Unbalanced Distribution Systems Research Articles

Optimal Battery Energy Storage System Management with Wind Turbine Generator in Unbalanced Low Power Distribution System

Wind Turbine Generators (WTG) are being integrated into distribution systems on a large scale worldwide as part of a global effort to capture green energy. Wind turbine generator intermittency may be mitigated by Battery Energy Storage Systems (BESS), which have emerged as a viable option in recent years. To find the best position and capacity for wind power generation and BESS charging/discharging dispatches, a Red Fox Optimisation (RFO) algorithm is used while optimising the imbalanced distribution network’s performance under technological restrictions. The charging or discharging criteria for this method is the average feeder load. The charging techniques for BESS using WTG and Sustainable Average Load (SAL) are evaluated in terms of the free-running mode of dispatch cycle. The suggested approach is tested on an IEEE-37 bus Unbalanced Radial Distribution Network (UDN). It has been shown that the suggested method enhances several performance objectives of the distribution system.

Search group algorithm for optimal allocation of battery energy storage with renewable sources in an unbalanced distribution system

ABSTRACT In recent decades, numerous distributed energy resources (DER) have been linked to distribution networks. Among these wind turbine generators (WTG) are popular for their uncertain power fluctuations. Using battery-based energy storage devices (BESS) as a solution to these unwanted fluctuations might be a realistic option. However, the integration of BESS with WTG on a wider scale requires additional attention to the size, position, and charge-discharge schedules. This article discusses these perspectives in addition to the location and power penetration levels of WTGs. In addition, a new charge-discharge control model is created for deciding when batteries should be charged or discharged at each hour. A multi-objective optimization problem is created with the goal of optimizing the economic, environmental, and technological goals of the unbalanced distribution network (UDN). The optimization task is solved using a Search Group Algorithm (SGA). The planning model leverages the average demand of the feeder at a particular hour of the day as the decision criteria for charging or discharging the battery. The charging of the BESS devices is totally done by the WTG power output. Furthermore, the conservative and free-running discharge approaches of the battery are studied. The proposed approach is tested using IEEE 37 bus UDN and the results demonstrate improvement in distribution system performance by coordinating BESS dispatches appropriately. The active and reactive power loss reduction for the three-phase system were 30.4% and 30.8% for the free-run mode, respectively, while the same for the conservative mode was 40.3% and 37.4%.

Optimal Operation of Distributed Generations in Four-Wire Unbalanced Distribution Systems considering Different Models of Loads

The distribution network is generally unbalanced due to the distribution of consumers in different phases and the different status of their energy consumption. Also, in recent years, the utilization of distributed generations (DGs) has flourished in the distribution network, thanks to their favorable operational and environmental benefits. Therefore, it is predicted that the optimal energy management of DGs in the unbalanced distribution network can improve the operation state of the network. Moreover, the consumer load model is generally a combination of constant impedance, constant current, and constant power conditions. Therefore, the current study focuses on the analysis of the operation of unbalanced four-wire distribution systems containing DGs, in which load models are also involved. An optimization structure is established to make the voltage deviation, power loss, neutral wire loss, and voltage unbalance minimized. Limitations of the problem include those related to the network and those concerning operating indices of the system like voltage magnitude and phase angle of buses, power flow through the distribution lines, constraints of operation of DGs, load model, and unbalanced conditions. The problem formed in this study is nonlinear and is solved using sequential quadratic programming (SQP) by implementing it in the GAMS simulation environment. To test the benefits of the introduced approach, a 13-bus distribution system has been adopted so that the optimal operation of DGs in the distribution network has been able to reduce the unbalanced situation of the network compared to the power flow studies. Also, this scheme has improved the operation of network, where energy losses and voltage drop have been reduced compared to power flow studies, and a smooth voltage profile has been extracted.

Practical Method for First-Screening Assessment of New PV Connection Requests on Unbalanced Low Voltage Distribution Systems

The massive growth of photovoltaic (PV) generators connected to low voltage (LV) systems is making it impractical for utilities to conduct a detailed technical analysis to approve every connection request. In response, this paper proposes simple equations to quickly estimate the PV hosting capacity on any circuit location without the need to run power flow simulations. By representing all loads and generators as constant current consumption/injection, the superposition theorem can be used to calculate the impact of each new PV on voltage magnitude and current flows. This approach can be used on a first screening assessment to immediately filter out cases that present no risk of technical violations to the circuit. Only connection requests flagged with risk of violation in this initial screening must be analyzed in detail by specialized engineers. Any type of PV connection (single-phase, two-phase, three-phase) in unbalanced multiphase LV systems can be analyzed. Extensive validation studies reveal that this approach is conservative, which makes it safe and reliable for quick first screening analyses. Its estimation errors are between 5% and 18%. Recommendations on how to employ the proposed approach in practice are also presented.

Optimal renewable resource for enhanced performance of unbalanced radial distribution systems

Optimal renewable resource for enhanced performance of unbalanced radial distribution systems

A Hybrid Compensator for Unbalanced AC Distribution System With Renewable Power

A hybrid compensator with a new coordinated control is proposed for mitigating power quality aspects and integration of renewable power in an unbalanced three-phase four-wire distribution system. The proposed compensator comprises of thyristor switched capacitor (TSC) banks, delta connected thyristor controlled reactor (TCR), a 3rd and a 5th harmonic tuned passive LC filter & a low rating three-phase four-wire D-STATCOM. The TSC-TCR operates asymmetrically for the base var compensation and also eliminates negative sequence current during unbalanced loading at the point of common coupling (PCC). The D-STATCOM works in coordination with the TSC-TCR and the passive filters to compensate fundamental var, zero sequence current, voltage flicker & 7th harmonic currents at the PCC. The D-STATCOM thus serves as a supportive var compensator as well as an active filter in selective harmonic compensation mode, thereby improving the var compensation and harmonic current filtering at the PCC. A new coordination control system is proposed to control the operation of the D-STATCOM which is also employed to integrate a PV source & a doubly fed induction generator (DFIG) based wind energy conversion system (WECS) to the PCC. This scheme with grid connected and islanded mode of operation using D-STATCOM exhibits low-voltage ride-through capabilities. Further, the chance of resonance of the passive filters used with source inductance is eliminated in the proposed scheme. Simulation results show that the proposed hybrid system effectively compensates var, negative & zero sequence current, reduces voltage flicker and harmonic currents at PCC.

Adaptive Particle Filter With Randomized Quasi-Monte Carlo Sampling for Unbalanced Distribution System State Estimation

Particle filter (PF) is an effective state estimation method for nonlinear unbalanced distribution systems with non-Gaussian noises. However, the computational inefficiency limits its real-time application in large-scale distribution systems. This paper proposes an adaptive PF (APF) method by using randomized quasi-Monte Carlo (RQMC) sampling to enhance computational efficiency. Firstly, an RQMC sampling method is introduced to enable uniform sampling based on the low discrepancy Sobol’ sequence. This even sampling accelerates the convergence rate of numerical integrations. Secondly, the standard PF is extended to be an RQMC-PF estimator by using the RQMC sampling instead of the MC sampling. Benefiting from the higher convergence rate, fewer particles are required to obtain precise state estimates, thus notably improving computation efficiency. Thirdly, to further make a trade-off between estimation accuracy and computational efficiency, the number of particles used in the RQMC-PF is adaptively determined with the root mean square of the estimated state covariance, yielding an APF. Test results on unbalanced distribution systems with different scales demonstrate that the proposed method can efficiently provide accurate estimates as well as achieve good scalability.

Adopting Dynamic VAR Compensators to Mitigate PV Impacts on Unbalanced Distribution Systems

Adopting Dynamic VAR Compensators to Mitigate PV Impacts on Unbalanced Distribution Systems

Log(v) 3LPF: A Linear Power Flow Formulation for Unbalanced Three-Phase Distribution Systems

In this work, we introduce Log(v) 3LPF, a linear power flow solver for unbalanced three-phase distribution systems. Log(v) 3LPF uses a logarithmic transform of the voltage phasor to linearize the AC power flow equations around the balanced case. We incorporate the modeling of ZIP loads, transformers, capacitor banks, switches and their corresponding controls and express the network equations in matrix-vector form. With scalability in mind, special attention is given to the computation of the inverse of the system admittance matrix, Ybus. We use the Sherman-Morrison-Woodbury identity for an efficient computation of the inverse of a rank-k corrected matrix and compare the performance of this method with traditional LU decomposition methods using Big- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathcal {O}$</tex-math></inline-formula> notation. We showcase the solver for a variety of network sizes, ranging from tens to thousands of nodes, and compare the Log(v) 3LPF with commercial-grade software, such as OpenDSS.

Discontinuities and unstable solutions beyond the maximum load point of nonlinear unbalanced distribution systems

• Discontinuities in the PV curves are inherent to the power flow formulation of distribution systems. • Discontinuities may change the operational point between two or more PV curves. • Defining if the maximum loading point is not part of a fully unstable curve is challenging. • A false maximum loading point may be used inappropriately when analyzing multiphase distribution systems. • Discontinuities may occur around the loading level that is related to when the eigenvalues of multiple Jacobians are on the same attraction area. Distribution feeders are usually modeled by a set of nonlinear equations that likely leads to multiple solutions on power flow tools if an adequate nonlinear mathematical model for multi-grounded unbalanced feeders is considered. Specifically, this work presents a study about these solutions through the analysis of PV curves obtained by using the multiphase continuation power flow tool. Herein, the paper discloses discontinuities on the PV curves, which are related to the occurrence of multiple Jacobians with several eigenvalues on the same attraction area. The results revealed the possibility of unstable solutions presenting greater maximum loading levels (around 29.5% higher) than the stable solution. Moreover, a power factor variation study has also indicated that unstable solutions might occur for a broad range of reactive power values. Finally, it is shown that, in some distribution systems, the maximum loading point found is not a global one and, most importantly, stable curves can be confused with unstable ones, leading users and researchers to wrong conclusions in their studies.

Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm

In this paper, a model free volt/var control (VVC) algorithm is developed by using deep reinforcement learning (DRL). We transform the VVC problem of distribution networks into the network framework of PPO algorithm, in order to avoid directly solving a large-scale nonlinear optimization problem. We select photovoltaic inverters as agents to adjust system voltage in a distribution network, taking the reactive power output of inverters as action variables. An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment. OPENDSS is used to output system node voltage and network loss. This method realizes the goal of optimal VVC in distribution network. The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm. Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.

Unbalanced Distribution System Expansion and Energy Storage Planning Under Wildfire Risk

Unbalanced Distribution System Expansion and Energy Storage Planning Under Wildfire Risk

An Adaptive Clustering-Based Distributed Voltage Regulation Scheme for Unbalanced Distribution Systems With Multiple Renewable DGs and OLTCs

An Adaptive Clustering-Based Distributed Voltage Regulation Scheme for Unbalanced Distribution Systems With Multiple Renewable DGs and OLTCs

Coordinated Control of Electric Vehicles and PV Resources in an Unbalanced Power Distribution System

Improving air quality, reducing greenhouse gas emissions, and achieving independence from fossil fuels have led most countries towards deploying solar photovoltaics (PV) in the power distribution grid and electrifying the transportation fleet. Internal combustion engine (ICE) vehicles are, in particular, one of the main culprits of injecting greenhouse gas emissions into the atmosphere, making electric vehicles (EVs) an important tool in combating climate change. Despite their considerable environmental and economic benefits, the integration of PVs and EVs can introduce unique operational challenges for the power distribution grid. If not coordinated, high penetration of PVs and EVs can result in variety of power quality issues, such as instances of overvoltage and undervoltage, frequency fluctuations, and/or increased losses. This paper proposes a mixed-integer multi-objective nonlinear optimization model for optimal energy dispatch in a power distribution grid with high penetration of PV and EV resources. The model proposed here is an extension of the traditional voltage and var optimization (VVO) into a comprehensive and coordinated control of voltage, active power, and reactive power. A modified version of the IEEE 123-bus test distribution system is used to demonstrate the effectiveness of the proposed solution.

An optimal placement and sizing of type-IV DG with reactive power support using UPQC in an unbalanced distribution system using particle swarm optimization

An optimal placement and sizing of type-IV DG with reactive power support using UPQC in an unbalanced distribution system using particle swarm optimization

Fault location algorithms for active distribution systems utilizing two-point synchronized or unsynchronized measurements

This paper introduces two alternative formulations of a fault location algorithm, based on two-point measurements, which is appropriate for unbalanced medium voltage overhead distribution systems of radial configuration with or without distributed generation. The first alternative is solely based on synchronized three-phase voltage signals taken from the two measurement points. The algorithm applies fundamental bus-impedance-matrix-based fault analysis theory and calculates voltage drops to derive a fault location equation set for each fault type. The standard bus impedance matrix theory is also the basis for the second alternative. By combining the expressions correlating unsynchronized voltage and currents measurements from the two points with the elements of a modified bus impedance matrix, the need for synchronization angle is eliminated. Then, a fault location equation set is formed to obtain the fault distance and resistance. A multiple solutions elimination methodology is also proposed which is applicable for both alternative fault location algorithms addressed in this paper Extensive simulation studies demonstrate a good performance for the proposed fault location algorithms under numerous short-circuit conditions with varying pre-fault system loading conditions, fault resistances and measurement errors.

Meter placement approaches for matrix completion-based distribution system state estimator

Traditional matrix and tensor completion approaches utilize latent structures in data to impute missing entries. Recent works on distribution system state estimators employing such data imputation techniques have identified the need to incorporate fundamental system equations as constraints to improve state estimation accuracy. As a result, these techniques provide superior state estimation performance compared to their model-free counterparts and conventional state estimators. In practice, the data required for these estimators are provided by sensors/meters deployed in the network. However, prior efforts do not explore the placement of sensors that optimize the performance of the estimators. Moreover, constraints on entries of these matrices and tensors result in specific combinations of known measurements to provide better imputation results than others. Therefore, this work proposes two-meter placement approaches that leverage network parameters and linearized power flow equations to identify sensor locations. These approaches achieve this by iteratively placing sensors with the highest contribution towards minimizing the voltage residual in the selected reference cases. The first approach identifies buses that provide the highest reduction in voltage residuals. In contrast, the second approach identifies locations of a heterogeneous set of sensors that provide the highest reduction in voltage residual. The proposed approaches can also extend existing sensor deployments such as distribution phasor measurement units (D-PMU) and supervisory control and data acquisition (SCADA) sensing and measurement devices (e.g., Bellwether meters) to improve state estimation performance. The approaches have been evaluated on the IEEE 33-node distribution system and an unbalanced 3-phase 559-node distribution system. • A meter placement approach to place SCADA sensors (e.g., Bellwether meters) and distribution phasor measurement unit (D-PMUs). • Iterative approach that places sensors with highest contribution towards minimizing voltage residual. • Power flow constraints introduce interactions between state measurement matrix elements which can be exploited to improve state estimation accuracy.

Injected Current Sensitivity Based Load Flow Algorithm for Multi-Phase Distribution System in the Presence of Distributed Energy Resources

This paper presents an injected current sensitivity (ICS) based multi-phase load flow (LF) methodology with minimal Jacobian computation for the three-phase unbalanced distribution system with multiple Distributed Energy Resources (DERs). In the proposed approach, first, a generalized bus admittance and Jacobian matrix have been formulated that include various distribution system components such as lines, shunt capacitors, voltage control devices such as regulators, different transformer connections, and load models. Second, DERs are modeled as a PV bus and incorporated into the proposed LF algorithm by formulating a reactive power injection-based sensitivity matrix that iteratively computes its net power injections. Unlike the traditional Jacobian matrix-based LF methods where an update of Jacobian (size and element) is required for each PV bus, this method does not require any update, hence, making it faster and more flexible to include a large number of DERs. From the various tests performed on the standard IEEE three-phase distribution network and their derivatives, it has been observed that the proposed approach is accurate, efficient, computationally less complex, and scalable.

Fast Flexible Direct Power Flow for Unbalanced and Balanced Distribution Systems

The study proposes a fast flexible direct power flow solution for radial distribution systems and a fast flexible direct weakly meshed power flow solution for weakly meshed distribution systems. The algorithm is based on the direct forward sweep power flow solution, which is an updated version of the backward/forward sweep solution. The fast flexible direct power flow uses a unique conversion matrix (CM) to rapidly determine the power flow solution. The inverted conversion matrix and its slide-modified matrix are used to solve the power flow problem in a single forward sweep step, which is a novel feature of this work. To ensure the invertibility of the conversion matrix, it is constructed to have a small condition number and a determinant of minus one, and all of its eigenvalues must be equal to that of minus one. Additionally, by modifying the conversion matrix to accommodate the loop branch using the break-point idea, a new weakly meshed conversion matrix (WMCM) is generated with the same following modification as for the radial network and employed in the fast flexible direct weakly meshed power flow (FFDWMPF) solution for the weakly meshed distribution network. The usage of a single matrix in the power flow solution and advanced direct techniques decreases the number of iterations and CPU execution time when MATLAB programming is executed. Furthermore, the proposed method is flexible enough to incorporate any changes in the radial or weakly meshed distribution system just by incorporating the changes in the CM and WMCM for any radial or weakly meshed system. Moreover, the robustness of FFDPF and FFDWMPF is evaluated under various loading scenarios on balanced radial and weakly meshed distribution networks. Finally, to validate the proposed algorithm, the proposed strategy is applied to numerous balanced and unbalanced distribution systems.

Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

In this paper, an improved slime mould algorithm (ISMA) is proposed for finding the optimal location and sizing of photovoltaic distributed generation units (PVDGUs) in unbalanced distribution systems (UDSs). The proposed method is developed by changing the control variable update mechanism of the original slime mould algorithm (SMA). Total power losses on distribution lines and voltage deviation index of all buses are minimized under the consideration of various constraints. The location and sizing of PVDGUs found by ISMA are added into the cosimulation between MATLAB and OpenDSS for reaching other remaining parameters of UDSs. In addition, sunflower optimization (SFO), social-ski drive (SSD), cuckoo search algorithm (CSA), salp swarm algorithm (SSA), bonobo optimizer (BO), and SMA are also run for finding PVDGUs placement solution on the unbalanced three-phase IEEE 123-bus test feeder. As a result, the proposed ISMA can reduce the power loss up to 78.88% and cut the voltage deviation up to 1.4779 pu while that of others is from 69.10% to 78.87% and from 1.5759 to 1.4996 pu. Thus, ISMA should be used to place PVDGUs in UDSs meanwhile the cosimulation between MATLAB and OpenDSS should be applied as a power flow calculation tool for UDSs.