Smart grid mechanism for green energy management: a comprehensive review

The smart grid is not a monolithic system, but rather is a collection of several renewable energy resources and enabling technologies in which, intelligent control is an integral part of its mechanism to improve the utilization of assets. The dynamic characteristics of a smart grid upgrade the conventional system requirements using advanced control strategies to provide continuous power to the load from intermittent renewable generation. The communication networks and control systems that enable the accommodation of distributed generation are crucial technologies in monitoring, protecting, and operating the smart grid in a centralized or decentralized manner. This paper improves the earlier published review articles by exploring the evolution of smart grids in light of renewable energy penetration with associated features. Then, the review gives an overview of notable research works in the literature aimed at developing the management and control of smart energy systems. The reader is provided with an in- depth analysis of advanced cloud computing, the internet of things, and blockchain technology with real examples for the related renewable energy projects in smart cities. Furthermore, a special interest has been paid to quantify the performance of communication technologies along with the protocols through the conceptual investigation of real cases using the optimized network engineering tools. The outcomes of the presented review can assist researchers to understand the driving mechanism of smart grid as a route to intelligently utilize renewable energy storage. It is concluded that the amalgamation of blockchain and artificial intelligence for renewable energy management is the key area where the avenue is still open for future research studies

An Effective Power Dispatch Strategy for Clustered Microgrids While Implementing Optimal Energy Management and Power Sharing Control Using Power Line Communication

The mitigation of uncertainty in the availability ofpower generation from microgrids to enable renewable resourcesto be dispatched is a daunting task for the individual operators. In-stalling energy storage systems may reduce the impact of renewableenergy intermittency. However, a peculiarity in energy manage-ment can be arisen, particularly, when different energy providersmanage these resources. Hence, an intelligent utilization approachshould be devised to maximize the benefits of using battery energystorage, since the cost of this system is the most expensive part. Thisarticle proposes an effective power dispatch strategy for clusteredmicrogrids. The developed hybrid algorithm implements optimalenergy management and power sharing control using binary data.The frequency-shift keying (FSK) technique has been adoptedfor transmitting the binary signal over the power line commu-nication (PLC). A part of the algorithm is utilized to deal withthe optimal scheduling control, whereas the other actuates thedynamic-demand-response-based photovoltaic power forecasting.The performance of the proposed approach with the formulatedbackup injection index has been validated using data collectedfrom the practical network of “Bario, Sarawak.” The presentedresults suggest that the implementation of the proposed strategy canimprove the efficiency of the overall system, causing less operatingcost and fast return. It was also found that the binary signal can betransferred with less distortion through PLC networks when usingthe FSK technique compared to other techniques

Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context

Most of the rural areas in Sarawak, particularly the remotest villages are not connected to the power grid. Integrating the local Renewable Energy Resources (RER) in these remote areas with certain capacities of energy storage and diesel generators in the form of hybrid generating system can be utilized to meet the growing need of electricity. However, the use of diesel generators as a backup is costly and environmentally troublesome. On the other hand, electrification of these areas is a daunting task and needs huge investment as it is difficult connecting them to the main power grid. On the same note, relying heavily on the battery during off-peak PV generation results in battery lifetime decrement which in turn increases the cost of energy (COE). Nowadays, the main issue is the random installation of RER without bearing in mind the optimal configuration. Furthermore, utilizing natural resources that form islanded microgrids located in different areas can pose peculiar energy management issues, when different energy providers manage the renewable and non-renewable small powerhouses. To address the above mentioned problems, a framework of an optimal standalone hybrid renewable energy system is proposed, which is the first instance of techno-economic analysis performed with a dynamic validation. The best configuration of the system is firstly selected by sensitively analyzing different microgrid models in terms of electricity price, initial capital cost, operating cost, carbon dioxide (CO2) emission reduction and the net present cost (NPC). In the next stage, an operational analysis has been applied to ensure the reliability and security of the system. Further, the framework has been extended to focus on an existing hybrid renewable design for minimizing the operating time of diesel generators and increasing the battery lifetime, taking into account the uncertainty of solar Photovoltaic (PV) power. With these aims, an effective power dispatch algorithm has been developed for clustered microgrids incorporating power sharing control using Power Line Communication (PLC). A part of the developed algorithm is used to deal with the optimal scheduling control while the other actuates the dynamic demand response based PV power forecasting. The performances of the proposed approaches with the formulated Backup Injection Index (BII) have been validated using two test systems from “Long San Village in Sarawak” and “Bario, Sarawak”. The initial studies of optimal economic analysis were carried out using the Hybrid Optimization Model for Electric Renewable (HOMER), while the operational analysis utilizing the Power System Computer Aided Design (PSCAD). The hybrid energy management algorithm-based the PLC signal was developed using the MATLAB. The results show that the optimal configuration with the lowest COE and NPC can be achieved if the installed solar PV is less than 61 kW with 85 kWh of energy storage and 11 kW of hydro generation. The dynamic analysis shows that in order to reduce the voltage drop during disturbances, it is crucial to carefully install the sources in the buses with the highest load demand. The usefulness of the proposed hybrid energy management system is more obviously indicated by the low usage of backup power from battery banks and diesel generators for 24 hours. For instance, in the current operation, the hybrid system requires 814 kW backup power from diesel, whereas this value reduces to 675 kW when analytical method is used. In the proposed hybrid energy management, the backup power needed is only 176 kW. It was also found that the frequency shift keying technique is capable to transfer the switching command with a minimum delay compared with other techniques. Keywords: Rural communities in Sarawak, standalone microgrids, energy storage, techno-economic studies, operational analysis, intelligent hybrid management system, power-line communication signal

An Attempt to Update a Checklist and Some Other Aspects of Murree Hills’ Avifauna

Birds are vital component of biodiversity as they are playing a significant role in an ecosystem. Increasing human interference might have affected previously reported diversity of birds. This study was designed to collect information about birds check list data of Murree hills. Area was surveyed at different times of day and different months of season. During visits, pictures of birds were taken and identification as well as preparation of list was carried out. Comparison of new checklist with previous literature was done in order to get revised checklist of existing species

Sustainable energy planning for cost minimization of autonomous hybrid microgrid using combined multi-objective optimization algorithm

With the development of scattered energy resources in the rural areas of Sarawak (Malaysia), various operational problems due to the unplanned installation of autonomous microgrids become gradually remarkable. To address this concern, the paper proposes an optimal strategy to evaluate the performance of different hybrid microgrid configurations for the Long San Village in Sarawak. A mathematical model is presented for sizing the component of the system to meet the maximum load demand under changing weather conditions and at the lowest possible cost. The developed approach simulates different microgrid models using deterministic and stochastic optimization methods to find the exact dynamic energy price of the selected optimal configuration in the context of system uncertainties. Furthermore, the operational feasibility of the system in terms of reliability and voltage security is studied in addition to economic feasibility with a comparative analysis of the environmental impact. The results show that the optimal configuration with the lowest cost of energy and net present cost can be achieved if the installed solar PV is less than 61 kW with 85 kWh of energy storage and 11 kW of hydro generation, where such system has 55,725 (kg/year) Carbon Dioxide and 330 (kg/year) Nitrogen Oxides. The findings also indicate that the dynamic energy pricing increases to 0.71 $/kWh when the power generation from renewable resources drops to zero. Further, the dynamic analysis shows that in order to reduce the voltage drop during disturbances, it is crucial to carefully install the sources in the buses connected to high energy demand

Rescue and Rehabilitation of an Indian Rock Python (Python Molurus): First Case Study from Pakistan

Pythons are facing the threat of extinction due to human annihilation and interference in natural habitats of pythons. Indian rock python (Python molurus) has been stated as Lower Risk/Near Threatened by International Union for the Conservation of Nature (IUCN). Therefore, there is an intense need to change the perception of people and encourage them to coincide with this big snake. Current study involved the rescue and rehabilitation of an Indian rock python (P. molurus) spotted at the shrine of Baba Shah Jeevan, Rawalpindi, Pakistan. Python was grasped by skilled snake catchers and taken to the wildlife sanctuary in Balkasar Research Complex, Chakwal, Pakistan for the purpose of conservation. The python was kept in cage designed for reptiles (especially for snakes) having proper soil bed and shelter. Proper hygienic condition is maintained in the cage with climbing structures for the python and an adult chicken is feed to it every week. After rescuing, the python was force-feed, however the natural feeding behavior of constriction and killing of prey was resumed by it after few weeks. Rescue, rehabilitation and release of pythons create a coexisting environment in between pythons and human being instead of python-human conflict, ultimately decreasing the risk of population decline of large snakes

An effective power dispatch strategy for clustered micro-grids while implementing optimal energy management and power sharing control using power line communication

The mitigation of uncertainty in the availability of power generation from microgrids to enable renewable resources to be dispatched is a daunting task for the individual operators. Installing energy storage systems may reduce the impact of renewable energy intermittency. However, a peculiarity in energy management can be arisen, particularly, when different energy providers manage these resources. Hence, an intelligent utilization approach should be devised to maximize the benefits of using battery energy storage, since the cost of this system is the most expensive part. This article proposes an effective power dispatch strategy for clustered microgrids. The developed hybrid algorithm implements optimal energy management and power sharing control using binary data. The frequency-shift keying (FSK) technique has been adopted for transmitting the binary signal over the power line communication(PLC). A part of the algorithm is utilized to deal with the optimal scheduling control, whereas the other actuates the dynamic-demand-response-based photovoltaic power forecasting. The performance of the proposed approach with the formulated backup injection index has been validated using data collected from the practical network of “Bario, Sarawak.” The presented results suggest that the implementation of the proposed strategy can improve the efficiency of the overall system, causing less operating cost and fast return. It was also found that the binary signal can be transferred with less distortion through PLC networks when using the FSK technique compared to other techniques

An Effective Power Dispatch Strategy for Clustered Micro-grids while Implementing Optimal Energy Management and Power Sharing Control using Power Line Communication

The mitigation of uncertainty in the availability of power generation from micro-grids to enable renewable resources to be dispatched is a daunting task for individual operators. Installing energy storage systems may reduce the impact of renewable energy intermittency. However, a peculiarity in energy management can be arisen, particularly, when different energy providers manage these resources. Hence, an intelligent utilization approach should be devised to maximize the benefits of using battery energy storage, since the cost of this system is the most expensive part. This paper proposes an effective power dispatch strategy for clustered micro-grids. The developed hybrid algorithm implements optimal energy management and power sharing control using binary data. Frequency shift keying (FSK) technique has been adopted for transmitting the binary signal over the power line communication (PLC). A part of the algorithm is utilized to deal with the optimal scheduling control while the other actuates the dynamic demand response based Photovoltaic (PV) power forecasting. The performance of the proposed approach has been validated using data collected from the practical network of “Bario, Sarawak”. The presented results suggest that the implementation of the proposed strategy can improve the efficiency of the overall system, causing less operating cost and fast return

Smart grid mechanism for green energy management: a comprehensive review

The smart grid is not a monolithic system, but rather is a collection of several renewable energy resources and enabling technologies in which, intelligent control is an integral part of its mechanism to improve the utilization of assets. The dynamic characteristics of a smart grid upgrade the conventional system requirements using advanced control strategies to provide continuous power to the load from intermittent renewable generation. The communication networks and control systems that enable the accommodation of distributed generation are crucial technologies in monitoring, protecting, and operating the smart grid in a centralized or decentralized manner. This paper improves the earlier published review articles by exploring the evolution of smart grids in light of renewable energy penetration with associated features. Then, the review gives an overview of notable research works in the literature aimed at developing the management and control of smart energy systems. The reader is provided with an in-depth analysis of advanced cloud computing, the internet of things, and blockchain technology with real examples for the related renewable energy projects in smart cities. Furthermore, a special interest has been paid to quantify the performance of communication technologies along with the protocols through the conceptual investigation obf real cases using the optimized network engineering tools. The outcomes of the presented review can assist researchers to understand the driving mechanism of smart grid as a route to intelligently utilize renewable energy storage. It is concluded that the amalgamation of blockchain and artificial intelligence for renewable energy management is the key area where the avenue is still open for future research studies

Sustainable Energy Management Design for Bario Microgrid in Sarawak, Malaysia

The use of diesel generators as a backup to supply the load demand in Bario is costly and environmentally troublesome. On the other hand, utilizing natural resources that form islanded microgrids located in different areas can pose peculiar energy management issues, particularly, when different energy providers manage the renewable and nonrenewable small powerhouses. This paper proposes a framework focusing on the design of sustainable aggregate management system for minimizing the operating time of diesel generators, and thus, reducing the fuel cost and increasing the battery lifetime, while at the same time protecting the environment. Initially, the paper discusses the structure of the existing system. Further, an energy management approach is presented for maximizing the generated power from the available renewable resources at different hours. The presented results show that the proposed sustainable design can be an effective method for planning the development of electrification in the rural areas of Sarawak