Active Power Curtailment Research Articles

Battery-less uncertainty-based control of a stand-alone PV-electrolyzer system

Solar photovoltaic (PV) energy is variable. The output power can change considerably in a matter of minutes, imposing challenges on the control of systems connected downstream. The power from these systems can be smoothed using electric storage, potentially increasing the system cost. An alternative is to deliberately curtail the power before it starts to change. This strategy relies on ultra-short-term forecasting to determine the curtailment point. Unfortunately, forecasting is prone to errors and high uncertainty even in the very short-term, leading to control errors. We propose an active power curtailment control strategy for a stand-alone solar photovoltaic system powering an electrolyzer. Our work’s novelty relies on the controller’s ability to deal with large forecasting errors and high uncertainty, combining artificial intelligence for predicting the power ramps and fuzzy logic to account for imperfect prediction. We validated our approach using a hardware emulator of the photovoltaic system, power converter and electrolyzer. Under clear sky conditions, the curtailment results in unnecessary energy loss, while under variable irradiance, the controller successfully smooths the power ramps within 10% of the PV system’s nominal power. Although our approach was designed for a stand-alone system, its concept can be directly applied to grid-connected systems as well.

An Enhanced Voltage Control Method for Fair Active Power Curtailment of Rooftop PV Systems in LV Distribution Networks

Solutions based on active power curtailment (APC) of photovoltaic inverters (PVIs) have been effectively used to alleviate overvoltages in low-voltage distribution networks (LVDNs) due to real power injection supplied by rooftop photovoltaic (PV) systems. However, volt–watt control methods presently available can lead to unfair APC among the PVIs, penalizing financially customers located far away from the distribution transformer of the LVDN. This paper proposes an innovative real-time voltage control method to address the unfair APC issue in LVDNs with rooftop PV systems. The proposed method is based on a centralized control architecture to calculate two fair curtailment factors for all PVIs of the LVDN. Additionally, to explore the extended communication infrastructure brought by centralized control architecture, this paper proposes a novel simplified method to compute the voltage sensitivity matrix (VSM) for applications on unbalanced three-phase LVDNs. Performance tests were conducted on a set of LVDNs, evaluating the effectiveness and fairness of APC quantitatively using Jain’s Fairness Index (JFI) as a metric. The results confirmed the effectiveness of the proposed control method for mitigating the overvoltage issue, ensuring fairness by presenting average JFI values close to one (the maximum allowed value). Furthermore, in comparison to conventional VWC strategies, penalties arising from the local dependence of PVIs on APC were eliminated for both curtailment factors. Finally, an accuracy test was performed on the proposed VSM model, based on voltage estimation through the linearized model of LVDN at a specific operating point. The findings demonstrated outstanding accuracy, with an error of less than 0.2%, compared to voltage estimation via power flow.

Control strategy for current limitation and maximum capacity utilization of grid connected PV inverter under unbalanced grid conditions

Under grid voltage sags, over current protection and exploiting the maximum capacity of the inverter are the two main goals of grid-connected PV inverters. To facilitate low-voltage ride-through (LVRT), it is imperative to ensure that inverter currents are sinusoidal and remain within permissible limits throughout the inverter operation. An improved LVRT control strategy for a two-stage three-phase grid-connected PV system is presented here to address these challenges. To provide over current limitation as well as to ensure maximum exploitation of the inverter capacity, a control strategy is proposed, and performance the strategy is evaluated based on the three generation scenarios on a 2-kW grid connected PV system. An active power curtailment (APC) loop is activated only in high power generation scenario to limit the current’s amplitude below the inverter’s rated current. The superior performance of the proposed strategy is established by comparison with two recent LVRT control strategies. The proposed method not only injects necessary active and reactive power but also minimizes overcurrent with increased exploitation of the inverter’s capacity under unbalanced grid voltage sag.

Integrated Active and Reactive Power Control Methods for Distributed Energy Resources in Distribution Systems for Enhancing Hosting Capacity

Recently, there has been a significant increase in the integration of distributed energy resources (DERs) such as small-scale photovoltaic systems and wind turbines in power distribution systems. When the aggregated outputs of DERs are combined, excessive reverse current may occur in distribution lines, leading to overvoltage issues and exceeding thermal limits of the distribution lines. To address these issues, it is necessary to limit the output of DERs to a certain level, which results in constraining the hosting capacity of DERs in the distribution system. In this paper, coordination control methodologies of DERs are developed and executed to mitigate the overvoltage and overcurrent induced by DERs, thereby increasing the hosting capacity for DERs of the distribution system. This paper proposes three coordinated approaches of active and reactive power control of DERs, namely Var Precedence, Watt Precedence, and Integrated Watt and Var Control. The Var and Watt Precedence prioritizes reactive power for voltage (Q–V) and active power for current (P–I) to address network congestion, thereby enhancing hosting capacity. Conversely, the Integrated Var and Watt Precedence propose a novel algorithm that combines four control indices (Q–V, P–V, Q–I, and P–I) to solve network problems while maximizing hosting capacity. The three proposed methods are based on the sensitivity analysis of voltage and current to the active and reactive power outputs at the DER installation locations on the distribution lines, aiming to minimize DER active power curtailment. Each sensitivity is derived from linearized power equations at the operating points of the distribution system. To minimize the computation burden of iterative computation, each proposed method decouples active and reactive power and proceeds with sequential control in its own unique way, iteratively determining the precise output control of distributed power sources to reduce linearization errors. The three proposed algorithms are verified via case studies, evaluating their performance compared to conventional approaches. The case studies exhibit superior control effectiveness of the proposed DER power control methods compared to conventional methods when issues such as overvoltage and overcurrent occur simultaneously in the distribution line so that the DER hosting capacity of the system can be improved.

Coordinated Q‐V/P‐f Control Strategy Using Virtual Power Factor for Autonomous AC Microgrid with PV Smart Inverters

Given the increasing interests in carbon neutrality due to climate change, photovoltaic (PV)‐based microgrid has become an important research topic worldwide. Typically, high PV penetration without proper control schemes causes power quality issues such as voltage or frequency violation, resulting in the limited PV hosting capacity. Reactive and active power support from the PV is effective to solve the issues, however, it is a critical challenge to efficiently contribute to the stabilizing controls under the inverter capacity constraint. Recent studies have applied smart inverters, equipped with fixed active and reactive power control reserves, for dynamic voltage and frequency support. In this paper, we proposed a control strategy in which the control reserves for voltage and frequency support are flexibly adjusted using virtual power factor (VPF) to improve the power quality with reducing active power curtailment. The effectiveness of the proposed Q‐V/P‐f control is verified through numerical simulations using a microgrid model developed in MATLAB/Simulink platform. It was observed through the simulation that the proposed method contributed to mitigating voltage and frequency fluctuation with satisfying the inverter capacity constraint. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Cyber Anomaly-Aware Distributed Voltage Control With Active Power Curtailment and DERs

Cyber Anomaly-Aware Distributed Voltage Control With Active Power Curtailment and DERs

A novel electric vehicle charging management with dynamic active power curtailment framework for PV-rich prosumers

A novel electric vehicle charging management with dynamic active power curtailment framework for PV-rich prosumers

Stochastic model for active distribution networks planning: An analysis of the combination of active network management schemes

The widespread adoption of distributed generation (DG) is changing the operation of distribution networks. To increase the control of power flows and avoid the detriments of DG intermittency, active distribution networks (ADN) emerge as a feasible solution. In this paper, we propose a convex model for ADN expansion planning. Four active network management (ANM) schemes are considered: DG active power curtailment, DG reactive power control, on-load tap changer (OLTC) tap adjustment, and shunt compensation device control. The problem is formulated as a mixed integer second-order cone programming problem (MISOCP) using the distflow equations and second-order cone relaxations (SOCR). By scenario analysis, we address the uncertainty associated with power demand, renewable generation, and electricity prices. The proposed model is used to study the benefits of different combinations of ANM schemes to a modified IEEE 33-bus system and compare them with the individual benefits of each scheme. The results indicate that ANM schemes can reduce total network costs, reduce losses, delay network reinforcement, and improve the voltage profile. In addition, some combinations of schemes develop synergies in which the combined economic benefits are greater than the sum of the individual benefits.

Stochastic MPC based double-time-scale voltage regulation for unbalanced distribution networks with distributed generators

With the increasing penetration of renewable energy resources, the uncertainty of renewable energy resources output introduces challenges to voltage control in distribution networks (DNs). To solve these problems, this paper proposes a double-time-scale voltage control scheme for unbalanced DNs based on stochastic model predictive control (SMPC) to coordinate multiple voltage control devices. In fast-time-scale control, the active and reactive power outputs of distributed generators (DGs) are optimized to minimize voltage deviation, active power curtailment and reactive power fluctuation. In the slow-time-scale control, optimal tap changes of on-load tap changers (OLTC), step voltage regulators (SVR), and switched capacitor banks (CBs) are calculated to reduce voltage deviation and tap operations. Additionally, in the fast-time-scale control, the SMPC-based scheme adopts a scenario generation approach to represent the uncertainty of DG output. Considering the temporal correlation of the DG output, different prediction scenarios and scenario probabilities are obtained by the empirical cumulative distribution function fitted by the historical measurement data. In this paper, the effectiveness of the proposed double-time-scale voltage control scheme is verified by the unbalanced IEEE123 node system. The case study demonstrates that the proposed voltage scheme can effectively keep the three-phase voltages in unbalanced DN within the secure operation range and achieve better voltage profiles.

Management of prosumers using dynamic export limits and shared Community Energy Storage

Integration of Distributed Energy Resources (DERs) can introduce challenges such as Over-Voltage (OV) and line congestion in distribution networks. Recently, the concept of dynamic export limits as well as Community Energy Storage (CES) have gained attention as potential solutions for these challenges. Within these concepts, this paper presents a novel framework where the Distribution Network Service Provider (DNSP) provides prosumers with dynamic export limits for networks with a CES. Moreover, this framework enables prosumers (through leasing) and the DNSP to collaboratively manage the CES. In each time step, the DNSP calculates the charging/discharging power for the unleased portion of the CES and collects data on the expected export and charging/discharging power from prosumers leasing the CES. Subsequently, while considering network voltage and current limits and a fairness objective, the DNSP computes and communicates dynamic export limits to prosumers, allowing them to manage their assets accordingly. The performance of the proposed framework is evaluated via various case studies conducted on a real-world LV test feeder with 49 prosumers. The results emphasize the critical role of dynamic export limits in resolving OV and congestion issues in DER-rich networks. Furthermore, the CES proves to be effective in reducing active power curtailment and increasing total generation, with a notable increase of 4.6%.

Security‐constrained active power curtailment considering line temperature and thermal inertia

AbstractA novel method is introduced to determine cost‐optimized active power curtailment (APC) of renewable energy sources (RES) considering weather‐dependent dynamic line rating (DLR). A new formulation of the security‐constrained optimal power flow (SC‐OPF) is developed and applied in a case study. The reduction of the required preventive APC in the case for secure grid operation due to the consideration of thermal inertia of overhead power lines is demonstrated. Considering thermal inertia allows relying on curative APC that is activated only after an situation occurs. The overhead power line temperature, calculated with the temperature‐dependent power flow (TDPF), acts as a new limit for line loading and releases unused transmission reserves. The TDPF algorithm is integrated in the open‐source Python library pandapower, providing access to it to the broader community. The power system can be utilized to a greater extent, with a reduced demand for congestion management.

An Irradiance Driven Adaptive PQV Droop for Voltage Regulation in Active Distribution System

Gradual increasing installation of solar photovoltaic inverters (SPVIs) at the low voltage (LV) network causes over-voltage issue at the SPVI-connected point-of-common-couplings (PCCs). Further, this problem deteriorates the voltage regulation of distribution transformers in active distribution system (ADS) due to high R/X ratio of the lines. To mitigate such issues, IEEE-1547-2020 recommends the constant QV-droop and PV-droop characteristics in the SPVIs. However, due to lack of adaptability of such characteristics with the variable irradiance level, the controller in SPVIs may under-utilize capacity of the SPVIs. In this paper, an irradiance driven adaptive PQV (IAPQV) droop control technique is proposed for the SPVIs to improve the voltage regulation of an ADS as compared to IEEE-1547-2020 recommended droop characteristic. Moreover, a Two-Bit-Priority (TBP) algorithm is proposed for distributed coordination among the SPVIs. During overvoltage situations, the TBP assists in minimizing active power curtailment at the SPVIs. Performance of the proposed method is verified under different scenarios in ADS. The results are validated through MATLAB/Simulink to show that the proposed IAPQV is more effective as compared to the IEEE-1547-2020.

PV Inverter-Based Fair Power Quality Control

Low voltage distribution networks incorporating solar photovoltaic (PV) panels experience overvoltage and voltage unbalance during periods of low load and high PV generation. Resolving overvoltage by active power curtailment (APC) is an effective and cost-efficient solution. However, current APC techniques result in excessive and unfair power curtailment for prosumers at the sensitive parts of the grid that might induce neutral current. In this work, an analytical approach for fair APC and Reactive Power Control is presented for voltage regulation along with neutral current compensation. The desired power quality is maintained by controlling each phase of the PV inverter independently. The proposed algorithm regulates the voltage at the point of common coupling (PCC) within grid limits, eliminates neutral current, and reduces the grid unbalance. Furthermore, the results demonstrate that reducing the neutral current reduces the voltage at the PCC and consequently decreases the power curtailment required for overvoltage regulation.

A Coordinated Voltage Regulation Algorithm of a Power Distribution Grid with Multiple Photovoltaic Distributed Generators Based on Active Power Curtailment and On-Line Tap Changer

The aim of this research is to manage the voltage of an active distribution grid with a low X/R ratio and multiple Photovoltaic Distributed Generators (PVDGs) operating under varying conditions. This is achieved by providing a methodology for coordinating three voltage-based controllers implementing an Adaptive Neuro-Fuzzy Inference System (ANFIS). The first controller is for the On-Line Tap Changer (OLTC), which computes its adequate voltage reference. Whereas the second determines the required Active Power Curtailment (APC) setpoint for PVDG units with the aim of regulating the voltage magnitude and preventing continuous tap operation (the hunting problem) of OLTC. Finally, the last component is an auxiliary controller designed for reactive power adjustment. Its function is to manage voltage at the Common Coupling Point (CCP) within the network. This regulation not only aids in preventing undue stress on the OLTC but also contributes to a modest reduction in active power generated by PVDGs. The algorithm coordinating between these three controllers is simulated in MATLAB/SIMULINK and tested on a modified IEEE 33-bus power distribution grid (PDG). The results revealed the efficacy of the adopted algorithm in regulating voltage magnitudes in all buses compared to the traditional control method.

A method to control distributed energy resources in distribution networks using smart meter data

Voltage regulation has been one of the major challenges for distribution network operators (DNOs) due to the integration of distributed energy resources in the recent years. Control approaches mitigating over-voltage (OV) generally require full network model, which for low-voltage distribution networks (LVDNs), can be inaccessible to DNOs. This paper presents a novel data-driven model-free control framework for improving voltage regulation in 4-wire 3-phase LVDNs. In the proposed approach, first, using smart meter data, the aggregated resistance and reactance matrices of the network are estimated. Then, these matrices serve as an input for the proposed optimal power flow (OPF) method to control the DERs’ active and reactive power outputs. This method also lets the DNO adjust the fairness in prosumers’ generation curtailment. The performance of the proposed approach is evaluated in various case studies conducted on a real-world low-voltage test feeder. The simulation results exhibit significant effectiveness in solving the OV problem associated with DERs. For example, in the studied network, the proposed approach limits the maximum voltage of the network to 1.1 pu, while without having control over the DERs output power, it can even overpass 1.17 pu during the peak generation period. In addition, utilizing DERs’ reactive control capability reduces the amount of active power curtailment, and prosumers are able to collectively inject 5.66% more active power.

A continuous-time voltage control method based on hierarchical coordination for high PV-penetrated distribution networks

The photovoltaic (PV) integration brings both fast photovoltaic generation (PVG) variations and a large number of PV inverters to the distribution networks (DNs). The management of the PVG variation and the PV inverter is an urgent problem. The discrete-time model can’t describe PVG variations during the schedule interval and the regulation potential of the PV inverter is limited by a fixed dispatching value. This paper proposes a continuous-time voltage control method based on hierarchical coordination for high PV-penetrated DNs. In the central schedule, based on the Bernstein polynomial method, continuous-time models of PVGs are established and reference values of local inverter control curves are dispatched as continuous-time functions in a sub-hourly timescale. In the local control, reactive power and active power curtailment of PV inverters are set as the reference values, i.e., the corresponding values of the continuous-time functions, every 30 s to optimize the central dispatching objective under the voltage constrains, and deviate from the reference values according to both the local control curve and voltage measurement only when the real-time bus voltage violation occurs. In addition, the cooperation between inverter and mechanical equipment in the continuous-time framework is also considered, and the Bernstein polynomial method is developed to the continuous-time modeling of voltage control in DNs. The simulation shows that the proposed method has lower maximum voltage magnitude and lower energy loss compared with discrete-time central schedule method.

A Hierarchical Multi-Stage Coordination of Inverters for Voltage Control in Active Distribution Networks with a µPMU-PDC

This paper proposes a hierarchical multi-stage approach based on a distributed level phasor measurement unit (µPMU) at local controllers and a phasor data concentrator (PDC) at the central control unit to restore system voltage when it exceeds the limits recommended by the IEEE 1547-2018 standard. The proposed algorithm does not need an accurate system model or employ optimization solutions. Therefore, it has less implementation complexity and would be popular among distribution network service providers (DNSPs) and distribution network operators (DNOs) as it does not suffer from cost and computational complexity limitations. A PMU-PDC-based communication platform has been developed as a more efficient alternative to the supervisory control and data acquisition (SCADA) system, and provides superior characteristics, including a higher sample rate, higher data resolutions, and faster communication. The proposed coordinated algorithm aims to postpone power generation curtailment in distributed energy resources (DERs) with overvoltage problems (local DERs) by incorporating all the DERs that are not subjected to voltage violation (remote DERs) by absorbing their maximum reactive power capacity. If the system voltage has not recovered after absorbing all of the reactive power capacity of all the DERs, a reduced active power curtailment proposed by the algorithm is then applied to the system to control the voltage. The proposed strategy has been simulated in MATLAB and applied to IEEE 13-bus and IEEE 33-bus radial distribution benchmark systems to validate the performance of the system, in terms of its ability to coordinate voltage control and the accuracy of the PMU-PDC-based communication interface.

Techno-economic impacts of Volt-VAR control on the high penetration of solar PV interconnection

This paper investigates the operation and control of smart inverters (SI) for solar and solar-plus-storage systems with an emphasis on Volt-VAR Control (VVC) at solar interconnections. The paper provides techno-economic recommendations for both normal-size and oversized solar inverters equipped with VVC. The objective is to minimize the voltage violations, and active power curtailment by providing reactive power support to the grid while the IEEE 1547-2018 standards are satisfied. Moreover, a collaborative VVC is tested where a battery storage system is paired with the solar facility which is becoming a popular configuration to enhance energy resilience in communities. An unbalanced distribution network is modeled based on a modified IEEE 13-bus system to which three 700 kW solar PV plants are connected through smart inverters. Solar data from the University of Louisiana’s 1.1 MW solar farm is used and grouped into 28 clusters. Those clusters represent a 2-year period with 15-min granularity. Typhoon HIL 402 real-time simulator is utilized for modeling and verifying the proposed approach. A control prototype is also developed on dSPACE MicroLabBox to further investigate the interaction between the controller and the rest of the system in a more realistic testing environment.

A Two-Stage Multi-Scenario Optimization Method for Placement and Sizing of Soft Open Points in Distribution Networks

The Soft Open Point (SOP) is an emerging power electronic device for active power flow control, reactive power compensation and post-fault service restoration in power distribution networks. In this paper, a novel two-stage multi-scenario optimization method for SOP placement and sizing is proposed to minimize power losses and active power curtailment of distributed generation (DG) in distribution systems. In Stage 1, the Loss Sensitivity Index (LSI) and Voltage Deviation Index (VDI) are used to identify candidate locations of SOPs, and a new method to estimate the LSI is proposed. In Stage 2, a mathematical optimization model is developed using AC power flow to optimally size each voltage source converter (VSC) of a SOP; the power factor constraint at the substation/grid interconnection is incorporated in this model to ensure security of the upstream grid. The proposed method is validated by a modified IEEE 33-node test system and a large 404-node unbalanced distribution system operated by Saskatoon Light and Power in Saskatoon, Canada.

Coordinated voltage control of three-phase step voltage regulators and smart inverters to improve voltage profile and energy efficiency in unbalanced distribution networks

This paper proposes a coordinated voltage control by three-phase step voltage regulators (3ϕSVRs) and photovoltaic (PV) units with smart inverters. An optimization problem is formulated to improve the voltage profile of distribution networks and reduce the active power curtailment of PVs. The tap positions of 3ϕSVRs and the active and reactive power output of PVs are coordinated by whale optimization algorithm. The effectiveness of the proposed approach is verified by case studies on the IEEE 123 node test feeder. The results show that the proposed approach achieves lower voltage unbalance while avoiding excessive PV curtailment, improving utility, consumer, and environmental benefits.