Distributed Generation Reactive Power Research Articles

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.

A Robust Multiobjective Strategy for Short-Term Distribution System Upgrading to Increase the Distributed Generation Hosting Capacity

This work proposes a strategy that estimates the maximum distributed generation (DG) capacity that can be connected to the electric distribution system (EDS), when EDS upgrading actions are implemented. The problem is viewed from the distribution system operator (DSO) perspective and is formulated as a multiobjective optimization model that maximizes the DG capacity and minimizes the upgrading cost. Upgrading options include allocation of voltage regulators (VRs) and conductor replacement, which are coordinated with the application of generation curtailment, DG reactive power support, and voltage control using VRs. The uncertainty and variability of demand and DG power production are accounted for resorting to a multi-period robust formulation. The problem solution generates a set of upgrading plans, from which the DSO can select the one that meets its economic expectation and provides the EDS with the necessary capacity to accommodate the expected new DG. A post-optimization analysis is proposed to evaluate the impact of EDS upgrading on the DSO profit. Simulations are performed on a 135-bus EDS, and results show that the proposed strategy reveals an upgrading plan that increases the DG capacity up to 64.39% with a gain in the DSO profit of 5.43%, compared to the case without EDS upgrading.

Optimal Power Flow Based DR in Active Distribution Network With Reactive Power Control

Demand response works as a bridge to enable activities between end customer and distribution network operators. Previously, most of the demand response work is concerned about maintaining supply–demand balance and reducing peak load demand without acknowledging distribution network behavior. This article presents a demand response scheme for an active distribution network via the operation of an unbalanced feeder line and consumer loads. The day-ahead dynamic price is coupled with active distribution network constraints to prevent the formation of new peaks. To tackle up the complexities of unbalanced network and distributed generation (DG) integration, the merits of symmetrical domain components are utilized. Power electronically interfaced DG reactive power component is also considered for constant power and voltage mode of operation. For optimizing the distribution network, optimal power flow is modified to achieve social welfare with distribution network constraints. The performance and computational efficiency of the proposed algorithm are verified through extensive case studies.

MILP-Based Service Restoration Method Utilizing Both Existing Infrastructure and DERs in Active Distribution Networks

This study proposes a service restoration method that utilizes the distributed energy resources (DERs) as the control measures as well as the existing infrastructure of the distribution system. The existing infrastructure includes switching operations, load shedding, and tap operations of the on-load tap changers (OLTCs). In addition, the DERs include reactive power control of the distributed generation (DG), charge/discharge of the energy storage system (ESS), and intentional islanding operation using the black-start function of the ESS. For this purpose, the following model is applied to the optimization problem based on mixed-integer linear programming. First, a linear constraint considering the voltage drop due to the impedance of the main transformer is used for practical application of an OLTC. Next, a linear constraint is formulated for grid code-based DG reactive power control. In addition, constraints for the ESS are defined. Here, the radiality constraints are formulated to distinguish the grid-connected and islanding operation modes based on the location and state of the ESS. Finally, simulations of the application of the control measures conducted on a 150-node test system, designed based on the data of the actual system in Korea, are conducted and the results are analyzed to verify the proposed method.

Dynamic reactive power optimization of distribution network with distributed generation based on fuzzy time clustering

In order to solve the coordinated optimization problem of distributed generation (DG), on-load tap changer (OLTC) and capacitor banks, a dynamic reactive power optimization (DRPO) method based on fuzzy time clustering is proposed. In the method, fuzzy time clustering algorithm is used to cluster the static optimal switching sequence of OLTC and capacitor banks. The time decoupling of control variables is realized and it meets the constraints of the maximum switching times. Next, the influencing factors of DG reactive power limit are analysed. Considering the control ability of OLTC, capacitor banks and DG in voltage and reactive power optimization, a coordinated optimization method is proposed. Since the adjustment of OLTC tap position directly affects the voltage and reactive power distribution of the whole line, the switching time and tap position of OLTC are determined based on the static optimization results of each time and fuzzy time clustering algorithm. Then, the switching time of capacitor banks is determined by fuzzy time clustering algorithm. At last, the switching capacity of capacitor banks and DG reactive power are jointly optimized to get the final control scheme. The proposed method demonstrated good performance in the modified IEEE33 node system and two actual power grid examples.

Probabilistic Load Flow–Based Optimal Placement and Sizing of Distributed Generators

Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor’s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper’s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively.

A multistage distribution network planning method considering distributed generation active management and demand response

This paper proposes a multistage distribution network planning (DNP) method that considers multiple planning alternatives, the active management of distributed generation (DG) units and demand response in the context of active distribution networks (ADNs). Representative days are selected for the consideration of uncertainties related with load demand and renewable power generation, during the planning period. The proposed DNP method aims at minimising the net present value of the total investment and operational cost. The proposed DNP considers multiple planning alternatives, such as the reinforcement of existing substations and existing distribution lines, the installation of new distribution lines, and the installation of capacitors. Furthermore, the proposed DNP method incorporates the control capabilities of DG active and reactive power output and demand response schemes. A 24-bus distribution network and a 144-bus real world distribution network are used to validate the performance of the proposed method.

A robust control strategy for a single‐phase grid‐connected multibus microgrid based on adaptive sliding mode control and dynamic phasor concept

Due to the increasing development of distribution networks, the need to use clean energy resources, and the existence of different single-phase and three-phase consumers, the maximum use of both single-phase and three-phase distributed generation (DG) units has become crucial. However, the presence of DG units in microgrids (MGs) requires efficient control strategies, for power control and voltage regulation, to achieve a rapid and proper dynamic response with respect to external disturbances and uncertainties. In this paper, in order to improve the dynamic and steady-state performance of an unbalanced multibus microgrid including inverter-based single-phase DGs, a robust control strategy is proposed for controlling the active and reactive power of DGs. The proposed control scheme is composed of a current controller based on an adaptive sliding mode control method in a virtual synchronous dq reference frame, to control the single-phase inverter output current, and a PI controller to regulate the voltage magnitude of the generation buses connected to DGs. In the proposed control structure, each single-phase inverter is controlled as a virtual balanced three-phase inverter, based on the dynamic phasor concept that makes decoupled control of the active and reactive powers of single-phase inverters possible. In order to evaluate the validity and effectiveness of the presented control structure, a multibus single-phase MG containing several inverter-based single-phase DG units has been simulated in MATLAB software environment, and the performance of the proposed control scheme has been investigated for various scenarios of parametric uncertainties and external disturbances.

Combined Firm and Renewable Distributed Generation and Reactive Power Planning

The benefits of integrating Distributed Generation (DG) into the distribution networks depend on the characteristics of different types of DG units, loads and Reactive Power Sources (RPS). These benefits can be optimized if the firm DG units such as biomass energy and renewable DG units such as photovoltaic (PV) and wind system are optimally sized, located and coordinated with reactive power sources. In this paper, by assuming that the Distribution System Operator (DSO) has got the ownership and operation of DG units and RPS, a new planning strategy is proposed for determining the optimal placement and rating of DG units and RPS. This strategy overcomes the challenge of intermittency of renewable production in order that this planning will assist the system operators in defining the better integration strategies of firm and intermittent energy systems and reactive power sources in distribution networks. The proposed planning is based on single objective optimization so that it optimizes one of the following objective functions every time: the system energy losses, voltage stability margin, self-adequacy of microgrids defined on the distribution system and exchange of active and reactive powers between the distribution system and upstream network. The proposed technique accounts for the uncertainties associated with solar irradiance, wind speed and demand through a probabilistic optimization. The formulation of each planning problem is presented and applied to the 69-bus distribution system. The results of different planning strategies are compared and analyzed. Furthermore, the impact of the planning with each objective function on other indices is evaluated.

Voltage Control for Distribution Networks via Coordinated Regulation of Active and Reactive Power of DGs

Fast-acting reactive power support from distributed generations (DGs) is a promising approach for tackling rapid voltage fluctuations in distribution networks. However, the voltage regulation range via reactive power of DGs alone is narrow especially in distribution networks with high resistance-reactance ratio. In this paper, a randomized algorithm is proposed to improve the voltage profile in distribution networks via coordinated regulation of the active and reactive power of DGs. To this end, first the variables of the proposed quadratically constrained quadratic programming problem on voltage control are partitioned into disjoint subsets, each of which corresponds to a unique low-dimensional subproblem. Second, these subsets are updated serially in a randomized manner via solving their corresponding subproblems, which overcomes the requirement for system-wide coordination among participating agents and guarantees an optimal solution. Compared with the existing algorithms, the proposed algorithm is resilient to network reconfigurations and achieves a wider voltage regulation range. The effectiveness and convergence performance of the proposed algorithm is validated by the case studies.

Optimal Sizing and Sitting of Distributed Generations in Power Distribution Networks Using Firefly Algorithm

Compared to centralized generation, distributed generations (DGs) have numerous advantages including real power loss reduction, voltage deviation reduction, network stability enhancement, emission reduction, capacity increase of transmission lines and congestion reduction in distribution networks. Optimum placement of DGs plays a crucial role in this regard. In this paper, Firefly Algorithm (FA) was employed for sizing / sitting of various DGs in distribution networks. The aim of this paper was to minimize power loss by taking into account power factor, active power, and reactive power of DGs. Furthermore, different active and/or reactive generating/consuming DGs were also considered. The performance analysis of the proposed method was validated on standard IEEE 33- and 69-bus test systems.

Stochastic Optimization of PQ Powers at the Interface between Distribution and Transmission Grids

This paper addresses the volt-var control of distribution grids embedding many distributed generators (DGs). Specifically, it focuses on the compliance of powers to specified PQ diagrams at the high voltage/medium voltage (HV/MV) interface while the voltages remain well controlled. This is achieved using a two-stage optimization corresponding to two different classes of actuators. The tap position of capacitor banks is selected on a daily basis, given a stochastic model of the input powers prediction, which allows infrequent actuation and increases the device lifespan. In a second stage, a confidence level optimization problem allows to tune on an hourly basis the parameters of the DGs reactive power affine control laws. Results on a real-size grid show that the combined tuning of these actuators allows the ability to comply with European grid codes while the control effort remains reasonable.

A Techno-Economic Approach for Increasing the Connectivity of Photovoltaic Distributed Generators

High penetration of distributed generation (DG) results in technical problems as voltage rise, voltage unbalance, substation reverse power, and transformer overloading. These problems adversely affect the connectivity of DGs either in the planning stage by decreasing the number of connected DGs, or in the operation stage by applying DGs' active power curtailment (APC). This paper presents a techno-economic approach for the enhancement of photovoltaic (PV) DGs connectivity. The proposed approach first employs a probabilistic economic technique for determining the non-curtailable portion of the PV DG power that ensures profitable DG investment. This portion is integrated, as an economic constraint, in the planning phase of the proposed approach that aims to maximize the number of PV DGs connected to the system. In the operation phase, the proposed approach utilizes the capabilities of the existing equipment on the system, i.e., regulators, capacitors, DGs reactive power, and DGs APC to mitigate all technical problems. The overall objective of this stage is to minimize the total DGs APC while fulfilling all technical and economic constraints. The proposed approach is tested on the modified IEEE 123-bus feeder. The results clarify the efficiency of the proposed techniques in increasing the connectivity of PV DGs while maintaining profitable DG project.

Optimal integration of distributed generation and conservation voltage reduction in active distribution networks

Energy efficiency and renewable energy are of paramount importance in the search for a sustainable energy system. This paper investigates the effect of conservation voltage reduction (CVR) on the optimal operation scheduling of active distribution networks with high shares of renewable energy sources (RES)-based distributed generation (DG). To this end, a probabilistic optimal power flow-based algorithm, formulated as a two-stage stochastic programming model, is proposed. In the first-stage, based on forecasts of load demand and DG production, the active power exports and imports, and tap settings of the on-load tap changer (OLTC) and voltage regulators (VRs), are scheduled for the 24 h of the next day. This schedule is optimized to minimize the energy imports and maximize the energy exports. The second-stage simulates the real-time operation of the system for scenario realizations of the uncertainties, and seeks to minimize the energy deficits and maximize the energy surplus once the first-stage decisions have been made. To achieve its objective, the second-stage regulates the DG active and reactive power outputs and coordinates its operation with the OLTC and VRs to reduce the energy consumption through the CVR procedure and maximize the energy harvested from RES, while satisfying system constraints. Results of case studies describe important benefits for energy efficiency, maximum utilization RES, and safe, reliable and economic system operation.

Optimal Controller Design for Inverter-Based Microgrids

This paper presents a comprehensive control scheme for inverter-based distributed generations (DGs) in grid-connected microgrids (MGs). The proposed control strategy regulates active and reactive power of DGs in order to adjust output voltages of the DGs under balanced/unbalanced loading and fault conditions. In this paper, an adaptive hyper-plane sliding mode controller is developed for positive and negative sequences of active and reactive power in dq0 reference frame based on quasi-dynamic phasor. All the parameters of controllers are derived via particle swarm optimization algorithm in order to minimize an appropriate cost function. This controller is fast, stable and robust against uncertainties of the output filter of the inverter, variations of the network parameters and load disturbances. In addition, the fault ride-through capability of the system can be improved. In the presence of unbalanced loads and faults, output voltages the DG are controlled to remain balanced and unchanged. Performance of the proposed controller is compared with a conventional PI controller and a conventional sliding mode controller. Effectiveness and accuracy of the proposed control strategy are verified through simulating a test microgrid in the presence of unbalanced loads and some faults.

Confidence Level Optimization of DG Piecewise Affine Controllers in Distribution Grids

Distributed generators (DGs) reactive powers are controlled to mitigate voltage overshoots in distribution grids with stochastic power production and consumption. Classical DGs controllers may embed piecewise affine laws with dead-band terms. Their settings are usually tuned using a decentralized method which uses local data and optimizes only the DG node behavior. It is shown that when short-term forecasts of stochastic powers are Gaussian and the grid model is assumed to be linear, nodes voltages can either be approximated by Gaussian or sums of truncated Gaussian variables. In the latter case, the voltages probability density functions (pdf) that are needed to compute the overvoltage risks or DG control effort are less straightforward than for normal distributions. These pdf are used into a centralized optimization problem which tunes all DGs control parameters. The objectives consist in maximizing the confidence levels for which voltages and powers remain in prescribed domains and minimizing voltage variances and DG efforts. Simulations on a real distribution grid model show that the truncated Gaussian representation is relevant and that control parameters can easily be updated even when extra DGs are added to the grid. The DG reactive power can be reduced down to 50% or node voltages variances can be reduced down to 30%.

Stochastic assessment of distributed generation hosting capacity and energy efficiency in active distribution networks

Active network management (ANM) aims to increase the capacity of variable distributed generation (DG), which can be connected to existing distribution networks. In this study, it is proposed to simultaneously consider the efficient use of energy resources when high shares of DG are procured through the ANM approach. To that end, a multi-period and multiobjective optimisation algorithm, based on the linearised optimal power flow, is formulated. The algorithm seeks to maximise the installed capacity of DG while minimising the energy losses and consumption of voltage-dependent loads. The objectives are optimised considering the coordinated operation of voltage regulators and on-load tap changers, and the management of DG generation curtailment and reactive power compensation from DG. Additionally, the effects of load and generation uncertainties are addressed through a two-stage stochastic programming formulation of the multiobjective problem. The result is a set of non-inferior solutions, which allows exploring the degree of conflict among the objectives. The proposed approach was tested on two IEEE test feeders and the solutions show a significant improvement in the system's energy efficiency with a low impact on the amount of connected DG.

Real-Time Fuzzy Voltage Regulation for Distribution Networks Incorporating High Penetration of Renewable Sources

This paper proposes a coordinated voltage regulation scheme for on-load tap changer (OLTC) and renewable distributed generation (DG) units to provide a proper voltage regulation for active distribution systems. The main motivation of applying fuzzy logic is that it can deal with environments of imperfect information, and thus, it can reduce communication requirements. The proposed regulation scheme consists of three fuzzy-based control algorithms. The first control algorithm is proposed for the OLTC such that it can mitigate the effect of DG units on the voltage profile. The second control algorithm is proposed to provide a DG reactive power sharing, in order to relax the OLTC tap operation. The third control algorithm aims to partially curtail DG active powers to restore a feasible solution from the OLTC prospective. The proposed fuzzy algorithms have the advantage of providing proper voltage regulation with relaxed tap operation, utilizing only the estimated system minimum and maximum voltages. Moreover, it avoids numerical instability and convergence problems associated with centralized approaches, as it does not require to run an optimization algorithm. Real-time simulations are developed to show the effectiveness of the proposed fuzzy algorithms on a typical distribution network, using OPAL-RT real-time simulator.

Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability

The integration of high-penetration distributed generators (DGs) with smart inverters and the emerging power electronics technology of soft open points provide increased controllability and flexibility to the operation of active distribution networks. Existing works on distributed energy storage planning have not fully considered the coordinated operation of these new power electronic devices with distributed energy storage systems, leading to less economic investment decisions. This paper proposes an optimal planning model of distributed energy storage systems in active distribution networks incorporating soft open points and reactive power capability of DGs. The reactive power capability of DG inverters and on load tap changers are considered in the Volt/VAR control. Moreover, soft open points are modeled to provide flexible active and reactive power control on the associated feeders. Hourly network reconfiguration is conducted to optimize the power flow by changing the network topology. A mixed-integer second-order cone programming model is formulated to optimally determine the locations and energy/power capacities of distributed energy storage systems. Finally, the effectiveness of the proposed model is validated on a modified IEEE 33-node distribution network. Considering soft open points, DG reactive power capability, and network reconfiguration, the results demonstrate the optimal distributed energy storage systems planning obtained by the proposed model achieves better economic solution.

Decentralized voltage control of distributed generation using a distribution system structural MIMO model

The voltage control problem in Low Voltage (LV) distribution systems is becoming increasingly important due to the presence of Distributed Generation (DG). Recently, DG units have been proposed to contribute to voltage control according to a Volt/Var law which does not realize regulation. Moreover, since the existing LV systems are operated in a decentralized way without communication links, the simultaneous response of the controllers of the DG units may result into operational conflicts and instability. To overcome these problems, the present paper illustrates a design methodology for decentralized voltage controllers that act on DG reactive power injections. The controllers are suitable for the LV systems since they ensure voltage regulation and stability by using only local measurements and without information exchanges. The design is based on a proposed structural MIMO model of the distribution system. Robust stability is also analyzed: changes in the operating conditions of the distribution system are modeled as unstructured additive uncertainties affecting the MIMO model. A case study gives evidence of the applicability of the proposed design; the performance of the controllers in terms of both stability and regulation of the nodal voltages of three DG units connected to a LV distribution feeder is tested by numerical simulations; finally, a comparison with a Volt/Var technique is performed.