Xinwei Shen

Expansion Planning of Active Distribution Networks With Centralized and Distributed Energy Storage Systems

A multistage active distribution network (ADN) planning model that is integrated with the application of energy storage system (ESS) is presented in this paper. Both the long-term investment cost and short-term operation conditions of ADN are considered in the proposed model. The power supply reliability improvement brought by ESS is also analyzed. At each planning stage, the operation conditions are divided into several typical day scenarios and an extreme condition scenario which are based on the load forecast data. The long-term expansion planning decisions including those for replacing and adding circuits, introducing ESS, and considering ADN short-term operation strategies for the ESS charging and discharging are optimized together in the proposed model. The ESS benefits pertaining to peak load shaving and power reliability enhancement are demonstrated using numerical cases, in which the centralized and the distributed ESS are considered as options for the ADN implementation. The effectiveness of the proposed model is demonstrated through various discussions in the paper.

Multi-Stage Planning of Active Distribution Networks Considering the Co-Optimization of Operation Strategies

This paper presents a multi-stage and multi-load-scenario Active Distribution Network (ADN) expansion planning model. The proposed model considers the applications of new distributed generation (DG) and construction of feeders at the planning level, and the utilization of DG supply and topology reconfiguration of distribution network (DN) including microgrid at the operation level. The proposed co-optimization model incorporates both investment and operation costs of ADN in the objective function. The ADN operation at each time stage is divided into several scenarios based on the load forecast data, in which the optimal reconfiguration of the ADN topology and the power output of DG units are calculated. The co-optimization considers investment decisions at each planning stage and operation strategies at each ADN loading scenario. The benefits of introducing DG and network construction as planning options, and DG supply and network reconfiguration as operation strategies, are discussed. The effectiveness of the proposed co-optimization of investment-operation is demonstrated using the numerical results.

Online clustering modeling of large-scale photovoltaic power plants

This paper presents an online clustering modeling method for large-scale photovoltaic (PV) power plants. The proposed method utilizes the defined feature distance of inverter control parameters as the clustering index to derive the equivalent PV plant model. Based on the offline parameter database and the online matching method, the feature distance weighted by online parameter sensitivity is obtained to cluster PV generation units by using the K-means clustering algorithm. The method to acquire equivalent parameters of each clustered PV model is also presented. Simulation results show that the proposed online modeling method is effective and can track the dynamic characteristics of PV power plants accurately.

Online clustering modeling of photovoltaic power plant with LVRT control function

This paper proposes an online clustering modeling method for photovoltaic (PV) power plant considering low voltage ride-through (LVRT) control. The proposed method takes the distance of the unit impulse response curves of the inverter controllers as the clustering index to build the clustering models of the inverter controllers. After all LVRT controllers are simplified and described by an equivalent LVRT model, the clustering equivalent model of the PV power plant can be established which is composed of the clustering models of inverter controllers combined with their own equivalent LVRT models. The simulation results show that the proposed method has a strong capability to track the dynamic characteristics of the PV power plant while the output distribution of PV units changes.

The dynamic characteristics of photovoltaic generation system under partially shaded conditions

This paper presents a simplified photovoltaic array model to describe the photovoltaic system features under partially shaded conditions. Based on the proposed model, the peak power sliding phenomenon of photovoltaic generation is studied during the above mentioned system dynamic process. The paper analyzes the mechanism of the peak power sliding and the critical sliding conditions. Simulation cases are provided to verify the theoretical analysis. The simulation results also show the difference of dynamic characteristics between shaded photovoltaic system and non-shaded photovoltaic system.

Active distribution network expansion planning integrated with centralized and distributed Energy Storage System

A multi-stage Active Distribution Network (ADN) planning model that integrated with the application of Energy Storage System (ESS) is presented in this paper. Both the longterm investment cost and short-term operation conditions of ADN are considered in the proposed model. The benefits of power supply reliability improvement brought by ESS in the ADN are also included. In each planning stage, the operation conditions are divided into several typical-day scenes and an extreme scene based on the load prediction data. The long-term expansion planning decisions including replacing and adding circuits, building up ESS, the short-term operation strategies of the ADN about charging and discharging ESS are optimized together in the model. The benefits of ESS, such as peak load shifting and power reliability enhancement are discussed based on some numerical cases, in which the centralized or distributed ESS become the options of ADN construction. Thus, the effectiveness of the proposed model is also demonstrated.

Multi-scene security constrained economic dispatch with rational wind power curtailment in micro-grid

This paper proposes a security constrained economic dispatch (SCED) method for micro-grid containing wind power. By using wind power forecast data to divide the range of wind power fluctuation into multiple scenes, this method optimizes power output of traditional generation units and their spinning reserve. Besides, the proposed SCED method avoids loadshedding in micro-grid while the wind power is fluctuated by including the cost of multi-scene load-shedding risk into an objective function and rational curtailment of wind power. Reliability and stability of micro-grid are guaranteed while the total operation cost is minimized. Based on the practical data of a micro-grid, the numerical experiment results demonstrate the effectiveness of the proposed SCED method.

d-q axis decoupling parameter identification strategy for the grid-connected inverter of photovoltaic generation system

This paper presents a parameter identification strategy based on the d-q axis decoupling for a typical PV inverter, which contains double loop control model. This strategy can reduce the order of the model and improve the accuracy of the identification. Firstly, a typical PV grid-connected system model is built up, in which the inverter controller is based on the d-q axis decoupling current control. Its a double loop control including the outer voltage loop and the inner current loop, and the maximum power point tracking (MPPT). Secondly, we take the system as a research object, deduce the decoupling characteristics of the d-q axis parameters of the inverter controller through theoretical calculation, and reduce the order of the inverter model. Lastly, we get disturbance data through the simulation of control target reference step, and identify the parameters with the nonlinear damped least square method. The experimental results show that: the error is less than 5% in the dominant parameters of the inverter model, which proves the correctness and validity of the identification strategy.