Determining loss minimum configuration in a distribution network is a hard discrete optimization problem involving many variables. Since more and more dispersed generators are installed on the demand ...side of power systems and they are reconfigured frequently, developing automatic approaches is indispensable for effectively managing a large-scale distribution network. Existing fast methods employ local updates that gradually improve the loss to solve such an optimization problem. However, they eventually get stuck at local minima, resulting in arbitrarily poor results. In contrast, this paper presents a novel optimization method that provides an error bound on the solution quality. Thus, the obtained solution quality can be evaluated in comparison to the global optimal solution. Instead of using local updates, we construct a highly compressed search space using a binary decision diagram and reduce the optimization problem to a shortest path-finding problem. Our method was shown to be not only accurate but also remarkably efficient; optimization of a large-scale model network with 468 switches was solved in three hours with 1.56% relative error bound.
Fast and accurate estimation of sensitivity matrices is significant for the enhancement of distribution system modeling and automation. Analytical estimations have mainly focused on voltage magnitude ...sensitivity to active/reactive power injections for unbalanced networks with Wye-connected loads and neglecting DERs' smart inverter functionality. Hence, this paper enhances the scope of analytical estimation of sensitivity matrices for unbalanced networks with 1-φ, 2-φ, and 3-φ Delta/Wye-connected loads, DERs with smart inverter functionality, and substation/line step-voltage regulators (SVR). A composite bus model comprising of DER, Delta- and Wye-connected load is proposed to represent a generic distribution bus, which can be simplified to load, PV, or voltage-controlled bus as required. The proposed matrix-based analytical method consolidates voltage magnitude and angle sensitivity to active/reactive power injection and tap-position of all SVRs into a single algorithm. Extensive case studies on IEEE and EPRI networks show the accuracy and wide scope of the proposed algorithm compared to the existing benchmark method.
This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous ...compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden. A distribution network with two 20 kV feeders and 8 DG units was used to validate the control performance of the proposed coordinated voltage control scheme.
This study focuses on the equitable loss allocation method for radial distribution networks integrated with distributed generators (DGs). As the traditional Shapley value method may cause a ...combinational explosion problem, the authors propose a sampling method for estimating the actual Shapley value. They use a stratified sampling method (SSM) to reduce the number of samples of Shapley value method with the subject to the overall equilibrium constraint. To determine the number of samples drawn from each stratum, they use the Neyman optimum allocation to minimise the variance of the sample mean. A reinforcement learning algorithm is introduced to estimate the standard deviations of the strata needed for the optimal stratified sampling. The proposed method is applied to a modified 17-bus distribution network and an actual distribution network in Zhejiang Province, People's Republic of China. The simulation results show that the proposed method can not only resolve the combinational explosion problem of Shapley value method but retain its desirable characteristics. The proposed method can dramatically reduce computational time by implementing a SSM. Therefore, the efficiency and superiority of the proposed method with regards to loss allocation are verified for radial distribution networks that include DGs.
Input-series-output-parallel (ISOP) isolated bidirectional direct current (dc)/dc converter (IBdc) becomes a preferred scheme connecting high-voltage and low-voltage bus in dc distribution network. ...Input-voltage-sharing (IVS) among modules is essential to realize the stable operation of ISOP system. Nowadays, with large-scale access of distributed energy sources and loads in dc grids, the fluctuations in bus voltage and connected load become frequent and great, deteriorating the IVS performance and stable operation of ISOP structure IBdc. To solve this issue, a triple-close-loop IVS strategy is proposed in this article. Compared with the conventional IVS strategy with constant input impedance, the proposed IVS strategy reshapes input impedance to be a full-order model containing high-order components and sensitive to fluctuation of output voltage, and IVS control based on reshaped impedance improves dynamics feature, maintains ideal output power, and avoids false protection and potential instability for ISOP structure IBdc under frequent and large fluctuation. Experimental results verify the correctness and effectiveness of the analysis and proposed strategy, providing a feasible, efficient, and practical control scheme for ISOP system in dc distribution network.
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.
With the increasing penetration of renewable energy (RE), the operations of distribution network are threatened and some issues may appear, i.e., large voltage deviation, deterioration of statistic ...voltage stability, high power loss, etc. In turn, RE accommodation would be significantly impacted. Therefore, we propose a many-objective distribution network reconfiguration (MDNR) model, with the consideration of RE curtailment, voltage deviation, power loss, statistic voltage stability, and generation cost. This aims to assess the trade-off among these objectives for better operations of distribution networks. As the proposed model is a non-convex, non-linear, many-objective optimization problem, it is difficult to be solved. We further propose a deep reinforcement learning (DRL) assisted multi-objective bacterial foraging optimization (DRL-MBFO) algorithm. This algorithm combines the advantages of DRL and MBFO, and is targeted to find the Pareto front of proposed MDNR model with better searching efficiency. Finally, we conduct case study on the modified IEEE 33-bus, 69-bus, and 118-bus power distribution systems, and results verify the effectiveness of the MDNR model and outperformance of the proposed DRL-MBFO.
This article provides a unique benchmark to integrate and systematically evaluate advanced functionalities of microgrid and downstream device controllers. The article describes Banshee, a real-life ...power distribution network. It also details a real-time controller hardware-in-the-loop (HIL) prototyping platform to test the responses of the controllers and verify decision-making algorithms. The benchmark aims to address power industry needs for a common basis to integrate and evaluate controllers for the overall microgrid, distributed energy resources (DERs), and protective devices. The test platform will accelerate microgrid deployment, enable standard compliance verification, and further develop and test controllers' functionalities. These contributions will facilitate safe and economical demonstrations of the state-of-the-possible while verifying minimal impact to existing electrical infrastructure. All aspects of the benchmark and platform development including models, configuration files, and documentation are publicly available via the electric power HIL controls collaborative (EPHCC).
Integration of rooftop photovoltaic (PV) systems in a three-phase four-wire distribution network cause voltage-violations namely voltage-rise and voltage unbalance. This study investigates the ...factors that affect both the voltage-rise and voltage unbalance in low voltage distribution network integrated with the rooftop PV systems. The concerning factors are classified into active factors such as; loads active powers, PV active powers, and bus reactive powers, and passive factors such as; numbers of feeder buses and neutral-grounded resistances. The study also determines the factors conditions at which the highest values of both voltage-rise and voltage unbalance occurred. Moreover, the most and least significant effects of individual factors on both voltage-rise and voltage unbalance are studied. The studied system is simulated and implemented in MATLAB software environment and the feeder loads are modelled based on Back–Forward Sweep method. The simulation results identify that the conditions of the worst voltage-rise and voltage unbalance cases depend on the collective influence of the studied factors.
Reliability is an essential factor in distribution networkt expansion planning. However, standard distribution reliability assessment techniques rely on quantifying the impact of a pre-specified set ...of events on service continuity through the simulation of component outages, one at a time. Due to such a simulation-based nature, the incorporation of reliability into distribution network expansion planning has customarily required the application of heuristic and metaheuristic approaches. Recently, alternative mixed-integer linear programming (MILP) models have been proposed for distribution network expansion planning considering reliability. Nonetheless, such models suffer from either low computational efficiency or over-simplification. To overcome these shortcomings, this paper proposes an enhanced MILP model for multistage reliability-constrained distribution network expansion planning. Leveraging an efficient, yet accurate reliability evaluation model, proposing a customized technique for effectively imposing radial operation, as well as utilizing pragmatic measures to model reliability-related costs are the salient features of this work. In this respect, practical reliability-related costs are considered based on reliability incentive schemes and the revenue lost due to undelivered energy during customer outages. The proposed planning approach is tested on four networks with 24, 54, 86, and 138 nodes to illustrate its efficiency and applicability.
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