t) and SOC (t) < SOCminWhen the electricity storage unit is completely discharged, Pbat(t)＝0；
Wherein: ppvt(t) the generated power of the photovoltaic power generation unit at time t, Pload(t) is the magnitude of the electrical load at time t, P* pum(t) is the reference electric power of the heat pump at time t, P* boi(t) is reference electric power of the electric boiler at time t, SOC (t) is electric charge of the electric storage unit at time t, SOCmaxIs the maximum charge capacity, SOC, of the electricity storage unitminIs the minimum charge of the electricity storage unit, Pbat(t) actual electric power of the storage unit at time t, Pbat-maxΔ t is the maximum charge-discharge power of the electricity storage unitLong.
4. The load tracking management operation policy of claim 3, wherein: in the step (2), when the actual electric power of the electricity storage unit is calculated according to the condition 1, the condition 2 or the condition 3.1, the actual electric power P of the heat pump is calculated at the time tpum(t)＝P* pum(t), the actual electric power P of the electric boiler at time tboi(t)＝P* boi(t), the actual heat transfer power H of the heat storage unit at time tsto(t)＝H* sto(t), under the conditions, the reference power of the thermodynamic system layer can be met, the electric load requirement can be met, and the power supply power P of the whole system at the moment tsue(t)＝Pload(t)。
5. The load tracking management operation policy of claim 3, wherein: in the step (2), when the actual electric power of the electricity storage unit is calculated according to the case 3.2, the case 3.3 or the case 4, the thermodynamic system layer reference power is preferably satisfied in the cases, specifically:
when P is presentpvt(t)≥Pbat(t)+P* pum(t)+P* boi(t), the actual electric power P of the heat pump is obtained at the time tpum(t)＝P* pum(t), the actual electric power P of the electric boiler at time tboi(t)＝P* boi(t), the actual heat transfer power H of the heat storage unit at time tsto(t)＝H* sto(t), in this case, the reference power of the thermodynamic system layer can be met, but the electric load demand cannot be met, and the power supply power P of the whole system at the moment tsue(t)＝Ppvt(t)-Pbat(t)-Ppum(t)-Pboi(t)；
When P is presentpvt(t)＜Pbat(t)+P* pum(t)+P* boi(t), under the condition, the reference power of the thermodynamic system layer cannot be met, the electric load requirement cannot be met, and the power supply power P of the whole system at the time of tsueWhen t is 0, the process proceeds to step (3).
6. The load tracking management operation policy of claim 1, wherein: in the step (3), the actual heat transfer power of the thermodynamic system layer is calculated through a heat load tracking link, and the following three conditions are specifically adopted:
case a: when P is present* boi(t) > 0 and Ppvt(t)≥Pbat(t)+P* pumWhen (t) is greater than Ppum(t)＝P* pum(t)，Pboi(t)＜P* boi(t) and Pboi(t)＝Ppvt(t)-Pbat(t)-P* pum(t)，Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)，Hboi(t)＝COPboi×Pboi(t)，Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)；
Case B: when P is present* boi(t) > 0 and Ppvt(t)＜Pbat(t)+P* pumWhen (t) is greater than Ppum(t)＜P* pum(t) and Ppum(t)＝Ppvt(t)-Pbat(t)，Hboi(t)＝Pboi(t)＝0，Hsuh(t)＝Hpum(t)-Hsto(t)-Hloss1(t)，Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)；
Case C: when P is present* boiWhen (t) is less than or equal to 0, Ppum(t)＜P* pum(t)，Hboi(t)＝Pboi(t) ═ 0, specifically, the following three cases are subdivided:
case C1: when H is present* stoWhen (t) > 0, Ppum(t)＝Ppvt(t)-Pbat(t)，Hpum(t)＝COPpum×Ppum(t)，
Hsto(t)＝max{0,Hpum(t)-Hload(t)-Hloss1(t)-Hloss2(t)}，
Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)-Hloss2(t)；
Case C2: when H is present* sto(t) is less than or equal to 0 and-H* sto(t)≥min{Hout-maxQ (t)/Δ t },
Ppum(t)＝Ppvt(t)-Pbat(t)，Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)，
Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)；
case C3: when H is present* sto(t) is less than or equal to 0 and-H* sto(t)＜min{Hout-maxQ (t)/Δ t },
H* sto2(t)＝-min{Hout-max,Q(t)/Δt}，P* pum2(t)＝Ppvt(t)-Pbat(t)，
H* pum2(t)＝COPpum×P* pum2(t)；
in this case, if H* pum2(t)-H* sto2(t)≤Hload(t)+Hloss1(t) then Ppum(t)＝P* pum2(t)，
Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* sto(t)，
Hsuh(t)＝Hpum(t)+Hboi(t)-Hsto(t)-Hloss1(t)
In this case, if H* pum2(t)-H* sto2(t)＞Hload(t)+Hloss1(t) then Ppum(t)＝P* pum2(t)，
Hpum(t)＝COPpum×Ppum(t)，Hsto(t)＝H* pum2(t)-Hload(t)-Hloss1(t)，Hsuh(t)＝Hload(t)；
Wherein: p* boi(t) is the reference electric power of the electric boiler at time t, Ppvt(t) the generated power of the photovoltaic power generation unit at time t, Pbat(t) actual electric power of the storage unit at time t, P* pum(t) is the reference electric power of the heat pump at time t, Ppum(t) actual electric power of the heat pump at time t, Pboi(t) actual electric power of the electric boiler at time t, Hsuh(t) heating power of the whole system at time t, Hpum(t) actual heat transfer power of the heat pump at time t, Hboi(t) actual heat transfer power of the electric boiler at time t, Hsto(t) actual heat transfer power of the heat storage unit at time t, Hload(t) is the magnitude of the thermal load at time t, Hloss1(t) heat loss power, COP, when the system supplies heat to the thermal load at time tboiAverage energy efficiency ratio, COP, of electric boilerpumIs the average energy efficiency ratio of the heat pump, H* sto(t) reference Heat transfer Power of the Heat storage Unit at time t, Hloss2(t) the heat loss power H when the system supplies heat to the heat storage unit at time tout-maxThe maximum heat release power of the heat storage unit is Q (t), the heat storage amount of the heat storage unit at the moment t is Q (t), delta t is iteration step length, H* sto2(t)、H* pum2(t) and P* pum2(t) are all intermediate variables.
7. The load tracking management operation policy of claim 1, wherein: in the step (4), when the iterative calculation process at the next moment is performed, the heat storage amount of the heat storage unit and the charge amount of the electricity storage unit are calculated and determined by the following formulas;
Q(t+1)＝Q(t)+Hsto(t)×Δt
SOC(t+1)＝SOC(t)+Pbat(t)×Δt
wherein: q (t +1) and Q (t) are the heat storage amount of the heat storage unit at the time t +1 and the time t respectively, SOC (t +1) and SOC (t) are the charge amount of the electricity storage unit at the time t +1 and the time t respectively, delta t is iteration step length, P is the voltage of the electricity storage unitbat(t) actual electric power of the storage unit at time t, HstoAnd (t) is the actual heat transfer power of the heat storage unit at the moment t.
8. The load tracking management operation policy of claim 1, wherein: the strategy provides a specific operation mode of the novel light, storage and heat energy supply system based on any optimal configuration scheme, provides a specific execution process during optimal configuration solving, is favorable for enabling the comprehensive energy network to efficiently operate under a certain optimization purpose, tracks load changes and provides working conditions of all units under current capacity configuration, and is favorable for reasonably adjusting the comprehensive energy network to enable the comprehensive energy network to economically and efficiently operate.
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