Grid Interaction Performance Evaluation of BIPV and Analysis with Energy Storage On Distributed Network Power Management

This research focuses on analysis of photovoltaic (PV) based active generator in microgrid and its utilization in not only for operational planning of the power system but also for instantaneous power flow management in the smart grid environment. The application of this system is part of a solution on handling a large scale deployment of grid connected distributed generators, especially PV system. By implementing the PV based active generator, it will be very flexible able to manage the power delivery from the active generator sources (e.g. PV system, energy storage technologies, active power conditioning devices). In Southern Norway, a smart village Skarpnes is developed for ZEBs. These ZEBs have Building Integrated Photovoltaic (BIPV) system. The energy efficient housing development should consider that a building should produce the same amount of electrical energy as its annual requirements (i.e. ZEB). In future, ZEBs are going to play a significant role in the upcoming smart grid development due to their contribution on the on-site electrical generation, energy storage, demand side management etc. In this work the main objective is to evaluate the usefulness of ZEBs for load matching with BIPV generation profiles and grid interaction analysis. Impact of BIPV system has been investigated on the distributed network power flow as well as on protection and protective relays analysis. Furthermore, techno-economic analysis of BIPV system is presented which will be useful to the utility for developing new business models as well as demand side management (DSM) strategies and for decentralized energy storage. The real operational results of a year are analyzed for annual energy balance with on-site BIPV generation and local load. This work provides quantitative analysis of various grid interaction parameters suitable to describe energy performance of the BIPV. The load matching and grid interaction parameters are calculated for a house to find relationship of BIPV generation and building load. The loss of load probability is analyzed for fulfilling the local load at desired reliability level. Results of this work are going to be useful for developing DSM strategies and energy storage as well as import/export energy to the grid. This work will be beneficial for future planning of the distributed network when the BIPV penetrations are going to increase

Grid Interaction Performance Evaluation of BIPV and Analysis with Energy Storage on Distributed Network Power Management

Doktorgradsavhandling ved Universitetet i Agder, Institutt for informasjons- og kommunikasjonsteknologi, 2017This research focuses on analysis of photovoltaic (PV) based active generator in microgrid and its utilization in not only for operational planning of the power system but also for instantaneous power flow management in the smart grid environment. The application of this system is part of a solution on handling a large scale deployment of grid connected distributed generators, especially PV system. By implementing the PV based active generator, it will be very flexible able to manage the power delivery from the active generator sources (e.g. PV system, energy storage technologies, active power conditioning devices). In Southern Norway, a smart village Skarpnes is developed for ZEBs. These ZEBs have Building Integrated Photovoltaic (BIPV) system. The energy efficient housing development should consider that a building should produce the same amount of electrical energy as its annual requirements (i.e. ZEB). In future, ZEBs are going to play a significant role in the upcoming smart grid development due to their contribution on the on-site electrical generation, energy storage, demand side management etc. In this work the main objective is to evaluate the usefulness of ZEBs for load matching with BIPV generation profiles and grid interaction analysis. Impact of BIPV system has been investigated on the distributed network power flow as well as on protection and protective relays analysis. Furthermore, techno-economic analysis of BIPV system is presented which will be useful to the utility for developing new business models as well as demand side management (DSM) strategies and for decentralized energy storage. The real operational results of a year are analyzed for annual energy balance with on-site BIPV generation and local load. This work provides quantitative analysis of various grid interaction parameters suitable to describe energy performance of the BIPV. The load matching and grid interaction parameters are calculated for a house to find relationship of BIPV generation and building load. The loss of load probability is analyzed for fulfilling the local load at desired reliability level. Results of this work are going to be useful for developing DSM strategies and energy storage as well as import/export energy to the grid. This work will be beneficial for future planning of the distributed network when the BIPV penetrations are going to increase

Analysis Of An Energy Storage Sizing For Grid-Connected Photovoltaic System

This paper present on the analysis of an energy storage sizing for a small grid-connected PV system. This project is to study the proper sizing of energy storage (battery) in a grid-connected PV system for consumers whom purchase and sell electricity from and to the utility grid. The goal is to minimize the total cost of the operation for a consumer with a PV system with a battery storage system. This is to make sure that minimizing the total annual operating cost while maintaining an efficient system. This study uses typical consumer load consumption, and solar irradiance data throughout a year, while varying the type of battery storage (study lead acid and Lithium ion battery) as an energy storage for a similar system. Since lithium ion is not the main options to be integrated with PV system, this study will then reveal the data in terms of cost on why it is not a popular choic

Output Power Forecasting for 2kW Monocrystalline PV System using Response Surface Methodology

 Photovoltaic (PV) system is a renewable energy source that not only able to reduce the effect of greenhouse gas towards the environment, but also a highly profitable industry nowadays. To determine the Return of Investment (ROI) of a newly installed system, forecasting is crucial. Thus, the purpose of this study is to produce a prediction model for the yearly output power of the PV system using three environmental elements; irradiance, module temperature and ambient temperature by Response Surface Methodology (RSM). To do so, MATLAB RStool which is consisting of four models; multiple linear regression (MLR), interaction, pure quadratic, and full quadratic is used. The 5 minute sampling size of yearly 2014 weather station data the three environmental elements and output power of a 2kW Monocrystalline real PV system are used for training. Whereas, yearly 2015 data of the aforementioned elements are used for validation. The coefficient of determination (R2) method and root mean square error (RMSE) approach were used to determine the most accurate prediction model. Results show that, full quadratic is the most accurate prediction model with R2 value of 0.9995 and RMSE of 8%. It is hoped that the prediction model introduced can be a viable method to be used by the PV system installer.

Frequency Control Reserve With Multiple Micro Grid Participation For Power System Frequency Stability

The introduction of this micro grids into the conventional distribution network system forces a new challenge to the system operation. The failure factor of the power system performance essentially due to the limitation of electrical power generation in which could not meet the load demand. In order to maintain the frequency stability of the system, the power sources must be matched instantaneously among all generators and constantly supply to the load demand. A deviation of system frequency from the set-point value will affect the entire stability of power system network. This paper investigates the impact of utilizing multiple micro grids in supporting and facilitating on grid’s frequency. A method called Frequency Control Reserve (FCR) is introduced, with intention to share the excessive power from all available micro grids. These power will be controlled effectively before being injected into the main grid to stabilize the power frequency. Simulation using MATLAB Simulink have been used to simulate the result and shows great potential to be integrated with distributed generation i.e. solar photovoltaic (PV) for Malaysia power system vicinit

Output Power Forecasting For 2kW Monocrystalline PV System Using Response Surface Methodology

Photovoltaic (PV) system is a renewable energy source that not only able to reduce the effect of greenhouse gas towards the environment, but also a highly profitable industry nowadays. To determine the Return of Investment (ROI) of a newly installed system, forecasting is crucial. Thus, the purpose of this study is to produce a prediction model for the yearly output power of the PV system using three environmental elements; irradiance, back module temperature and ambient temperature by Response Surface Methodology (RSM). To do so, MATLAB RStool which is consisting of four models; multiple linear regression (MLR), interaction, pure quadratic, and full quadratic were used. The 5 minute sampling size of year 2014 weather station data of the three environmental elements and output power of a 2kW Monocrystalline real PV system were used for training. Whereas, year 2015 data of the aforementioned elements were used for validation. The coefficient of determination (R2) method and root mean square error (RMSE) approach were used to determine the most accurate prediction model. Results shown that, full quadratic is the most accurate prediction model with R2 value of 0.9995 and RMSE of 8%. It is hoped that the prediction model introduced can be a viable method to be used by the PV system installer

Grid Interaction Performance Evaluation of BIPV and Analysis with Energy Storage on Distributed Network Power Management

This research focuses on analysis of photovoltaic (PV) based active generator in microgrid and its utilization in not only for operational planning of the power system but also for instantaneous power flow management in the smart grid environment. The application of this system is part of a solution on handling a large scale deployment of grid connected distributed generators, especially PV system. By implementing the PV based active generator, it will be very flexible able to manage the power delivery from the active generator sources (e.g. PV system, energy storage technologies, active power conditioning devices). In Southern Norway, a smart village Skarpnes is developed for ZEBs. These ZEBs have Building Integrated Photovoltaic (BIPV) system. The energy efficient housing development should consider that a building should produce the same amount of electrical energy as its annual requirements (i.e. ZEB). In future, ZEBs are going to play a significant role in the upcoming smart grid development due to their contribution on the on-site electrical generation, energy storage, demand side management etc. In this work the main objective is to evaluate the usefulness of ZEBs for load matching with BIPV generation profiles and grid interaction analysis. Impact of BIPV system has been investigated on the distributed network power flow as well as on protection and protective relays analysis. Furthermore, techno-economic analysis of BIPV system is presented which will be useful to the utility for developing new business models as well as demand side management (DSM) strategies and for decentralized energy storage. The real operational results of a year are analyzed for annual energy balance with on-site BIPV generation and local load. This work provides quantitative analysis of various grid interaction parameters suitable to describe energy performance of the BIPV. The load matching and grid interaction parameters are calculated for a house to find relationship of BIPV generation and building load. The loss of load probability is analyzed for fulfilling the local load at desired reliability level. Results of this work are going to be useful for developing DSM strategies and energy storage as well as import/export energy to the grid. This work will be beneficial for future planning of the distributed network when the BIPV penetrations are going to increase

Optimal Selection Of Renewable Energy Installation Site In Remote Areas Using Segmentation And Regional Technique: A Case Study Of Sarawak, Malaysia

Electricity access in many remote areas in Sarawak, Malaysia is very little due to some limitations including the complicated geographical factors and high costs. In fact, there are about 1623 locations in Sarawak without electricity, whereas 420 locations (small settlements) can be only electrified using isolated renewable energy microgrid. However, it is impossible to install individual systems for each location. Thus, the optimal clustering of these locations and the selection of sites that are located in the centers of these clusters is necessary. Therefore, in this research, image segmentation and regional technique are used to analyze the map of remote electrification in Sarawak. The image segmentation which includes color thresholding, circular hough transform, and K-means technique is used in this research to identify the optimal installation site. HOMER software is then used to optimize the proposed renewable energy systems. Results show that nine locations out of 420 locations are optimum locations for the installation of renewable power systems. These nine locations are the centers of the obtained nine clusters of communities and small villages. Finally, it is found that most of the recommended combinations are hybrid renewable energy systems, where photovoltaic and hydropower systems combination is found the best hybrid system for the rural areas in Sarawak

I-Sajadah Prayer Rug With Smart Raka’ah Notification Device

Perform five times of solah per day is an obligation for all Muslims. Each of the five solah has different raka’ah. While performing the solah, there is possibility to forget how many raka’ah have been completed especially in performing four raka’ah solah which are Zuhr, Asr and Isya’. This difficulty of remembering the raka’ah sequences could happen to inexperienced children, the elderly and those having cognitive and memory weakness. This situation may affect the concentration while performing solah. Therefore i-Sajadah is proposed as a smart device to notify the user on exact raka’ah that has been completed. This device consists of sensory component, processor and indicator system. As a result, the innovation of i-Sajadah presents high potential solution as a user-friendly device to help Muslims to mastery the daily raka’ah sequences thus improves the concentration and quality of solah