Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems

The optimum penetration of distributed generations into the distribution grid provides several technical and economic benefits. However, the computational time required to solve the constrained optimization problems increases with the increasing network scale and may be too long for online implementations. This paper presents a parallel solution of a multi-objective distributed generation (DG) allocation and sizing problem to handle a large number of computations. The aim is to find the optimum number of processors in addition to energy loss and DG cost minimization. The proposed formulation is applied to a 33-bus test system, and the results are compared with themselves and with the base case operating conditions using the optimal values and three popular multi-objective optimization metrics. The results show that comparable solutions with high-efficiency values can be obtained up to a certain number of processors

Optimal voltage control in distribution feeders with large penetration of wind

This paper develops coordinated voltage control with high penetration of wind in power distribution systems. In the proposed method, daily schedule of optimal voltage profiles are determined by using optimization technique based on predicted values of load demand and by controlling tap positions of regulators, switched capacitors, and reactive power outputs of the inverters. In this paper, three optimal voltage control models are developed: the first model uses capacitors as control devices; the second model uses capacitors and tap changers of voltage regulators; and the third model includes the inverters of the wind turbines as well. We use a recently developed heuristic, Sine-cosine algorithm, to solve the optimal voltage control problems. The case studies carried out on a modified 33-node feeder shows the effectiveness of the proposed optimization models in controlling the voltages in distribution feeders

Reinforcement of the distribution grids to improve the hosting capacity of distributed generation: Multi-Objective Framework

Excessive penetration of renewable energy resources into the distribution grid without additional preventive measures has led to several operational problems. However, most strategies developed to accommodate more renewable energy units suffered from other operational problems. Therefore, further efforts are needed to address the other key vulnerabilities of the grid in addition to maximizing the hosting capacity. In this regard, this study is devoted to a new multi-objective formulation to maximize the hosting capacity and minimize the total energy losses while satisfying the operational constraints and maximizing the energy transferred to off-peak hours. The Multi-Objective Advanced Gray Wolf Optimization (MOAGWO) algorithm is used as a solution tool. The proposed formulation and solution algorithm are tested on IEEE-33-bus and 69-bus medium voltage test systems. The impacts of energy storage systems, voltage regulators, and static var compensators on the hosting capacity and the objective functions are identified using several scenarios. The results showed that the optimal device type and locations depend on the level of DG penetration. Finally, a comparison according to two popular multi-objective performance indices showed that the quality of the Pareto front distribution obtained by MOAGWO was better than the ones obtained with the two other popular heuristic methods

Branch Outage Simulation Based Contingency Screening by Gravitational Search Algorithm

Power systems contingency analysis is an important issue for electric power system operators. This paper performs branch outage simulation based contingency screening using a bounded network approach. Local constrained optimization problem representing the branch outage phenomena is solved by the gravitational search algorithm. The proposed method is applied to IEEE 14, 30, 57, and 118 Bus Test systems and its performance from the point of capturing violations is evaluated. In addition, false alarms and the computational accuracy of the proposed method are also analyzed by using scattering diagrams. Finally, the proposed gravitational search based contingency screening is compared with full AC load flow solutions from the point of computational speed. Copyright (C) 2012 Praise Worthy Prize S.r.l. - All rights reserved

A Novel Approach For Voltage Control In Electrical Power Distribution Systems

This paper proposes a novel approach for voltage control in 3-phase unbalanced distribution systems. The approach is based on the change of the magnetizing reactances of the voltage regulators in the system. We used an augmented Lagrangian-based optimization model to determine the optimal settings on a modified IEEE 123 Bus Test System with large PV penetration. Simulations were performed on a minute-based resolution either by controlling regulators or by controlling the magnetizing reactances of the regulators only. The simulation results presented and their comparison show that the control of the magnetizing reactances of the regulators may improve the voltage profile, and may be an addition or alternative to both traditional voltage control devices, such as capacitors, tap changers, and newer devices such as smart inverters

Assessment of harmonic distortion on distribution feeders with electric vehicles and residential PVs

Power-electronic interfacing based devices such as photovoltaic (PV) panels and electric vehicles (EVs) cause voltage/current harmonic distortions on the power grid. The harmonic current profiles from EVs and PVs depend on the design of the controllers integrated to the PV inverters and EV chargers. Similarly, the voltage and current harmonic distortions on a grid change throughout the day as the PV output power, number of grid connected EVs, and the other load pattern change. In this context, we present harmonic assessment to demonstrate cumulative effect of large number of EVs and PVs on a medium voltage distribution grid. We will demonstrate the case studies on the IEEE 123-node distribution feeder with 20%, 50%, and 100% PV and EV penetrations, based on time series simulations carried out for an entire day

A multi-objective framework for distributed energy resources planning and storage management

The use of energy storage systems (ESS) and distributed generators (DGs) to improve reliability is one of the solutions that has received much attention from researchers today. In this study, we utilize a multi-objective optimization method for optimal planning of distributed generators in electric distribution networks from the perspective of multi-objective optimization. The objective is to improve the reliability of the network while reducing the annual cost and network losses. A modified version of the multi-objective sine–cosine algorithm is used to determine the optimal size, location, and type of DGs and the optimal capacity, location, and operation strategy of the ESS. Three case studies of IEEE 33-bus, 69-bus and 141-bus test systems with Turkish DG and load data were conducted to validate the effectiveness of the proposed approach. The distribution of the Pareto front solutions and the optimal objective functions are compared with the other known algorithms. The simulation results show that the average energy not supplied and annual energy losses for the test systems are reduced by up to 68% and 64%, respectively. Moreover, the Pareto fronts of the proposed method show a better distribution and dominate those obtained by MOGWO, MOSMA, NSGA-II, MOPSO and MOEA-D according to three different Pareto optimization metrics. Finally, the computational effort result shows faster convergence of MOSCA compared to MOGWO, MOSMA, NSGA-II, MOPSO and MOEAD