Meysam Shamshiri

A review of recent development in smart grid and micro-grid laboratories

In recent decades, smart grid have become increasingly attractive to both energy producers and consumers. Amongst the main challenges for the successful realization of smart grid includes the integration of renewable energy resources, real time demand response and management of intermittent energy resources. Apart from smart grid, the development of micro-grids should take into consideration of issues such as the system performance, modeling, monitoring and controlling of the micro-grids. In particular, the recent advancements in information and communication technologies (ICTs) could facilitate the effective development of the future micro-grid system. This paper presents an overview of smart grids features and highlights the recent development of micro-grid laboratories in Europe, US and Japan.

Probabilistic evaluation of the impact of residential photovoltaic system on Malaysia low-voltage network using Monte Carlo approach

Electricity is usually generated in bulk from large scale conventional power stations and transmitted unidirectional from high to low voltage level where the users are located. More recently, the integration of solar Photovoltaic(PV) systems has been gaining attention in Malaysia given their potential technical benefits and strong governmental support. However, investigation on the potential impact of residential rooftop PV systems on the distribution network has not been properly addressed in the Malaysian context. Therefore, this paper aims to probabilistically assess the impact of different levels of PV penetration on the Malaysian low-voltage (LV) distribution network using the Monte Carlo approach. More specifically, a real and typical residential network in Malaysia has been utilized and used as the test network in this paper. In addition, uncertainties in terms of PV generation intermittency, distribution of the connected PV system capacities as well as allocations of PV systems across the different phases of the network were considered in the study. These allow a more meaningful conclusion to be made. Furthermore, two types of networks, namely, newly developed and matured networks were considered in performing the network impact assessment study. The network output performance metrics include voltage profiles, voltage unbalance, feeder and transformer thermal limits, as well as network losses. The results from the study suggest voltage unbalance and voltage rise are the two main reasons that could limit the higher PV penetration level in typical Malaysian residential LV networks.

Performance Assessment of Slip Mode Frequency Shift (SMS) Islanding Detection Methods

The awareness concerning the grid connected Photovoltaic (PV) has become vital and a major concern nowadays. Islanding detection is one of the most dominant challenges for distributed generation system connected to the utility grid. In addition, islanding has not been a preferable option as it may pose safety hazard and may cause damage to power generation and power supply facilities as a result of unsynchronized re-closer. Therefore, the islanding detection techniques are needed to ensure safe and reliable system operation. One of the established islanding prevention methods is the Slip Mode Frequency Shift (SMS) islanding method, which has numerous advantages over the other techniques. This paper investigates the active islanding detection methods and specifically focused on the SMS islanding method. The results show that the SMS islanding method successfully detected an unintentional fault and managed to isolate the system within the prescribed time range.

Assessment of distribution networks performance considering residential photovoltaic systems with demand response applications

The large penetration of solar photovoltaic (PV) systems at low voltage (LV) networks has started to introduce new challenges to distribution network operators. With the emergence of smart grid technology, the demand response (DR) has been identified as one of the promising approaches for network operators to increase operational flexibility, particularly in the presence of renewable energy resources. Therefore, it is important to investigate how DR applications at a LV consumer level can help to improve network performance. However, so far, only a limited number of works have addressed the implications of DR at LV networks with a PV system. The parametric analysis of the benefits of DR has not been adequately addressed for LV networks with multiple DR-PV interaction scenarios. In this regard, three case studies have been considered in this work, namely, consumers who respond to their own demand profile, consumers who respond to the PV generation profile, and the optimized demand response from consumers. ...

Integration of PV system into LV distribution networks with Demand Response application

The increasing number of PV system connected to LV distribution networks may trigger network reinforcement to maintain voltages and power flows within the statutory limits. The paper aims to investigate how different levels of Demand Response (DR) participation can facilitate the integration of PV. In order to get robust conclusion, fractal-based generic distribution network model is used to generate many statistically similar networks. Subsequently, a Particle Swarm Optimization approach to model the optimal demand pattern for various levels of DR participation is investigated in the study. The results suggest that DR can significantly improve self (local) consumption of PV output. As a result, network losses decrease and the voltage rise effect at high PV penetration can be alleviated.

Optimal Capacitor Allocation in Distribution System using Particle Swarm Optimization

Capacitor installation is one of the most commonly used methods for reactive power compensation in the distribution networks. In this paper, the optimum capacitor placement and its sizing has been applied in the distribution network in terms of power losses minimization and voltage profile improvement. The maximum and minimum bus voltage and the maximum possible capacitor size are the constraints of optimum capacitor placement and sizing problem. There are considered as the penalty factor in the objective function. In order to evaluate the obtained objective function, the Particle Swarm Optimization (PSO) is utilized to find the best possible capacitor placement and capacity. The OpenDSS software has then been utilized to solve the power flow through Matlab coding interface. To validate the functionality of the proposed method, the IEEE 13-bus test system is implemented and the obtained results have been compared with the IEEE standard case without capacitor compensation. The results show that the proposed algorithm is more cost effective and has lower power losses as compared to the IEEE standard case. In addition, the voltage profile has been improved, accordingly.