CN106712082B - Distributed power generation system based on multiple intelligent agents - Google Patents

Abstract

The invention discloses a distributed power generation system based on multiple intelligent agents, which comprises a control system and a power generation system; the control system comprises a main management intelligent agent, a coordination intelligent agent, a circuit management intelligent agent and a power generation equipment intelligent agent; the main management intelligent agent is provided with an analysis module, can collect data of load electricity consumption and power generation equipment electricity production and provides reasonable prediction; the intelligent generating equipment body is connected with the generating equipment, monitors the operating environment of the generating equipment and manages and controls the operating state of the generating equipment; the power generation system comprises power generation equipment, a power converter, an energy storage device and a switch, wherein the power generation equipment is connected with the power converter, the power converter is connected with the energy storage device, the other end of the energy storage device is connected with a load, and the power generation equipment is directly connected with the load through the power converter. According to the invention, through improvement of the distributed power generation system, the micro-grid is ensured to have long-term stable power supply capability, and the defect of unstable current of the micro-grid is solved.

Description

A Distributed Power Generation System Based on Multi-Agent

Technical field:

The invention relates to a distributed power generation system, in particular to a multi-agent-based distributed power generation system.

Background technique:

With the development of the economy, the demand for electricity is increasing day by day. At present, the world still uses centralized power generation, long-distance power transmission and large power grid interconnection as the primary way of power generation, transmission and distribution, but its operation costs are high and difficult, and it is difficult to adapt to various power demands.

The microgrid formed by distributed power generation technology has the advantages of small investment, flexible power generation, reliable power supply, clean and environmental protection, etc., and has been widely concerned and applied. However, the green energy used by distributed power generation technology, such as wind power and photovoltaics, has high environmental requirements, and the power generation has the disadvantages of intermittent and random, and the generated current is unstable. If it is directly applied, it will cause damage to the electrical appliances on the load line. Invention patent CN201110326620.0 discloses a distributed micro-grid system that utilizes wind energy, solar energy complementary and comprehensively utilized with mains power, uses dispatching system to intelligently control the micro-grid, and solves the shortcoming of unstable current generated by the micro-grid. However, the distributed micro-grid system has low intelligence and cannot reasonably predict the power required by the load. When the power generation conditions are bad, it is easy to cause the distribution system to be in a power-deficit state. The power supply pressure during peak hours reduces the role of distributed generation systems.

Invention content:

The present invention proposes based on the above technical problems, introduces multi-agents into the distributed power generation system, and installs an analysis module in the management agent to reasonably predict the power generation and load power consumption, so as to ensure that the microgrid has long-term stable power supply ability. Through the intelligent control of the power generation equipment and energy storage device, the energy storage device is used to cooperate with the current generated by the power generation equipment to form a stable current and send it to the load line, which solves the shortcomings of current instability in the microgrid formed by distributed power generation technology.

In order to solve the problems of the technologies described above, the present invention adopts the scheme as follows:

A distributed power generation system based on multi-agents, characterized in that the distributed power generation system includes a control system and a power generation system; the control system includes a main management agent, a coordination agent, a circuit management agent, and a power generation device Intelligent body; the coordinating intelligent body is connected with each intelligent body for data transmission; the main management intelligent body is equipped with an analysis module, which can collect data on load power consumption and power generation equipment production, and provide reasonable predictions; The power generation equipment intelligent body is connected with the power generation equipment, monitors the operating environment of the power generation equipment, and controls the operation status of the power generation equipment; the power generation system includes power generation equipment, power converters, energy storage devices and switches; the power generation equipment It is connected with a power converter to convert the current into a current that meets the input specifications of the energy storage device; the power converter is connected to the energy storage device; the energy storage device is also connected to the load; the power generation equipment is directly connected to the connected to the load.

Further, the distributed power generation system also includes an information collection agent, which is connected to the coordination agent and automatically collects the environment and load power consumption information published in the network.

Further, the energy storage device of the distributed power generation system is a storage battery.

Further, the energy storage device of the distributed power generation system is flywheel energy storage.

Further, the power generation equipment of the distributed power generation system includes wind power generators, photovoltaic power generators, gas turbines and fuel cells.

Compared with the prior art, the present invention has the following beneficial effects:

1. By applying the distributed power generation system of the present invention, the main management system analyzes each parameter, predicts the future power generation and power consumption through the analysis module, and reasonably applies different system operation modes to reduce the load's dependence on the public power grid, even if If the generator fails to operate normally, the energy storage device can also be charged through the public grid during the low power consumption period, and the energy storage device supplies power to the load during the peak power consumption period, so as to reduce the load's demand on the public grid during the peak power consumption period.

2. By applying the distributed power generation system of the present invention, real-time monitoring and collection of parameters such as generator environment, generator power, and load power consumption can be achieved, and generators, energy storage devices, and loads can be protected.

3. By applying the distributed power generation system of the present invention, the energy storage device is used to solve the shortcomings of the intermittent and random nature of the current generated by the generator, so that the load can obtain a stable current, and avoid the load on the load caused by the unstable current of the generator. Electrical damage.

Description of drawings:

Fig. 1. The connection concept diagram of the power generation system of the present invention;

Fig. 2. the distributed power generation system diagram of the multi-agent of embodiment one of the present invention;

Fig. 3. The structural diagram of the main management agent of the present invention;

Fig. 4. A diagram of a distributed power generation system of a multi-agent in Embodiment 2 of the present invention.

Detailed ways:

In order to make the purpose, technical solution and beneficial effects of the present invention more clear, a multi-agent-based distributed power generation system of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. The specific embodiments described here are only used to explain the present invention, not to limit the present invention.

Example 1:

Fig. 2 is the multi-agent distributed power generation system figure of embodiment one, and the power generation equipment of described distributed power generation system is wind power generator, photovoltaic generator and fuel cell generator; Described wind power generator, fuel cell generator are respectively Connected to the storage battery through an AC/DC converter, the photovoltaic generator is connected to the storage battery through a DC/DC converter; the storage battery is connected to the load line through a DC/AC converter; the DC/AC converter is also connected to the AC through a logic switch /DC converter and DC/DC converter are connected; the load line is also connected to the power grid through a logic switch; the distributed power generation system also includes wind power generation intelligent body, photovoltaic power generation intelligent body, fuel cell intelligent body, main management Intelligent body, coordination intelligent body, circuit management intelligent body; said wind power generation intelligent body, photovoltaic power generation intelligent body and fuel cell intelligent body are respectively connected with wind power generator, photovoltaic generator and fuel cell generator; said coordination intelligent body is respectively It is connected with wind power generation intelligent body, photovoltaic power generation intelligent body, fuel cell intelligent body, main management intelligent body and circuit management intelligent body; said circuit management intelligent body is connected with battery, logic switch and load line.

When generating electricity, the wind power generation intelligent body, the photovoltaic power generation intelligent body and the fuel cell intelligent body respectively monitor the environmental conditions required for the generator to work in real time. When the environment meets the working conditions of the generator, the generator agent sends a command to start the generator, and when the environment is not suitable for the generator to operate, the generator agent sends a command to shut down the generator. The generator agent records the generator power P to _{generate electricity} and sends it to the main management agent through the coordinating agent. The current generated by the generator is changed to direct current that meets the input current requirements of the battery through the AC/DC converter to charge the battery. The battery releases a stable DC current, which is changed to a stable AC power supply load through the power converter. The current generated by the generator can also be directly supplied to the load through the DC/AC converter. The circuit management agent monitors and records the battery storage power P _storage , discharge power P _{battery discharge} and load line power P _load , and controls the battery and logic switches.

Figure 3 is a structural diagram of the main management agent. The data receiving and statistics module receives data information, summarizes and processes the data information through the analysis module, and speculates the possible future power generation P _{power generation} and power consumption P _load . The main analysis methods are as follows:

Collect the electric power P _{load 1} of this day, compare it with the electric power P _{load 2} of the same day last week, and determine the rate of change in power consumption X, X=P _{load 1} /P _{load 2} . According to the daily power consumption change curve of last week, combined with the power consumption change rate X, the power consumption P _load of tomorrow is estimated. For example, in order to speculate on the possible power consumption P _Thursday of this Thursday, collect the power consumption P _Wednesday of this week, and compare it with the power consumption P _{of last Wednesday} to determine the power consumption change rate X, X= _PWednesday / _{PLast Wednesday} , Then preliminarily determine the possible electric power P _{Thursday preliminary} =X(P _{last Thursday} ) this Thursday. In order to ensure that the maximum power demand of the load can be met, 20% is added on the basis of the estimated power consumption, and the power consumption P _load of this Thursday is determined = (1+20%) _{PThursday Preliminary} .

The estimated electric power P _load is divided into power P _{peak load} during peak power consumption period and power P _{valley load} during low power consumption period. Combining the existing power of the battery, the storage power P _storage and the discharge power P _{battery discharge} , the future system operation mode is formulated and sent to the knowledge base. The decision-making module combines the system operation mode in the knowledge base and the real-time information sent by the data receiving and statistics module to make an operation decision for the distributed power generation system, and sends it to each downstream intelligence through the execution command module through the token manager, member manager and coordinator body.

The main system operation mode is as follows:

When the predicted P _generation ≥ P _load + P _storage , the system operation mode is determined to be that the generator charges the battery on the basis of satisfying the power consumption of the load, and the excess power is sent to the grid. During actual operation, the circuit management agent controls the battery to stop discharging, and closes switch 1 and switch 2. The current generated by the generator directly supplies power to the load and the battery through the power converter, and the excess power is sent to the grid through the switch 2.

When the predicted P _load ≤ P _{power generation} < P _load + P _storage , the system operation mode is determined to be that the generator meets the power consumption of the load, and the excess power is transferred to the battery. During actual operation, the circuit management agent controls the battery to stop discharging, close switch 1, and open switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the excess power is sent to the battery.

When the predicted P _{power generation} < P _load < P _{power generation} + P _{battery discharge} , it is determined that the system operation mode is that the generator supplies power to the load, and the battery supplies power to the load. During actual operation, the circuit management agent controls the battery to stop charging, cooperates with the generator to discharge, closes switch 1, and turns off switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the battery supplies power to the load.

When the predicted P _{power generation} + P _{battery discharge} < P _load , and P _{power generation} + P _{battery discharge} > P _{peak load} , it is determined that the system operation mode is that the public grid supplies power to the load during the low power consumption period, and the generator charges the battery. During the peak period of electricity, the generator supplies power to the load, and the battery supplies power to the load. During the actual operation, the circuit management agent controls the battery to stop discharging and charge the battery during the period of low power consumption, close switch 2, and open switch 1. Electricity generated by the generator directly charges the battery, while the load is supplied by the public grid. The circuit management agent controls the battery to stop charging during the peak period of electricity consumption, cooperates with the generator to discharge, closes switch 1, and turns off switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the battery supplies power to the load.

When the predicted P _{power generation} + P _{battery discharge} < P _load , and P _{power generation} + P _{battery discharge} < P _{peak load} , the system operation mode is determined to be powered by the public grid to the load and battery during the low power consumption period, and the power demand of the load is met. At the same time, the battery is charged by the public grid and the generator to ensure that P _{power generation} + P _{battery discharge} ≥ P _{peak load} , so that the generator supplies power to the load during the peak period of power consumption, and the battery supplies power to the load, reducing the load during peak power consumption. long-term dependence on the public grid. During the actual operation, the circuit management agent controls the battery to stop discharging, charge and close the switch 1 and switch 2 during the period of low power consumption. The current generated by the generator directly charges the battery, and the public grid charges the battery through an AC/DC converter while supplying power to the load. The circuit management agent controls the battery to stop charging during the peak period of electricity consumption, cooperates with the generator to discharge, closes switch 1, and turns off switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the battery supplies power to the load.

In the embodiment of the present invention, by applying the distributed power generation system based on multi-agents, the main management system analyzes each parameter, predicts the future power generation and power consumption through the analysis module, and reasonably applies different system operation modes to reduce the load on the public power grid. Even if the generator fails to operate normally, the battery can be charged through the public grid during the low power consumption period, and the battery can supply power to the load during the peak power consumption period, so as to reduce the load's demand on the public grid during the peak power consumption period. At the same time, real-time monitoring and collection of parameters such as the generator environment, generator power, and load power consumption are achieved, and the battery is used to stabilize the generator to generate current, so that the load can obtain a stable current, avoiding the load on the load caused by the generator current instability. Electrical damage.

Embodiment 2:

Fig. 4 is the distributed generation system diagram of the multi-agent of embodiment two, and the generating equipment of described distributed generation system is wind power generator, photovoltaic generator and fuel cell generator; The wind power generator, fuel cell generator The flywheel energy storage is connected to the flywheel energy storage through the AC/AC converter, and the photovoltaic generator is connected to the flywheel energy storage through the DC/AC converter; the flywheel energy storage is connected to the load line through the AC/AC converter; the AC/AC conversion The inverter is also connected to the AC/AC converter and the DC/AC converter through a logic switch; the load line is also connected to the grid through a logic switch; the distributed power generation system also includes a wind power generation intelligent body, a photovoltaic power generation intelligent body, Fuel cell intelligent body, main management intelligent body, coordinating intelligent body, circuit management intelligent body and information collection intelligent body; the wind power generation intelligent body, photovoltaic power generation intelligent body and fuel cell intelligent body are respectively connected with wind power generator, photovoltaic generator and The fuel cell generator is connected; the coordination agent is respectively connected with the wind power generation agent, the photovoltaic generation agent, the fuel cell agent, the main management agent, the circuit management agent and the information collection agent; the circuit management agent Interface with flywheel energy storage, logic switch and load lines.

When generating electricity, the wind power generation intelligent body, the photovoltaic power generation intelligent body and the fuel cell intelligent body respectively monitor the environmental conditions required for the generator to work in real time. When the environment meets the working conditions of the generator, the generator agent sends a command to start the generator, and when the environment is not suitable for the generator to operate, the generator agent sends a command to shut down the generator. The generator agent records the generator power P to _{generate electricity} and sends it to the main management agent through the coordinating agent. The current generated by the generator is changed through the power converter to direct current that meets the input current requirements of the flywheel energy storage to charge the flywheel energy storage. The flywheel energy storage releases a stable DC current, which is changed to a stable AC power supply load through the AC/AC converter. The current generated by the generator can also be directly supplied to the load through the AC/AC converter. The circuit management agent monitors and records the energy storage power P energy storage of the flywheel energy _storage , the discharge power P _{battery discharge} and the electric power P _load of the load line, and controls the flywheel energy storage and logic switch.

The information collection agent collects the future light, wind intensity, fuel volume of the fuel cell and the historical power consumption of the local load in the generator area, and sends it to the main management agent through the coordination agent, and the analysis module predicts the possible future power generation P _{For power generation} and power consumption P _load , the main analysis methods are as follows:

Method 1: In order to estimate the power consumption P of this _Thursday , make statistics on the power consumption of previous Thursdays collected by the information collection agent, and determine that the highest power consumption P is the _{highest on Thursdays} . In order to ensure that the maximum power demand of the load can be met, 20% is increased on the basis of the determined maximum power consumption, and the power consumption P _load of this Thursday is determined = (1+20%) P is _{the highest on Thursday} .

Method 2: In order to estimate the power consumption P of this _Thursday , make statistics on the past weekly power consumption curves collected by the information collection agent, and calculate the power consumption change rate from Wednesday to Thursday X= _PThursday / _PWednesday , determine the maximum change rate of power consumption X _maximum from Wednesday to Thursday, combined with the power consumption P of _Wednesday to determine the highest possible power consumption P of _Thursday = the maximum X _maximum P of _{this Wednesday} . In order to ensure that the maximum power demand of the load can be met, 20% is increased on the basis of the determined maximum power consumption, and the power consumption P _load of this Thursday is determined = (1+20%) X _maximum P this Wednesday.

The electric power P _load is estimated by the above analysis method, and the electric power P _load is divided into the power P _{peak load} during the peak period of power consumption and the power P _{valley load} during the low power consumption period. Combining the existing power of flywheel energy storage, energy storage power P _{energy storage} and discharge power P _{battery discharge} to formulate the future system operation mode.

The main system operation mode is as follows:

When the predicted P _generation ≥ P _load + P _{energy storage} , it is determined that the system operation mode is that the generator charges the flywheel energy storage on the basis of meeting the load power consumption, and the excess power is sent to the grid. During actual operation, the circuit management agent controls the flywheel energy storage to stop discharging, and closes switch 1 and switch 2. The current generated by the generator directly supplies power to the load and the flywheel energy storage through the power converter, and the excess power is sent to the grid through the switch 2.

When the predicted P _load ≤ P _{power generation} < P _load + P _{energy storage} , the operating mode of the system is determined to be that the generator meets the power consumption of the load, and the excess power is sent to the flywheel for energy storage. During actual operation, the circuit management agent controls the flywheel energy storage to stop discharging, close switch 1, and open switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the excess power is sent to the flywheel for energy storage.

When the predicted P _{power generation} < P _load < P _{power generation} + P _{battery discharge} , it is determined that the system operation mode is that the generator supplies power to the load, and the flywheel energy storage supplies power to the load. During actual operation, the circuit management agent controls the flywheel energy storage to stop charging, cooperate with the generator to discharge, close switch 1, and open switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the flywheel energy storage supplies power to the load.

When the predicted P _{power generation} + P _{battery discharge} < P _load , and P _{power generation} + P _{battery discharge} > P _{peak load} , it is determined that the system operation mode is that the public grid supplies power to the load during the low power consumption period, and the generator charges the flywheel energy storage. During the peak period of electricity consumption, the generator supplies power to the load, and the flywheel energy storage supplies power to the load. During the actual operation, the circuit management agent controls the flywheel energy storage to stop discharging, charge, close the switch 2, and open the switch 1 during the low power consumption period. Electricity generated by the generator directly charges the flywheel energy storage, while the load is supplied by the public grid. The circuit management agent controls the flywheel energy storage to stop charging during the peak period of electricity consumption, cooperates with the generator to discharge, closes switch 1, and turns off switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the flywheel energy storage supplies power to the load.

When the predicted P _{power generation} + P _{battery discharge} < P _load , and P _{power generation} + P _{battery discharge} < P _{peak load} , the system operation mode is determined to be powered by the public grid to the load and flywheel energy storage during the low power consumption period. At the same time of electricity demand, the flywheel energy storage is charged by the public grid and the generator to ensure that P _{power generation} + P _{battery discharge} ≥ P _{peak load} , so that the generator supplies power to the load during the peak period of power consumption, and the flywheel energy storage supplies power for the load. Reduce the load's dependence on the public grid during peak power consumption periods. During actual operation, the circuit management agent controls the flywheel energy storage to stop discharging, charge, and close switch 1 and switch 2 during low power consumption periods. The current generated by the generator directly charges the flywheel energy storage, and the public grid charges the flywheel energy storage through the AC/AC converter while supplying power to the load. The circuit management agent controls the flywheel energy storage to stop charging during the peak period of electricity consumption, cooperates with the generator to discharge, closes switch 1, and turns off switch 2. The current generated by the generator directly supplies power to the load through the power converter, and the flywheel energy storage supplies power to the load.

In the embodiment of the present invention, by installing an information collection agent in the control system, the future illumination, wind intensity, fuel volume of the fuel cell, and historical power consumption data of the local load are collected in the generator area, so that the main management agent can have more Summarize experience based on a large amount of data, accurately predict future power _generation P and power consumption P _load , so that the distributed power generation system can apply a more suitable system operation mode, rationally allocate electric energy, and maximize the use of resources. In the embodiment, the flywheel energy storage is used to improve the service life and energy storage density of the energy storage unit. Because of its low environmental hazards, it is especially suitable for installation near residential areas and powering loads at close distances.

The parts of the present invention that are not described in detail are common knowledge in the field.

Claims (1)

1. A distributed power generation system based on multi-agents, characterized in that, the distributed power generation system includes a control system and a power generation system; the control system includes a main management agent, a coordination agent, a circuit management agent, Power generation equipment intelligent body; the power generation system includes power generation equipment, power converters, storage batteries and switches; the coordination intelligent body is connected with each intelligent body for data transmission; the main management intelligent body is equipped with an analysis module, which can analyze the load Data collection of power consumption and power generation of power generation equipment, and provide reasonable forecasts; the intelligent body of the power generation equipment is connected with the power generation equipment, monitors the operating environment of the power generation equipment, and controls the operating status of the power generation equipment; the power generation equipment It is connected with a power converter to convert the current into a current that meets the input specifications of the storage battery; the power converter is connected to the storage battery; the storage battery is also connected to the load; the power generation equipment is directly connected to the load through the power converter; the circuit The management agent is connected to the storage battery, switch and load line, and the distributed power generation system also includes an information collection agent, which is connected to the coordination agent, and automatically collects the environment and load power consumption information published in the network; The power generation equipment of the distributed power generation system is a wind generator, a photovoltaic generator and a fuel cell generator; the wind generator and the fuel cell generator are respectively connected to the storage battery through an AC/DC converter, and the photovoltaic generator is connected to the storage battery through a DC/DC converter. The DC converter is connected to the battery; the battery is connected to the load line through the DC/AC converter; the DC/AC converter is also connected to the AC/DC converter and the DC/DC converter through a logic switch; the load line It is also connected to the power grid through a logic switch; the intelligent body of the power generation equipment also includes a smart body for wind power generation, a smart body for photovoltaic power generation, and a smart body for fuel cell; The wind power generator, the photovoltaic generator and the fuel cell generator are connected; the coordination agent is also connected with the wind power generation agent, the photovoltaic generation agent, and the fuel cell agent respectively; the circuit management agent is connected with the storage battery, logic switch and load line connection; The working method of the distributed power generation system is as follows: when generating electricity, the wind power generation intelligent body, the photovoltaic power generation intelligent body and the fuel cell intelligent body respectively carry out real-time monitoring of the environmental conditions required for the generator to work; when the environment meets the generator working conditions When the power generation equipment intelligent body sends a command to start the generator operation, when the environment is not suitable for the generator operation, the power _generation equipment intelligent body sends a command to shut down the generator; the power generation equipment intelligent The body sends it to the main management agent; the generator generates current through the AC/DC converter and changes it to a DC power that meets the battery input current requirements to charge the battery; the battery releases a stable DC current, which is changed into a stable AC power supply through the DC/AC converter Load; the current generated by the generator can be directly supplied to the load through the DC/AC converter; the circuit management agent monitors and records the battery storage power P _storage , discharge power P _{battery discharge} and load line power P _load , and the battery and logic switch for control; When the predicted P _generation ≥ P _load + P _storage , the system operation mode is determined to be that the generator charges the battery on the basis of meeting the power consumption of the load, and the excess power is sent to the grid; When the predicted P _load ≤ P _{power generation} < P _load + P _storage , the system operation mode is determined to be that the generator meets the power consumption of the load, and the excess power is transferred to the battery; When the predicted P _{power generation} < P _load < P _{power generation} + P _{battery discharge} , it is determined that the system operation mode is that the generator supplies power to the _load , and the battery supplies power to the _load ; The power P _{low load} during the low power period, when the predicted P _{power generation} + P _{battery discharge} < P _load , and P _{power generation} + P _{battery discharge} > P _{peak load} , it is determined that the system operation mode is to supply power to the load by the public grid during the low power consumption period , the generator charges the battery, and the generator supplies power to the load during the peak period of power consumption, and the battery supplies power to the load; When the predicted P _{power generation} + P _{battery discharge} < P _load , and P _{power generation} + P _{battery discharge} < P _{peak load} , the system operation mode is determined to be powered by the public grid to the load and battery during the low power consumption period, and the power demand of the load is met. At the same time, the battery is charged by the public grid and the generator to ensure that P _{power generation} + P _{battery discharge} ≥ P _{peak load} , so that the generator supplies power to the load during the peak period of power consumption, and the battery supplies power to the load, reducing the load during peak power consumption. long-term dependence on the public grid.