Model Of Active Distribution Network Research Articles

Multiple-Zone Synchronous Voltage Regulation and Loss Reduction Optimization of Distribution Networks Based on a Dual Rotary Phase-Shifting Transformer

For the problem in which accessing a high proportion of renewable energy results in exceeding the limit in distribution network voltage, the existing regulating method experiences difficulty in considering the two-way voltage regulation and loss reduction optimization function. This study proposes a series-type dual rotary phase-shifting transformer (DRPST) based on the principle of phase volume synthesis. This transformer exhibits bidirectional voltage regulation, high reliability, and low cost. First, the topology, operating principle, and equivalent circuit of DRPST are introduced, and its simplified circuit model is established. On the basis of this model, the causes of voltage exceeding the limits are analyzed and the active distribution network model that contains DRPST is constructed. A real-time rolling two-layer optimization strategy based on DRPST is proposed. The inner layer model is solved using the multi-objective particle swarm optimization algorithm with the objective of minimizing voltage deviation and line loss. The optimal compromise solution of the Pareto solution set of the inner layer model is determined using the fuzzy subordinate degree function method. The outer model is based on the optimal compromise solution of the inner model, and the DRPST output rotor angle is controlled without deviation through double closed-loop proportional–integral regulation. Finally, the correctness and effectiveness of the proposed topology and control method are verified via simulation and experimental analysis.

Active Distribution Network Expansion Planning With Dynamic Thermal Rating of Underground Cables and Transformers

The rapid development of renewable distributed generation in active distribution networks (ADNs) imposes an increasing burden on the transfer capability of the ADNs, bringing new challenges to the distribution network expansion planning (DNEP) problem. Dynamic thermal rating (DTR), which evaluates the equipment rating based on the actual weather conditions and equipment thermal states, can enhance the equipment transfer capability to support the integration of renewable distributed generation. In this paper, we propose a DNEP model of ADNs incorporating the DTR of cables and transformers, given that underground cable feeder is preferred in the rapid urbanization trends. Then, we derive a linear reformulation of the original DNEP model and propose a modified Benders decomposition (MBD) algorithm to solve the DNEP model. To select more effective representative day scenarios, we propose a cost-based clustering method for representative day selection applicable to solving the DNEP model. Case studies based on the IEEE 33-node system and the PG&E 69-node system show that the implementation of DTR saves 14.7% and 15.1% of the investment costs of the two systems respectively. The effectiveness of the MBD algorithm and the cost-based clustering method is also verified by the case studies.

Study on multi-type flexible load control method of active distribution network based on dynamic time-sharing electricity price

Accurate load control is the basis of safe operation and optimal dispatching in active distribution network, and the demand response system of flexible electricity price mechanism and incentive mechanism is the premise of load control. Aiming at the complexity increase of load control caused by the integration of conventional loads, electric vehicles, and micro-grid multi-type user loads in the existing active distribution network, this study comprehensively takes the power consumption willingness of multiple typesof users in active distribution network into account for the first time. This study dominated by the user willingness selects a typical active distribution network load-related data onto a certain area to conduct a calculation example analysis. Firstly, a multi-type user load demand response model of active distribution network is constructed. Then, in order to achieve flexible control of active distribution network loads, a dynamic time-of-use electricity price game model considering the target function and the willingness of multiple usersis proposed, in order to achieve the maximum of user satisfaction and interests of power supply enterprises. Furthermore, the example results are compared with the intrinsic electricity price.Finally, the simulation results show that the time-of-use price established by the multi-type user load game is effective inguiding users to adjust their power consumption habits, making the load curve shift, controlling the electricity load within the maximum power supply limit, and thus alleviating the pressure of power grid expansion.

Real-Time Reduced Model of Active Distribution Networks for Grid Support Applications

Real-Time Reduced Model of Active Distribution Networks for Grid Support Applications

Uncertainty risk assessment of overloading violation based on security region and risk scheduling of active distribution networks

With increased uncertainties and depressed security margins of distribution networks, the risk of violating load or voltage constraints has increased. The usual risk-prevention method is to set an appropriate optimal schedule of active distribution networks to reserve enough margin without incurring extra operating costs. In this study, an optimal scheduling method for an active distribution network is proposed that allows for a low level of violation risk to minimize operating costs while maintaining good system security. Overload violation risk cost is a financial cost due to the cost of countermeasures needed to avoid overload violation. In this study, the N-0 security regions of overload are set as the constraint that provides the definition and calculation of the bidirectional violation distance of overloading for active distribution networks based on the N-0 security region. The relationship between the violation distance of overloading and the countermeasures against overload violation have been established based on the power flow equations, enabling the calculation of the countermeasures cost. The assessment model for the overload violation risk cost is derived from the cost of countermeasures and probability distributions of nodal power. The point estimation algorithm is introduced to simplify the calculation. The calculation of risk cost is fixed through the conditional value-at-risk. On this basis, a novel optimization scheduling model of active distribution networks that considers risk cost is constructed. Examples of the optimal schedule are designed and the validity of the proposed method is verified.

Novel Faulted-Section Location Method for Active Distribution Networks of New-Type Power Systems

This paper puts forward a fault location method combining the improved matrix algorithm and the genetic tabu algorithm based on multi-source information in view of the limitation of existing fault location methods in active distribution networks, such as long-time consumption, low accuracy, and low tolerance performance. Firstly, the fault region location method is proposed to simplify the active distribution network model and reduce the matrix calculation dimension. Secondly, the improved matrix algorithm is proposed to locate the fault section, and a positioning result verification method is proposed to improve the tolerance performance. Finally, the genetic tabu algorithm is proposed to optimize suspicious fault sections when the verification is incorrect and obtain the positioning result. The simulation results show that the fault location method proposed in this paper locates faster and performs better in both accuracy and tolerance in different fault conditions than others.

Voltage and active power local PI control of distributed energy resources based on the effective transfer function method

This paper presents the design of local PI regulators to control voltage and active power of the Distributed Energy Resources (DERs) in grid-connected Active Distribution Networks (ADNs). The design is developed based on the proposed Multiple-Input Multiple-Output (MIMO) model of ADN. Firstly, the Relative Gain Array (RGA) matrix is used to address the problem of input–output pairing and to show that the voltage control loops are coupled whereas the active power control loops are decoupled. Subsequently the method of the Effective Open-Loop Transfer Function (EOTF) is used to decompose the multi-loop voltage control system into a set of equivalent Single-Input Single-Output (SISO) loops. Then, each PI regulator is independently designed to fulfill some control objectives dictated by the designer. The proposed design procedure is simple and straightforward. The fixed-parameters PI regulators facilitate the integration of DERs into traditional distribution networks which are usually operated without or with limited communication infrastructure. The simulation results presented for various scenarios of two different ADN confirm that performance objectives and regulation at the desired set-points are achieved in a robust sense.

Distributed optimization method for economic dispatch of active distribution networks via momentum with historical information and forecast gradient

In the context of vigorously developing new energy sources, the economic dispatch(ED) of active distribution network (ADN) is essential. Due to the single fault affecting the global and high communication cost in centralized scheduling, we propose a distributed gradient method, namely the fast Nesterov accelerated gradient method(FNAGM), which can solve the economic dispatch problem(EDP) in ADN. The distributed architecture does not need to collect global information and only uses a sparse communication network to complete communication exchanges. It is the distributed architecture that can protect users’ private information and reduce communication pressure. By constructing the acceleration matrix based on the upper limit of the second derivative, the convergence speed can be effectively improved while satisfying the equality constraints. Eventually, the FNAGM combined with the historical momentum information and the forecast gradient, which is simulated in the bi-layer model of ADN via MATLAB. The verification results show that the algorithm with the historical momentum information and the forecast gradient can complete the optimal scheduling of controllable distributed generator(DG). What is more, the convergence efficiency performance is greatly improved.

Coordinated restoration method of transmission and distribution network considering distribution network fault repair scenario

With the development of active distribution network (ADN) technology, coordinated restoration of transmission network (TN) and ADNs has received widespread attention. As an important part of power system resilience, power system restoration should consider the influence of low-probability high-risk events. Such extreme events are often accompanied by component damage, so the coordination of restoration process and repair scheduling needs to be considered. First, the handling of fault repair scenario on TN and ADNs side during black-start restoration (BSR) is discussed. The interaction between the coordinated restoration of TN/ADNs and the fault repair schemes of ADNs is analyzed. Next, the coordinated restoration of TN/ADNs considering the ADN fault repair scenario is modelled in this paper. For the restoration model of TN, the restoration logic relationship of plants/lines, the subsystem division, frequency constraints of the restored system and the power scheduling constraints of source/load are considered. For the restoration model of ADNs, the restoration logic relationship of DGs/lines/buses, the scheduling logic of repair crews and emergency power sources, frequency constraints and the power scheduling constraints of source/load are considered. Then, an analytical target cascading algorithm is used to solve the optimization model. Finally, a TN/ADNs system is constructed by an IEEE_30 bus transmission system and two IEEE_33 bus distribution system, the numerical case study on the TN/ADNs system verifies that the distributed collaborative optimization of the TN/ADNs restoration plan and the fault repair plan of ADNs can improve the overall restoration efficiency during BSR.

Fault Analysis Method of Active Distribution Network Under Cloud Edge Architecture

Efficient fault treatment of active distribution network is an important guarantee to ensure the steady-state reliability of the system. In order to improve the accuracy of distribution network fault identification and analysis, a fault processing method based on deep learning is proposed in this paper. This method collects massive heterogeneous data sets using patrol robot to realize real-time perception and accurate acquisition of distribution network status. Relying on the processing mode of distribution network cloud edge collaboration, the principal component analysis method is used at the edge to effectively remove redundant data, providing a complete and reliable data support for the deep network model. Meanwhile, the attention mechanism is added to the cloud to improve the depth confidence network, further realizing the extraction of useful feature information for complex data sets and avoiding the interference of irrelevant information on the recognition results. The simulation experiment is based on the actual active distribution network model. The experimental results show that the fault identification accuracy of the proposed method can reach 0.9255, indicating an excellent distribution network fault identification and analysis ability to support safe operation of active distribution network.

Multilevel optimization of economic dispatching in active distribution network based on ADMM

With the continuous improvement of the penetration rate of renewable energy and the continuous integration of advanced network control technology and measurement equipment, the traditional distribution network is developing into an active distribution network (ADN) with the characteristics of flexible scheduling control, high user interaction, and high energy utilization. This article fully considers the economy of the overall operation of the distribution network, and proposes a hierarchical optimization economic dispatch method for active distribution networks based on the alternating direction multiplier method (ADMM). Firstly, a hierarchical optimization scheduling model of active distribution network is established with the goal of minimizing the overall operating cost of the distribution network. The alternating direction multiplier method algorithm is decomposed into upper and lower layers to solve. The upper layer is optimized with the goal of minimizing the overall operating cost of the distribution network, and the lower layer considers the distribution network. The distributed photovoltaic and energy storage units connected to the internal nodes of the network are optimized with the goal of minimizing the local energy storage operation cost and power purchase cost. The upper and lower layers, through the exchange of limited boundary information, iterate each other until the convergence conditions are met, and the optimal solution is obtained. Finally, a design example is tested to verify the effectiveness and feasibility of the proposed scheduling method.

Robust dispatching model of active distribution network considering PV time-varying spatial correlation

With a high proportion of photovoltaic (PV) connected to the active distribution network (ADN), the correlation and uncertainty of the PV output will significantly affect the grid dispatching operation. Therefore, this paper proposes a novel robust ADN dispatching model, which considers the dynamic spatial correlation and power uncertainty of PV. First, the dynamic spatial correlation of PV output is innovatively modeled by dynamic conditional correlation (DCC) generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model. DCC can accurately represent and forecast the spatial correlation of the PV output and reflect its time-varying characteristics. Second, a time-varying ellipsoidal uncertainty set constructed using the DCC, is introduced to bound the uncertainty of the PV outputs. Subsequently, the original mixed integer linear programming (MILP) model is transformed into the mixed integer robust programming (MIRP) model to realize robust optimal ADN dispatching. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method.

General Modelling Method for the Active Distribution Network with Multiple Types of Renewable Distributed Generations

With a proliferation of diverse types of renewable distributed generation (DG) into the distribution network, an equivalent model of an active distribution network (ADN) is extremely important, since the detailed modeling of the whole ADN is much more complex and time consuming. However, different studies developed different model structures of ADNs, which are difficult to be applied in a power system simulation. At the same time, the DG’s low voltage ride through the (LVRT) control was not considered in the existing ADN model, which may lead to a large modelling error. In this paper, a general equivalent model is developed for the ADN with a significant amount of DGs, based on a two-step modelling method. Step one, motivated by the dynamic similarities between the doubly-fed induction generator (DFIG)-based wind turbines, direct drive permanent magnet synchronous generator (DDPMSG)-based wind turbines, and photovoltaic (PV) generation, a general model structure of a renewable DG is initially developed. Then, an aggregation method for the DG’s nonlinear subsystems of the low voltage ride through (LVRT) control and the converter’s current limits are presented. Step two, the ADN model is represented by a general renewable DG model paralleled with a composite load model, and the model is validated, based on an actual distribution network with different renewable DG penetrations and different disturbance degrees. The simulation results show that our model outperforms others with acceptable errors.

Multi-target Programming Method for Active Distribution Network Considering the Multiple Collaborative Interaction Effect

The effect of indeterminacy of distributed generation should be fully considered in the planning of active distribution network. Based on the conventional load forecasting, the trusted output model of distributed generation connected to active distribution network is built. Thinking the influence of load demand side response on the forecasted load results, a distribution network load forecasting model considering the multiple synergistic interaction effect of source, load and storage is proposed. Based on the results of load forecasting, a double-deck multi-objective programming model of active distribution network is established. The upper deck function is the problem of power grid optimization planning, and the goal is to minimize the annual network comprehensive cost; The lower level programming model determines the active power output of manageable resources such as energy stored based on the typical daily system operation economy under the grid achieved by the upper part planning. Through the optimization solution, the distribution network planning scheme and the location and capacity scheme of energy storage under the active management mode are obtained. In result, we use an active distribution network in Shanghai to prove the scientificity and effectiveness of the proposed programming method

Multi-Voltage Level Active Distribution Network With Large Share of Weather-Dependent Generation

Utility-scale and small scale wind and solar power installations along with electric vehicle charging stations, and other active sources of energy are increasing at the medium and lower voltage levels in the distribution grid. This situation requires a better understanding of the impact of high penetration of weather-dependent renewable energy sources on the operating conditions of the distribution network at both medium and low voltage levels. Despite the need, a multi-voltage level distribution network model, based on real network data and weather-dependent renewable generation data, has not been presented for distribution grid studies. This paper presents a comprehensive multi-voltage level active distribution network model based on real network data along with load and generation time-series for about a year. The network topology is modelled based on geographical data for various rural, semi-urban, and urban locations. The distribution network is embodied with a large share of renewable generation sources, with generation time-series simulated from meteorological data. The network is also flexible to incorporate other assets such as electric vehicle charging stations, storage, etc. The presented active distribution network model can be used to study, optimize, and control the effects of weather-dependent generation and other network assets in the distribution grid.

Active distribution network active and reactive power coordinated dispatching method based on discrete monkey algorithm

The operation and dispatching pressure of active distribution network is gradually increasing with the integration of distributed generators into urban distribution network unevenly. It is necessary to carry out research on active and reactive power coordinated dispatching. In order to obtain the coordinated dispatching scheme rapidly, the active and reactive power coordinated dispatching is decoupled in this paper. Reactive power optimization and active power dispatching are carried out respectively. The final coordination dispatching scheme is formulated through the cross iteration of active power dispatching and reactive power optimization. Firstly, the reactive power optimization model is set by mainly considering adjusting transformer tap and changing capacitor output capacity. The model is solved by a two-stage method to obtain the dynamic dispatching scheme. Secondly, active power dispatching model of active distribution network is set considering network reconfiguration. To obtain the solution quickly, the discrete monkey algorithm is used to solve the model, among which particle swarm optimization algorithm is used in the climb process to solve the sequential coupling problem of switch state variables. Finally, the node voltage quality can be effectively improved and grid loss of distribution transformer cluster can be significantly reduced by a few of adjustments of transformer taps, shunt capacitors and switch. The practicability of dynamic coordination dispatching method is proved.

Hierarchical multi-objective optimal planning model of active distribution network considering distributed generation and demand-side response

Power grid planning is the basis of power system development, the structure of distribution network in China has changed from single source unidirectional network to multi-source multidirectional complex power network, which further increases the uncertainty and complexity of distribution network operation and planning. From the perspective of distributed energy grid connection, this paper constructs a hierarchical optimization model of distribution network planning under active management mode. The relationship among balanced network loss, line investment, power purchase cost, carbon emission cost and policy subsidies are comprehensively considered. To improve the convergence and effectiveness of the algorithm, NSGA-TS hybrid algorithm is applied for example analysis, which has better global search and local search ability. From the calculation and analysis results of an example, it can be seen that the model is effective in practical analysis, and expands the analysis idea of distribution network planning.

A d-axis based current differential protection scheme for an active distribution network

The emergence of distributed generators has changed the operational mode and fault characteristics of the distribution network, in a way which can severely influence protection. This paper proposes a d-axis-based current differential protection scheme. The d-axis current characteristics of inverter-interfaced distributed generators and synchronous generators are analyzed. The differential protection criterion using sampling values of the d-axis current component is then constructed. Compared to conventional phase-based current differential protection, the proposed protection reduces the number of required communication channels, and is suitable for distribution networks with inverter-interfaced distributed generators with complex fault characteristics. Finally, a 10 kV active distribution network model is built in the PSCAD platform and protection prototypes are developed in RTDS. Superior sensitivity and fast speed are verified by simulation and RTDS-based tests.

Distributed dispatching method of active distribution network considering multiple regulation resources

In view of the low capacity of distribution network to accept renewable energy such as wind power and photovoltaic, which leads to the failure of active distribution network to achieve the expected economic benefits, a distributed scheduling method of active distribution network considering multiple regulation resources is proposed in this paper. In the case of multiple coupled energy access, the resource collaborative scheduling principle is designed, the business process of adjustable resources participating in the emergency coordination control of auxiliary distribution network is proposed, and the supply side resources and demand side resources are planned. The installation location and initial capacity of distributed generation are determined by network sensitivity factor method. After optimizing the capacity, the location and scale of distributed generation are obtained. Considering the load response and distribution of distributed generation, the distributed dispatching model of active distribution network is established with the goal of minimizing output cost and dispatching cost. The net annual value method is used to calculate the operation benefit increment of distribution network, so as to evaluate the effect of control. Taking the pilot project in Zhejiang as an example, the maximum operating benefit increment of this method is 367600 yuan, which is 32800 yuan and 45300 yuan higher than the scheduling method based on power load temporal and spatial correlation and risk distribution respectively, which can improve the operating benefit for the power grid company.

Maximum openable capacity optimization method of active distribution network considering multiple users access

With the development of active distribution network (ADN), the situation that multiple users such as distributed generations and loads are connected to multiple nodes of ADN at the same time may occur. In this case, the power flow of ADN will change a lot when compared with the situation that a user is connected to only one node of ADN. Therefore, a maximum openable capacity optimization model of ADN considering multiple users access is proposed in this paper to deal with the situation that multiple users such as distributed generations and loads are connected to multiple nodes of ADN at the same time. The improved non-dominated sorting genetic algorithm (NSGA-II) is utilized to solve the proposed model, and case study based on IEEE 33-bus ADN is performed for verifying the effectiveness of the proposed maximum openable capacity optimization method.