Hybrid GMR Sensor Detecting 950 pT/sqrt(Hz) at 1 Hz and Room Temperature.

Advances in the magnetic sensing technology have been driven by the increasing demand for the capability of measuring ultrasensitive magnetic fields. Among other emerging applications, the detection of magnetic fields in the picotesla range is crucial for biomedical applications. In this work Picosense reports a millimeter-scale, low-power hybrid magnetoresistive-piezoelectric magnetometer with subnanotesla sensitivity at low frequency. Through an innovative noise-cancelation mechanism, the 1/f noise in the MR sensors is surpassed by the mechanical modulation of the external magnetic fields in the high frequency regime. A modulation efficiency of 13% was obtained enabling a final device's sensitivity of ~950 pT/Hz1/2 at 1 Hz. This hybrid device proved to be capable of measuring biomagnetic signals generated in the heart in an unshielded environment. This result paves the way for the development of a portable, contactless, low-cost and low-power magnetocardiography device

Assessment of Optimum Renewable Energy System for the Somalia–Turkish Training and Research Hospital in Mogadishu

Somalia–Turkish Training and Research Hospital in Mogadishu, is only powered by diesel generator currently. In this paper, the energy demand of this hospital is utilized by determining the optimum hybrid renewable energy generating system. By HOMER, a sensitivity analysis has been made with emphasis on three significant variables such as average wind speed, present diesel price, and solar radiation. From the results, it can be said that an optimum system is the standalone wind-diesel-battery storage Hybrid Renewable Energy System (HRES) with the configuration of 1,000 kW wind turbine, 350 kW diesel generator, 250 kW power converters, and 300 batteries. Additionally, the net present cost of the optimum system is calculated to be $5,056,700 and its cost of energy is estimated to be 0.191$/kWh. The present cost of energy for Somalia is 0.5 $/kWh. This shows that the energy cost for the proposed HRES is cheaper than the conventional one. Lastly, according to the results, it is clear that the wind–diesel–battery storage HRES seems more environment friendly than other HRESs

Optimization of energy storages in microgrid for power generation uncertainties

Microgrid is a cluster of distributed generation units, energy storages, and loads which can operate grid-connected and islanded. This research focuses on selecting an economic standalone supply system for small and remote off-grid towns in Western Australia. Existing power systems of such towns have adverse environmental impacts due to the utilization of diesel and gas. The suitable electricity supply system is a hybrid system composed of generators, renewables, and energy storages

A Feasibility Study of A Zero Energy Building in Egypt

Abstract— According to studies, buildings use around 40% of the total energy consumption in the world. Most of this consumed energy comes from fossil fuel, one of the sources of environmental pollution. The Net Zero Energy Building (NZEB) is an alternative to this alarming pollution. With its reduced energy needs and renewable energy systems, a ZEB can return as much energy as it takes from the utility on an annual basis. Thus the main objective of this study is to discuss the economical and friendly environmental renewable energy system integrated to building in Egypt to be (NZEB) economical by maximizing the renewable energy fraction and minimizing the greenhouse gases (GHG) emissions. The system consists of two renewable energy sources, comprising photovoltaic system, a wind turbine are considered for the proposed building under the study. By Utilizing the well-known Hybrid Optimization of Multiple Electric Renewables software to get the optimal configuration of a hybrid renewable energy system, based on the user inputs of loads, costs, technical details, solar and wind resources availability

Energy Management of Grid-Connected Microgrids, Incorporating Battery Energy Storage and CHP Systems Using Mixed Integer Linear Programming

In this thesis, an energy management system (EMS) is proposed for use with battery energy storage systems (BESS) in solar photovoltaic-based (PV-BESS) grid-connected microgrids and combined heat and power (CHP) applications. As a result, the battery's charge/discharge power is optimised so that the overall cost of energy consumed is minimised, considering the variation in grid tariff, renewable power generation and load demand. The system is modelled as an economic load dispatch optimisation problem over a 24-hour time horizon and solved using mixed integer linear programming (MILP) for the grid-connected Microgrid and the CHP application. However, this formulation requires information about the predicted renewable energy power generation and load demand over the next 24 hours. Therefore, a long short-term memory (LSTM) neural network is proposed to achieve this. The receding horizon (RH) strategy is suggested to reduce the impact of prediction error and enable real-time implementation of the energy management system (EMS) that benefits from using actual generation and demand data in real-time. At each time-step, the LSTM predicts the generation and load data for the next 24 h. The dispatch problem is then solved, and the real-time battery charging or discharging command for only the first hour is applied. Real data are then used to update the LSTM input, and the process is repeated. Simulation results using the Ushant Island as a case study show that the proposed online optimisation strategy outperforms the offline optimisation strategy (with no RH), reducing the operating cost by 6.12%. The analyses of the impact of different times of use (TOU) and standard tariff in the energy management of grid-connected microgrids as it relates to the charge/discharge cycle of the BESS and the optimal operating cost of the Microgrid using the LSTM-MILP-RH approach is evaluated. Four tariffs UK tariff schemes are considered: (1) Residential TOU tariff (RTOU), (2) Economy seven tariff (E7T), (3) Economy ten tariff (E10T), and (4) Standard tariff (STD). It was found that the RTOU tariff scheme gives the lowest operating cost, followed by the E10T tariff scheme with savings of 63.5% and 55.5%, respectively, compared to the grid-only operation. However, the RTOU and E10 tariff scheme is mainly used for residential applications with the duck curve load demand structure. For community grid-connected microgrid applications except for residential-only communities, the E7T and STD, with 54.2% and 39.9%, respectively, are the most likely options offered by energy suppliers. The use of combined heat and power (CHP) systems has recently increased due to their high combined efficiency and low emissions. Using CHP systems in behind-the-meter applications, however, can introduce some challenges. Firstly, the CHP system must operate in load-following mode to prevent power export to the grid. Secondly, if the load drops below a predefined threshold, the engine will operate at a lower temperature and hence lower efficiency, as the fuel is only half-burnt, creating significant emissions. The aforementioned issues may be solved by combining CHP with a battery energy storage system. However, the dispatch of CHP and BESS must be optimised. Offline optimisation methods based on load prediction will not prevent power export to the grid due to prediction errors. Therefore, a real-time EMS using a combination of LSTM neural networks, MILP, and RH control strategy is proposed. Simulation results show that the proposed method can prevent power export to the grid and reduce the operational cost by 8.75% compared to the offline method. The finding shows that the BESS is a valuable asset for sustainable energy transition. However, they must be operated safely to guarantee operational cost reduction and longer life for the BESS

Performance Analysis of a VPV/FC Hybrid System for Generating Electricity in Iraq's Remote Areas

A reliable electrical energy supply is a prerequisite for improving the standard economic and quality of life levels in a country. As is the case in many countries, Iraq is home to a collection of remote villages. Since it is uneconomical to connect these villages to the existing grid, the installation of stand-alone electrical power generators has become common practice. As a result, diesel stand-alone power generators see widespread use in these remote locales, which, whilst fit for their intended purpose, unfortunately suffer from several drawbacks, including instability in regards to everyday oil prices and a number of environmental issues. The implementation of a PV/FC hybrid power system could be one potential alternative to help solve these problems. Therefore, this paper will present PV/FC system control strategies alongside information relating to the performance of such system components, based on a case study that was conducted in Al-Gowair, Iraq. This study is especially important in terms of envisioning the future energy supply needs of Iraq. The HOMER simulation results showed that by using the proposed control strategies and suggested components of a PV/FC system, it was able to produce a satisfactory outcome

Techno-economic optimization and environmental life cycle assessment of microgrids using genetic algorithm and artificial neural networks

This dissertation focuses primarily on techno-economic optimization and environmental life cycle assessment (LCA) of sustainable energy generation technologies. This work is divided into five papers. The first paper discusses the techno-economic optimization and environmental life cycle assessment of microgrids located in the USA using genetic algorithm. In this paper, a methodology was developed that assessed the techno-economic and environmental performance of a small scale microgrid located in US cities of Tucson, Lubbock and Dickinson. Providing uninterrupted power the microgrid was composed of seven components -- solar photovoltaics, wind-turbines, lead acid batteries, biodiesel generators, fuel cells, electrolyzers and H2 tanks. The second paper is an extension of first paper and utilizes Artificial Neural Networks to predict energy demand while also incorporating social costs. With an aim to incorporate LCA methodology, the third paper discusses the upstream biodiesel production process which is a vital fuel source for the microgrid. In this paper, a supercritical biodiesel production process from waste cooking oil (WCO) using methanol in the presence of propane as a co-solvent was technically analyzed using Aspen Plus software. In the fourth paper, a system dynamics model of the cast iron foundry process was developed and validated with the actual energy consumption data based on which recommendations were made to reduce energy consumption by 26% or $2.6 million. In the fifth paper, an assessment of the threats to the aquatic resources due to rapid growth in the extraction of Shale gas in the US was performed with an application to the Kurdistan region of Iraq --Abstract, page iv

Environmental Impact Assessment of Power Generation Systems at GSM (Global Systems for Mobile Communication) Base Station Site

Hybrid power systems were used to minimize the environmental impact of power generation at GSM (global systems for mobile communication) base station sites. This paper presents the comparative environmental impact assessment of a diesel gas (DG) and hybrid (PV/wind/hydro/diesel) power system for the base station sites. The assessment was based on theoretical modeling of the power stations using Hybrid Optimization Model for Electric Renewables (HOMER) software. The model was designed to provide an optimal system configuration based on hour-by-hour data for energy availability and demands. Energy source, energy storage and their applicability in terms of performance are discussed. The proposed hybrid (solar, wind & hydro) + DG system was simulated using the model which results in eight different topologies: hybrid (solar, wind & hydro) + DG, hybrid (solar & hydro) + DG, hybrid (wind & hydro) + DG, hydro only + DG, hybrid (solar & wind) + DG, solar only + DG, wind only + DG, DG. From the simulation results, it is shown that a 69% renewable energy penetration in the designed hybrid PV/wind/hydro/diesel system reduces the quantity of different air pollutants relative to the case of a diesel-only system. Details of the comparisons are presented

Design and simulation of a building-based off-grid photovoltaic microgrid using PVsyst: A case study

In the absence of a main or central grid, an off-grid renewable energy-based system could be a viable solution to address the electricity demand of a particular region by utilizing the available renewable energy sources (RES) of that area. This also leads society to a step toward sustainable energy development. A planned RES-integrated microgrid system not only fulfills the energy crisis and reduces electricity costs but also plays a significant role in the conservation of fossil fuels. Therefore, the design and simulation of RES integrated systems are indispensable as this type of analysis determines the vital parameters of the system e.g., the system performances including electricity output, energy conversion efficiency, yearly energy potential, and the system losses before being involved in practical implementation. Further, the cell temperature of the Photovoltaic (PV) panel based on regional weather conditions, the system life cycle based on the uncertainty factor of weather, total system installation cost with a full account of the annual savings and payback etc. can also be determined by designing and simulating such systems. This paper presents a design of a 40 kW off-grid photovoltaic (PV) microgrid system according to the load requirements at the Department of Electronics and Communication Engineering (ECE), Tezpur University, India using PVsyst software. The proposed design has been created to meet the daily peak load demand of 37 kW of the department. The energy available through the generating units of the proposed designed PV system is 45.46 MWh/Year and the system performance ratio in terms of efficiency over the year is 0.814. The overall performance analysis and simulation results would be helpful in determining the efficiency and viability of the proposed PV system while implementing it practically in the near future