Reactive Power Coordination Research Articles

Active and reactive power coordination optimization for active distribution network considering mobile energy storage system and dynamic network reconfiguration

The active distribution network (ADN) can face with challenges due to the increasing renewable distributed generation (RDG), which may result in elevated network losses and voltage fluctuations. To address these issues, a novel operation strategy is proposed which integrates the mobile energy storage system (MESS) and dynamic network reconfiguration (DNR) to adjust the active and reactive power of the ADN. The transportation network (TN) is modeled considering the traffic congestion, and the path movement of MESS in TN is converted to the switching of virtual switch (VS) in ADN. A coordinated optimal model is formulated for DNR and MESS, furthermore, which can be transformed into a mixed-integer second-order cone programming (MISOCP) model. The penalty alternating direction method (PADM) is employed to enhance the computational efficiency. Then the proposed strategy is tested by the IEEE 33-bus system coupled with the 15-node transportation systems, and the stability of the proposed strategy was validated in a larger scale expansion system. The simulation results demonstrate that the coordinated optimal strategy considering MESS and DNR can effectively reduce network loss and transportation cost, enhance the voltage quality of the ADN and promote the consumption of renewable energy.

A multi-objective coordinating model for distribution network with EVs, energy storage, and reactive power compensation devices

Promoting electric vehicles (EVs) is regarded as an effective solution for reducing carbon emissions and addressing growing environmental concerns. However, the increasing number of EVs has significantly heightened the demand for electric power charging, posing challenges to distribution systems. Studies have shown that a coordination strategy combining various compensation devices, such as energy storage systems and reactive power compensation devices, can enhance the integration capability of EVs. Furthermore, EVs can be managed as controllable loads that can be shed at low costs, contributing to the flexibility of the distribution network. This paper explores the uncertainties of EV load sizes and the coordination of active and reactive power. A multi-objective optimization model was developed to augment the flexibility of the distribution network and mitigate the risk of load shedding. The Monte Carlo method is utilized to simulate scenarios with EV load uncertainties. To simplify the power flow calculations in the proposed convex optimization model, the Distflow equation was adopted. Case study results demonstrate that managing EV loads in the distribution network can significantly reduce load shedding costs by 80 %, and the proposed EV charging strategy can effectively eliminate load shedding costs in most scenarios.

Voltage Hierarchical Control Strategy for Distribution Networks Based on Regional Autonomy and Photovoltaic-Storage Coordination

High-penetration photovoltaic (PV) integration into a distribution network can cause serious voltage overruns. This study proposes a voltage hierarchical control method based on active and reactive power coordination to enhance the regional voltage autonomy of an active distribution network and improve the sustainability of new energy consumption. First, considering the reactive power margin and spatiotemporal characteristics of distributed photovoltaics, a reactive voltage modularity function is proposed to divide a distribution grid into voltage regions. Voltage region types and their weak points are then defined, and the voltage characteristics and governance needs of different regions are obtained through photovoltaic voltage regulation. Subsequently, a dual-layer optimal configuration model of energy storage that accounts for regional voltage regulation is established. The upper-layer model focuses on planned configurations to minimize the annual comprehensive operating cost of the energy storage system (ESS), while the lower-layer model focuses on optimal dispatch to achieve the best regional voltage quality. KKT conditions and the Big-M method are employed to convert the dual-layer model into a single-layer linear model for optimization and solution. Finally, an IEEE 33-node system with high-penetration photovoltaics is modeled using MATLAB (2022a). A comparative analysis of four scenarios shows that the comprehensive cost of an ESS decreased by 8.49%, total revenue increased by 19.36%, and the overall voltage deviation in the distribution network was reduced to 0.217%.

Voltage control method for multi-energy system based on the coupling of renewable energy hydrogen production and storage

Renewable energy power generation combined with hydrogen storage, is an important way to realize the deep integration of hydrogen energy and renewable energy in multi-energy systems. In the multi-energy system of renewable energy power generation and hydrogen production in AC/DC hybrid. Due to the fluctuation of heat load and electric hydrogen production load in the system and the multi-time scale characteristics of energy flow transmission of heat storage and hydrogen storage. It will lead to the difficulty of power coordination in the whole Multi Energy System (MES). In order to solve the problem of power imbalance in MES, this paper first establishes the hybrid power flow equation of MES cluster composed of AC/DC and hydrogen energy transmission channels. The reactive voltage fluctuation characteristics of the AC/DC system under the fluctuation of energy exchange, system energy conversion, and renewable energy output of the MES cluster interconnection channel are analyzed. Secondly, a multi-energy flow model of the multi-energy system is established. The main factors affecting the voltage-reactive power of the AC system are analyzed. A reactive power model based on electro-thermal conversion, hydrogen storage, and multi-energy transmission channels is established. Then, a generation algorithm of the safe and stable boundary of pipeline pressure is proposed to maintain the pressure of hydrogen production and storage system within a safe range. The robust optimization control method is used to control the coupling of multi-energy sources. Finally, based on the actual operation data of the multi-energy power system. The simulation model of reactive power dynamic optimization control for multi-energy interconnected systems is established. The simulation results show that the control method proposed in this paper is adopted. Through the coordinated distribution of energy among multi-energy systems, the voltage stability level of the system can be effectively improved.

Multiscale dynamic time‐domain simulation of regional integrated energy considering seasonal load difference

AbstractTo improve the multiscale dynamic dispatching and distribution capacity of regional integrated energy, a multiscale dynamic time‐domain dispatching model of regional integrated energy with seasonal load difference is proposed. The master–slave game coordination planning model of regional comprehensive energy multiscale dispatching is constructed, and the difference fusion model of regional comprehensive energy multiscale dynamic dispatching is established by using the active and reactive power coordination control method according to the influence factors of voltage deviation and line overload absorption. Maximize the weight factors of the positive contribution of distributed photovoltaic (PV) power to the active distribution network. On the basis of the quantitative regulation analysis method of demand response power based on the equivalent slope of the load curve, establish an energy absorption capacity analysis model of seasonal load differentiation. On the basis of the dynamic interaction between different systems, a multiscale dynamic time‐domain analysis and dynamic simulation model of regional integrated energy is constructed by using the method of PV absorptive capacity assessment on both sides of demand uncertainty, to achieve multiscale dynamic time‐domain feature extraction of integrated energy and integrated scheduling of seasonal load differences. The simulation results show that the multiscale dynamic time‐domain allocation of regional comprehensive energy using this method improves the energy dispatching and balanced allocation capability, and the time‐domain dynamic allocation capability is good. Considering the terminal load demand and the electricity price demand formulated by the distribution network investment operators, the seasonal load response and comprehensive dispatching capability are improved.

Research on Reactive Power Coordination Control Strategies of Multi-Infeed Line-Commutated Converter–High-Voltage Direct Current Systems

For a receiving-end power grid with multi-infeed LCC-HVDC systems, simultaneous commutation failures may seriously threaten the safe and stable operation of the system. To evaluate the impact of commutation failure and improve the voltage stability of the commutation buses in multi-infeed HVDC systems, this paper proposes a method for evaluating the voltage stability of commutation buses and a reactive power coordination control (RPCC) method for commutation failure of multiple HVDC systems. Firstly, three indicators and the entropy weight method are adopted to comprehensively evaluate the voltage stability of commutation buses. Then, an RPCC method is proposed to resist commutation failure. The proposed RPCC method uses the voltage interaction factor (VIF) to screen out DC systems that are strongly related to dynamic reactive power compensation devices and activates the devices to provide RPCC to the DC systems through an auxiliary controller. Finally, the effectiveness of the proposed method is verified through a practical example of the Jiangsu power grid.

Hierarchical Central-Local Inverter-Based Voltage Control in Distribution Networks Considering Stochastic PV Power Admissible Range

This paper proposes a hierarchical distribution network voltage control method considering active and reactive power coordination of PV units in both central and local control stages. In contrast to the traditional local control methods, the proposed method defines the admissible range (AR) of PV power and determines it via centralized optimization to realize active PV power curtailments in the local control stage. The affine decision rule (ADR) is adopted to control the reactive power with respect to active power within AR. A distributionally robust chance constraint is designed, based on statistical indices of active PV power, to assess the probability that active PV power generation would fall inside AR. A two-stage optimization problem that can simultaneously provide central and local control strategies is proposed, which is transformed into tractable formulas based on the Gauss Inequality as well as ADR and binary expansion techniques. The proposed method solutions are compared with those of the theoretically optimal method, a robust central-local control method, and a local control method to show the value of hierarchical inverter control with AR in reducing PV power curtailment and ensuring nodal voltages within limits.

Active and Reactive Power Coordination Optimization of the Active Distribution Network

The operation and control of the active distribution network are faced with great challenges due to a mass of tunable and controllable devices connected to the network, resulting in large active power loss and voltage deviation. In this paper, a method of active and reactive power coordination optimization for the active distribution network based on a one-dimensional convolutional neural network (1D-CNN) is proposed. This method can mine valuable information from the historical data of distribution networks, and use one-dimensional convolutional neural networks to map the complex nonlinear relationship between node load and optimization strategy. The simulation results of the modified IEEE33 node distribution network system show that the active power loss and the node voltage deviation of the proposed method are significantly reduced.

Fast Solving Method for Two-Stage Multi-Period Robust Optimization of Active and Reactive Power Coordination in Active Distribution Networks

This paper considers constraints on the cycle number of energy storage systems (ESSs), travel distances of switchable capacitors reactors (SCRs), on load tap changers (OLTCs) and step voltage regulators (SVRs). The characteristics and operational constraints of these equipments are properly formulated with binaries and big-M method, obtaining desirable linear descriptions. The branch flow equations of distribution systems for active and reactive power coordination are constructed. Considering physical constraints, a multi-period mixed-integer deterministic second-order conic programming (SOCP) to minimize network losses is formulated. Then, considering uncertainties of loads and active power of renewable distributed generators (DGs), a two-stage robust model is developed. A directly iteratively solving method between the first and second stage models is proposed. In contrast to the traditional column-and-constraint generation (CCG) method, increases to variables and constraints are not needed to solve the first stage model. To solve the second stage multi-period model, only the model of each single period needs to be solved first. Then their objective function values are accumulated, and the worst scenarios of each period are concatenated. As a result, the solving complexity is greatly reduced. The capabilities of the proposed method are validated by three simulation cases. It is found that the computational rate using the proposed method is significantly enhanced with much less computer storage. Specifically, the simulation results of 4, 33 and 69-bus systems indicate that the computing rate of the proposed method is about 28 times higher than CCG method when 8 iterations are performed. Meanwhile, the precision of optimization results is also improved.

Research on reactive power optimization method of distributed wind farm based on harmony search algorithm

The large-scale access of distributed generation brings challenges to the operation, control and protection of traditional distribution network. The reactive power coordination optimization problem of wind power connected to distribution network was studied in this paper. A reactive power optimization model considering economy and voltage quality was established, and AHP method was used to select the weight, which overcomes the problem that the multi-objective weight is subjective and difficult to solve. Moreover, harmony search algorithm and particle swarm optimization algorithm were introduced to solve the model respectively to avoid the shortcomings of traditional algorithm which is easy to fall into local optimum. Finally, the control strategy of distribution network reactive power optimization was obtained. The simulation results show that the proposed optimization model and algorithm can ensure the voltage quality and economic benefits of distribution network nodes under relevant constraints.

A coordination control strategy for power quality enhancement of an active distribution network

Integration of power electronics-based converter-interfaced distributed generators (DGs) into the existing power systems have created several power quality related challenges. These challenges include reduced voltage rigidness at the point of common coupling (PCC), total harmonic distortion (THD), lack of inertial response and power imbalance due to unconsumed power from DGs. To address these challenges, this paper proposes a coordination control strategy which has two major objectives: (1) to regulate the apparent impedance at the PCC of the active distribution network (ADN) using coordination of DGs; (2) to use active and reactive power of battery energy storage system (BESS) for transient suppression at PCC and reactive power for power factor improvement of DGs. The proposed control strategy is applied to an ADN based on a 7 - bus test system. This study confirms that the unique method of regulating the apparent impedance of PCC using active and reactive power coordination of DGs significantly improves the power quality at the PCC of ADN. For instance, using the proposed method, the percentage overshoot (%OS) of active and reactive power injection at PCC of ADN was reduced up to 19.55% and 12.8%, respectively. Similarly, the THD of the grid current reduced from 4.71% to 2.85%.

Study on control strategy of large-scale renewable energy connect to LCC-HVDC system

One of the important issues facing large-scale renewable energy development is to ensure the maximum consumption of large-scale renewable energy bases and the safe and stable operation of the power grid after connect. The research results show that when large-scale renewable energy generation is connected to the power grid, its volatility, randomness and intermittentness will have a certain impact on the system power balancing, reactive voltage and transient stability of the power grid. Renewable energy connect to LCC-HVDC is one of the commonly used long-distance large-scale power transmission methods. On the one hand, in order to ensure stable operation, the LCC-HVDC system needs to provide sufficient reactive power support for itself and the system. On the other hand, for large-scale renewable energy power stations, the collection lines are often long, and each renewable energy generator usually uses its own optimal operation as the control target, which causes reactive voltage control problems and harmonic amplification in the power station problem. Therefore, in order to coordinate the reactive power coordination and voltage regulation after the renewable energy is connected to the LCC-HVDC system, this paper studies the large-scale renewable energy power generation LCC-HVDC transmission connection and the supporting technology required for the development of renewable energy power generation. And the use of guidance is of great significance to help increase the accommodation space of large-scale renewable energy generation.

Coordination Strategy of Large-Scale DFIG-Based Wind Farm for Voltage Support With High Converter Capacity Utilization

Due to the long-distance transmission, external grid cannot effectively support the access point voltage (APV) of the large-scale wind farm (WF), which thus entails DFIG-based WF to provide its ancillary services on reactive power generation. Considering factors of limited down-sized converter capacity, various operating modes of wind turbines (WTs), and the large pressure of large-scale WF communication on the central governor, this paper proposes a distributed active power and reactive power coordination scheme for APV support. A reactive power self-allocation scheme is developed and operated in each WT for reactive power dispatch. Based on the mechanism of distributed consensus control and aligning with the principle of preferential and proportional utilization of spare reactive power capacity (RPC), the proposed method collaborates the rotor side converters and the grid side converters of all WTs but without the necessity of knowing the total RPC. Further, in case that the total RPC is insufficient for the demand, a coordinating factor for RPC extension is generated to weaken the active power. Through a current-enforced PQ coordinating loop, it guarantees a high utilization of converter capacity as well as an exact compensation on the reactive power imbalance, which thereby reduces the wind power curtailment for the RPC release. Several case studies verify the effectiveness of the proposed method.

Real-Time Operation of Microgrids

Microgrid (MG) systems effectively integrate a generation mix of solar, wind, and other renewable energy resources. The intermittent nature of renewable resources and the unpredictable weather conditions contribute largely to the unreliability of microgrid real-time operation. This paper investigates the behavior of microgrid for different intermittent scenarios of photovoltaic generation in real-time. Reactive power coordination control and load shedding mechanisms are used for reliable operation and are implemented using OPAL-RT simulator integrated with Matlab. In an islanded MG, load shedding can be an effective mechanism to maintain generation-load balance. The microgrid of the German Jordanian University (GJU) is used for illustration. The results show that reactive power coordination control not only stabilizes the MG operation in real-time but also reduces power losses on transmission lines. The results also show that the power losses at some substations are reduced by a range of 6% - 9.8%.

Cluster-Based Predictive PCC Voltage Control of Large-Scale Offshore Wind Farm

A large number of wind turbine generators in the large-scale offshore wind farm system poses a challenge to the wind farm control system due to the computational burden in the central control methods or the complexity of the communication network in the decentralized control strategies. A hybrid control method based on the distributed consensus control and the central model predictive control is proposed in this study to overcome the problem. Typically, the wind turbine generators in the large-scale offshore wind farm system are clustered into several groups. The consensus-based distributed reactive power coordination control is proposed to each cluster and the centralized predictive voltage control is used to manage the total reactive powers of all clusters and regulate the voltage at the point of common coupling. The gradient-descent algorithm for the optimal design of the consensus-based cluster control is presented firstly. Based on the convergence property of the consensus control, the equivalent model of the total reactive power response of each cluster is identified, which is used for the design of the centralized predictive voltage control. Eigenvalue analysis of the proposed predictive control strategy is carried out to verify the stability of the distributed and predictive control systems. The robustness of the proposed predictive controller is evaluated in the conditions of significant model errors due to the communication delay in each cluster. A comparison study with the full distributed control based on consensus algorithm is presented to demonstrate the effectiveness of the proposed control method. The feasibility of the proposed predictive controller is evaluated by the control-hardware-in-the-loop simulation using OPAL-RT Technologies. An additional comparison study in term of computation time with the central control method is also carried out. Real-time simulation results show the superior performance of the proposed hybrid method compared to the full distributed consensus controller or the central control strategies.

Two-Stage Active and Reactive Power Coordinated Optimal Dispatch for Active Distribution Network Considering Load Flexibility

A high proportion of renewable energy connected to the power grid has caused power quality problems. Voltage-sensitive loads are extremely susceptible to voltage fluctuations, causing power system safety issues and economic losses. Considering the uncertainty factor and the time-varying characteristic, a linearized random ZIP model (constant impedance (Z), constant current (I), and constant power (P)) with time-varying characteristics was proposed. In order to improve the voltage quality of the voltage-sensitive loads in the day-here stage in an active distribution network (ADN), a linearized two-stage active and reactive power coordinated stochastic optimization model was established. The day-ahead active and reactive power coordination optimization was to smooth the large voltage fluctuation and develop a reserve plan to eliminate the unbalanced power caused by the prediction error in the day-here optimization. In the day-here real-time redispatch, the voltage was further improved by the continuous reactive power compensation device. Finally, the simulation results on the IEEE-33 bus system showed that the control strategy could better eliminate the unbalanced power caused by the prediction error and obviously improve the voltage of sensitive loads in the real-time stage on the premise of maintaining economic optimality.

Coordination of Active and Reactive Power in Active Distribution Networks Based on Successive Linear Approximation

Active distribution network (ADN) is an important part of the future power market, which undertakes the mission of accommodating high penetration distributed generation. However, traditional dispatch mode of the distribution system cannot accommodate high-penetrated renewable energy. In this paper, a novel optimal scheduling model is developed to optimize the accommodation of distributed renewable energy by coordinating active and reactive power. The proposed model takes capacitor bank (CB), energy storage systems (ESS) and static var generator (SVG) as management devices, optimize the day-ahead dispatchable resources of active distribution system in a centralized manner. Different from second-order cone programming method that cannot cooperate with the maximum DG penetration objective, we apply the successive linear approximation method to transform the original non-convex and nonlinear optimal dispatch model with AC balance equation into a mixed-integer linear programming (MILP) model, so that the model can be solved efficiently and accurately by commercial optimization software. A real distribution system in Nantong is employed to verify the proposed model.

Model-Free Dynamic Voltage Control of Distributed Energy Resource (DER)-Based Microgrids

In this paper, we present a new control technique for sustaining dynamic voltage stability by effective reactive power control and coordination of distributed energy resources (DERs) in microgrids. The proposed control technique is based on model-free control (MFC), which has shown successful operation and improved performance in different domains and applications. This paper presents its first use in the voltage stability of a microgrid setting employing multiple synchronous generator (SG)-based and power electronic (PE)-based DERs. MFC is a computationally efficient, data-driven control technique that does not require modelling of the different components and disturbances in the power system. It is utilized as an online controller to achieve the dynamic voltage stability of a microgrid system under different disturbances and fault conditions. A 21-bus microgrid system fed by multiple DERs is considered as a case study and the overall dynamic voltage stability is investigated using time-domain dynamic simulations. Numerical results show that the proposed MFC provides improvements on the dynamic load bus voltage profiles and requires less computational time as compared to the traditional enhanced microgrid voltage stabilizer (EMGVS) scheme. Due to its simplicity and low computational requirement, MFC can be easily implemented in resource-constrained computing devices such as smart inverters.

Two-stage stochastic scheduling approach for AC/DC hybrid distribution system with renewable energy integration

This paper proposes a stochastic scheduling approach for AC/DC hybrid distribution system considering the output uncertainty of wind and photovoltaic. The energy coordination problem has been formulated as a two-stage resource scheduling problem. The first-stage decision produces an hourly day-ahead pre-scheduling plan for the dispatchable distributed generators. For a set of possible scenarios over the next 24 h, the second stage determines the appropriate corrective decisions to handle the output uncertainty. Besides, the scheduling model for AC/DC hybrid system belongs to the non-convex optimization problem, which is transformed into a mixed integer second-order cone programming problem by second-order cone relaxation and linearization techniques. In this way, the optimization problem can be solved effectively. The proposed model has been tested on a modified IEEE 33 bus AC/DC hybrid system. Simulation results demonstrate that the proposed two-stage stochastic scheduling model can better cope with the renewable energy uncertainty and the active and reactive power coordination scheduling can ensure the safe operation of the entire system.

PV system reactive power coordination with ULTC & shunt capacitors using grey wolf optimizer algorithm

The presence of PV systems increases rapidly in distribution systems to improve reliability and quality of supply. This will influence the performance of under load tap changing (ULTC) transformer and related reactive power devices. Therefore, many researchers are working on this area. This paper main objective is to reduce switching operations of reactive power devices (ULTC and Shunt capacitors) together with system power loss. Distribution system load and solar system power will predict one day in advance and grey wolf optimizer (GWO) algorithm proposed to solve the objective function. Reactive power of solar system is coordinated together with ULTC and shunt capacitors (SCs) with the aid of forecasted load. Distribution system losses and switching operations of ULTC and SCs converted into objective function in terms of cost. The proposed method is applied on practical 10KV system and the results are compared with conventional and particle swarm optimization (PSO) methods considering grid conditions.