CN110544961A - dynamic economic dispatching method for isolated grid type alternating current-direct current hybrid micro-grid - Google Patents
dynamic economic dispatching method for isolated grid type alternating current-direct current hybrid micro-grid Download PDFInfo
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract
The invention discloses a dynamic economic dispatching method for an isolated grid type alternating current-direct current hybrid micro-grid, which is realized based on a consistency algorithm and a secondary regulation plan and aims to minimize daily power generation cost of the alternating current-direct current hybrid micro-grid. The method avoids the traditional centralized control method, adopts a consistency algorithm which is one of distributed control methods, sets the marginal cost as a consistency variable, optimizes the active power output of each distributed power generation unit in the microgrid based on a multi-agent communication system, and makes a secondary adjustment plan to ensure that the requirement of tie line constraint and the stable operation of the system are met. The method can effectively promote the consumption of the microgrid on the renewable energy, is suitable for a distributed power generation mode due to the large-scale grid connection of the renewable energy, improves the economic benefit of the microgrid, and has stronger robustness compared with the traditional method.
Description
Technical Field
The invention belongs to the technology of analysis and control of an electric power system, particularly relates to a dynamic economic dispatching method for an isolated grid type alternating current-direct current hybrid micro-grid, and particularly relates to a dynamic economic dispatching method for an alternating current-direct current hybrid micro-grid based on a consistency algorithm and a secondary regulation plan.
background
with the gradual decrease of fossil fuels and the rapid development of a distributed power generation mode of large-scale renewable energy grid connection, a micro-grid generator (MG) becomes a research hotspot in the field of current power systems. In recent years, the development of micro-grids is greatly impacted by the demand of a direct-current power supply and a large amount of loads connected to the power grid, and alternating-current and direct-current hybrid micro-grids are generated. The alternating current-direct current hybrid micro-grid comprises a direct current bus and an alternating current bus, the alternating current sub-micro-grid and the direct current sub-micro-grid are divided into two areas according to a distributed power supply and a load type, the sub-grids are connected through a bidirectional current converter, a direct current type power supply (photovoltaic, energy storage and the like) can be directly connected into the micro-grid to supply power for a direct current load, an alternating current type power supply can be directly supplied power for an alternating current load, unnecessary alternating current-direct current conversion and equipment investment cost are reduced, power loss in a power conversion process is reduced, and the operation efficiency and reliability of the whole system are improved.
The economic dispatching problem is the basis of micro-grid research. Currently, to solve the Economic Dispatch Problem (EDP) of micro-grids, many optimization methods have been proposed. The traditional methods comprise a particle swarm algorithm, a genetic algorithm and the like, which are mostly centralized control methods, a control center is needed to collect global information, the communication structure is complex, the flexibility and the robustness are lacked, the distributed control can realize global optimization only by exchanging information of neighbor units, the error of single-point communication does not affect the optimal result, and the method is also suitable for the management of the microgrid with changeable communication topological structure under the high renewable energy permeability.
on the basis of the analysis, an isolated island type micro alternating current and direct current hybrid micro-grid is taken as a research object, the problem of power distribution of micro-grid scheduling operation is focused, and a dynamic economic scheduling model of the isolated grid type alternating current and direct current hybrid micro-grid based on a multi-agent consistency algorithm is provided. The distributed power supply of the alternating current-direct current hybrid micro-grid is divided into all controllable output units according to the category, each unit is regarded as an intelligent agent, state information of each unit is transmitted through adjacent intelligent agents to optimize marginal operation cost of each unit, active output of each unit is coordinated, and the aim of minimizing total daily power generation cost of the micro-grid is fulfilled under the condition that load requirements are met. The method has stronger robustness and flexibility for the general communication topological structure change of the micro-grid, and can promote the consumption of the micro-grid on renewable energy sources and ensure the running stability of the alternating current-direct current hybrid micro-grid.
disclosure of Invention
The purpose of the invention is as follows: aiming at the defects in the prior art, the invention aims to provide a dynamic economic dispatching method for an isolated grid type alternating current and direct current hybrid micro-grid, and the dynamic economic dispatching method for the alternating current and direct current hybrid micro-grid based on a consistency algorithm and a secondary regulation plan is realized.
the technical scheme is as follows: a dynamic economic dispatching method for an isolated grid type alternating current-direct current hybrid micro-grid is based on a consistency algorithm and a secondary regulation plan and comprises the following steps:
(1) Establishing a dynamic economic dispatching system model of the alternating current-direct current hybrid microgrid, taking the minimum daily power generation cost of the microgrid as a target function, and carrying out global optimization on the system based on a consistency algorithm;
(2) judging whether the interactive power between the alternating current side and the direct current side exceeds the capacity constraint of the bidirectional converter or not based on the global optimization result of the alternating current-direct current hybrid micro-grid, if so, executing the step (3), otherwise, skipping the step (3) and executing the step (4);
(3) performing secondary adjustment planning based on load virtual value adjustment and a consistency algorithm;
(4) and iterating the steps at each single time interval, and outputting an economic dispatching result of the alternating current-direct current hybrid micro-grid under a complete dispatching cycle.
a scheduling cycle T of the dynamic economic scheduling system model is divided into 24 single time periods, the minimum daily power generation cost of the micro-grid is taken as a target function, and the mathematical expression of the model is as follows:
in the formula, STG is a traditional generator set unit set, and Ci (PTG, i (t)) is a cost function of a traditional generator set i; SWT is a fan unit set, and Ck (PSL, k (t)) is a cost function of a fan unit j; SSL is a photovoltaic unit set, and Ck (PSL, k (t)) is a cost function of the photovoltaic unit k; SBS is the set of energy storage units and Cr (PBS, r (t)) is the cost function of the energy storage device r.
further, the cost function of the traditional generator set unit operation in the dynamic economic dispatching system model is a quadratic convex function, and the mathematical expression of the quadratic convex function is as follows:
C(P(t))＝a(P(t))+bP(t)+c
in the formula, i belongs to the STG, ai, bi and ci is the power generation cost coefficient of the traditional generator set i, and PTG, i (t) is the active output of the traditional generator set i in the period of [ t-1, t ]; the output constraints of the corresponding traditional generator set are as follows:
in the formula, PTG, i is the minimum output power of the conventional generator set i, and is the maximum output power, and Δ Pd, i and Δ Pu, i are the lower limit and the upper limit of power ramp, and are the upper limit and the lower limit of the adjustable active power output of the conventional generator i at the time [ t-1, t ] in which various constraints are comprehensively considered.
Further, the wind turbine set and the photovoltaic set in the dynamic economic dispatching system model are controllable units, and the specific operation costs are respectively expressed as follows:
In the formula, j belongs to SWT, k belongs to SSL, ω j is a wind abandoning cost coefficient, ω k is a light abandoning cost coefficient, PWT, j (t) and PSL, k (t) are respectively the active output of a fan (WT) unit j and a Photovoltaic (PV) unit k at the time of [ t-1, t ] and the maximum output of the fan (WT) unit and the Photovoltaic (PV) unit at a single time interval, and are related to environmental factors;
The power constraint conditions of the fan unit and the photovoltaic unit are respectively expressed as follows:
the cost function of the energy storage unit in the dynamic economic dispatching system model is specifically expressed as follows:
C(P(t))＝a(P(t))
In the formula, r belongs to SBS, ar is the cost coefficient of the energy storage device r, PBS, r (t) is the active power sent or absorbed by the energy storage device r in the period of [ t-1, t ], when PBS, r (t) is more than 0, the energy storage device discharges to make up the power shortage of the power grid, when PBS, r (t) is less than 0, the energy storage device absorbs the redundant output of the power grid, and the power fluctuation of the micro-power grid is stabilized;
the capacity charge state constraint of the energy storage device is as follows:
based on the state of charge constraint of the energy storage device, the power constraint of charging and discharging of the energy storage device is as follows:
in the formula, the PBS, r is the maximum output power of the energy storage device r and is the minimum output power, the delta PBSd, r and the delta PBSu, r are the lower limit and the upper limit of power ramp, and the PBS, r is the power required by the energy storage device r to charge to the upper limit and discharge to the lower limit in the period of [ t-1, t ]. The method comprises the steps of comprehensively considering various constraints, namely the upper power limit of the charging state and the lower power limit of the discharging state of the energy storage device r at the moment of [ t-1, t ].
furthermore, the dynamic economic dispatching system model further comprises a power balance equality constraint and a tie line safety inequality constraint, and the specific expression is as follows:
in the formula, SDM is a set of loads distributed by the microgrid to each distributed power generation unit, PDM, s (t) is a load demand under a unit s, all distributed unit outputs in each time period are required to meet a system load demand, PAC _ DC is power transmitted from the ac side to the DC side, PAC _ DC is power transmitted from the DC side to the ac side, and PAC _ DC is a corresponding tie line constraint, that is, a maximum interaction power allowed by the bidirectional converter.
further, the method comprises the step of performing active output optimization on each distributed generation unit of the alternating current-direct current hybrid micro-grid based on a consistency algorithm, and specifically comprises the following steps:
(a) Obtaining a mathematical expression of a marginal cost function according to the cost functions of all the distributed power generation units in the dynamic economic model as follows:
λ＝aP+b
in the formula, ai and bi are cost coefficients of the distributed power generation unit i, and Pi is the active output of the unit i;
(b) the optimized marginal cost lambda i is calculated based on a consistency algorithm, namely the active output of the distributed power generation unit can be optimized, and the mathematical expression is as follows:
in the formula, Ω i is a set of all distributed power generation units, wij is an update coefficient of the kth iteration of the marginal cost of the unit i, and is related to the marginal cost of an adjacent unit, σ is a feedback influence factor and represents the influence degree of the supply and demand balance constraint on the iteration convergence speed, and Pmis, i (t) is a supply and demand difference and is represented as follows:
In order to satisfy the supply and demand balance of the system, the supply and demand difference Pmis, i (t) is used as a negative feedback term of the system and is updated along with the iteration of lambdai until the negative feedback term is updated to zero, and the system obtains the supply and demand balance.
further, the secondary adjustment plan includes performing secondary optimization on the system according to the load virtual value adjustment strategy, and the specific process is as follows:
assuming that power PAC _ DC is transmitted to the direct current side by the alternating current side in a single time period, the load virtual value is adjusted if the tie line constraint is exceeded, and then the subnets are respectively re-optimized based on a consistency algorithm, wherein a specific load virtual value adjustment strategy is implemented as follows:
an alternating current side:
Direct current side:
In the formula, m is the number of units in the sub-microgrid, PDM, s (t), and is a numerical value before and after load adjustment in a unit i in a period of [ t-1, t ] respectively.
Has the advantages that: compared with the prior art, the method provided by the invention can effectively promote the consumption of the microgrid on the renewable energy, is suitable for a distributed power generation mode of large-scale grid connection due to the renewable energy, improves the economic benefit of the microgrid and has stronger robustness.
drawings
FIG. 1 is a flow chart of an embodiment of the method of the present invention;
FIG. 2 is a schematic diagram of a communication topology of an AC/DC hybrid micro-grid according to the present invention;
FIG. 3 is a schematic diagram of daily load, photovoltaic daily output and fan daily output in the embodiment;
FIG. 4 is a schematic diagram of the convergence of the margin cost of the whole network in the embodiment;
FIG. 5 is a schematic diagram of active power output of a full grid output unit in the embodiment;
FIG. 6 is a schematic diagram of the supply and demand balance of the whole network in the embodiment;
FIG. 7 is an embodiment of a subnet communication topology;
Fig. 8(a) is a schematic diagram of marginal cost convergence of the ac microgrid;
FIG. 8(b) is a schematic diagram of the output optimization of each unit in the embodiment;
Fig. 9 is a schematic diagram of supply and demand balance of the ac microgrid in the embodiment;
fig. 10(a) is a schematic diagram of marginal cost convergence of the dc sub-microgrid in the embodiment;
FIG. 10(b) is a schematic diagram of the output optimization of each unit in the embodiment;
fig. 11 is a schematic diagram of supply and demand balance of the dc microgrid in the embodiment;
Fig. 12 is the result of the microgrid full-time optimization in the embodiment.
Detailed Description
in order to explain the technical solutions disclosed in the present invention in detail, the following embodiments are further described with reference to the accompanying drawings.
the invention discloses a dynamic economic dispatching method for an isolated grid type alternating current-direct current parallel-serial micro-grid, and the implementation flow of the method is shown in figure 1. The method is a dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid based on a consistency algorithm and a secondary regulation plan, and comprises the following specific implementation steps of:
1. Global optimization
(1) According to the cost function of each distributed power generation unit in the model, a marginal cost function shown as follows is obtained
λ＝aP+b
In the formula, ai and bi are cost coefficients of the distributed power generation unit i, and Pi is the active output of the unit i.
(2) the optimized marginal cost lambda i is calculated based on a consistency algorithm, namely the active power output of the distributed power generation unit can be optimized, and the method is expressed as follows
In the formula, Ω i is a set of all distributed power generation units, and wij is an update coefficient of the kth iteration of the marginal cost of the unit i, and is related to the marginal cost of the adjacent unit. Sigma is a feedback influence factor, which represents the influence degree of supply-demand balance constraint on the iterative convergence speed, and generally, the sigma is small, but too small leads to slow convergence. Pmis, i (t) is the supply-demand balance.
(3) In order to satisfy the supply and demand balance of the system, the supply and demand difference Pmis, i (t) is used as a negative feedback term of the system and is updated along with the iteration of lambdai until the negative feedback term is updated to zero, and the system obtains the supply and demand balance.
2. Interactive power constraint determination
after the global optimization, if the interactive power between the alternating current side and the direct current side of the alternating current-direct current hybrid micro-grid exceeds the capacity constraint of the bidirectional converter, continuing to execute the step 2; otherwise, step 3 is executed.
3. Plan of secondary adjustment
(1) The load virtual value adjustment strategy is the key of secondary optimization, assuming that the alternating current side transmits power PAC _ DC to the direct current side in a single time period, and the specific load virtual value adjustment strategy is executed as follows if the tie line constraint is exceeded:
An alternating current side:
Direct current side:
in the formula, m is the number of units in the sub-microgrid, PDM, s (t), and is a numerical value before and after load adjustment in a unit i in a period of [ t-1, t ] respectively.
(2) And based on a consistency algorithm, optimizing the active power output of the AC sub-microgrid and the active power output of the DC sub-microgrid are carried out by taking the minimum power generation cost of the AC sub-microgrid and the minimum power generation cost of the DC sub-microgrid as targets.
4. Complete scheduling cycle
and (3) sequentially executing the steps 1 and 2 in each single time period until t is greater than 24, stopping iteration, and outputting an economic dispatching result of the alternating current-direct current hybrid micro-grid in a complete dispatching cycle.
to verify the feasibility and reliability of the invention, the invention selects a typical peak electricity demand period 19: 00-20: 00, and gives specific examples.
The communication network topology of the ac/dc hybrid microgrid established in this embodiment is shown in fig. 2, and details of technologies known in the art are not described herein. The system constructed by the embodiment comprises 1 fan unit (WT), 1 photovoltaic unit (PV), 4 traditional generator unit (G1, G2, G3 and G4) and 2 energy storage device units (BESS1 and BESS2), and specific power generation cost coefficients and operation parameters of the 8 distributed power generation units are shown in table 1.
TABLE 1 microgrid operating parameters
the data of the typical daily load Pload, the photovoltaic PV daily output and the fan WT daily output are shown in fig. 3.
According to the steps disclosed by the method, whether the system can be globally optimal or not is considered, the marginal cost lambda of the output of each unit is shown in fig. 4, the marginal cost of all the power generation units is converged to an optimal value 13.6991, and at the moment, the feedback influence factor takes a value of 0.01. Fig. 5 shows that as the marginal cost converges the output optimization of each unit, the optimal output value of each unit is within the output constraint, and the global supply-demand balance condition of the microgrid is good, as shown in fig. 6. However, in the present embodiment, a low-voltage microgrid system is considered, the capacity constraint of the bidirectional converter connected between the ac side and the dc side is set to 60KW, and the power transmitted from the dc area to the ac area under the global optimal plan reaches 80.4197KW, which exceeds the tie line constraint, so that the global optimal plan is abandoned, and a subnet independent optimization plan based on a load virtual value adjustment strategy, that is, a secondary adjustment plan, is adopted.
the bidirectional converter is disconnected, communication among the sub-networks is interrupted, the independent communication topological structures of the alternating current sub-micro-network and the direct current sub-micro-network are shown in fig. 7, the optimization results of the alternating current sub-micro-network are shown in fig. 8(a) (b) and fig. 9, marginal cost converges to 16.6151, the optimized output of the fan unit, 2 traditional generator unit units and the energy storage device unit are 116.6150KW, 182.6881KW, 173.4783KW and 10.9003KW respectively under the condition that output constraint is met, and obviously, the regional supply and demand balance requirement of the alternating current micro-network is met along with convergence of the marginal cost.
the optimization results of the direct current sub-microgrid are shown in fig. 10(a) (b) and fig. 11, the optimal marginal cost is 10.5149, the optimized output results of the photovoltaic unit, the 2 traditional generator unit units and the energy storage device unit are respectively 0KW, 93.0698KW, 125.2481KW and 18KW, and the supply and demand balance condition is good.
finally, the operation condition of the full-time alternating current-direct current hybrid micro-grid under the isolated grid is shown in fig. 12.
in the method disclosed by the invention, the alternating current-direct current hybrid micro-grid has the advantages of a direct current micro-grid and an alternating current micro-grid, is more suitable for a distributed power generation mode, can promote the consumption of the micro-grid on renewable energy sources, and improves the economic benefit. A consistency algorithm of one of the distributed control has stronger robustness to the problem of connection errors of the micro-grid communication topology, and is suitable for the situation that the micro-grid communication topology structure is flexibly adjusted according to requirements.
Claims (8)
1. a dynamic economic dispatching method for an isolated grid type alternating current-direct current hybrid micro-grid is characterized by comprising the following steps: the method is based on a consistency algorithm and a quadratic adjustment plan, and comprises the following steps:
(1) establishing a dynamic economic dispatching system model of the alternating current-direct current hybrid microgrid, taking the minimum daily power generation cost of the microgrid as a target function, and carrying out global optimization on the system based on a consistency algorithm;
(2) judging whether the interactive power between the alternating current side and the direct current side exceeds the capacity constraint of the bidirectional converter or not based on the global optimization result of the alternating current-direct current hybrid micro-grid, if so, executing the step (3), otherwise, skipping the step (3) to execute the step (4);
(3) Performing secondary adjustment planning based on load virtual value adjustment and a consistency algorithm;
(4) And iterating the steps at each single time interval, and outputting an economic dispatching result of the alternating current-direct current hybrid micro-grid under a complete dispatching cycle.
2. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1, characterized by comprising the following steps: a scheduling cycle T of the dynamic economic scheduling system model is divided into 24 single time periods, the minimum daily power generation cost of the micro-grid is taken as a target function, and the mathematical expression of the model is as follows:
in the formula, STG is a traditional generator set unit set, and Ci (PTG, i (t)) is a cost function of a traditional generator set i; SWT is a fan unit set, and Ck (PSL, k (t)) is a cost function of a fan unit j; SSL is a photovoltaic unit set, and Ck (PSL, k (t)) is a cost function of the photovoltaic unit k; SBS is the set of energy storage units and Cr (PBS, r (t)) is the cost function of the energy storage device r.
3. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1 or 2, characterized by comprising the following steps: the cost function of the traditional generator set unit operation in the dynamic economic dispatching system model is a quadratic convex function, and the mathematical expression of the quadratic convex function is as follows:
C(P(t))＝a(P(t))+bP(t)+c
in the formula, i belongs to the STG, ai, bi and ci is the power generation cost coefficient of the traditional generator set i, and PTG, i (t) is the active output of the traditional generator set i in the period of [ t-1, t ]; the output constraints of the corresponding traditional generator set are as follows:
P in the formula, PTG, i is the minimum output power of the conventional generator set i, and is the maximum output power, and Δ Pd, i and Δ Pu, i are the lower limit and the upper limit of power ramp, and are the upper limit and the lower limit of the adjustable active power output of the conventional generator i at the time [ t-1, t ] considering all constraints comprehensively.
4. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1 or 2, characterized by comprising the following steps: the wind turbine set and the photovoltaic set in the dynamic economic dispatching system model are controllable units, and the specific operation cost is respectively expressed as follows:
in the formula, j belongs to SWT, k belongs to SSL, ω j is a wind abandoning cost coefficient, ω k is a light abandoning cost coefficient, PWT, j (t) and PSL, k (t) are respectively the active output of a fan (WT) unit j and a Photovoltaic (PV) unit k at the time of [ t-1, t ] and the maximum output of the fan (WT) unit and the Photovoltaic (PV) unit at a single time interval, and are related to environmental factors;
the power constraint conditions of the fan unit and the photovoltaic unit are respectively expressed as follows:
5. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1 or 2, characterized by comprising the following steps: the cost function of the energy storage unit in the dynamic economic dispatching system model is specifically expressed as follows:
C(P(t))＝a(P(t))
In the formula, r belongs to SBS, ar is the cost coefficient of the energy storage device r, PBS, r (t) is the active power sent or absorbed by the energy storage device r in the period of [ t-1, t ], when PBS, r (t) is more than 0, the energy storage device discharges to make up the power shortage of the power grid, when PBS, r (t) is less than 0, the energy storage device absorbs the redundant output of the power grid, and the power fluctuation of the micro-power grid is stabilized;
the capacity charge state constraint of the energy storage device is as follows:
Based on the state of charge constraint of the energy storage device, the power constraint of charging and discharging of the energy storage device is as follows:
P In the formula, the PBS, r is the maximum output power of the energy storage device r and is the minimum output power, Δ PBSd, r and Δ PBSu, r are the lower limit and the upper limit of power ramp, and are the power required by the energy storage device r to charge to the upper limit and discharge to the lower limit in the [ t-1, t ] period. The method comprises the steps of comprehensively considering various constraints, namely the upper power limit of the charging state and the lower power limit of the discharging state of the energy storage device r at the moment of [ t-1, t ].
6. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1 or 2, characterized by comprising the following steps: the dynamic economic dispatching system model also comprises a power balance equality constraint and a tie line safety inequality constraint, and the specific expression is as follows:
in the formula, SDM is a set of loads distributed by the microgrid to each distributed power generation unit, PDM, s (t) is a load demand under a unit s, all distributed unit outputs in each time period are required to meet a system load demand, PAC _ DC is power transmitted from the ac side to the DC side, PAC _ DC is power transmitted from the DC side to the ac side, and PAC _ DC is a corresponding tie line constraint, that is, a maximum interaction power allowed by the bidirectional converter.
7. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1 or 2, characterized by comprising the following steps: the method comprises the following steps of carrying out active output optimization on each distributed generation unit of the alternating current-direct current hybrid micro-grid based on a consistency algorithm, wherein the active output optimization comprises the following specific steps:
(a) Obtaining a mathematical expression of a marginal cost function according to the cost functions of all the distributed power generation units in the dynamic economic model as follows:
λ＝aP+b
In the formula, ai and bi are cost coefficients of the distributed power generation unit i, and Pi is the active output of the unit i;
(b) Calculating the optimized marginal cost lambda i based on a consistency algorithm, and optimizing the active output of the distributed power generation unit, wherein the mathematical expression is as follows:
in the formula, Ω i is a set of all distributed power generation units, wij is an update coefficient of the kth iteration of the marginal cost of the unit i, and is related to the marginal cost of an adjacent unit, σ is a feedback influence factor and represents the influence degree of the supply and demand balance constraint on the iteration convergence speed, and Pmis, i (t) is a supply and demand difference and is represented as follows:
In order to meet the supply and demand balance of the system, the supply and demand difference Pmis, i (t) is used as a negative feedback term of the system and is updated along with the iteration of lambdai until the negative feedback term is updated to zero, and the system obtains the supply and demand balance.
8. The dynamic economic dispatching method of the isolated grid type alternating current-direct current hybrid micro-grid according to claim 1, characterized by comprising the following steps: the secondary adjustment plan comprises the step of carrying out secondary optimization on the system according to the load virtual value adjustment strategy, and the specific process is as follows:
assuming that power PAC _ DC is transmitted to the direct current side by the alternating current side in a single time period, the load virtual value is adjusted if the tie line constraint is exceeded, and then the subnets are respectively re-optimized based on a consistency algorithm, wherein a specific load virtual value adjustment strategy is implemented as follows:
an alternating current side:
Direct current side:
In the formula, m is the number of units in the sub-microgrid, PDM, s (t), and is a numerical value before and after load adjustment in a unit i in a period of [ t-1, t ] respectively.
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Application publication date: 20191206 |