Yun Seng Lim

Bio: Yun Seng Lim is an academic researcher from Universiti Tunku Abdul Rahman. The author has contributed to research in topics: Photovoltaic system & Energy storage. The author has an hindex of 17, co-authored 65 publications receiving 1124 citations. Previous affiliations of Yun Seng Lim include University of Manchester.

Energy Storage System for Mitigating Voltage Unbalance on Low-Voltage Networks With Photovoltaic Systems

Abstract: The growth of building integrated photovoltaic (BIPV) systems in low-voltage (LV) networks has the potential to raise several technical issues, including voltage unbalance and distribution system efficiency. This paper proposes an energy storage system (ESS) for mitigating voltage unbalance as well as improving the efficiency of the network. In the study, a power system simulation tool, namely PSCAD, is used to model two generic LV networks, BIPV systems and an ESS in order to simulate the performance of the networks with various levels of BIPV penetrations. A control algorithm is developed and implemented in the energy storage model in order to study the ability of the ESS to mitigate network voltage unbalance and reduce losses. Experimental studies are carried out in the experimental small-scale energy zone to investigate the effectiveness of the energy storage system under various levels of PV penetration and load conditions. The simulation and experimental studies carried out clearly show the effectiveness of the ESS in reducing the voltage unbalance factor and improving the efficiency of the two networks considered.

Grid-connected photovoltaic system in Malaysia: A review on voltage issues

Abstract: Photovoltaic (PV) systems are the most promising renewable energy source in Malaysia due to its abundant solar irradiation. The Malaysian government has launched various renewable energy programs to encourage the use of PV systems. Most of the PV systems are single-phase and the installation is customer driven. Therefore, the growth of PV system in low voltage (LV) distribution network has the potential to raise several technical issues including voltage rise and voltage unbalance. Furthermore, Malaysia is a warm country and geographically surrounded by the sea. The vaporization of the sea water together with the seasonal winds results in a large amount of passing clouds, making this country to be, possibly, the cloudiest region in the world. The solar irradiation is therefore highly scattered and fluctuating. The power output from PV is highly intermittent, hence producing an enormous amount of voltage fluctuations and flickers on the LV distribution networks. All these voltage issues have to be studied experimentally and addressed thoroughly at the early stage before the amount of PV on the network becomes substantial. Therefore, a 7.2 kW grid connected PV system on a radial LV distribution network has been set up to study the voltage issues at the point of common coupling. The power outputs of the PV system are characterised and compared with that of other countries. The probability density of voltage rise and voltage unbalanced factors are derived from the measurement data. Short-term and long-term voltage flicker indexes are calculated to evaluate the severity of the flicker emission. These results are valuable to the policy makers, electricity regulatory body, utility company, customers and PV manufacturers because they can change the policy on the renewable energy and the regulatory framework.

Analytical approach to probabilistic prediction of voltage sags on transmission networks

Abstract: Quantification of voltage sags at a location of interest is the basic requirement for assessing the compatibility between equipment and electrical supply An analytical method is described that has been developed to determine the probability density functions of voltage sags caused by three phase faults across the network The method takes into account the impact of fault positions along transmission circuits and patterns of generation associated with the corresponding load demands on the voltage sag profiles The developed algorithm is applied to the IEEE 24-bus reliability test system to verify the technique and illustrate its application

Electrical energy storage systems: A comparative life cycle cost analysis

Abstract: Large-scale deployment of intermittent renewable energy (namely wind energy and solar PV) may entail new challenges in power systems and more volatility in power prices in liberalized electricity markets. Energy storage can diminish this imbalance, relieving the grid congestion, and promoting distributed generation. The economic implications of grid-scale electrical energy storage technologies are however obscure for the experts, power grid operators, regulators, and power producers. A meticulous techno-economic or cost-benefit analysis of electricity storage systems requires consistent, updated cost data and a holistic cost analysis framework. To this end, this study critically examines the existing literature in the analysis of life cycle costs of utility-scale electricity storage systems, providing an updated database for the cost elements (capital costs, operational and maintenance costs, and replacement costs). Moreover, life cycle costs and levelized cost of electricity delivered by electrical energy storage is analyzed, employing Monte Carlo method to consider uncertainties. The examined energy storage technologies include pumped hydropower storage, compressed air energy storage (CAES), flywheel, electrochemical batteries (e.g. lead–acid, NaS, Li-ion, and Ni–Cd), flow batteries (e.g. vanadium-redox), superconducting magnetic energy storage, supercapacitors, and hydrogen energy storage (power to gas technologies). The results illustrate the economy of different storage systems for three main applications: bulk energy storage, T&D support services, and frequency regulation.

Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids

Abstract: Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application side, different tasks for storage deployment demand distinct properties of the storage system. This review aims to serve as a guideline for best choice of battery technology, system design and operation for lithium-ion based storage systems to match a specific system application. Starting with an overview to lithium-ion battery technologies and their characteristics with respect to performance and aging, the storage system design is analyzed in detail based on an evaluation of real-world projects. Typical storage system applications are grouped and classified with respect to the challenges posed to the battery system. Publicly available modeling tools for technical and economic analysis are presented. A brief analysis of optimization approaches aims to point out challenges and potential solution techniques for system sizing, positioning and dispatch operation. For all areas reviewed herein, expected improvements and possible future developments are highlighted. In order to extract the full potential of stationary battery storage systems and to enable increased profitability of systems, future research should aim to a holistic system level approach combining not only performance tuning on a battery cell level and careful analysis of the application requirements, but also consider a proper selection of storage sub-components as well as an optimized system operation strategy.

Accurate photovoltaic power forecasting models using deep LSTM-RNN

Abstract: Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure operation and economic integration of PV in smart grids, accurate forecasting of PV power is an important issue. In this paper, we propose the use of long short-term memory recurrent neural network (LSTM-RNN) to accurately forecast the output power of PV systems. The LSTM networks can model the temporal changes in PV output power because of their recurrent architecture and memory units. The proposed method is evaluated using hourly datasets of different sites for a year. We compare the proposed method with three PV forecasting methods. The use of LSTM offers a further reduction in the forecasting error compared with the other methods. The proposed forecasting method can be a helpful tool for planning and controlling smart grids.

Photovoltaic penetration issues and impacts in distribution network - A review

Abstract: The solar energy generation has grown significantly in the past years. The importance of PV penetration in power system as a major element of renewable energy source has seen it being widely used on a global scale. Despite its promising success, PV penetration presents various issues and its impact on the distribution system has to address for seamless integration in the power system. In this paper, a comprehensive overview on important issues affecting the distribution system as a result of PV penetration is presented. Pertinent issues such as voltage fluctuation, voltage rise, voltage balance, and harmonics and their effect on the system are discussed in details. The islanding issues, which are of critical importance to the stability and integrity of the system, are also thoroughly reviewed. Details on different islanding techniques – remote and local techniques and their advantage and disadvantages are shown. Therefore, this paper can provide useful information and serve as a reference for researchers and utility engineers on issues to be considered with regards to PV penetration.