Search

ObjectivesConsidering the difference of primary frequency regulation ability of wind turbines under different wind conditions in wind farms, the evaluation method of frequency regulation capability of wind turbines was optimized on the basis of sag control and inertia control strategy.MethodsAn improved multi-unit frequency modulation reference power cooperative control strategy was proposed.ResultsThe introduction of multi-unit cooperative control method can effectively improve the distribution of frequency modulation reference power among units, thus effectively adjust the degree of each unit participating in the primary frequency regulation of the system. An improved cooperative control strategy was introduced on the basis of inertia control and sag control. According to the operation state of the unit under the actual wind condition, the reference power of the unit which can effectively participate in the primary frequency modulation was evaluated. The introduction of frequency modulation capability coefficient can realize the energy distribution of the reference value of frequency modulation power among units.ConclusionsThe cooperative control strategy can effectively protect the speed of wind turbine and improve the frequency response of power grid.

This paper proposes a day-ahead optimal economic dispatch model for building Combined Cooling, Heat and Power (CCHP) system based on centralized energy storage infrastructure. In the model, the loads are met by the centralized energy storage equipment directly, and the storage equipment are charged by varieties of energy supply devices in the energy station of the building CCHP system. The model is solved by the interior point method with Hessian matrix iteration. Simulation results show that by performing the schedule made by the dispatch model, the storage status of the centralized energy storage fluctuates in large dynamic range by flexible charging and discharging and the daily operation cost of the building CCHP system decreases remarkably compared with other traditional schedule strategies. DOI: http://dx.doi.org/10.5755/j01.eie.24.4.21478

As wind penetration level into power systems increases, provision of frequency support from wind plant is anticipated to become a requirement in grid codes. In addition to the virtual inertial response, two different approaches to delivering droop response from wind plant are presented and compared in this paper. The combination of droop and inertial response from wind plant has been assessed for a frequency time series. Simulation results show that the proposed approaches to delivering combined droop and inertial response can provide superior performance to either inertial or droop response alone.

This study proposes a day-ahead optimal energy dispatch model for integrated energy system based on AC/DC interconnected infrastructure. In the infrastructure, micro-turbines turn high-frequency AC power into industrial-frequency AC power and incorporate it into the energy system's power system. Within the process, waste heat is sent into the waste heat boiler and lithium bromide chillier to interconnect with the heating and cooling systems. DC battery and photovoltaic generations connected with the energy system's power grid through the inverter are used as the flexible energy storage and power generation unit to build an autonomous integrated energy system based on AC/DC interconnection. In the optimisation model, the goal is set as system's lowest daily operation cost and lowest energy consumption. The constraints include system operation constraints and equipment constraints. Simulation results show that by performing the schedule made by the dispatch model, the operating efficiency of various types of AC/DC equipment in the energy system has been improved, energy waste scene has been reduced significantly and energy consumption in the energy system is reduced by 16% compared with other energy supply structure without AC/DC interconnected infrastructure under traditional schedule strategies.

Wind power systems participating in primary frequency regulation have become a novel trend. In order to solve the problem of the over-speed deloading (OSD) control of wind power systems failing to provide reserved capacity for primary frequency regulation while under turbulent winds, this paper analyzes the influence mechanism of turbulence characteristics on the OSD control and the relationship between the reserve capacity of OSD control and the deloading power coefficient under turbulent wind speeds, while also quantifying the relationship between the turbulence characteristic index and deloading power coefficient. The range of the deloading power coefficient is obtained accordingly, based on which improved OSD control is proposed to dynamically optimize the deloading power coefficient according to the turbulence characteristics, which improves the frequency regulation performance of wind power systems under turbulent wind speed. According to the simulations and experimental results, the improved method proposed in this paper has good effectiveness and superiority in frequency regulation effect and rotor speed performance. [ABSTRACT FROM AUTHOR]

Building a new type of power system is an important guarantee to support China's "dual carbon" goal. Due to the inseparable relationship between industrial and agricultural production and electric energy utilization, there must be interdisciplinary integration to achieve the goal of "dual carbon". The disciplines of horticulture and electric power are taken as examples in this paper to analyze the feasibility of carbon emission reduction through coordinating agricultural photovoltaic (PV) greenhouse and electric vehicle (EV) energy storage. Firstly, the mechanism of carbon emission difference caused by electric energy supplementing during EV charging is analyzed. Secondly, in the context of the contradiction between the reduction of battery life caused by discharging (increasing carbon emission) and the increase in PV output consumption by orderly charging and discharging (reducing carbon emission), an optimization model for the synergistic operation of EV clusters and greenhouse PVs (with the objective of minimizing carbon emissions) is proposed. Finally, the effectiveness of the proposed model is verified through simulation cases. The energy storage characteristics of EVs is capable of realizing the transfer of PV power generation in the time dimension, and the coordinated operation of greenhouse PVs and EVs' charging and discharging can effectively reduce carbon emission during the EV operation period. In a typical summer scenario of PV output, the carbon emission of EVs in V2G (vehicle to grid) mode was reduced by 69.13% compared to disorderly charging. It is shown that the adequacy of PV generation and the orderly dispatching of the charging and discharging of EVs are the key factors in reducing carbon emission throughout the life cycle of EVs. [ABSTRACT FROM AUTHOR]

Soft open point (SOP) can improve the flexibility and reliability of power supplies; thus, they are widely used in distribution network systems. Traditional single-vector model predictive control (SV-MPC) can quickly and flexibly control the power and current at both ports of the SOP. However, SV-MPC can only select one voltage vector in a sampling time, producing large current ripples, and power fluctuations. In order to solve the above problems, this paper proposes a three-vector-based low complexity model predictive control (TV-MPC). In the proposed control method, two effective voltage vectors and one zero voltage vector are selected in a sampling time. For the two-port SOP, methods are given to judge the sectors on both sides and select the voltage vectors. Furthermore, the calculation method of the distribution time is proposed as well. Finally, the effectiveness of the proposed method is verified by steady-state and dynamic-state simulation results compared with the SV-MPC. [ABSTRACT FROM AUTHOR]

Summary: To reduce the investment cost of voltage sag mitigation equipment and the probability of voltage sag at the installation nodes of sensitive load, a comprehensive voltage sag mitigation strategy based on sensitive load clustering is proposed. The Monte Carlo method is used to get the stochastic estimation model of voltage sag to determine the lines with high fault probability, so as to get the weak links in the power grid, that is, the voltage sag vulnerable area. This paper proposes four sensitive indicators called tolerance magnitude of voltage sag, endurance duration of voltage sag, equipment capacity, and power dependence. The weight of each indicator is determined by the combination weighting method, and the affinity propagation (AP) clustering algorithm is used to classify different sensitive loads. The sensitive loads are mitigated by installing the energy storage equipment and dynamic voltage restorer (DVR), and the energy storage capacity is configured with the goal of minimum life cycle cost under the premise of voltage compensation. The result using MATLAB/Simulink and the laboratory equipment shows that, compared with existing mitigation strategies, the proposed mitigation strategy can not only effectively reduce the investment cost and the probability of voltage sag but also make the voltage distribution more reasonable. [ABSTRACT FROM AUTHOR]

Soft open point (SOP) is a key power electronic device to improve the flexibility and stability of the distribution network and is becoming a research hotspot. The traditional double closed-loop control of SOP has a complex structure, difficult process of parameter design, and poor output power quality. To solve these problems, finite control set model predictive control (FCS-MPC) has been adopted. Since FCS-MPC involves a large amount of calculation and experiences delay in current tracking, an improved FCS-MPC with delay compensation is proposed for three-port SOP in this paper to replace the inner loop current control strategy. Improved model predictive control combines the two-step prediction method based on the voltage vector and vector angle compensation method. The vector method is used to construct a mathematical model and a prediction model of three-port SOP. Based on FCS-MPC, the two-step prediction method that takes voltage as the target is used to compensate for the current delay problem, and the amount of calculation is reduced by converting the control target. Meanwhile, the vector angle compensation method is used to compensate the future reference value. Finally, a simulation model is built in MATLAB/Simulink. The simulation results under steady state and dynamic conditions show that the proposed strategy can effectively improve the current delay and reduce the amount of calculation. Furthermore, it has better current tracking accuracy and faster dynamic response speed. [ABSTRACT FROM AUTHOR]

With the large-scale integration of distributed photovoltaic (DPV) power plants, the uncertainty of photovoltaic generation is intensively influencing the secure operation of power systems. Improving the forecast capability of DPV plants has become an urgent problem to solve. However, most of the DPV plants are not able to make generation forecast on their own due to the constraints of the investment cost, data storage condition, and the influence of microscope environment. Therefore, this paper proposes a master-slave forecast method to predict the power of target plants without forecast ability based on the power of DPV plants with comprehensive forecast system and the spatial correlation between these two kinds of plants. First, a characteristics pattern library of DPV plants is established with K-means clustering algorithm considering the time difference. Next, the pattern most spatially correlated to the target plant is determined through online matching. The corresponding spatial correlation mapping relationship is obtained by numerical fitting using least squares support vector machine (LS-SVM), and the short-term generation forecast for target plants is achieved with the forecast of reference plants and mapping relationship. Simulation results demonstrate that the proposed method could improve the overall forecast accuracy by more than 52% for univariate prediction and by more than 22% for multivariate prediction and obtain short-term generation forecast for DPV or newly built DPV plants with low investment. [ABSTRACT FROM AUTHOR]

Considering the importance of reducing system operating costs and controlling pollutant emissions by optimizing the operation of the integrated energy system, the energy supply structure of the integrated energy system and the joint multiobjective optimization dispatching structure is analyzed in this paper based on a day-ahead economic optimization dispatching model of the integrated energy system. Afterwards, the multiobjective optimization model of the integrated energy system is studied and multiobjective hierarchical progressive parallel algorithm based on improved NSGA-II is proposed according to the characteristics of the model. The algorithm improves the nondominated layer sorting algorithm, changes the convergence judgment condition while introducing the target reaching method to accelerate convergence, and introduces parallel computing technology according to the characteristics of the algorithm. The case shows that the proposed algorithm not only has advantages on the diversity in searching solutions but also can achieve better results in many aspects such as the iteration time and algorithm convergence which are required in practical engineering projects. [ABSTRACT FROM AUTHOR]

The high penetration of renewable energy brings great challenges to power system operation and scheduling. In this paper, a multi-timescale coordinated method for source-grid-load is proposed. First, the multi-timescale characteristics of wind forecasting power and demand response (DR) resources are described, and the coordinated framework of source-grid-load is presented under multi-timescale. Next, economic scheduling models of source-grid-load based on multi-timescale DR under network constraints are established in the process of day-ahead scheduling, intraday scheduling, and real-time scheduling. The loads are classified into three types in terms of different timescale. The security constraints of grid side and time-varying DR potential are considered. Three-stage stochastic programming is employed to schedule resources of source side and load side in day-ahead, intraday, and real-time markets. The simulations are performed in a modified Institute of Electrical and Electronics Engineers (IEEE) 24-node system, which shows a notable reduction in total cost of source-grid-load scheduling and an increase in wind accommodation, and their results are proposed and discussed against under merely two timescales, which demonstrates the superiority of the proposed multi-timescale models in terms of cost and demand response quantity reduction. [ABSTRACT FROM AUTHOR]

A real-time error correction operation model for an integrated energy system is proposed in this paper, based on the analysis of the real-time optimized operation structure of an integrated energy system and the characteristics of the system. The model makes real-time corrections to the day-ahead operation strategy of the integrated energy system, to offset forecast errors from the renewable power generation system and multi-energy load system. When unbalanced power occurs in the system due to prediction errors, the model comprehensively considers the total capacity of each energy supply and energy storage equipment, adjustable margin, power climbing speed and adjustment cost, to formulate the droop rate which determines the unbalanced power that each device will undertake at the next time interval, while taking the day-ahead dispatching goals of the system into consideration. The case study shows that the dispatching strategy obtained by the real-time error correction operation model makes the power output change trend of the energy supply equipment consistent with the day-ahead dispatching plan at the next time interval, which ensures the safety, stability and economy of the real-time operation of the integrated energy system. [ABSTRACT FROM AUTHOR]