CN110957722B - Day-ahead optimal scheduling method for micro energy network with electricity-to-gas equipment - Google Patents
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Abstract
The invention discloses a day-ahead optimization scheduling method for a micro energy network containing Power to Gas (P2G) equipment. Firstly, a micro energy network model for combined supply of electricity, gas, heat and cold is established in an energy concentrator mode. The energy concentrator comprises energy coupling equipment such as a micro-gas turbine, a P2G, an electric boiler, a gas boiler, an electric refrigerator, an absorption refrigerator and the like. Secondly, a day-ahead optimal economic dispatching model which takes the minimum running cost of the micro energy network and the P2G income into consideration is established, and the economy of the P2G on the micro energy network and the consumption capability of renewable energy are inspected. The economic dispatch model includes an objective function, an element model, and a network constraint. Finally, verification is carried out in a mode of establishing contrast, and the result shows that P2G plays a positive role in both system operation cost and renewable energy consumption.
Description
Technical Field
The invention belongs to the field of microgrid optimization scheduling of a power system, and particularly relates to a power, gas, heat and cold combined scheduling method of a micro energy grid comprising electricity-to-gas.
Background
Renewable energy sources such as wind energy, solar energy and the like are connected into a power grid, so that carbon emission caused by a traditional power generation mode is reduced. However, with the rapid increase of installed capacities of wind power and photovoltaic power, the phenomena of wind abandoning and light abandoning in some areas are increasingly serious. Mainly caused by the uncertainty of wind and light output, the inverse peak regulation, the inverse distribution of power supply and load in China, and the like.
Renewable energy is connected into the microgrid for local consumption, and the technical form and key technology of the renewable energy utilization problem energy internet can be effectively improved. The combined cooling heating and power technology optimizes the energy distribution of the microgrid, improves the energy utilization rate and meets the requirements of different energy loads such as electricity, gas, heat, cold and the like in the microgrid. The electric energy storage equipment in the microgrid is charged at the valley of the power load and discharged at the peak of the load, so that the fluctuation of the power grid can be smoothed, and the consumption capacity of the system to intermittent energy sources is improved. However, due to the cost of operation, the capacity of the electrical energy storage devices and their role are generally limited.
The Power to Gas (P2G) technology converts electric energy into hydrogen or methane. The hydrogen and methane have wide application, convenient transportation and small margin coefficient of gas storage cost, and are easy to realize long-time and large-scale storage. Compared with other storage forms of electric energy, such as water pumping energy storage and battery energy storage, the electric energy is stored in a gas form, so that the electric energy storage device has a wider prospect.
The methane generated by the P2G technology is injected into the natural gas network in a quantity and quality according with the safety regulations of the natural gas, so that the coupling degree of the power grid and the natural gas network is deepened, and the consumption capacity of the system on renewable energy sources is greatly enhanced. Therefore, the P2G is added into the dispatching operation of the micro energy network, and the method has good function and important significance.
Disclosure of Invention
The invention aims to solve the technical problem of providing a day-ahead optimal economic dispatching method of a micro energy network considering electricity to gas, which can improve the utilization rate of renewable energy.
The invention adopts the technical scheme that a day-ahead optimal economic dispatching method of a micro energy network considering electricity to gas comprises the following contents:
the electric gas conversion technology comprises two chemical reaction processes, wherein the first process is an electrolytic reaction of water molecules under the conditions of catalyst, high temperature and electrification, and the reaction finishes the conversion of electric energy into chemical energy. The second process is the reaction of hydrogen and carbon dioxide under high temperature and pressure conditions to produce natural gas, as shown in formulas 1 and 2.
The microgrid energy hub is used for describing the relation between various energy requirements (electricity, gas, heat and cold) on the load side and the supply and conversion of electric energy and natural gas on the supply side. Macroscopically, the energy conversion module can be divided into an energy input module, an energy conversion module, an energy storage module and an energy output module, and a relational expression as shown in formula 3 is established among the modules according to the energy conservation law:
P out ＝P in +P EH +ΔP s (3)
in the formula: p is in 、P EH 、ΔP s 、P out The energy input matrix, the energy conversion matrix, the energy storage output matrix and the energy output matrix of the energy concentrator are respectively.
The energy input matrix contains electrical energy and gas energy. When the fan and photovoltaic output are insufficient, the electric energy is provided by an external network:
in the formula: p wind 、P pv Respectively inputting electric energy for a fan and a photovoltaic,
respectively the electric energy and the gas energy purchased from the external network for the microgrid.
The energy conversion matrix describes the conversion relationships under different energy re-energy hubs:
in the formula:
electric energy consumed by the P2G equipment, the electric boiler and the electric refrigerator respectively;
respectively the gas energy consumed by the micro gas turbine and the gas boiler;
the power generation efficiency of the micro-combustion engine is obtained;
the conversion efficiency of the P2G equipment;
the heat efficiency of an electric boiler, a micro-gas turbine and a gas boiler is respectively;
the refrigeration efficiencies of the electric refrigerator and the absorption refrigerator respectively; xi shape 1 、ξ 2 Proportionality coefficient ξ for heating and cooling of heat energy produced by micro-combustion engine 1 +ξ 2≤ 1。
The energy output matrix contains all types of load requirements within the microgrid:
P out ＝[L e L g L h L c ] T (6)
in the formula: l is e 、L g 、L h 、L c Respectively represents four load powers of electricity, gas, heat and cold.
The micro-grid form studied in the invention only has two energy storage devices, namely electricity and gas, so that the energy storage output matrix is as follows:
in the formula: delta P se 、ΔP sg The output conditions of the electricity storage and the gas storage are respectively represented, the value is positive time energy release, and the value is negative time energy storage.
Establishing a daily electricity-to-gas multi-source energy storage type microgrid economic dispatching optimization model, which comprises an element model, a target function and constraints:
1. element model
(1) P2G model
And (4) making a P2G operation plan by predicting the next day electricity price, the hydrogen price and the natural gas price so as to achieve the maximum benefit. From the P2G model shown in fig. 1-3, the mathematical model of P2G can be expressed as:
in the formula:
is the methane which is synthesized by the synthesis of the methanol,
hydrogen generated from electrolysis of water but not participating in methane synthesis,
h consumed for P2G 2 ，η P2H In order to improve the efficiency of the hydrogen production by electrolyzing water,
the conversion efficiency of the P2G device.
(2) Micro-combustion engine model
The micro-combustion engine has the following relations between the power generation power and the heating power and the fuel consumption power:
the formula (9) is a relation function of the output electric energy and the consumed fuel of the micro-combustion engine; the formula (10) is a relation function of the output heat and the output electricity of the micro-combustion engine,
in order to generate the power for the micro-combustion engine,
in order to provide heating power for the micro-combustion engine,
consuming power for fuel, a 1 、b 1 、c 1 Is the coefficient of the functional expression in equation (9), a 2 、b 2 、c 2 Is the coefficient of the functional expression in equation (10).
(3) Energy storage battery model
The charge level and the running state of the energy storage battery have the following relations:
in the formula: soc (t + 1) and Soc (t) are the charge levels of the energy storage battery at the time t +1 and the time t respectively; q bat Is the energy storage battery capacity; mu.s ch 、μ dis 、μ sta All are variables with the value range of 0-1, respectively represent a charging mark, a discharging mark and a standing mark, and mu is dis +μ ch +μ sta ＝1；η ch 、η dis For the charging efficiency and the discharging efficiency, Δ t represents a time differential.
(4) Gas energy storage equipment model
The storage gas of the gas storage device in operation can have the following relationship:
W 1 ＝W 0 +∫Q ch (t)-Q dis (t)dt (12)
in the formula: w 0 、W 1 Respectively representing the energy storage level of the gas storage equipment before and after the operation time t; q ch (t)、Q dis And (t) are output and input functions of the gas storage device respectively.
(5) Electric boiler, gas boiler, electric refrigerator and absorption type refrigerator model
These four energy conversion device models can be uniformly expressed as:
P out ＝ηP in (13)
in the formula: p is a radical of in 、p out Inputting and outputting power for the equipment; η is the corresponding energy conversion efficiency.
2. Objective function
According to the method, the consumption effect of P2G on renewable energy is considered, so that the microgrid operation mode is set to be a grid-connected state, but energy is only purchased from the main grid, and energy is not sold to the main grid. Establishing an optimization model by taking the total operating cost of the micro-energy network as the lowest and considering P2G profit, wherein the operating cost mainly comprises the following aspects:
(1) Cost of energy purchase
In the formula: in the formula: t represents a time period divided equally in one day, T represents time, lambda e (t) and lambda g (t) real-time prices for electricity and gas purchased by the micro-energy network to the external network,
and
respectively the electric energy and the gas energy purchased by the micro-energy network from the external network at the time t.
(2) Cost of operating and maintaining equipment
In the formula: lambda [ alpha ] om，i For the unit operation cost of the ith equipment, N represents the equipment number of the micro-energy network, P i (t) represents the power of the ith station device at time t.
(3) Total operating cost of P2G
In the formula: c buy And C sell Operating cost and revenue of P2G equipment respectivelyYi, λ co 2 (t) is purchased CO 2 Real-time price of λ H2 (t) and λ o 2 (t) are respectively sold H 2 And O 2 Real-time price of (2);
and
CO consumed by P2G respectively 2 And H 2 ，
O representing production of P2G 2 。
3. Constraint conditions
(1) Micro-energy grid internal power balance constraints
The micro energy network researched by the method comprises four energy systems of electricity, gas, heat and cold:
in the formula:
representing the energy storage battery power;
natural gas produced by a P2G plant;
respectively representing the waste heat of the micro-gas turbine, the heat production power of a gas boiler and the heat production power of an electric boiler;
the refrigeration power of the absorption refrigerator and the refrigeration power of the electric refrigerator are respectively.
(2) Power switching point transmission capacity constraints
The micro-energy network and an external network only exchange electric energy and gas energy power:
in the formula:
respectively representing the minimum value and the maximum value of the electric energy exchange power;
respectively representing the minimum value and the maximum value of the gas energy exchange power.
4. Element constraint
(1) P2G constraints
The load power of the P2G equipment is flexible based on a large-scale power energy storage technology of high-temperature electrolysis, and the power of the P2G equipment is mainly limited by the capacity of the equipment on the assumption that the production of the P2G equipment is not constrained by the storage capacity and the market demand.
(2) Micro-combustion engine restraint
The power generation efficiency of the micro-combustion engine is increased along with the increase of the output power, and when the output power is lower, the pollutant emission ratio is higher due to insufficient fuel combustion. Micro-combustion engine constraints were formulated according to document [19 ]:
in the formula:
is the rated generating power of the micro-combustion engine,
the climbing rate of the micro-combustion engine is determined,
the power is generated by the micro-combustion engine in unit time.
(3) Energy storage battery restraint
The service life of the energy storage battery is determined by the total charge and discharge electric quantity and the charge and discharge depth of the energy storage battery, so that the energy storage battery in operation is limited by the charge and discharge depth of the storage battery while meeting the charge and discharge power.
Soc min ≤Soc(t)≤Soc max (24)
In the formula:
respectively representing the minimum value and the maximum value of the power of the energy storage battery; soc min 、Soc max Respectively representing the minimum value and the maximum value of the discharge depth of the energy storage battery.
The charge level of the energy storage battery is the same at the beginning and the end of the operation period.
Soc(T)＝Soc(0) (25)
In the formula: soc (T) and Soc (0) respectively represent the charge levels of the energy storage battery at the beginning and end of the operation cycle.
(4) Gas energy storage device restraint
The gas energy storage equipment is limited by capacity and input and output power.
W min ≤W≤W max (26)
In the formula: w is a group of max 、W min Respectively an upper limit and a lower limit of gas storage of the equipment,
inputting a lower limit and an upper limit of the gas storage device;
respectively outputting a lower limit and an upper limit for the gas storage device.
According to the literature, to guarantee the regulation capacity of the gas storage device, the gas storage level is the same at the beginning and end of the scheduling period.
W(T)＝W(0) (29)
In the formula: w (T) and W (0) respectively represent the charge levels of the gas storage equipment at the beginning and the end of the operation period.
(5) Electric boiler, gas boiler, electric refrigerator, absorption refrigerator restraint
The four devices are mainly operated under the constraint of rated power and climbing rate:
in the formula:
respectively representing the minimum value and the maximum value of the operating power of the equipment; delta P out Which represents the output power of the device per unit of time,
and representing the rated climbing rate of the equipment.
Drawings
Fig. 1 shows a P2G-containing microgrid energy hub;
FIG. 2 is a P2G operational model;
FIG. 3 is a micro-combustion engine model;
FIG. 4 is a daily load of the micro-energy grid;
FIG. 5 is electricity, gas prices;
FIG. 6 is a renewable energy output;
FIG. 7 is renewable energy usage;
fig. 8 is the battery Soc level;
figure 9 is an electrical network in operating mode 1;
figure 10 is an electrical network in operating mode 2;
FIG. 11 is a gas network in operating mode 1;
fig. 12 shows the gas network in operating mode 2.
Detailed Description
The invention is further described below with reference to specific embodiments and the accompanying drawings.
In order to verify the enthusiasm of the P2G-containing micro energy network for the consumption of renewable energy, the embodiment analyzes the day-ahead economic scheduling results of the micro energy network in the two operation modes by setting a comparison method. The micro-web devices for both modes of operation are shown in table 1.
TABLE 1 Equipment for different modes of operation
Operation mode 1: the micro-energy network does not contain P2G and gas storage equipment. And (4) observing the utilization condition of renewable energy sources of the micro energy network only containing the micro gas turbine, the energy storage battery and other equipment under economic dispatching.
Operation mode 2: P2G and gas energy storage are introduced in the operation mode 1. And (3) observing the effect of P2G on the operation cost of the micro-energy network and the consumption of renewable energy sources.
The electrical, gas, heat and cold loads are shown in detail in fig. 4. Fig. 5 is a real-time price of electricity and natural gas purchased by the micro-power grid from an external network on the same day. Fig. 6 shows the output of the fan and the photovoltaic in the same day.
And (4) calling GUROBI through MATLAB to solve the daily economic scheduling model of the micro-energy network. As can be seen from fig. 7 and 8, in the operation mode 2 with P2G, the renewable energy utilization rate of the microgrid is significantly improved compared with that of the operation mode 1 as a whole, and particularly, the phenomenon of wind curtailment at night is greatly improved. This is because the wind power generation is in the peak period at night, and the load level is low during this period, and the energy storage battery cannot absorb a large amount of electric energy due to the limitation of cost and capacity. At this time, the P2G operation cost is the lowest, and the P2G device will absorb surplus electric energy with the maximum capacity. As shown in table 2, the total energy rejection rate is reduced by 9.66% in the operation mode 2 compared with the operation mode 1, and the effect of improving the utilization rate of renewable energy is remarkable.
TABLE 2 renewable energy utilization in different operating modes
Tables 3 and 4 show the energy quantity purchased and the system operation cost of the micro energy network in different operation modes respectively. Fig. 9 and 10 are input and output relations of electric energy of the micro-energy network under two operation modes respectively. It can be seen from the above chart that after the P2G and the gas storage are added, the quantity of electric energy and natural gas purchased by the micro energy network to the external network is reduced. Analysis of fig. 11 and 12 reveals that this is because the micro power grid is in operation mode 2 and the natural gas produced by P2G is used as gas boiler heating, so that the electric boiler consumes less electric power.
TABLE 3 energy purchase in different operating modes
TABLE 4 cost of operating the microgrid for different operating modes
In this embodiment, it is assumed that all hydrogen in the first P2G reaction link of the micro energy grid is used for generating natural gas in the operation mode 2, and then the reduction of the operation cost of the micro energy grid mainly includes two reasons, one is that the energy purchase cost is less, and the reduction of the charge and discharge electricity of the energy storage battery makes the operation cost of the equipment lower.
While the present invention has been described in detail with reference to the embodiments, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.
Claims (6)
1. A day-ahead optimal scheduling method for a micro energy network with electric gas conversion equipment is characterized by comprising the following steps:
step 1, establishing a micro energy network model for electricity, gas, heat and cold combined supply in an energy concentrator mode;
step 2, establishing an energy input matrix, an energy conversion matrix, an energy output matrix and an energy storage matrix of the micro energy network;
step 3, establishing a day-ahead optimized economic dispatching model of the micro energy network, wherein the model comprises a target function, an element model and constraints;
the objective function aims at the lowest day-ahead operation cost and the maximum P2G benefit of the micro energy network, and specifically comprises the following steps:
(1) cost of energy purchase
In the formula: t represents a time period divided equally in one day, T represents time, lambda e (t) and lambda g (t) real-time prices for electricity and gas purchased by the micro-energy network to the external network,
and
respectively purchasing electric energy and gas energy from an external network at the moment t by the micro-energy network;
(2) cost of equipment operation and maintenance
In the formula: lambda [ alpha ] om,i For the unit operation cost of the ith equipment, N represents the equipment number of the micro-energy network, P i (t) represents the power of the ith device at time t;
(3) total operating cost of P2G
In the formula: c buy And C sell Respectively the operating cost and the profit of the P2G equipment,
for purchased CO 2 The real-time price of (a) is,
and
respectively is sold H 2 And O 2 Real-time price of (2);
and
CO consumed by P2G respectively 2 And H 2 ，
O representing production of P2G 2 ；
The component model is specifically as follows:
(1) P2G model
Through the prediction to next day electricity price and hydrogen price and natural gas price, formulate P2G's operation plan to reach the maximum profit, P2G's mathematical model is:
in the formula:
in order to obtain the synthetic methane, the synthesis gas is,
hydrogen generated from electrolysis of water but not participating in methane synthesis,
h consumed for P2G 2 ，η P2H In order to improve the efficiency of the hydrogen production by electrolyzing water,
the conversion efficiency of the P2G equipment;
(2) micro-combustion engine model
The micro-combustion engine has the following relations between the power generation power and the heating power and the fuel consumption power:
(3) energy storage battery model
The charge level and the running state of the energy storage battery have the following relations:
Soc(t+1)＝Soc(t)+(1-μ sta )(μ ch η ch +μ dis /η dis )P e bat (t)Δt/Q bat (11)
in the formula: soc (t + 1) and Soc (t) are the charge levels of the energy storage battery at the time t +1 and the time t respectively; q bat Is the energy storage battery capacity; mu.s ch 、μ dis 、μ sta All are variables with the value range of 0-1, respectively represent a charging mark, a discharging mark and a standing mark, and mu is dis +μ ch +μ sta ＝1；η ch 、η dis To the charging efficiency and the discharging efficiency, Δ t represents time differentiation;
(4) gas energy storage equipment model
The stored gas energy of the gas storage device in operation has the following relationship:
W 1 ＝W 0 +∫Q ch (t)-Q dis (t)dt (12)
in the formula：W 0 、W 1 Respectively representing the energy storage level of the gas storage equipment before and after the operation time t; q ch (t)、Q dis (t) respectively an output function and an input function of the gas storage device;
(5) electric boiler, gas boiler, electric refrigerator and absorption refrigerator model
These four energy conversion device models can be uniformly expressed as:
P out ＝ηP in (13)
in the formula: p is a radical of in 、p out Inputting and outputting power for the equipment; eta is the corresponding energy conversion efficiency;
the constraints are specifically as follows:
(1) micro-energy grid internal power balance constraints
The micro energy network comprises four energy systems of electricity, gas, heat and cold:
in the formula:
electric energy consumed by the P2G equipment, the electric boiler and the electric refrigerator respectively;
representing the energy storage battery power;
natural gas produced by a P2G plant;
respectively representing the waste heat of the micro-combustion engine, the heat production power of a gas boiler and the heat production power of an electric boiler;
the refrigeration power of the absorption refrigerator and the electric refrigerator, P wind 、P pv Respectively, fan and photovoltaic input power, L e 、L g 、L h 、L c Respectively representing four load powers of electricity, gas, heat and cold;
(2) power switching point transmission capacity constraints
The micro-energy network and the external network only exchange electric energy and gas energy power:
in the formula:
respectively representing the minimum value and the maximum value of the electric energy exchange power;
respectively representing the minimum value and the maximum value of the gas energy exchange power;
(3) element constraint
1) P2G constraints
Assuming that the production of P2G devices is not constrained by storage capacity and market demand, their power is limited primarily by device capacity
2) Micro-combustion engine restraint
In the formula:
is the rated generating power of the micro-combustion engine,
the climbing rate of the micro-combustion engine is high,
generating power for the micro gas turbine in unit time;
3) Energy storage battery restraint
Soc min ≤Soc(t)≤Soc max (21)
In the formula:
respectively representing the minimum value and the maximum value of the power of the energy storage battery; soc min 、Soc max Respectively representing the minimum value and the maximum value of the discharge depth of the energy storage battery;
the charge level of the energy storage battery is equal to the beginning and the end of the operation cycle
Soc(T)＝Soc(0) (22)
In the formula: soc (T) and Soc (0) respectively represent the charge levels of the energy storage battery at the beginning and the end of the operation period;
4) Gas energy storage device restraint
The gas energy-storage equipment is limited by capacity and input and output power
W min ≤W≤W max (23)
In the formula: w max 、W min Respectively an upper limit and a lower limit of gas storage of the equipment,
inputting a lower limit and an upper limit of the gas storage device;
respectively outputting a lower limit and an upper limit for the gas storage equipment;
in order to ensure the regulating capacity of the gas storage equipment, the gas storage level is the same at the beginning and the end of the dispatching period
W(T)＝W(0) (26)
In the formula: w (T) and W (0) respectively represent the charge levels of the gas storage equipment at the beginning and the end of the operation period;
5) Electric boiler, gas boiler, electric refrigerator, absorption refrigerator restraint
The four devices are mainly operated under the constraint of rated power and climbing rate:
in the formula:
respectively representing the minimum value and the maximum value of the running power of the equipment; delta P out Which represents the output power of the device per unit time,
representing the rated climbing rate of the equipment;
and 4, solving the day-ahead optimized economic dispatching model in the step 3.
2. The day-ahead optimal scheduling method for the micro energy grid with the electric gas conversion equipment as claimed in claim 1, wherein the energy concentrator in step 1 comprises a micro gas turbine, a P2G device, an electric boiler, a gas boiler, an electric refrigerator, an absorption refrigerator, an energy storage battery and a gas storage device.
3. The method for day-ahead optimal scheduling of the micro energy grid with the electric gas conversion equipment according to claim 1, wherein the energy input matrix in the step 2 is as follows:
in the formula:
respectively the electric energy and the gas energy purchased from the external network by the micro energy network.
4. The method for day-ahead optimal scheduling of the micro energy grid with the electric power conversion equipment according to claim 1, wherein the energy conversion matrix in step 2 is:
in the formula:
respectively consumed by the P2G equipment, the electric boiler and the electric refrigerator；
The gas energy consumed by the micro-gas turbine and the gas boiler is respectively;
the power generation efficiency of the micro-combustion engine is obtained;
the conversion efficiency of the P2G equipment;
the heat efficiency of an electric boiler, a micro-gas turbine and a gas boiler is respectively;
the refrigeration efficiencies of the electric refrigerator and the absorption refrigerator respectively; xi shape 1 、ξ 2 Proportionality coefficient xi for heat energy generated by micro-combustion engine to heat supply and refrigeration 1 +ξ 2 ≤1。
5. The method for day-ahead optimal scheduling of the micro energy grid with the electric power conversion equipment according to claim 1, wherein the energy output matrix in the step 2 is:
P out ＝[L e L g L h L c ] T (3)。
6. the method for day-ahead optimal scheduling of the micro energy grid with the electric gas conversion equipment according to claim 1, wherein the energy storage matrix in the step 2 is:
in the formula:
the output conditions of electricity storage and gas storage are respectively shown, the energy is released when the value is positive, and the energy is stored when the value is negative.
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