Ahmad Reza Malekpour

Multi-Objective Stochastic Distribution Feeder Reconfiguration in Systems With Wind Power Generators and Fuel Cells Using the Point Estimate Method

This paper presents a multi-objective algorithm to solve stochastic distribution feeder reconfiguration (SDFR) problem for systems with distributed wind power generation (WPG) and fuel cells (FC). The four objective functions investigated are 1) the total electrical energy losses, 2) the cost of electrical energy generated, 3) the total emissions produced, and 4) the bus voltage deviation. A probabilistic power flow based on the point estimate method (PEM) is employed to include uncertainty in the WPG output and load demand, concurrently. Different wind penetration strategies are examined to capture all economical, operational and environmental aspects of the problem. An interactive fuzzy satisfying optimization algorithm based on adaptive particle swarm optimization (APSO) is employed to determine the optimal plan under different conditions. The proposed method is applied to Taiwan Power system and the results are validated in terms of efficiency and accuracy.

Reactive power and voltage control in distribution systems with photovoltaic generation

This paper presents the interaction of traditional centralized voltage regulators such as load-tap-changing (LTC) transformers with the new emerging inverter-based distributed photovoltaic (PV) generators in reactive power and voltage control of distribution systems. Different reactive power control strategies for inverter-based PVs are considered and their interaction with LTC transformers is analyzed. The investigated objective function is the total electric losses for the 24 hours while satisfying the system operational constraints. Discrete Particle swarm optimization (DPSO) is used to determine the LTC operation scheme as an integer nonlinear optimization problem. The performance is validated by applying the proposed method to the standard IEEE 33 bus test system.

Goal-Based Holonic Multiagent System for Operation of Power Distribution Systems

Large-scale integration of rooftop solar power generation is transforming traditionally passive power distribution systems into active ones. High penetration of such devices creates new dynamics for which the current power distribution systems are inadequate. The changing paradigm of power distribution system requires it to be operated as cyber-physical system. A goal-based holonic multiagent system (HMAS) is presented in this paper to achieve this objective. This paper provides details on design of the HMAS for operation of power distribution systems. Various operating modes and associated goals are discussed. Finally, the role of HMAS is demonstrated for two applications in distribution systems. The first one is associated with control of reactive power at solar photovoltaic installations at individual homes for optimal operation of the system. The second deals with the state estimation of the system leveraging different measurements available from smart meters at homes.

Optimal Allocation of Distributed Generations and Remote Controllable Switches to Improve the Network Performance Considering Operation Strategy of Distributed Generations

Abstract This article proposes a new generation worth index for each load level to evaluate whether or not the distributed generation in that load level is worthwhile. The proposed index regards the impact of a distributed generation operation strategy on generation cost and reliability of the network. Based on the proposed generation worth index, the annual optimal operation strategy of distributed generation can also be estimated. Obviously, there is a mutual impact between the optimal operation strategy and the optimal site and size of distributed generations in the network. Hence, in the second part of the article, the proposed generation worth index and annual distributed generation operation strategy are utilized to determine the optimal size and location of distributed generations and the optimal location of remote controllable switches. The generation worth index is calculated to reduce the network energy loss, energy cost, and expected energy not supplied. The annual load is considered to be multilevel, and a genetic algorithm based method is developed for this optimization. Numerical results on a 33-bus distribution test network show the benefits of the proposed approach.

Inverter-based var control in low voltage distribution systems with rooftop solar PV

Drop in prices of PV panels and increased awareness of environmental concerns is resulting in high number of rooftop solar PV installations. Rapid irradiance changes on partly cloudy days causes severe fluctuations in PV power output resulting in rapid fluctuations in voltage, which makes large-scale integration of rooftop solar PV into the grid a major challenge. This paper presents an inverter-based var control strategy to damp fast fluctuations in voltages. Different reactive power control strategies for inverter-based PVs are studied and their effects are analyzed in a second by second time frame. The proposed strategies have been tested on the modified IEEE 37 bus test system. Simulations demonstrate that the proposed strategies outperform the current standard (IEEE 1547) for voltage control.

A Dynamic Operational Scheme for Residential PV Smart Inverters

This paper presents an operational scheme for photovoltaic (PV) inverter reactive power control to accommodate higher levels and leverage efficient use of rooftop PV penetration in distribution systems. The scheme proposes three states of operation with specific operational goals for the PV inverter based on weather conditions and voltage at the interconnection point, and adapts the reactive power control strategy accordingly. In normal state with slowly changing solar irradiance, the control modulates reactive power to reduce power losses. In fluctuating state with rapidly varying solar irradiance due to intermittent passing clouds, the control dynamically changes the reactive power in order to mitigate voltage fluctuations. In contingency state in which the PV terminal voltage violates the nominal operating range, the control adjusts the PV inverter as reactive power sink or source in order to push the voltage back within the range. This paper also proposes a coordination strategy in order to switch control between the states and manage interaction between the fast PV inverter controllers, and the slow on-load tap-changer for voltage regulation. A large-scale distribution network based on the IEEE 37-node test feeder was developed in order to investigate performance of the proposed algorithm.

Distributed volt/var control in unbalanced distribution systems with distributed generation

Future power distribution systems are expected to have large number of scale smart measuring devices and distributed generation (DG) units which would require real-time network management. Integration of single-phase DG and advanced metering infrastructure (AMI) technologies will add further complexity to the power distribution system which is inherently unbalanced. In order to alleviate the negative impacts associated with the integration of DG, transformation from passive to active control methods is imperative. If properly regulated, DGs could provide voltage and reactive power support and mitigate the volt/VAr problem. This paper presents a distributed algorithm to provide voltage and reactive power support and minimize power losses in unbalanced power distribution systems. Three-phase volt/VAr control problem is formulated and active/reactive powers of DGs are determined in a distributed fashion by decomposing the overall power distribution system into zonal sub-systems. The performance is validated by applying the proposed method to the modified IEEE 37 node test feeder.

Hierarchical Architecture for Integration of Rooftop PV in Smart Distribution Systems

This paper presents a novel hierarchical multilevel decentralized optimal power flow (OPF) for power loss minimization in three-phase unbalanced large-scale distribution systems via optimal reactive power scheduling of rooftop photovoltaics generators. The system is decomposed into three levels corresponding to: 1) the primary; 2) the lateral; and 3) the secondary feeder subnetworks of distribution systems. A distributed sequential coordination scheme based on analytical target cascading method is developed to minimize power losses while considering the operational constraints. Results based on the proposed method are compared with centralized OPF for validation. Control based on the proposed method is compared with no reactive power control and local reactive power control to identify its effectiveness. Further, a virtual feeder is introduced to separate the coupled subnetworks into decomposed layers, which enables parallel processing of the optimization problems to reduce computational complexity and provide faster solution. A 559-node large-scale distribution network built based on the IEEE 37 node test system is used to demonstrate performance of the proposed algorithm.

Radial Test Feeder including primary and secondary distribution network

This paper describes development of a three-phase unbalanced distribution network test case, considering primary and secondary level distribution systems. Primary feeders, lateral feeders, and secondary feeders are modeled from the substation transformer to the house level based on the networks physical hierarchical structure. Researchers can use the developed benchmark for test case analysis and to address issues associated with integration of rooftop photovoltaics (PVs) and distributed energy resources (DER) in existing unbalanced networks, including incremental power losses, voltage violations, voltage fluctuations, volt/var control, and other power quality concerns.