Economic Operation Of Power Grid Research Articles

Optimal operation of electric–freshwater energy system considering load regulation strategy of individual hydrogen electrolyzer

AbstractIn view of the existing literature, only the optimization operation of hydrogen energy–wind/light new energy is considered, and the research problems such as comprehensive utilization of water resources and load control strategies are ignored. Based on the analysis of load characteristics of offshore wind power, this paper has established an optimal operation model of power‐fresh water energy system based on “wind‐hydrogen‐water‐electricity” interaction. Meanwhile, an electrolytic hydrogen individual load control strategy is proposed to match wind power fluctuations from the perspective of internal load regulation of electrolytic hydrogen system. From the economic characteristics, operation characteristics, accommodation situation and other simulation analysis, it can reduce the total operating cost by about 3.1%, improve the utilization rate of electrolytic cell capacity, and meet the water demand of coastal users. It shows that the individual control strategy and optimal operation model have advantages, which is of great significance for realizing low‐carbon, safe, and economical operation of power grid in the future.

Genetic Algorithm Based Temperature-Queuing Method for Aggregated IAC Load Control

In recent years, demand response (DR) has played an increasingly important role in maintaining the safety, stability and economic operation of power grid. Due to the continuous running state and extremely fast speed of response, the aggregated inverter air conditioning (IAC) load is considered as the latest and most ideal object for DR. However, it is easy to cause load rebound when the aggregated IAC load participates in DR. Existing methods for controlling air conditioners to participate in DR cannot meet the following three requirements at the same time: basic DR target, load rebound suppression, and users’ comfort. Therefore, this paper has proposed a genetic algorithm based temperature-queuing control method for aggregated IAC load control, which could suppress load rebound under the premise of ensuring the DR target and take users’ comfort into account. Firstly, the model of the aggregated IAC load is established by the Monte Carlo method. Then the start and end time of DR are selected as the main solution variables. A genetic algorithm is used as the solving tool. The simulation results show that the proposed strategy shows better performance in suppressing load rebound. In the specific application scenario of adjusting the frequency fluctuation of the microgrid, the results of the case show that this strategy can effectively control the frequency fluctuation of the microgrid. The effectiveness of the strategy is verified.

Load identification method of household smart meter based on decision tree algorithm

In order to ensure the safe and economic operation of power grid, a load identification method of household smart meters based on decision tree algorithm is proposed. This paper pre-processes the missing data, noise data and inconsistent data in the load data of household smart meter, and uses the decision tree algorithm to predict the load data after pre-processing. According to the prediction results, combined with mathematical tools, from the PQ characteristics, current characteristics, V-I characteristics The load characteristics of household smart meters are extracted from the characteristics, harmonic characteristics and instantaneous characteristics and the objective function of load identification is constructed based on the combination of characteristics, so as to realise the load identification of household smart meters based on decision tree algorithm. Comparative results show that this method can reduce the error rate of load, to improve the efficiency of identification, identifying the shortest time of only 1.5 s.

Intra‐day Dynamic Optimal Dispatch for Power System Based on Deep Q‐Learning

AbstractSource‐load stochasticity affects the safety, stability and economical operation of power grid, and makes it difficult to design optimal dispatch. Currently, due to the low accuracy of day‐ahead forecast for wind power and load, dynamic optimal dispatch based on ultra‐short‐term wind power prediction is an effective way to reduce the power deviation in power system and to relieve the operating pressure on automatic generation control (AGC) unit. In this paper, by comprehensively considering the source‐load stochasticity, the dispatch properties of unit, and the constraints of AGC regulating range, we establish a dynamic optimal dispatch model to minimize the running cost of the underlying power system, including the coal consumption cost of thermal unit, and the output adjustment cost of both the dispatchable unit and the AGC unit. Since each dynamic dispatch order has an impact, direct or indirect, on the subsequent system operation, we formulate the dynamic optimal dispatch problem as a Markov decision process (MDP) problem. In this framework, a deep Q‐learning method is provided to optimize the dispatch strategy. Finally, the feasibility and the effectiveness of the proposed method is validated by means of numerical experiments on IEEE 30‐node system. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Research on distribution network investment allocation method considering actual demand and investment benefit

under the new situation, improving the quality and efficiency has become an important means to enhance the core competitiveness of power grid enterprises and ensure the steady improvement of business efficiency. Distribution network is an important part of the power grid of power grid enterprises, and the current distribution network investment distribution lacks scientific quantitative basis. Therefore, how to scientifically plan the scale of power grid investment and improve the efficiency and efficiency of power grid investment is the foundation to ensure the safe and stable, efficient and economic operation of power grid, and it is also a practical problem to be solved.

Defect analysis of the same batch of substation equipment based on big data analysis algorithm

High-quality power equipment is the basis for ensuring the safe operation of the power grid and improving the reliability of power supply. In actual operation, although some electrical equipment can continue to be used, abnormal operation or hidden dangers will affect the safety of people, equipment and power grid, reliable and economic operation of power grid and equipment, equipment output or life span, and power quality. Therefore, research on multi-dimensional analysis of the same batch of substation equipment, and identification of suspected family defects and frequent defects is of great significance for improving the company’s equipment management and defect management. The maturity and promotion of unstructured text data mining, graph computing technology, and semantic analysis have provided a wider dimensional space for the analysis of power equipment defect data. Aiming at the shortcomings of traditional defect data analysis, this article summarizes and analyzes the defects and hidden dangers found in the equipment, traces the distribution status of the same equipment through the physical “ID”, carries out multi-dimensional analysis of the same batch of equipment, and investigates the hidden dangers of equipment family defects. A big data analysis algorithm to build automatic identification models of suspected familial defects and frequent defects in main substation equipment such as transformers, disconnectors, circuit breakers, and use graph computing technology to quickly integrate analysis capabilities in multi-source heterogeneous data fusion with hidden relationship discovery capabilities, identify equipment defects with potential impact relationships. From historical data, discover which manufacturers or purchased batches of equipment are more likely to have the same defect, and which defect types have a higher frequency, improve the recognition model of family defects and frequent defects, and improve the accuracy and comprehensiveness of defect recognition.

Design and Research of 110kv Intelligent Substation in Electrical System

Substation is an indispensable part of power system, responsible for the heavy task of power transmission and redistribution, and plays a pivotal role in the safe and economic operation of power grid. This design builds a 110 KV step-down substation. First of all, select the connection mode of each voltage level and choose the best flexible connection mode in terms of technology and economy. Secondly, calculate that short-circuit current. Obtain the values of the short-circuit steady-state current and the impulse current when the short-circuit occurs in the working bus of each voltage level from the three-phase short-circuit calculation. Finally, the equipment selection is made according to the rated voltage and the maximum continuous operating current of each voltage level, and then verified.

Study on Influence of Voltage Deviation on Loss of Low Voltage Distribution Network

Voltage deviation is one of the important power quality problems. Studying its impact on the power loss of low voltage distribution network is of great significance for the development of loss reduction measures and the realization of economic operation of power grid. The calculation models of transformer and line loss considering voltage deviation are derived firstly. The influence of voltage deviation on iron loss and copper loss of transformer and line loss under different load types are analysed in depth. The relationships between voltage deviation and additional loss of low voltage distribution network are obtained. The simulation verifications are carried out in PSCAD/EMTDC, which prove the accuracy and effectiveness of the calculation models.

Bidding strategy of pumped storage power station in spot market considering different optimization periods

Pumped storage power station has multiple functions, such as alleviating the contradiction between peak and valley, to ensure the safe and economic operation of power grid. In the non market stage, pumped storage power stations mainly obey the system operator’s scheduling. In the market stage, pumped storage power stations in China are likely to participate in the competitive power market and provide peak power, frequency regualtion and recovery services. The paper studies the bidding strategies of the pumped storage power stations participating in the power market, and provides decision support for the pumped storage power stations to maximize market returns.

Joint optimal dispatch of electric vehicles and air conditioning loads in office buildings based on demand response

Centralized use of air conditioning loads and the disordered charging and discharging of large-scale electric vehicles in cities have become the important reason for peak-valley difference increase of grid load in summer, deepening the contradiction between supply and demand during the peak period. Therefore, it is of great significance to improve power grid load characteristic and realize stable and economic operation of power grid by excavating peak shaving potential of large-scale air conditioning loads and electric vehicles. Taking into account the dispatching cost of power grid companies and the benefits of power users, a joint optimal dispatching model of electric vehicle and air-conditioning load is proposed. The power grid provided a low price compensation for loads and a high price compensation for EVs due to its battery loses. The objective function is optimized with the minimum load difference rate of office buildings and the maximum total revenue of users. Analysis of calculation example shows that air conditioning load and electric vehicle have complementary characteristics in energy use, and the joint optimal dispatching has certain effect on office building "peak load reduction", eliminating "secondary peak load" and improving electricity user income.

A hybrid wind speed forecasting model based on a decomposition method and an improved regularized extreme learning machine

Abstract Accurate wind speed forecasting plays a critical role in wind farm planning for economic operation of power grid. New forecasting methods which lead to better performances are urgently demanded for the wind energy management as there is no one model that is qualified in all cases. In this paper, a novel hybrid model is developed by integrating Fast Ensemble Empirical Mode Decomposition (FEEMD) and Regularized Extreme Learning Machine (RELM) optimized by Backtracking Search Algorithm (BSA) to realize the accurate short-term wind speed forecasting. This hybrid model can be partitioned into three phases: data preprocessing, training RELM by BSA, and aggregated calculation. Experiments have been conducted under different forecasting horizons and seasons with the proposed method as well as five benchmark models (RBF, GRNN, RELM, FEEMD-RELM, and BSA-RELM), respectively. Experimental results show the proposed model reduces RMSE by about 60% on average for all four cases than single RELM and it is superior to all the involved models in short-term wind speed forecasting.

Calculation of TTC for AC/DC Power Systems Based on Improved Continuation Power Flow

A model of total transfer capability (TTC) for the AC/DC system with multi-terminal voltage source converter DC (VSC-MTDC) system is set up in this paper. As the load and generator power in traditional continuation power flow (CPF) algorithm increased with equal proportion, a novel continuous power flow approach based on economic operation of power grid is proposed. In the method, taking the minimum generation cost as the goal, the distribution of generator output is optimized by economic dispatching based on linear programming method, which can avoid the defects of some existing methods that caused by the piecewise linearization of incremental ratio of generator consumption curve. The distribution of load increment and the parameters of VSC control modes are optimized by mathematical optimization method to minimize the network loss, which can get the TTC under economic conditions. Finally, cases study based on modified IEEE 9-node system and modified IEEE 30-node system verify the rationality and effectiveness of the proposed methods.

Research on Low Carbon Dispatching of Hybrid Power Generation System with Wind Power and Pumped Storage Station

The joint operation of wind farms and pumped-storage plants is an effective solution to the challenge that large scale wind power integration brings to the economic operation of power grid. In the low carbon dispatching of the hybrid power system with wind power and pumped storage, the economic efficiency is met by considering the environmental benefits. In this paper, the modeling and optimization algorithm of low carbon scheduling problem for hybrid system with wind power, thermal power and pumped storage station is studied. Firstly, the wind power scenario model is built based on the probability distribution of wind power prediction error. Then a two-stage stochastic programming model is established based on day-ahead scheduling and hour-ahead scheduling. Secondly, the improved differential evolution based the ε-constraint method and Pareto non-dominance sorting is applied to solve the low carbon scheduling problem for multi-objective optimization with mixed integer programming. Finally, an example is provided to verify the feasibility of the proposed algorithm by the use of MATLAB software.

Analysis and Research on the effect of the Operation of Small Hydropower in the Regional Power Grid

The analysis of reactive power balance and voltage of power network not only affects the system voltage quality, but also affects the economic operation of power grid. In the calculation of reactive power balance and voltage analysis in the past, the problem of low power and low system voltage has been the concern of people. When small hydropower stations in the wet period of low load, the analysis of reactive power surplus and high voltage for the system, if small hydropower unit the capability of running in phase is considered, it can effectively solve the system low operation voltage of the key point on the high side.

Discussion on joint operation of wind farm and pumped-storage hydroplant

Due to the random fluctuations in wind power, large amounts of grid integration will have a negative impact on grid operation and the consumers. The joint operation with pumped-storage hydroplant with good peak shaving performance can effectively reduce the negative impact on the safety and economic operation of power grid, and improve the utilization of wind power. In addition, joint operation can achieve the optimization of green power and improve the comprehensive economic benefits. Actually, the rational profit distribution of joint operation is the premise of sustainable and stable cooperation. This paper focuses on the profit distribution of joint operation, and applies improved shapely value method, which taking the investments and the contributions of each participant in the cooperation into account, to determine the profit distribution. Moreover, the distribution scheme can provide an effective reference for the actual joint operation of wind farm and pumped-storage hydroplant.

Intelligent Location and Analysis of Power Grid Fault Trip Based on Multi-source Data

China’s southern power grid has been plagued by frequent disasters, such as lightning strikes, wildfires, ice and typhoons, and so on, which pose a great threat to the reliable operation of the grid. It is difficult to meet the requirement of automatic operation in the way of the traditional manual or limited fault location, cause analysis and failure summary analysis report. Data based on the fusion of all kinds of business system, realize the reason of the fault tripping device and automatic analysis, automatic generation of fault tripping analysis report, automatic push in monitoring system fault alarm and send real-time alarm messages. Fault tripping intelligent positioning analysis is helpful to quick accurate positioning, help operations staff in a timely manner to solve fault, quickly restore power, effectively reduce the operations staff report provided workload, improve work efficiency, thus effectively ensure the safe, stable and economic operation of power grid.

Discussion on strategy of stabilizing high proportion of renewable energy power fluctuation

The power fluctuation of power system with high proportion of renewable energy and its access have caused a huge challenge to the safe and reliable operation of the power grid. What kind of method should be adopt to stabilize the power fluctuations of renewable energy generation and what to do to ensure the safe and economic operation of power grid have become the focus of research in the world. On the basis of the detailed investigation and study over the power fluctuation of renewable energy based on wind and solar energy, high energy consumption load regulation characteristics, as well as natural gas and oil pipeline network characteristics, this paper puts forward the general idea about stabilizing the high proportion of renewable energy power fluctuation in China. The idea considers the conentrated renewable energy and the distributed renewable energy. First, considerding the concentrated renewable energy. Combined with the characteristics of China’s energy resource development and load distribution, a strategy of transferring high energy consumption load from eastern region to western and northern regions where renewable energy are developed centrally is put forward in this paper. The high energy consumption load such as electrolytic aluminium which was thought had no contribution to the satability of frequency before have developed a new role in this paper. The potential power regulation capability of high energy consumption load is developed to achieve the partly in-situ consumption and the stabilization of fluctuations of the large-scale renewable energy power generation. On the other hand, considering the distributed renewable energy. The method by combining power grid with natural gas pipeline network and oil pipeline network at the receiving-end of power grid of renewable energy distributed utilization is proposed to build the household and commercial hybrid energy system. This system mentioned above can achieve the stabilization of power generation fluctuation at the receiving-end of the power grid. The concept of combing power grid with natural gad pipeline nerwork and oil pipeline network is novel. On this basis, a detailed explanation of the principle of stablizing the concentrated renewable energy power generation fluctuation at the sending-end of the power grid and the principle of stablizing the distributed renewable energy power generation fluctuation at the distribution network side are given in this paper. To improve the effectiveness of this method, the regulation capacity of the two ways to stabilize renewable energy power fluctuation with different development mode of renewable energy in 2020 and 2030 is evaluated in this paper. The result turns out that by transferning the power regulation capability of high energy consumption load to stable the concentrated renewable energy power generation fluctuation at the sending-end of the power grid and combining power grid with natural gas pipeline network and oil pipeline network to stable the distributed renewable energy power generation fluctuation at the distribution network side, the power system with high proportion of renewable energy would be in safe operation.

Research on the Effect of the Integration of Renewable Energy Resources on Economical Operation of Power Grid Based on System Dynamics

The integration of renewable energy resources (RERs) not only shows significant environmental effect, social effect and economic effect, but also brings many challenges to grid planning and economic operation of power grid. Based on systematic dynamics, from the perspective of changes of cost and benefit of grid enterprises caused by the integration of RERs, the effect of the integration of RERs on economical operation of power grid is studied. Finally, a simulation of effect trend based on empirical data of one province demonstrates the validity of the model proposed in this paper.

Study of Economical Operation of Power Grid Considering the Integration of Large-scale Renewable Energy

Study of Economical Operation of Power Grid Considering the Integration of Large-scale Renewable Energy

Research of New Generation of Energy Management System Considering Large-Scale Wind Power Integration

AbstractA trend of large-scale wind power integration has been formatted in China. However, current conventional Energy Management System (EMS) can not be suitable for this new demand. In this paper, based on the operational characteristics of wind power and the concept of uniform dispatch, the basic supporting platform, application modules and their key technologies and implementation methods of EMS are analyzed to ensure the safe and economic operation of power grid with large-scale wind power integration.