Analysis of Multi-intelligent Coordinated Optimal Control Strategy of Source Network with Distributed Power Supply

The hybrid microgrid with distributed power supply which includes wind turbine (WT), photovoltaic (PV) inverter and power converter system (PCS), not only could be connected to the power distribution network, but also can operate independently. It is realized switch from grid-connected mode to off-grid mode through the microgrid controller. Whether the microgrid can achieve smooth switching from grid-connected to off-grid has great influence on the safety and stability of the power grid. In order to accurately evaluate the influence of the microgrid switch to the distribution network, it is needed to research on the distributed source modeling technology, and establish an accurate microgrid model. In this paper, using a 400V voltage grade microgrid system with PV, WT and PCS as an example, model the internal equipment and the microgrid control system, and establish a microgrid model for simulation. At the meantime, it carries out the microgrid switch testing, and compare with the measured waveform to verify the accuracy of the model. It is confirmed the accuracy of the microgrid model by the contrast result.

After a large number of distributed generation (DG) access to the distribution network, it will have a great impact on the static voltage stability of the distribution network. How to effectively reduce the impact of distributed power supply on the distribution network voltage after grid connection has become an urgent problem to be solved. Based on the IEEE33 node distribution network and Matlab simulation software platform, the distributed power supply to the distribution network is studied through multi-angle analysis of access location, access quantity, output capacity, power factor, permeability and network loss. The effect of voltage distribution. The results show that only by properly configuring the distributed power supply can the node voltage of the distribution network be effectively improved.

With the extensive grid connection of distributed generation (DG), due to the safe and stable operation restrictions of the distribution network, the abandoning of wind and solar energy become more serious. As a new type of power distribution device, soft open point (SOP) is reliable and efficient in power control, which not only effectively solve a series of problems caused by distributed power supply access, but also greatly increase the flexibility and economy of active distribution network(ADN). This paper considers the distributed power supply characteristics and demand response (DR), and establishes the planning model of SOP in the active distribution network combining planning and operation. The network layer uses the minimum integrated cost of the power distribution company as the objective function to perform SOP location and capacity. The load layer adjusts the load with the minimum cost of participating DR users. The operation optimization layer determines the power at both ends of the SOP with the minimum cost of the distribution network in each scenario as the objective function. In order to account for the timing characteristics and uncertainties of distributed power output and load, this paper analyzes the distributed power output and load curve in typical scenarios. The time-of-use electricity price mechanism is introduced to reflect the demand side characteristics of the active distribution network. In this paper, an improved multi-objective particle swarm optimization (IMOPSO) is used to solve the above model. Finally, the IEEE-33 node power distribution system is selected as an example to simulate. Through comparative analysis, it is found that the planning model of this paper can maximize economic benefits and has higher feasibility.

The location and capacity optimization configuration of distributed power supplies ensures that they. Make better technical and economic use. When the distributed power supply is connected to the distribution network, it will cause the trend size and direction of each branch to change, so that the system loss is not only related to the load size, but also related to the location and capacity of DG. Therefore, it is important to study the rational planning of DG in depth. In order to improve the system network loss effectively, a distributed power distribution power distribution network reactive optimization model with the minimum active loss of the system is established, and an improved multi-target firefly algorithm is proposed for the problem that the traditional firefly algorithm will oscillate repeatedly near the extreme point later in the iteration. In view of the shortcomings of the traditional firefly algorithm, which is easy to precocious and over-dependent on control parameters, the chaotic search strategy and global idea are integrated into the firefly algorithm, and an improved firefly algorithm is proposed, which is applied to solve the planning problem of distributed power supply. The example shows that the proposed algorithm has good practicability and adaptability, and also verifies the practical significance of the proposed model[1].

In the context of increasing energy shortage, the application of various renewable and dispersed energy sources for power generation and energy supply will become increasingly widespread. As a small local power grid containing multiple distributed power sources connected to the distribution network, micro grid (MG) can be linked to the distribution network to operate, or can be disconnected from the distribution network to operate when the grid fails or when is needed. Due to the randomness of distributed power and load operation in MG, the direction of power transmission between MG and the distribution network is also uncertain. When the distributed power generation capacity of MG is small and the load level is high, MG must absorb electrical energy from the distribution network to meet the demand of the internal load of itself, which is equivalent to operating in the load state; and when the amount of power generated by the distributed power supply is large, the excess power will be sent back to the distribution network, which is equivalent to the power supply state, and this case will have a great impact on the original protection of the distribution network. In this paper, through the establishment of MG and distribution network grid structure simulation, the impact of MG to distribution network protection in power supply state and load state is analyzed respectively and a variety of improvement measures are proposed based on the actual situation.

Distributed generators are usually connected to medium and low voltage distribution networks. The structure of distribution networks has changed from a single radial network to a two-terminal and multi-terminal network with multiple power sources. The characteristics of power flow and voltage distribution in power networks have become more complex. Aiming at the problem of voltage control of distributed generation in distribution network, this paper firstly theoretically analyses the coupling relationship between voltage and active/reactive power in distribution network, and then compares the reactive and active power control methods under different R/X conditions. Then, by dividing the operation of distribution network into three states: normal, early warning and emergency, coordination control strategy of multi-distributed photovoltaic power under different conditions are proposed, which is validated by the IEEE standard example. The coordinated control strategy proposed in this paper has important application value for ensuring reliable and stable operation of distribution network and distributed power supply.

China's wind power capacity is increasing so rapidly that some areas are not able to consume all the produced wind power. Therefore, it has already become the inevitable trend in wind power integration to achieve the controlled operation of wind turbine. This paper first offers a method to predict the maximum generation capacity of every type of wind turbine, including both under-controlled wind turbine and uncontrolled wind turbine. And then a strategy for active power control of wind farm based on the predicting results is proposed. Considering thoroughly the active power fluctuation of wind turbine and the error of the prediction, the strategy adopts both long and short controlling periods to carry out coordinated optimization control. The simulation results show that the strategy can keep the active power output of wind farm in step with the control order, and consequently the generating efficiency is improved. In addition, the strategy is also applicable to the wind farm with some uncontrollable wind turbines, and the controlling precision can be satisfied.

With the development of the economy and the improvement of people’s living standards, energy has become an increasingly indispensable substance. The large-scale development and utilization of fossil energy has caused problems of energy crisis and environmental pollution. In order to solve these two problems, it is necessary to develop and utilize renewable energy sources, and access distributed power sources in the distribution network to form an active distribution network. The active distribution network contains a large number of distributed power sources, energy storage units and reactive power compensation equipment. Although it provides more convenience for voltage and reactive power regulation of the distribution network, the intermittent and volatility of renewable energy sources will also be Its voltage has a big impact. In order to solve the voltage dip and overvoltage problem of active distribution network, a new active distribution network voltage control strategy is proposed by using model prediction control technology. Inaccurate system modeling is reduced by establishing active distribution bus voltages, distributed power supplies, and energy storage device prediction models. With the minimum adjustment cost as the control target, the second-order cone relaxation method is used to optimize the action behavior of each control device. Finally, the IEEE33 node simulation example is built on the matlab simulation platform. The results show that the proposed voltage control strategy has good control effect and robustness.

With a large number of distributed power sources connected to the distribution network, power supply reliability has always been one of the most concerned indicators for power supply companies. Fault mode and effect analysis (FMEA) can predict the impact of fault isolation and load switching diversity in active intelligent distribution networks. In this paper, a standardized model of reliability system evaluation is constructed by FEMA table, and the reliability index is solved by combining Monte Carlo analysis method. The simulation with IEEE-RBTS BUS6 as an example shows that the method can quantify the effect of distributed power supply on the reliability of active distribution network, which proves that the proposed method is effective and feasible to solve the index.

With the development of new power system construction, distribution network as an important part, its safe and stable operation is more important. In order to make the distribution network have self-identification, self-positioning and self-healing functions, it is necessary to study the decentralized autonomous technology of the distribution network, including the state assessment and fault location technology of distributed power supply. In this paper, the autonomous intelligent agent unit (IA) is designed based on digital twin technology, which has the functions of state assessment, fault location and isolation. Through IEEE33-node with distributed power supply and MA-PSO algorithm, the internal autonomy of IA is simulated and analyzed. The results show that the proposed scheme and algorithm are fast, accurate and referable.

With the increasing scale and penetration of inverter-type power supplies, the network structure of the distribution network has changed, making it vulnerable to reclosing malfunctions and arc reignition during grid faults. In this paper, we propose an inverter-based distributed generation handling method during grid fault that eliminates the adverse effects of reclosing and automatic input device for backup. By reconstructing the external fault characteristics of the distributed power supply so that it does not output short-circuit current during low voltage periods and automatically restores power to the distributed power supply after a successful reclosing or automatic input device for backup, we use a finite state machine model to implement distributed power supply fault handling switching control. Simulation results verify that the method is simple and easy to implement and can improve the level of active distribution self-healing during grid fault.

power quality problems such as high line loss, low voltage exist commonly in rural power grid of China due to few supply points, long power transmission and distribution line. Huge fund is required to increase the quantity of supply points in rural power grid; installation of var compensators on line nodes could not solve power quality problems on the whole line. At the same time, as distributed power supply, wind power is also restricted by peak regulation, insufficient line output capacity and other factors in large scale centralized grid-connected output, wind curtailment often occurs. In order to solve the above-mentioned two problems simultaneously, electric power of wind farm may be output via nearby rural power grid line, thus not only utilization rate of wind power is increased, but also power quality of rural power grid is improved.This paper takes an example of a district in Fuxin City, summarizes power quality change data of relevant rural power grid before and after the distributed grid connection of wind farm is made, the analysis shows that distributed grid connection of wind power could improve load flow distribution of the power system, reduce system transmission loss in this district obviously, increase economical efficiency of the system operation effectively. At the same time, effectiveness of static var generator in substation to overcome the impact of such grid connection mode on power grid is verified.

In order to realize the reliability and economy of virtual power plant, landscape theory is applied to the construction of virtual power plant with distributed generation. Firstly, according to the complementarity of intermittent energy output of various distributed power sources, the attractive parameters between different distributed power sources are introduced, and then the matching degree and energy loss degree of the system based on panoramic theory are established. Then, considering the complex operation constraints of various distributed power sources, such as wind power, photovoltaic power, energy storage and electric vehicles, as well as the operation economy and energy loss after aggregation, a multi-objective function virtual power plant building model was constructed. In view of the complexity of the model, the model is transformed into a mixed integer linear single objective optimization model, and GAMS software is used for simulation solution. The simulation results show that the system operation cost is reduced and the output volatility is improved when the distributed power supply is aggregated into virtual power plant.

HIES: Cases for hydrogen energy and I-Energy

With rapid increase in wind power penetration into the power grid, unbalanced power flow in distribution network with distributed generators is becoming increasingly important to power sysytem. Due to the variability and uncertainty of wind, such traditional unbalanced power flow analysis method for distributed power supply limit the use of the existing tools for decision-making under uncertain conditions. As a result, unbalanced power flow analysis method, which provides information on uncertainty associated with wind power analysis, is gaining increased attention. This paper presents a novel hybrid intelligent algorithm for deterministic unbalanced power flow in distribution network with distributed generators that utilizes a combination of Cauchy particle swarm optimization(CPSO) and fuzzy ARTMAP (FA) network, which is optimized by using PSD-BPA. The performance of the proposed model is assessed utilizing wind power data from the Baolihua wind farm in Southern China. Unbalanced power flow in distribution network with distributed generators is researched. The typical static load model is established and the impact of distributed generators on feeder voltage profile is analyzed under unbalanced loads. The simulation results are given. References for the global planning of unbalance compensation in distribution network can be provided by the study.