CN104065074A - A subnetwork structure and control method suitable for power optimization of single-phase microgrid - Google Patents

Abstract

The invention discloses a subnet structure and a control method suitable for single-phase micro-grid electric energy optimization, the subnet structure comprises traditional loads, elastic loads, energy storage devices including a storage battery, a bi-directional inverter, other micro sources including a photovoltaic battery, a subnet electric energy optimization controller and a direct-current line. Through control over output power of the bi-directional inverter and adjustment of the elastic loads, electricity utilization power of a subnet is controlled, so that the disturbance of the traditional loads, a wind driven generator, the photovoltaic battery and other micro sources is overcome, and time-sharing constancy of the electricity utilization power of the subnet is achieved so as to meet the dispatching requirement for the subnet by a superior micro-grid. Meanwhile, on the basis of the real-time electricity price, fuel price and others, the optimal control law is selected intelligently, and the electricity utilization cost of the subnet is optimized.

Description

A subnetwork structure and control method suitable for power optimization of single-phase microgrid

technical field

The invention relates to a microgrid system, in particular to a single-phase microgrid subnet structure and control method that can be dispatched by a superior microgrid and can optimize its own electricity cost.

Background technique

The microgrid is an important part of the smart distribution network. The microgrid integrates micro-resources such as micro-power sources, distributed energy storage, and elastic loads to form an autonomous system for power generation and distribution. However, due to the high randomness of renewable power sources such as wind power and photovoltaic power generation, the uncertainty of clean power sources such as traditional loads and fuel cells, and the controllable and adjustable elastic loads, the microgrid has become an uncertain load in the public power grid. , which has a huge impact on the stability and optimization of the public power grid.

The current microgrid research generally takes the microgrid electricity cost as the optimization goal, only considers the performance of the microgrid itself, and lacks the interaction with the public grid, making the microgrid still uncertain for the public grid.

The current micro-grid control technology is based on the background of three-phase power consumption in a region, and there is a lack of single-phase micro-grid optimization control methods.

The current micro-grid control technology divides the micro-grid into two states of grid-connected and isolated grid, and a grid-connected switch is set. This needs to upgrade and transform the power lines for users who have already laid power lines, which reduces the enthusiasm of users to participate.

Contents of the invention

The purpose of the present invention is to overcome the above-mentioned defects in the prior art, and propose a subnetwork structure and control method suitable for power optimization of single-phase microgrids, using elastic loads, energy storage devices, and micropower supplies for power complementation, and realizing microgrids The time-sharing power of the sub-network is constant to meet the scheduling requirements of the upper-level microgrid for the sub-network. At the same time, based on real-time electricity prices and fuel prices, the cost of sub-network electricity consumption is optimized.

In order to achieve the above object, the present invention has taken the following technical solutions:

A subnetwork structure and control method suitable for single-phase microgrid power optimization, the subnetwork structure includes traditional loads, elastic loads, storage batteries and other energy storage devices, bidirectional inverters, photovoltaic cells and other micro power sources, and subnetwork power optimization Controller, DC line. It is characterized in that: under the control of the sub-network power optimization controller, the power consumption of the single-phase microgrid subnet can be constant in time, and at the same time, the power consumption cost of the subnet can be optimized.

The microgrid subnetwork structure and control method control the power consumption of the subnetwork by controlling the output power of the bidirectional inverter and adjusting the elastic load.

In the microgrid subnetwork structure and control method, the subnetwork power optimization controller can realize time-sharing constant power consumption of the subnetwork by controlling the power consumption of the subnetwork according to the scheduling requirements of the superior microgrid for the subnetwork.

The microgrid subnetwork structure and control method described above do not require a physical switch for subnetwork connection, and the subnetwork power optimization controller realizes three states of the subnetwork by controlling the power consumption of the subnetwork, that is, the microgrid is connected to the subnetwork. Power supply status, subnet feeding status to microgrid, subnet isolated grid status.

In the microgrid subnet structure and control method, the bidirectional inverter, micro power supply, and energy storage device are connected through a DC line, and the charging and discharging power of the energy storage device is controlled by controlling the output power of the bidirectional inverter and the output power of the micro power supply. .

According to the microgrid subnet structure and control method, according to the real-time electricity price, fuel cost, and the remaining power of the energy storage device, by adjusting the elastic load, and controlling the output power of the bidirectional inverter and the output power of the micro power supply, the electricity cost of the subnet is realized. Optimization.

In the subnetwork structure and control method of the microgrid, the micropower supply can be freely increased or deleted according to the optimization of the electricity cost of the subnetwork;

In the microgrid subnetwork structure and control method, the subnetwork power optimization controller can be connected with the upper-level microgrid dispatching system through a communication network.

Advantage and positive effect of the present invention are:

The invention provides a sub-network structure and control method suitable for power optimization of single-phase micro-grids. Various types of micro-power sources, energy storage devices, etc. are uniformly connected to bidirectional inverters and connected in parallel with loads to form a The microgrid subnetwork system with constant output power time-sharing greatly simplifies the scheduling optimization difficulty of the superior microgrid and improves the stability of the microgrid. At the same time, the microgrid subnet realizes the optimization of the electricity cost of the subnet through internal adjustment. The present invention does not need to upgrade the existing power line, and the micro power supply can be increased or decreased freely, which is beneficial to the network design, control, maintenance and expansion of the micro grid.

Description of drawings

The accompanying drawings constituting a part of this application are used to provide further understanding of the present invention, and the schematic embodiments and descriptions of the present invention are used to explain the present invention, and do not constitute an improper limitation of the present invention. In the attached picture:

Fig. 1 is a schematic diagram of a single-phase microgrid subnetwork structure and a control method according to an embodiment of the present invention.

Detailed ways

1 is a schematic diagram of a single-phase microgrid subnet structure and control method according to an embodiment of the present invention, including traditional loads, elastic loads, energy storage devices, bidirectional inverters, micro power sources, subnetwork power optimization controllers, and DC lines; The bidirectional inverter, micro power supply, and energy storage equipment are connected through a DC line, and the micro power supply and energy storage equipment can be freely increased or decreased according to actual conditions; the bidirectional inverter is directly connected in parallel with the load.

The sub-network power optimization controller is connected to the upper-level micro-grid dispatching system through the communication network, and receives the application for the power consumption and running time of the elastic load; detects the power consumption of traditional loads through the power sampling circuit; and calculates the remaining power of the energy storage device through an internal algorithm. Electricity, as well as the maximum generating power of micro-power sources such as wind turbines and photovoltaic cells.

The sub-network power optimization controller takes the scheduling requirements of the upper-level micro-grid dispatching system and the safe and stable operation of the sub-network as constraints for optimization control, optimizes the sub-network according to information such as real-time electricity prices, fuel prices, and constructs an optimization objective function as follows:

$\mathrm{<span\; class="notranslate">\; J</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; k</span>}}{\overset{<span\; class="notranslate">\; \&infin;</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; price</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; Fuel</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>$

Among them, k is the discrete stage; U(·) represents the cost of electricity consumption; Price(i) is the real-time electricity price, C _Fuel is the unit fuel price; u(i) is the control strategy vector, including bidirectional inverter, elastic load and micro Power control strategy; x(i) is the remaining power of the energy storage device.

According to the optimization model, the subnetwork power optimization controller uses an adaptive dynamic programming algorithm to optimize the subnetwork internally, and the specific steps include:

1) Initialize the optimization objective function J ₀ (k), define the iterative stage l=0, 1, 2, ..., give the remaining power of the energy storage device, and give the calculation accuracy;

2) The control strategy and optimization objective function are iteratively updated according to the following formula:

${\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; arg</span>}\mathrm{<span\; class="notranslate">\; min</span>}}<span\; class="notranslate">\; \{</span>\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; price</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; Fuel</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; u</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; x</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; J</span>}}_{\mathrm{<span\; class="notranslate">\; l</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span>$

J _l+1 (k)＝U(Price(k), C _Fuel , u _l+1 (k), x(k))+J _l (k+1)

3) The iteration end condition is: ||J _l+1 (k)-J _l (k)||<ε.

Through the above optimization algorithm, the sub-network power optimization controller can calculate the optimal control strategy of the bidirectional inverter, elastic load and micro-power supply, and realize the optimal control of the electricity cost of the sub-network under the condition of time-sharing constant power consumption.

Claims (8)

1. subnet structure and a control method that is applicable to single-phase micro-electrical network electric energy optimizing, its subnet structure comprises micro-power supply, subnet electric energy optimizing controller, the DC line such as the energy storage devices such as traditional load, elastic load, storage battery, two-way inverter, photovoltaic cell, it is characterized in that: it is constant that the electric power of described single-phase micro-electrical network subnet can be realized timesharing under the control of subnet electric energy optimizing controller, realize the optimization of subnet electric cost simultaneously.

2. micro-electrical network subnet structure according to claim 1 and control method, is characterized in that: by controlling two-way inverter power output, and the adjusting to elastic load, control the electric power of subnet.

3. micro-electrical network subnet structure according to claim 1 and control method, it is characterized in that: subnet electric energy optimizing controller can the scheduling requirement to subnet according to the micro-electrical network of higher level, by controlling the electric power of subnet, the timesharing that realizes subnet electric power is constant.

4. micro-electrical network subnet structure according to claim 1 and control method, it is characterized in that: without the grid-connected physical switch of subnet, subnet electric energy optimizing controller is by controlling the electric power size of subnet, realize three kinds of states of subnet, micro-electrical network is to subnet power supply state, subnet to micro-electrical network feed condition, the lonely net state of subnet.

5. micro-electrical network subnet structure according to claim 1 and control method, it is characterized in that: two-way inverter, micro-power supply, energy storage device are connected by DC line, by controlling two-way inverter power output and micro-output power of power supply, control energy storage device and discharge and recharge power.

6. micro-electrical network subnet structure according to claim 1 and control method, it is characterized in that: according to Spot Price, fuel cost, energy storage device dump energy, by adjustable elastic, load, and control two-way inverter power output, micro-output power of power supply, realize the optimization of subnet electric cost.

7. micro-electrical network subnet structure according to claim 1 and control method, is characterized in that: micro-power supply can be optimized situation and freely increases or delete according to subnet electric cost.

8. micro-electrical network subnet structure according to claim 1 and control method, is characterized in that: subnet electric energy optimizing controller can be connected with the micro-power network dispatching system of higher level by communication network.