Alireza Seifi

Optimal Reactive Power Control in Hybrid Power Systems

Abstract Optimal reactive power flow accounts for the major reduction in active power loss as well as more stable system operation. This article presents a novel model for optimal reactive power flow in hybrid power systems. Hybrid systems consist of an AC-DC system and flexible AC transmission system devices. Contrary to conventional methods that approximate the reactive power optimization in hybrid AC/DC systems to a simple AC reactive power optimization joint with a DC-part re-initialization stage, this study yields the optimum reactive power flow by simultaneously adjusting the control factors of both AC and DC parts. Conventional control factors associated with the AC part consist of control bus voltage, transformer tab, and static VAR compensators. This work introduces a number of DC part-related control factors, including Vdc , Idc , and DC transformer tabs to be used beside the conventional control factors inferred from a unified power flow controller aided AC system. Also, the contribution of control parameters of the unified power flow controller is considered in the reactive power optimization modeling. The proposed method is performed on modified IEEE 14- and 30-bus systems, and it is shown to have less calculation burden and more minimized cost function than the conventional method.

Fast and Perfect Damping Circuit for Ferroresonance Phenomena in Coupling Capacitor Voltage Transformers

Abstract This article investigates the effect of a few types of ferroresonance suppression circuits on suppression of the phenomenon of ferroresonance in coupling capacitor voltage transformers. A novel technique is proposed for damping of dangerous overvoltages due to ferroresonance. In this technique, by using power electronic devices, a damping resistance is switched to the secondary side of the system transformer during dangerous oscillations. This technique leads to important cost and damping-time reductions when compared with conventional alternatives. Additional devices, such as surge arresters, may be added to improve the performance of the ferroresonance suppression circuit. The technique proposed in this article is a “novel but classic” technique. The prediction of ferroresonance is achieved by detailed modeling using a digital computer transient analysis program such as the EMTP/ATP.

A Novel Method Mixed Power Flow in Transmission and Distribution Systems by Using Master-Slave Splitting Method

Abstract Traditionally, transmission and distribution power flows are studied and developed separately. In order to face keen competition in the market, the coordinated operation between transmission and distribution systems is required. Therefore, in order to balance the boundary mismatch between the transmission and distribution system models existing in the results of traditional power-flow methods, the transmission and distribution systems are studied as a whole in this article. A novel master–slave splitting iterative method is developed for solving the hybrid mixed power-flow problem. Several case studies are carried out, and the accuracy, convergence, efficiency, and reliability of the proposed method are validated.

Smart grid: An intelligent way to empower energy choices

People of the world are now fully aware of the importance of measures against global warming. It raises high expectations for clean power generation and advanced technologies. In this regard, Smart Grid, which effectively controls supply and demand of electric power by information technology, is a leading tool for developing a “new town”. Although many aspects of such new town have been observed recently and worth knowledge has been achieved, rarely can be found an article to make a comprehensive overview on smart grid and its related vision, therefore, in this paper a working definition is presented that will help to put in context the framework for better realization of smart grids.

Optimal Operation of Renewable-Based Residential Energy Hubs for Minimizing PV Curtailment

This chapter models a residential multi-carrier energy system as an energy hub. A combined heat and power (CHP) unit, a gas boiler, a heat storage system, a plug-in hybrid electric vehicle (PHEV), and photovoltaic (PV) generation are modeled in the proposed residential energy hub to provide heat and electrical demands. This chapter also investigates the issue of PV generation curtailment in the operation of the residential energy hub. To this end, an optimization-based problem is solved not only to minimize the operation cost of the energy hub, but also to minimize the PV curtailment. The impact of PHEV and the heat storage system on the operation of the energy hub and the amount of PV curtailment is investigated in this chapter. Since the availability of PHEV during a day is not usually concurrent with the PV generation, the results show that considering PHEV in the energy hub model may have low impacts on the PV curtailment. However, the presence of the storage system can reduce the PV curtailment significantly. The presented study and results show the effectiveness of the proposed optimization procedure in this chapter.

Reactive power planning in distribution systems using a reinforcement learning method

This work presents a new reinforcement learning (RL) algorithm for capacitor allocation in distribution feeders. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The formulation is a multi-objective and non-differentiable optimization problem. The proposed method of this article uses RL procedure for sizing and siting of capacitors in radial distribution feeders. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder and also a 34-bus radial distribution feeder for the sake of conclusions supports. A comparison has been made between the proposed method of this paper and similar methods in other research works to show its effectiveness for solving optimum capacitor planning problem.