CN113762632B - Collaborative optimization operation method and system of electric comprehensive energy system - Google Patents
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Abstract
The invention discloses a collaborative optimization operation method and a collaborative optimization operation system of an electric comprehensive energy system, wherein the method comprises the steps of establishing an energy optimization operation model of the electric comprehensive energy system taking various standby resources into account, wherein the various standby resources comprise standby resources of a generator, standby resources of energy storage equipment and standby resources capable of interrupting loads; setting a system reserve capacity deliverability constraint considering sudden accidents according to an energy optimization operation model of the electric-gas comprehensive energy system, and taking the constraint as a robust operation constraint of the electric-gas comprehensive energy system of the energy optimization operation model of the electric-gas comprehensive energy system; decoupling the energy optimization operation model of the electric-gas comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; and solving the model by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an optimal solution for energy optimization scheduling of the electric-gas comprehensive energy system, and completing collaborative optimization of the electric-gas comprehensive energy system.
Description
Technical Field
The invention relates to the technical field of collaborative optimization operation of comprehensive energy systems, in particular to a collaborative optimization operation method and a collaborative optimization operation system of an electric comprehensive energy system.
Background
With the gradual decrease of global fossil energy reserves and the prominent environmental problems, many countries are seeking the transition and breakthrough of energy fields, and the worldwide popularity of renewable energy is rapidly increasing. Traditional fossil energy sources such as coal, petroleum and the like on the power generation side in the power system are gradually replaced by renewable clean energy sources, and wind power development is particularly rapid. By the year 2020, the Chinese wind installation has reached 2.81 hundred million kilowatts. However, wind power is greatly affected by meteorological conditions, and the output condition is difficult to accurately predict. In order to cope with the intermittent and fluctuating characteristics of renewable energy sources such as wind power, the duty ratio of a gas turbine set with rapid climbing capacity in an electric power system is continuously improved. The gas unit deepens the coupling degree of the power system and the natural gas system, and forms an electric comprehensive energy system containing high-proportion clean energy.
From the current state of development of China, abundant and flexible regulation resources become necessary conditions for the operation of a power system. In order to ensure safe and stable operation of the power grid and to utilize renewable energy to the greatest extent, the following three solutions are adopted for the intermittence, the volatility and the difficulty in predictability of the renewable energy generation: first, enhancing power supply regulation flexibility, i.e., increasing gas turbine ratio with rapid hill climbing performance; secondly, the spare regulating capability of the system is improved, namely the energy storage equipment is reasonably configured; thirdly, the peak regulation pressure at the two sides of supply and demand is lightened, namely a demand side response means is adopted. Therefore, the electric comprehensive energy system should fully consider various spares in the system in operation, so as to realize the collaborative optimization operation of energy.
However, in practice, since the power system and the natural gas system are not generally governed by the same organization, the operation schedule and the energy management between the two systems are independent, and the power company and the natural gas company exchange only limited information to protect the data privacy. In this case, centralized optimization cannot be achieved, and only a distributed optimization method can be adopted. The stable operation of the electric comprehensive energy system in the face of sudden accidents is also one of the targets of energy cooperative operation. Therefore, considering system accidents, how to cooperatively optimize the coupled electric comprehensive energy system under the conditions of guaranteeing independent data and operation of two systems of electric power and natural gas, and realizing optimal utilization of energy are the problems to be solved.
Disclosure of Invention
The invention aims to provide a cooperative optimization operation method and a system of an electric comprehensive energy system, and provides the cooperative optimization operation method of the electric comprehensive energy system considering various standby resources, which are used for solving the following two problems: firstly, the intermittence and fluctuation of the clean energy output bring flexible operation of the electric comprehensive energy system to difficulty; second, data privacy protection for power systems and natural gas system operators presents a difficulty for centralized solutions. The method takes into account four standby resources of non-gas units, system energy storage and interruptible load, considers the deliverability of the standby resources under the condition of system emergency, and improves the operation flexibility and economy of the electric comprehensive energy system on the basis of ensuring the operation safety of the system.
The invention is realized by the following technical scheme:
in a first aspect, the present invention provides a method for collaborative optimization operation of an electrical integrated energy system, the method comprising:
Step 1: establishing an energy optimization operation model of an electric comprehensive energy system considering a plurality of standby resources, wherein the plurality of standby resources comprise generator standby resources, energy storage equipment standby resources and interruptible load standby resources;
Step 2: setting a system reserve capacity deliverability constraint considering sudden accidents according to the energy optimization operation model of the electric comprehensive energy system, and taking the constraint as an electric comprehensive energy system robust operation constraint of the energy optimization operation model of the electric comprehensive energy system;
step 3: based on a system decoupling idea, decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; and solving the optimal operation model of the electric power system and the optimal operation model of the natural gas system by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an optimal solution for energy optimal scheduling of the electric comprehensive energy system, and completing cooperative optimization of the electric comprehensive energy system.
The working principle is as follows: the invention provides a cooperative optimization operation method of an electric comprehensive energy system taking multiple standby resources into consideration, which has the technical key points and protection points that: firstly, taking a standby power generator, energy storage equipment and interruptible load as standby power resources of a system together so as to reduce the standby load of the power generator of an electric comprehensive energy system with high-proportion wind power access, improve the flexibility of system operation and reduce the air discarding quantity; secondly, the system operation constraint considers the deliverability of the spare capacity of the system in the face of sudden accidents, and ensures the safety and stability of the system operation; thirdly, the distributed collaborative optimization solution is carried out by adopting an alternate direction multiplier method with self-adaptive penalty parameters, so that the solution efficiency is improved, the data privacy among different energy operators is effectively protected, and only the gas turbine set data of both sides are needed in the solution process.
Further, the step of establishing the energy optimization operation model of the electric comprehensive energy system in the step1 is as follows:
Step 11, setting an objective function of the energy optimization operation model of the electric comprehensive energy system, wherein the objective function is that the total operation cost of the system in the operation scheduling period of the system is the lowest, and the total operation cost of the system comprises energy supply cost C 1, wind abandoning cost C 2 and upward and downward standby capacity cost C 3 of the system; wherein:
The energy supply cost C 1 comprises the power generation cost, the natural gas production cost, the storage battery charge and discharge cost and the interruption compensation cost of the interruptible load of the conventional generator; the system up and down back-up capacity cost C 3, the up and down back-up capacity of the system being provided by the generator, battery and interruptible load together;
and step 12, setting an electric power system operation constraint, a natural gas system operation constraint and a system coupling constraint for the objective function.
Further, the objective function set in step 11 is as follows:
Wherein, C i and P i,t respectively represent the cost coefficient and the generating capacity of the non-gas unit; c g and F g,t are cost coefficients and gas production, respectively, of the natural gas supply; c s is the unit charge-discharge cost of the battery, and P s,t is the charge or discharge power of the battery; And The unit power interruption compensation cost of the interruptible load and the dispatching power of the interruptible load are adopted; c w The unit penalty cost of the abandoned wind and the abandoned wind quantity of the system are respectively represented; And The load shedding cost and the load shedding power are respectively represented; And The cost coefficients for the up and down standby respectively,AndThe upward capacity and the standby capacity provided by a standby source r, which is a generator standby or a storage battery or an interruptible load, respectively; And Representing the cost factor for the up and down standby of the gas turbine,AndThe amount of natural gas reserved for the gas turbine to provide up and down reserve capacity, N G, represents the number of gas units.
Further, the robust operation constraint of the electric comprehensive energy system energy optimization operation model in the step 2 comprises a generator shutdown constraint, a line interruption constraint and a natural gas pipeline constraint.
Further, in the step 3, decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; and relaxing the coupling consistency constraint of the electric power system and the natural gas system, adding the punishment items into the optimized operation model of the electric power system and the optimized operation model of the natural gas system, and obtaining the optimized operation model of the electric power system and the optimized operation model of the natural gas system after adding the punishment items.
Specifically, the optimal operation model of the power system and the optimal operation model of the natural gas system are obtained by decoupling as follows:
Wherein, minf e is the optimal operation model of the power system, and minf g is the optimal operation model of the natural gas system.
Specifically, the objective functions of the optimized operation model of the electric power system and the optimized operation model of the natural gas system after the penalty term is added are respectively expressed as follows:
Wherein, minf e is the optimized operation model of the electric power system after adding penalty term, and minf g is the optimized operation model of the natural gas system after adding penalty term; gamma j,t and p represent the lagrangian multiplier and penalty parameters, respectively.
Further, in the step 3, an optimal operation model of the electric power system and an optimal operation model of the natural gas system are solved by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an optimal solution for energy optimization scheduling of the electric comprehensive energy system, and the cooperative optimization of the electric comprehensive energy system is completed; the method specifically comprises the following substeps:
S31: variable initialization: setting an iteration index n=1, setting original and dual convergence thresholds epsilon p and epsilon d, and initializing the gas consumption of the gas turbine The reserve of gas reserved for the gas turbine, which can provide upward and downward reserve capacity, isAndA Lagrangian multiplier λ and a penalty parameter ρ;
s32: solving the optimal operation result of the power system sub-problem 1: according to AndInitial value to obtain optimal solution result of current power systemAnd
S33: updating the auxiliary variable: order theSharing boundary variables with natural gas systemsAnd
S34: solving the optimal operation result of the natural gas system sub-problem 2: according toAndInitial value to obtain optimal solution result of current natural gas systemAnd
S35: updating the auxiliary variable: order theSharing boundary variables with power systemsAndInformation of (2);
s36: calculating boundary variables by formulas (9) and (10) AndOriginal residual and dual residual of (a);
S37: checking convergence: if the maximum residual meets constraint conditions (11) and (12) or N > N, terminating the iterative process and outputting a solution; otherwise, go to S38; if the current iteration number N is greater than the maximum iteration limit N, the solving process is regarded as being incapable of converging;
S38: updating the Lagrangian multiplier by equation (13), and updating the penalty parameter by equations (14) and (15); let n=n+1, go to S32 and repeat the iterative process.
If it isThen
Wherein,AndRepresenting raw residuals related to gas turbine gas consumption, upward reserve and downward reserve, respectively; And The dual residuals related to gas turbine gas consumption, upward reserve and downward reserve are represented, respectively; And The lagrangian parameter updates associated with gas turbine gas consumption, upward gas reserve, and downward gas reserve, respectively.
In a second aspect, the present invention also provides a co-optimizing operation system of an electrical integrated energy system, the system supporting the co-optimizing operation method of the electrical integrated energy system, the system comprising:
a preliminary model construction unit: the energy optimization operation model is used for establishing an energy optimization operation model of the electric comprehensive energy system taking various standby resources into account, wherein the various standby resources comprise generator standby resources, energy storage equipment standby resources and interruptible load standby resources;
the model constraint setting unit is used for setting the system reserve capacity deliverability constraint when the sudden accident is considered according to the electric comprehensive energy system energy optimization operation model, and taking the system reserve capacity deliverability constraint as the electric comprehensive energy system robust operation constraint of the electric comprehensive energy system energy optimization operation model;
The model decoupling unit is used for decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system;
The optimization solving unit is used for solving the optimization operation model of the electric power system and the optimization operation model of the natural gas system by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an energy optimization scheduling optimal solution of the electric comprehensive energy system;
And the output unit is used for outputting the optimal solution of the energy optimization scheduling of the electric comprehensive energy system to finish the collaborative optimization of the electric comprehensive energy system.
Further, the establishing process of the energy optimization operation model of the electric comprehensive energy system in the preliminary model establishing unit is as follows:
Setting an objective function of the energy optimization operation model of the electric comprehensive energy system, wherein the objective function is that the total operation cost of the system in a system operation scheduling period is the lowest, and the total operation cost of the system comprises energy supply cost C 1, abandoned wind cost C 2 and upward and downward standby capacity cost C 3 of the system; wherein: the energy supply cost C 1 comprises the power generation cost, the natural gas production cost, the storage battery charge and discharge cost and the interruption compensation cost of the interruptible load of the conventional generator; the system up and down back-up capacity cost C 3, the up and down back-up capacity of the system being provided by the generator, battery and interruptible load together; the set objective function is as follows:
Wherein, C i and P i,t respectively represent the cost coefficient and the generating capacity of the non-gas unit; c g and F g,t are cost coefficients and gas production, respectively, of the natural gas supply; c s is the unit charge-discharge cost of the battery, and P s,t is the charge or discharge power of the battery; And The unit power interruption compensation cost of the interruptible load and the dispatching power of the interruptible load are adopted; c w represents the unit penalty cost of the wind curtailment; And The cost coefficients for the up and down standby respectively,AndThe upward capacity and the standby capacity provided by a standby source r, which is a generator standby or a storage battery or an interruptible load, respectively; And Representing the cost factor for the up and down standby of the gas turbine,AndThe amount of natural gas reserved for the gas turbine to provide up and down reserve capacity, N G, represents the number of gas units.
And setting an electric power system operation constraint, a natural gas system operation constraint and a system coupling constraint for the objective function.
Further, in the model constraint setting unit, robust operation constraints of the electric comprehensive energy system energy optimization operation model include generator shutdown constraints, line interruption constraints and natural gas pipeline constraints.
Further, the model decoupling unit decouples the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; and relaxing the coupling consistency constraint of the electric power system and the natural gas system, adding the punishment items into the optimized operation model of the electric power system and the optimized operation model of the natural gas system, and obtaining the optimized operation model of the electric power system and the optimized operation model of the natural gas system after adding the punishment items.
Specifically, the optimal operation model of the power system and the optimal operation model of the natural gas system are obtained by decoupling as follows:
Wherein, minf e is the optimal operation model of the power system, and minf g is the optimal operation model of the natural gas system.
Specifically, the objective functions of the optimized operation model of the electric power system and the optimized operation model of the natural gas system after the penalty term is added are as follows:
Wherein, minf e is the optimized operation model of the electric power system after adding penalty term, and minf g is the optimized operation model of the natural gas system after adding penalty term; gamma j,t and p represent the lagrangian multiplier and penalty parameters, respectively.
Compared with the prior art, the invention has the following advantages and beneficial effects:
Compared with the existing optimized operation method and system of the centralized electric comprehensive energy system, the method and system have the beneficial effects that: the standby load of the generator can be effectively reduced by considering standby resources such as standby power of the generator, energy storage equipment, interruptible load and the like, the flexibility of system operation is improved, and the air discarding quantity and the total operation cost are reduced; the distributed collaborative optimization solving strategy based on the alternating direction multiplier method with the self-adaptive punishment parameters can effectively protect the data privacy of different energy institutions, and only the gas turbine data of both parties are needed in the solving process.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:
FIG. 1 is a flow chart of a method for collaborative optimization operation of an electrical integrated energy system in accordance with the present invention.
Fig. 2 is a schematic diagram of a simulation topology of an electrical integrated energy system according to an embodiment of the present invention.
FIG. 3 is a schematic diagram of a solution strategy process of the present invention.
Fig. 4 is a block diagram of a co-optimizing operation system of the electric integrated energy system of the present invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Example 1
As shown in fig. 1, the method for collaborative optimization operation of an electrical integrated energy system of the present invention includes:
Step 1: establishing an energy optimization operation model of an electric comprehensive energy system considering a plurality of standby resources, wherein the plurality of standby resources comprise generator standby resources, energy storage equipment standby resources and interruptible load standby resources;
Step 2: setting a system reserve capacity deliverability constraint considering sudden accidents according to the energy optimization operation model of the electric comprehensive energy system, and taking the constraint as an electric comprehensive energy system robust operation constraint of the energy optimization operation model of the electric comprehensive energy system;
step 3: based on a system decoupling idea, decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; and solving the optimal operation model of the electric power system and the optimal operation model of the natural gas system by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an optimal solution for energy optimal scheduling of the electric comprehensive energy system, and completing cooperative optimization of the electric comprehensive energy system.
For further explanation of the present embodiment, the steps for establishing the energy optimization operation model of the electric comprehensive energy system for taking into account the plurality of standby resources in step 1 are as follows:
Step 11, setting an objective function of the energy optimization operation model of the electric comprehensive energy system, wherein the objective function is that the total operation cost of the system in the operation scheduling period of the system is the lowest, and the total operation cost of the system comprises energy supply cost C 1, wind abandoning cost C 2 and upward and downward standby capacity cost C 3 of the system; wherein:
The energy supply cost C 1 comprises the power generation cost, the natural gas production cost, the storage battery charge and discharge cost and the interruption compensation cost of the interruptible load of the conventional generator; the system up and down back-up capacity cost C 3, the up and down back-up capacity of the system being provided by the generator, battery and interruptible load together;
The set objective function is as follows:
Wherein, C i and P i,t respectively represent the cost coefficient and the generating capacity of the non-gas unit; c g and F g,t are cost coefficients and gas production, respectively, of the natural gas supply; c s is the unit charge-discharge cost of the battery, and P s,t is the charge or discharge power of the battery; And The unit power interruption compensation cost of the interruptible load and the dispatching power of the interruptible load are adopted; c w represents the unit penalty cost of the wind curtailment; And The cost coefficients for the up and down standby respectively,AndThe upward capacity and the standby capacity provided by a standby source r, which is a generator standby or a storage battery or an interruptible load, respectively; And Representing the cost factor for the up and down standby of the gas turbine,AndThe amount of natural gas reserved for the gas turbine to provide up and down reserve capacity, N G, represents the number of gas units.
And step 12, setting an electric power system operation constraint, a natural gas system operation constraint and a system coupling constraint for the objective function. The method comprises the following steps:
the power system operating constraints include:
(1) Energy storage device charge-discharge constraints:
Wherein E s,t is the electric quantity (kWh) stored in the storage battery at time t, mu loss is the energy loss rate of the storage battery itself, For the battery charging efficiency, Δt is the charge-discharge time interval (h),For battery discharge efficiency, cap E is battery capacity, γ ch is maximum charge rate, γ dc is maximum discharge rate, ω s,t and ω r,t are binary variables indicating battery charge and discharge states, ω s,t =1 indicating that charging is occurring.
(2) Interruptible load constraint:
Wherein, AndMaximum capacity and minimum capacity of interruptible load connected to the ith node, respectively. u k,t is a 0-1 variable, indicating the operational state of the interruptible load.AndRepresenting the minimum on-time and minimum off-time limits of the interruptible load, respectively.AndThe accumulated turn-on time and the accumulated interrupt time of the interruptible load before the time t are respectively indicated.
(3) System power balance constraint:
wherein P i,t is the total power of the generator set in the system, and comprises a conventional generator set and a gas unit; p w,t is the power generated by the wind farm connected with the system; p s,t is the discharge power provided by the battery in the system; l d,e,t is the total load of the system; The dispatch power provided for the interruptible load of the system, N E、Nw、NS、Ne、Nint, represents the number of nodes in the system connecting the generator, wind farm, battery, load and interruptible load, respectively.
(4) Generator ramp rate constraint:
wherein, P i,t is the power generated by the unit i at the time t, P i,t+1 is the power generated by the unit i at the time t+1, and r i is the climbing rate of the unit i.
(5) Generator backup capacity constraint:
Wherein, The upward reserve capacity provided for the unit i,The downward reserve capacity provided for the unit i,The maximum power generation capacity of the unit i.
(6) Generator standby response time constraints:
Where T r is the standby response time requirement of the unit.
(7) Wind farm output constraints:
Wherein P w,t is the actual value of the wind power output at the time t, And the predicted value of the wind power output at the time t.
(8) Line transmission capacity constraints:
Wherein, Represents the maximum power transfer limit for line m, K being the power distribution coefficient.
(9) Energy storage device charge-discharge power constraint:
Wherein, Is the maximum charge power of the storage battery.Is the maximum discharge power of the storage battery. Omega s,t and omega r,t are 0-1 variables indicating the charge and discharge states of the energy storage device, and when the value is 1, the storage battery is charged or discharged, and when the value is 0, the storage battery is not operated.
(10) Energy storage device remaining energy constraint:
wherein E s,t is the energy remaining at time t of the battery. AndThe maximum energy storage capacity and the minimum energy storage capacity of the storage battery are respectively. When a complete operational schedule period has ended, the energy storage E s,T in the system will be set to the initial energy storage E s,0.
(11) Energy storage reserve capacity constraint:
Wherein, AndIndicating the upward reserve capacity and the downward reserve capacity provided by the battery, respectively.AndRespectively, the charge and discharge efficiency of the battery.
(12) Spare capacity demand constraint:
An interruption of the maximum installed capacity of the system is considered to be the most serious N-1 emergency, and thus, the spare capacity against the unexpected situation is set as the maximum installed capacity of the generator. The overall upward and downward backup constraints within the system are as follows:
Where β d and β w are the reserve demand coefficients for load and wind energy. Indicating the maximum installed capacity of the genset.
The natural gas system operating constraints include:
(1) Duct airflow restriction:
Where C mn is a constant, F mn is the gas flow, and pi is the node pressure, depending on the characteristics of the pipe (e.g., length, diameter, temperature, etc.).
(2) Gas output constraint:
Wherein, AndThe upper and lower gas output limits of the gas well are indicated, respectively.
(3) Node air pressure constraint:
Wherein, AndRepresenting the upper and lower limits of node air pressure, respectively.
(4) Node airflow balancing constraints:
Wherein F g,t is the natural gas output of the gas well, L d,g,t is the node connection natural gas load, F mn,t is the gas flow in the pipeline mn, Is the gas consumption of the node gas turbine.
Nonlinear non-convex natural gas pipeline airflow equations in natural gas networks are key factors that increase model complexity. In order to reduce the solving difficulty of the collaborative optimization model, the gas flow constraint of the natural gas pipeline can be subjected to linearization treatment through an incremental piecewise linearization method.
The system coupling constraint includes:
Gas turbine as coupling element of power system and natural gas system, natural gas consumption of gas turbine And power generation amount P j,t and upward standby capacityAnd a downward standby capacityThe relation between the two is:
Wherein α j is the thermal conversion efficiency coefficient of the gas turbine, related to the unit itself; HHV is the fixed higher heating value of natural gas.
In order to further explain the embodiment, step 2 sets a system spare capacity deliverability constraint considering an accident as an electrical comprehensive energy system robust operation constraint of the electrical comprehensive energy system energy optimization operation model;
It is assumed that electrical integrated energy systems are subject to accidents (generator and line breaks) and prediction errors (wind power generation and load demand prediction errors) in real-time operation and will call for reserve capacity to maintain power balance. In order to ensure the operation safety and reliability of the electric comprehensive energy system, the deliverability constraint of the spare capacity is considered, so that the spare capacity can timely fill a system power gap when an accident occurs in the system in real-time operation, and the operation safety of the system is ensured.
(1) Generator shutdown constraint
The sudden N-1 generator shutdown failure maintains power balance by planning reserve capacity as shown in equation (39). The transmission limit of the line at this time is represented by formula (40). Equation (41) indicates that the real-time scheduled reserve capacity should not exceed the total reserve capacity preset by the system.
Where G is a power generation unit that may fail within the dispatch range.
(2) Line break constraint
The line that fails within the scheduling range is denoted by L. Active power shortage caused by wind power fluctuation can also be solved by scheduling system reserve capacity as shown in formula (42). The transmission capacity limit of the line is expressed as formula (43). Equation (44) indicates that the scheduled reserve capacity should not exceed the predetermined reserve capacity.
Where KL is the power distribution coefficient taking into account the line L failure.
(3) Natural gas pipeline restraint
Gas turbines may also provide backup service in electrical power systems. However, when the gas consumption of the gas turbine increases during operation, the natural gas pipeline may become blocked, thereby failing to meet the gas demand of the gas turbine. It is therefore necessary to verify that the gas consumption of the gas turbine can be met by the gas network when additional backup is required. The constraint is expressed as follows:
for further explanation of the present embodiment, step 3 comprises the sub-steps of:
Step 31, reset the objective function.
The objective function (formula (1)) of the electric comprehensive energy system collaborative optimization operation model can be decomposed into two sub-objective functions of the electric power system and the natural gas system, which are shown in the formulas (5) and (6).
Step 32, relaxing the coupling constraint.
The two energy subsystems (power system, natural gas system) obey the coupling element constraint and in the same solutionAndThe optimal solution results within the two energy subsystems should remain consistent as shown in equation (49).
Wherein the method comprises the steps ofAndRepresenting the optimal outcome of boundary variables in the power system,AndRepresenting the optimal results of boundary variables in the natural gas system.
And relaxing the coupling consistency constraint of the two energy subsystems, and adding a penalty term into the self-optimizing objective function of the two energy subsystems. The objective functions solved by the power system and the natural gas system are respectively expressed as formulas (7) and (8) after penalty terms are added.
Step 33, solving by using a distributed algorithm.
Solving an electric comprehensive energy system collaborative optimization operation model by using an alternating direction multiplier method (ADMM-SAP) algorithm with adaptive penalty parameters, wherein the method specifically comprises the following steps of:
S31: variable initialization: setting an iteration index n=1, setting original and dual convergence thresholds ε p and ε d, initializing gas turbine gas consumption The reserve of gas reserved for the gas turbine, which can provide upward and downward reserve capacity, isAndA Lagrangian multiplier λ and a penalty parameter ρ;
s32: solving the optimal operation result of the power system sub-problem 1: according to AndInitial value to obtain optimal solution result of current power systemAnd
S33: updating the auxiliary variable: order theSharing boundary variables with natural gas systemsAnd
S34: solving the optimal operation result of the natural gas system sub-problem 2: according toAndInitial value to obtain optimal solution result of current natural gas systemAnd
S35: updating the auxiliary variable: order theSharing boundary variables with power systemsAndInformation of (2);
s36: calculating boundary variables by formulas (50) and (51) AndOriginal residual and dual residual of (a);
S37: checking convergence: if the maximum residual meets constraint conditions (52) and (53) or N > N, terminating the iterative process and outputting a solution; otherwise, go to S38; if the current iteration number N is greater than the maximum iteration limit N, the solving process is regarded as being incapable of converging;
S38: updating the Lagrangian multiplier and penalty parameters by formula (54), and updating the penalty parameters by formula (55) and formula (56); let n=n+1, go to S32 and repeat the iterative process.
If it isThen
The invention provides a cooperative optimization operation method of an electric comprehensive energy system taking multiple standby resources into consideration, which has the technical key points and protection points that: firstly, taking a standby power generator, energy storage equipment and interruptible load as standby power resources of a system together so as to reduce the standby load of the power generator of an electric comprehensive energy system with high-proportion wind power access, improve the flexibility of system operation and reduce the air discarding quantity; secondly, the system operation constraint considers the deliverability of the spare capacity of the system in the face of sudden accidents, and ensures the safety and stability of the system operation; thirdly, the distributed collaborative optimization solution is carried out by adopting an alternate direction multiplier method with self-adaptive penalty parameters, so that the solution efficiency is improved, the data privacy among different energy operators is effectively protected, and only the gas turbine set data of both sides are needed in the solution process.
In specific implementation, the simulation is as follows:
The invention designs an electric comprehensive energy system which is formed by coupling an improved IEEE RTS24 node system and a natural gas 6 node system as a simulation system. Wherein, the IEEE RTS24 node system has 23 Bus nodes (namely Bus1-Bus 23 in FIG. 2) and comprises 10 conventional non-gas units G1-G10;2 gas units G11-G12 are respectively positioned on No. 13 and No. 23 buses; the bus 3 and the bus 6 are respectively connected with a wind farm (W1 and W2); the Storage battery energy Storage equipment (Storage) of the system is positioned on a No. 6 bus; the bus 3 and the bus 10 are respectively connected with an Interruptible Load (IL). The natural Gas system has a total of 6 Gas nodes (Node 1-Node 6) comprising two Gas wells N1 and N2, five pipelines and two natural Gas loads (Gas Load 1 and Gas Load 2). The power system and the natural gas system are coupled by two gas turbines G11 and G12. The system parameters are shown in the following table:
TABLE 1 non-gas turbine operating parameters
| Generating set | Maximum output (MW) | Climbing rate (MW/h) | Power generation quotation ($/MW) | Spare quotation ($/MW) |
| G1 | 192 | 100 | 19.6 | 5.88 |
| G2 | 192 | 100 | 19.2 | 5.76 |
| G3 | 300 | 200 | 29.1 | 8.73 |
| G4 | 394 | 280 | 25.4 | 7.62 |
| G5 | 215 | 120 | 14.1 | 4.23 |
| G6 | 155 | 100 | 14.1 | 4.23 |
| G7 | 400 | 300 | 7.8 | 2.34 |
| G8 | 400 | 300 | 7.8 | 2.34 |
| G9 | 300 | 180 | 19.2 | 5.76 |
| G10 | 310 | 200 | 14.1 | 4.23 |
TABLE 2 gas turbine operating parameters
TABLE 3 Battery operating parameters
TABLE 4 interruptible load operation parameters
TABLE 5 other System parameters
| Parameters (parameters) | Value taking |
| Natural gas price ($/kcf) | 2.5 |
| Wind disposal fine ($/MW) | 100 |
| Load shedding fine ($/MW) | 27 |
| Systematic prediction error (MW) | Sum of 5% load and 10% wind power forecast |
| Line fault set | 1. Branches 3, 4, 12, 13, 23 and 27 |
| Original residual convergence threshold ε p | 0.5 |
| Dual residual convergence threshold epsilon d | 0.5 |
| Maximum number of iterations N | 200 |
| Initial value ρ of penalty parameter | 0.1 |
| Penalty parameter maximum ρ max | 1000 |
| Scheduling period (h) | 1 |
| Total scheduling period (h) | 24 |
The predicted values of power load, natural gas load, and wind power output in the system for dispatch reference are shown in table 6.
TABLE 6 predicted values of load and wind Power output during scheduled time periods
The model simulation program is written by MATLAB 2018a and solved using a commercial solver gurobi.1.1.
In order to analyze the economical efficiency and the robustness of the dispatching of the electric comprehensive energy system under the situation, four different calculation examples are set for comparison analysis.
Calculation example 1: the system has no storage battery and interruptible load, only the non-gas unit, the gas unit and the wind power are used for providing energy for the power system, namely, model constraint conditions related to P s,t、Rs,t、Rint and P int are removed, and the standby capacity of the system is provided by the standby of the generator.
Calculation example 2: there are battery and interruptible loads in the system, but both are only involved in power scheduling and not in system standby scheduling, i.e. the model constraints associated with R s,t and R int are removed.
Calculation example 3: the system has storage batteries and interruptible loads, and the storage batteries and the interruptible loads participate in power dispatching and standby dispatching of the system, and the deliverability constraint of the standby capacity of the system under three emergency conditions of generator failure, line interruption and natural gas pipeline blockage is considered. The calculation example reflects an electric comprehensive energy system collaborative optimization scheduling basic model which considers various energy storage and is researched by the invention.
Calculation example 4: the constraint set by equations (39) through (48) in the model is removed regardless of the spare capacity deliverability constraint.
The results of the solutions for the respective examples are shown in tables 7 to 8.
TABLE 7 running costs of different examples
TABLE 8 electric quantity of each power generation device of electric power system in different calculation examples
| Calculation example | Gas turbine/MWh | Non-gas unit/MWh | Interruptible load/MWh | Wind power disposal/MWh |
| Example 1 | 3215.0 | 43303.1 | / | 100.9 |
| EXAMPLE 2 | 2767.9 | 43265.2 | 422.9 | 4.4 |
| EXAMPLE 3 | 2707.4 | 43442.2 | 298.0 | 7.4 |
| EXAMPLE 4 | 2876.6 | 43284.5 | 286.1 | 7.0 |
Compared with the prior art, the invention has the following beneficial effects: firstly, compared with the traditional electric comprehensive energy system which only depends on the standby capacity of the generator, the electric comprehensive energy system collaborative optimization operation method provided by the invention has the advantages that the standby of the generator, the energy storage equipment and the interruptible load are taken as standby resources for the system operation together, the collaborative complementary advantages among multiple types of standby resources can be fully utilized, the standby supply pressure of the generator is lightened, the operation economy of the electric comprehensive energy system is improved, and the air discarding quantity is obviously reduced; secondly, the collaborative optimization operation model of the electric comprehensive energy system has better robustness because the influence of system emergencies on standby capacity scheduling is considered.
Example 2
As shown in fig. 4, the difference between the present embodiment and embodiment 1 is that the present embodiment provides a co-optimizing operation system of an electrical integrated energy system, which supports a co-optimizing operation method of an electrical integrated energy system described in embodiment 1, and the system includes:
a preliminary model construction unit: the energy optimization operation model is used for establishing an energy optimization operation model of the electric comprehensive energy system taking various standby resources into account, wherein the various standby resources comprise generator standby resources, energy storage equipment standby resources and interruptible load standby resources;
the model constraint setting unit is used for setting the system reserve capacity deliverability constraint when the sudden accident is considered according to the electric comprehensive energy system energy optimization operation model, and taking the system reserve capacity deliverability constraint as the electric comprehensive energy system robust operation constraint of the electric comprehensive energy system energy optimization operation model;
The model decoupling unit is used for decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system;
The optimization solving unit is used for solving the optimization operation model of the electric power system and the optimization operation model of the natural gas system by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an energy optimization scheduling optimal solution of the electric comprehensive energy system;
And the output unit is used for outputting the optimal solution of the energy optimization scheduling of the electric comprehensive energy system to finish the collaborative optimization of the electric comprehensive energy system.
The specific execution process of each unit is executed according to the specific steps of the collaborative optimization operation method of the electrical comprehensive energy system described in embodiment 1, and in this embodiment, details are not repeated.
Compared with the existing optimized operation method and system of the centralized electric comprehensive energy system, the method and system have the beneficial effects that: the standby load of the generator can be effectively reduced by considering standby resources such as standby power of the generator, energy storage equipment, interruptible load and the like, the flexibility of system operation is improved, and the air discarding quantity and the total operation cost are reduced; the distributed collaborative optimization solving strategy based on the alternating direction multiplier method with the self-adaptive punishment parameters can effectively protect the data privacy of different energy institutions, and only the gas turbine data of both parties are needed in the solving process.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (4)
1. A collaborative optimization operation method of an electric comprehensive energy system is characterized by comprising the following steps:
Step 1: establishing an energy optimization operation model of an electric comprehensive energy system considering a plurality of standby resources, wherein the plurality of standby resources comprise generator standby resources, energy storage equipment standby resources and interruptible load standby resources;
Step 2: setting a system reserve capacity deliverability constraint considering sudden accidents according to the energy optimization operation model of the electric comprehensive energy system, and taking the constraint as an electric comprehensive energy system robust operation constraint of the energy optimization operation model of the electric comprehensive energy system;
step 3: decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; solving an optimal operation model of the electric power system and an optimal operation model of the natural gas system by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an optimal solution for energy optimal scheduling of the electric comprehensive energy system, and completing cooperative optimization of the electric comprehensive energy system;
The step of establishing the energy optimization operation model of the electric comprehensive energy system in the step 1 is as follows:
Step 11, setting an objective function of the energy optimization operation model of the electric comprehensive energy system, wherein the objective function is that the total operation cost of the system in the operation scheduling period of the system is the lowest, and the total operation cost of the system comprises energy supply cost C 1, wind abandoning cost C 2 and upward and downward standby capacity cost C 3 of the system; wherein:
The energy supply cost C 1 comprises the power generation cost, the natural gas production cost, the storage battery charge and discharge cost and the interruption compensation cost of the interruptible load of the conventional generator; the system up and down back-up capacity cost C 3, the up and down back-up capacity of the system being provided by the generator, battery and interruptible load together;
Step 12, setting an electric power system operation constraint, a natural gas system operation constraint and a system coupling constraint for the objective function;
The robust operation constraint of the electric comprehensive energy system energy optimization operation model in the step 2 comprises generator shutdown constraint, line interruption constraint and natural gas pipeline constraint;
Step 3, decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; adding the punishment items into an optimized operation model of the electric power system and an optimized operation model of the natural gas system to obtain the optimized operation model of the electric power system and the optimized operation model of the natural gas system after the punishment items are added;
The objective functions of the optimized operation model of the electric power system and the optimized operation model of the natural gas system after the penalty term is added are as follows:
Wherein, minf e is the optimized operation model of the electric power system after adding penalty term, and minf g is the optimized operation model of the natural gas system after adding penalty term; gamma j,t and p represent the lagrangian multiplier and penalty parameters, respectively; The cost of the cut load is indicated, Representing the cut load power.
2. The method for collaborative optimization operation of an electrical energy system according to claim 1, wherein the objective function set in step 11 is as follows:
Wherein, C i and P i,t respectively represent the cost coefficient and the generating capacity of the non-gas unit; c g and F g,t are cost coefficients and gas production, respectively, of the natural gas supply; c s is the unit charge-discharge cost of the battery, and P s,t is the charge or discharge power of the battery; And The unit power interruption compensation cost of the interruptible load and the dispatching power of the interruptible load are adopted; c w represents the unit penalty cost of the wind curtailment; And The cost coefficients for the up and down standby respectively,AndThe upward capacity and the standby capacity provided by a standby source r, which is a generator standby or a storage battery or an interruptible load, respectively; And Representing the cost factor for the up and down standby of the gas turbine,AndThe amount of natural gas reserved for the gas turbine to provide up and down reserve capacity, N G, represents the number of gas units.
3. The collaborative optimization operation method of an electrical comprehensive energy system according to claim 1, wherein in step 3, an optimization operation model of the electrical comprehensive energy system and an optimization operation model of a natural gas system are solved by adopting an alternating direction multiplier method based on self-adaptive penalty parameters, so as to obtain an energy optimization scheduling optimal solution of the electrical comprehensive energy system, and complete collaborative optimization of the electrical comprehensive energy system; the method specifically comprises the following substeps:
S31: variable initialization: setting an iteration index n=1, setting original and dual convergence thresholds ε p and ε d, initializing gas turbine gas consumption The reserve of gas reserved for the gas turbine to provide upward and downward reserve capacity isAndA Lagrangian multiplier λ and a penalty parameter ρ;
s32: solving the optimal operation result of the power system sub-problem 1: according to AndInitial value to obtain optimal solution result of current power systemAnd
S33: updating the auxiliary variable: order theSharing boundary variables with natural gas systemsAnd
S34: solving the optimal operation result of the natural gas system sub-problem 2: according toAndInitial value to obtain optimal solution result of current natural gas systemAnd
S35: updating the auxiliary variable: order theSharing boundary variables with power systemsAndInformation of (2);
S36: calculating boundary variables AndOriginal residual and dual residual of (a);
S37: checking convergence: if the maximum residual meets the constraint condition or N > N, terminating the iterative process and outputting a solution; otherwise, go to S38; if the current iteration number N is greater than the maximum iteration limit N, the solving process is regarded as being incapable of converging;
S38: updating the lagrangian multiplier and penalty parameters, letting n=n+1, and repeating the iteration after going to step S32.
4. A co-optimizing operation system of an electric integrated energy system, characterized in that the system supports a co-optimizing operation method of an electric integrated energy system according to any one of claims 1 to 3, the system comprising:
a preliminary model construction unit: the energy optimization operation model is used for establishing an energy optimization operation model of the electric comprehensive energy system taking various standby resources into account, wherein the various standby resources comprise generator standby resources, energy storage equipment standby resources and interruptible load standby resources;
the model constraint setting unit is used for setting the system reserve capacity deliverability constraint when the sudden accident is considered according to the electric comprehensive energy system energy optimization operation model, and taking the system reserve capacity deliverability constraint as the electric comprehensive energy system robust operation constraint of the electric comprehensive energy system energy optimization operation model;
The model decoupling unit is used for decoupling the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system;
The optimization solving unit is used for solving the optimization operation model of the electric power system and the optimization operation model of the natural gas system by adopting an alternating direction multiplier method with self-adaptive penalty parameters to obtain an energy optimization scheduling optimal solution of the electric comprehensive energy system;
the output unit is used for outputting the optimal solution of the energy optimization scheduling of the electric comprehensive energy system and finishing the cooperative optimization of the electric comprehensive energy system;
the primary model building unit comprises the following building steps:
Setting an objective function of the energy optimization operation model of the electric comprehensive energy system, wherein the objective function is that the total operation cost of the system in a system operation scheduling period is the lowest, and the total operation cost of the system comprises energy supply cost C 1, abandoned wind cost C 2 and upward and downward standby capacity cost C 3 of the system; wherein:
The energy supply cost C 1 comprises the power generation cost, the natural gas production cost, the storage battery charge and discharge cost and the interruption compensation cost of the interruptible load of the conventional generator; the system up and down back-up capacity cost C 3, the up and down back-up capacity of the system being provided by the generator, battery and interruptible load together;
Setting an electric power system operation constraint, a natural gas system operation constraint and a system coupling constraint for the objective function;
the robust operation constraint of the electric comprehensive energy system energy optimization operation model comprises a generator shutdown constraint, a line interruption constraint and a natural gas pipeline constraint;
The model decoupling unit decouples the energy optimization operation model of the electric comprehensive energy system to obtain an optimization operation model of the electric power system and an optimization operation model of the natural gas system; adding the punishment items into an optimized operation model of the electric power system and an optimized operation model of the natural gas system to obtain the optimized operation model of the electric power system and the optimized operation model of the natural gas system after the punishment items are added;
The objective functions of the optimized operation model of the electric power system and the optimized operation model of the natural gas system after the penalty term is added are as follows:
Wherein, minf e is the optimized operation model of the electric power system after adding penalty term, and minf g is the optimized operation model of the natural gas system after adding penalty term; gamma j,t and p represent the lagrangian multiplier and penalty parameters, respectively; The cost of the cut load is indicated, Representing the cut load power.
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