Combination Of Renewable Energy Sources Research Articles

Techno-economic assessment of a hybrid microgrid using PSO

In Hybrid micro grid Renewable source offers a cost-effective and reliable solution for utilizing the power generation. As we are going to provide the combination of renewable energy sources with Energy storage system and diesel generator as a back-up System. For Wind and Solar energy (Wind Speed, Temperature and irradiance) were taken on annual and regional basis. Here we are going to consider four cases (Generation with respect to Load), by using Partial Swarm Optimization (PSO) technique on the basis of economic and reliability aspects to minimize the Cost of Electricity (COE) and to maximize Loss of Power Supply Probability (LPSP). Three regions are chosen for the techno-economic assessment of the Hybrid Micro grid. The performance of the hybrid micro grid considered in these three regions is assessed in two aspects economical and reliability aspects. Four Case studies are considered for the effective assessment of the micro grid performance under various circumstances. The contribution of the renewable is analyzed for a typical load Profile.

Improving Hybrid Power Supply System for Telecommunication Service Providers in Nigeria

Abstract: The aim of this research is to use a combination of renewable energy sources and conventional diesel generator to model a cost effective, alternative energy source for telecommunication base stations in Nigeria. Actually, this study uses various theoretical and mathematical modelling tools, such as, Mat lab Simulink and HOMER software. In the same way, the study references several Base Transceiver Stations (BTS) from gsm providers at select geographical locations in Rivers State. The study references BTS infrastructure in locations such as Ogoni, Port Harcourt and Emohua. These locations were selected to reflect different climatic conditions in Rivers state. Against this background, various hybrid combinations comprising at least two sources of renewable energy e.g Wind Turbine generator(WTG) and Solar Photovoltaic (SPV) were modelled. Also, Fuzzy logic optimization algorithm was used in tracking the maximum power in the SPV. A sample Diesel Generator(DG) was studied to analyze which possible combination gives optimum performance and is most cost effective. The total cost for installation and maintenance of the hybrid system was also considered. Consequently, one of the common negative effects of conventional power generation and usage, which is environmental pollution, was also highlighted during the study. In the course of this research, Homer was used to model a hybrid system in which the initial capital Cost (ICC) was N101,517,040 for 96 nos battery, 1 no 10kw WTG, 1 no hydro-turbine, 48 nos converters, labour etc. The replacement cost for component has a depreciation of 30%; while maintenance for diesel is 30% of the ICC. Eventually, the results obtained from the simulations showed that with an increase in supply from renewable energy sources the overall cost spent when compared to using a diesel generator only is cut by 50%, while the pollution effects also dropped. In fact, the cost also reduces if the renewable energy system is designed efficiently to track and harness maximum power. Furthermore, it is also evident that the location of the base station site and the availability of Renewable energy source affects the efficiency and cost of the entire system. Hence, it is recommended that any telecommunication company which intends installing a hybrid power system for its base stations must carry out detailed feasibility studies using input parameters described here; especially, as it relates to siting of base stations in rural off-grid areas. Keywords: Hybrid Power Supply System

Fault Management Architecture Based on a Digital Twin Approach

AbstractFault management of systems is a key component in mission/operation success of each system or technology. Fault management can be implemented into various different applications, power generation, industrial processing, aviation and transportation, and electrical grids with combinations of renewable energy sources. As the complexity of the overall system design increases, reliance on just pure physics-based or pure data-based modeling is shown to be deficient in the accuracy of fault management. This work shows the potential of a combination of digital twin and a fault management algorithm. The algorithm is designed to be robust, accurate, reliable, and fast; it is based on both physics and data-based model modeling. The algorithm compares physical and data-based approaches to provide the most reliable fault management solution, through a digital twin. The fault management algorithm is designed to use physics-based model validated on real/synthetic data (data-based model).

State Transitions Logical Design for Hybrid Energy Generation with Renewable Energy Sources in LNG Ship

In terms of energy generation and consumption, ships are autonomous and isolated power systems with energy requirements related to the type and kind of power demands and according to ship types: passenger ships, or commercial ships. Power supply on ships is traditionally based on engines thermal generators, which use fossil fuels, diesel, or natural gas. Due to the continuous operation of thermal generators in ships, this ends up increasing polluting gas emissions for the environment, mainly CO2. A combination of Renewable Energy Sources (RES) with traditional ship thermal engines can reduce CO2 emissions, resulting in a ‘greener’ interaction between ships and the environment. Due to the varying power needs for ship operation, considering the varying nature of load demands during long distance travels and during harbor entry, the use of RES must be evaluated. This paper presents a new control method to balance LNG ship load demands and power generation from RES, based on an accurate model and solution in real conditions. The Energy Management System (EMS) is designed and implemented in a Finite State Machine structure using the logical design of state transitions. The results prove that the reduction of consumption of fossil fuels is feasible, and, if this is combined with RES, it reduces CO2 emissions.

A Circular Approach to Upgrade Cement-based CO2 and Renewable H2: Techno-economic Analysis of SNG Production

The present work introduces a feasible, carbon-free integrated process that is based on the catalytic hydrogenation of industrially captured CO2 via green H2 towards the production of synthetic natural gas (SNG). Overall, three systems are being assessed from an economic point of view (sizing and simulation through Aspen Plus and HOMER software): a) H2 production through a combination of renewable energy sources (RES) and water electrolysis, b) cement-based CO2 capture through amines in a continuous absorption/regeneration cycle and c) CO2 catalytic hydrogenation. The basis for the process simulation and the subsequent economic analysis lies on the exploitation of 1,400 kt/y CO2 that are emitted from a typical cement industrial plant. According to this capacity, the integrated system is assessed for a yearly SNG production rate of ~500 kt/y. As was derived from the screening of different market exploitation scenarios (e.g., funding options, increase of CO2 tariffs), a sustainable and feasible solution can be achieved (based on current market values), as long as the RES-H2 system is funded by up to ~35 % or CO2 penalty costs reach levels of >140 €/t in the near future.

Renewable energy integration/techno-economic feasibility analysis, cost/benefit impact on islanded and grid-connected operations: A case study

On-grid and off-grid renewable energy sources have emerged as a more efficient way to meet large-scale urban and rural needs. The integration of renewables into the utilities/island mode as well as into the techno-economic feasibility studies determines the financial viability, technical and operational viability of the project. This study was conducted to integrate renewables and techno-economic feasibility analysis using the utility grid-connected and islanded mode to meet the demand for community and commercial loads with these strategic objectives. Three main analytical tasks have been performed, including: optimization, simulation, and sensitivity analysis. We selected four sensitivity cases and further divided each sensitivity case into four sensitivity loops, including different combinations of renewable energy sources, e.g., photovoltaics, wind turbines, battery banks, power grids, converters, and diesel generators. The following parameters were used to conduct a techno-economic feasibility analysis: capital costs, replacement costs, operating and maintenance costs, salvage costs, fuel costs, real-time commercial/community load, and climate data. The best results of sensitivity case-2 were selected for the techno-economic feasibility analysis of the remaining four sensitivity cases. The islanded mode net present and annualized sensitivity loop-1 costs in sensitivity case-2 were noted at $1381080.42 and $106832.62, respectively. Net present and annualized sensitivity loop-1 costs in sensitivity case-2 of the grid-connected utility mode were noted at $512792.1 and $39,666.71, respectively. The proposed utility grid-connected mode cost is two times lower than that of the islanded mode, so we have chosen sensitive case-2 for hourly, seasonal, and annual electrical load flow and techno-economic feasibility analysis to meet the community and commercial load demand.

Автоматизація об'єднаних систем автономного енергозабезпечення лабораторної установки

Тепер всі світові тенденції енергії прямують на використанні і комбінуванні поновлюваних джерел енергії. Поєднання декількох поновлюваних джерел енергії і залучання не поновлюваних джерел приводить до часткової незалежності. У цій роботі була протестований лабораторний пристрій для нагріву і охолодження рідини. Протягом експерименту були використані правила Карно, гідродинаміка, динамічна компресія газів і багато інших принципів. Запропоноване поєднання декількох систем замінимої енергії, зазначене у графіках, відобразило кількість джерел, необхідних для роботи експериментального врегулювання. Були зняті показники в різних термінах роботи експериментального врегулювання, для цієї мети воно було обладнане великою кількістю чутливих елементів. Досліджуваний час, температура, тиск на різних проміжках врегулювання управляється он-лайн з мобільного пристрою. Для конструкції і оцінки адекватності математичного зразкового збирання показників від сенсорів залежно від температурних індексів умови експлуатації, яка вимагає детальніших спостережень, для цього дослідження знадобилося більше ріку, залежно від часу щорічної і бажаної температури в приміщенні. Зняті показники з експериментальної частини, дозволили отримати апроксимовану інформацію для конструкції діаграм залежностей нагнітання тиску від температур. Дослідним результатом стали побудовані графічні залежності тиску від температур на трьох основних ділянках врегулювання. Отримані дані надають можливості побудувати математичну модель для послідовної модернізації врегулювання.

Application of digital twins of equipment for managing complex renewable energy

The paper describes a control system for renewable energy complexes with optimization of operating modes based on digital twins of equipment. The application of digital twins allowed us to develop a simulator that simulates the main processes occurring in the ground heat pump system. The simulator allows: to perform computer experiments to study different modes of Polygon operation; to demonstrate the physical essence of the ongoing processes to form the qualifications and skills of students in the field of non-traditional and renewable sources of electric and thermal energy. The use of digital twins also allows the implementation of a renewable energy combination management system to improve the energy efficiency of hybrid power complexes. The algorithm developed by the authors for selecting combinations of renewable energy sources to increase the energy efficiency of the complexes takes into account the current values of the operating parameters of the equipment, the forecast of energy consumption, as well as the forecast of power generation by each of the components of the complex.

Life cycle assessment of fuel cell systems for light duty vehicles, current state-of-the-art and future impacts

Electric vehicles are a key technology for achieving a significant reduction of greenhouse gas directly emitted by the fleet of light duty vehicles. In the past, the production impacts of alternative vehicle technologies have been widely assessed within the life cycle assessment framework, with large uncertainties regarding fuel cell electric vehicles (FCEVs). FCEVs allow an almost double driving range with a single charge or refill of the tank and more than ten times the fueling/charging rate compared to batteries. However, FCEVs currently suffer from two major issues, lack of widespread fueling infrastructure coverage and high production costs, compared to the well-established Li-ion batteries. Furthermore, the data used for life cycle assessments of the technology should be constantly updated, as their technological development is rapidly moving forward. In this regard, an early detection of the likely environmental impacts from this fast development is fundamental to guide the progress of the technology.In this study we perform a life cycle assessment of a fuel cell system for FCEV currently on the market. We found that the production of the tanks, the catalyst and the fuel cell auxiliaries are the components with lower environmental performance of the system, across all the investigated impact categories. Currently, the production of a fuel cell system with a net power output of 80 kW, and two storage tanks with a total capacity of 5 kg of H2, generates approximately 5 ton CO2-eq. In addition, in line with the targets set by the US Department of Energy, we performed an assessment of the prospective technological developments to identify its future impact. In the assessed prospective scenarios, we analyzed the effects of the technical improvements, and we subsequently combined them with the use of a higher share of renewable energy sources and secondary platinum. In essence, the technology shows potential reduction of the environmental footprints ranging from 25% to 70%, depending on the impact category. However, to achieve these results, the combination of renewable energy sources and a high learning rate must take place.

Size optimisation of RES-based grid connected hybrid power system using harmony search algorithm

In the present context, renewable energy sources are recognised as the best alternative of fossil fuels in order to fulfil the ever increasing demand with minimum harmful impact on environment. The combination of renewable energy sources can also be used in grid connected environment. This will help in reducing the burden of increasing demand on grid. Also, utility grid can supply deficit demand in case available generation from renewable energy sources becomes less than the demand. In the present paper, intelligent modelling of grid connected hybrid system has been carried out. Further, the total net present cost (NPC) of the considered system is optimised under the constraints of power reliability, storage limit on battery, etc. Finally, a comparative analysis has also been performed between the grid connected and standalone hybrid system based on the size and cost of components.

Machine Learning Based Energy Management Model for Smart Grid and Renewable Energy Districts

The combination of renewable energy sources and prosumer-based smart grid is a sustainable solution to cater to the problem of energy demand management. A pressing need is to develop an efficient Energy Management Model (EMM) that integrates renewable energy sources with smart grids. However, the variable scenarios and constraints make this a complex problem. Machine Learning (ML) methods can often model complex and non-linear data better than the statistical models. Therefore, developing an ML algorithm for the EMM is a suitable option as it reduces the complexity of the EMM by developing a single trained model to predict the performance parameters of EMM for multiple scenarios. However, understanding latent correlations and developing trust in highly complex ML models for designing EMM within the stochastic prosumer-based smart grid is still a challenging task. Therefore, this paper integrates ML and Gaussian Process Regression (GPR) in the EMM. At the first stage, an optimization model for Prosumer Energy Surplus (PES), Prosumer Energy Cost (PEC), and Grid Revenue (GR) is formulated to calculate base performance parameters (PES, PEC, and GR) for the training of the ML-based GPR model. In the second stage, stochasticity of renewable energy sources, load, and energy price, same as provided by the Genetic Algorithm (GA) based optimization model for PES, PEC, and GR, and base performance parameters act as input covariates to produce a GPR model that predicts PES, PEC, and GR. Seasonal variations of PES, PEC, and GR are incorporated to remove hitches from seasonal dynamics of prosumers energy generation and prosumers energy consumption. The proposed adaptive Service Level Agreement (SLA) between energy prosumers and the grid benefits both these entities. The results of the proposed model are rigorously compared with conventional optimization (GA and PSO) based EMM to prove the validity of the proposed model.

Thermo-economic and environmental analysis of integrating renewable energy sources in a district heating and cooling network

This paper presents the technical, environmental, and economic evaluation of integrating various combinations of renewable energy sources-based systems in the expansion of a district heating and cooling network of a Technology Park near Barcelona in Spain. At present, a combined heat and power plant running on fossil fuels serves the heating, cooling, and electricity demand of the Park. However, this energy demand is expected to increase substantially in the coming years. EnergyPRO software was used to model the energy demand growth till 2030. Validation of the software application was done by making a base model using real plant data from the year 2014. The software was then used to project the energy supply based on three 15-year scenarios, having different combinations of renewable energy technologies, from 2016 until 2030. Primary energy consumption, CO2 emissions, and the net present value obtained in each scenario were used to decide the best combinations of renewable energy sources. The results of the study showed that presently, biomass boilers combined with absorption chillers and supported with solar thermal cooling are the most competitive technologies in comparison to ground source heat pumps for large DHC networks. This is mainly because of the lower primary energy consumption (624,380 MWh/year in 2030 vs. 665,367 MWh/year), higher net present value (NPV) (222 million € vs. 178 million €), and lower CO2 emissions (107,753 tons/year in 2030 vs. 111,166 tons/year) obtained as a result of the simulations.

Design of wind-PV based hybrid standalone energy systems for three sites in central India

The aim of this study is to design renewable energy based hybrid standalone systems to supply two rural and one urban sites of Madhya Pradesh state in India. These locations characterize different load profiles and wind and solar resources. The wind speed data measured at these sites and solar radiation data obtained from NASA are utilized to carry out theanalyses of these systems using HOMER Pro. These systems are designed to cater for domestic electricity demand of one rural site, domestic and agricultural demand of another rural site and residential load demand of staff quarters of an urban institution. The pattern of power consumption of the loads considered for these sites is suitably modelled and different combinations of hybrid systems are simulated to identify the optimal system based on least life cycle cost. Results show that the most economically feasible system to supply the load demand of the three sites is comprised of different combinations of renewable energy sources viz. only wind, wind- solar and only solar based systems. Each design also includes diesel generator back up and battery storage to ensure reliability of power supply and a converter to maintain the energy flow between ac and dc components.

Impact of a Periodic Power Source on a RES Microgrid

The aim of this article is to highlight the impact of a periodic power source, such as a tidal turbine, on the operation and sizing of an autonomous hybrid microgrid with photovoltaic panels and storage. The technique of hill climbing (repeated local search) is used to find the optimum combination of Renewable Energy Sources (RES) and storage units with respect to the required capital cost for various load curves and weather conditions. To model the operation of the microgrid devices, analytical and phenomenological models, have been used, which take into account the specifications of actual commercial devices. Six different case studies are presented, with and without a tidal generator, which are based on six different sets of electrical consumption data corresponding to the Euripus campus of the National & Kapodistrian University of Athens (NKUA) in Psachna, Evia, Greece, and respective meteorological and tidal current data from the region. The results show that tidal energy may be used in a RES microgrid, where applicable, to satisfy the base load requirements, leading to a reduction in installed capacities of intermittent RES and storage, accompanied with cost reduction, especially in cases where a high load factor is observed or may be achieved, through demand response mechanisms. Such a hybrid microgrid configuration may be appropriate for regions where low velocity tidal and marine currents exist along with substantial solar and/or wind energy potential, such as the Mediterranean coast line and islands.

마이크로그리드에서 신재생에너지의 최적 용량 및 위치 선정

Currently, with the increasing interest in renewable energy sources (RES), their penetration in the power system is expected to increase considerably. South Korea plans to increase the proportion of renewable energy to 20% by 2029 based on the 7th basic plan for long-term electricity supply and demand. On the other hand, expanding the penetration of renewable energy sources is a new challenge for conventional power systems. Most renewable energy sources, such as photovoltaic and wind power, are intermittent, and thus difficult to control without a loss of power. In addition, the intermittent characteristics leads to an imbalance of power and load. This can be solved by combining renewable energies because the output characteristics of wind power and solar are different. A reliability assessment is an appropriate method for achieving the optimal combination of renewable energy sources. Therefore, this paper proposes the optimal sizing and location of renewable energy sources in a microgrid based on a reliability assessment. In addition, a stochastic method for LOLE (Loss of Load Expectation) is also proposed to evaluate the reliability. In this case study, optimal sizing and locations are determined by the minimum LOLE and power loss in an IEEE 34-bus system.

Optimal Operation and Bidding Strategy of a Virtual Power Plant Integrated With Energy Storage Systems and Elasticity Demand Response

As an aggregator involved in various renewable energy sources, energy storage systems, and loads, a virtual power plant (VPP) plays a key role as a prosumer. A VPP may enable itself to supply energy and ancillary services to the utility grid. This paper proposes a novel scheme for optimizing the operation and bidding strategy of VPPs. By scheduling the energy storage systems, demand response, and renewable energy sources, VPPs can join bidding markets to achieve maximum benefits. The potential uncertainties caused by renewable energy sources and the demand response are considered in a robust optimization model. Moreover, the robust VPP optimization accounts for its influence on markets to ensure optimal energy and reserve capacity bidding transactions in the day-ahead market and deals balancing in the real-time market. To demonstrate the performance of the proposed scheme, markets comprising various participants and managed by the system operator are implemented using mathematical models. The proposed method is evaluated using an illustrative system and the practical Taiwan power (Taipower) system with diverse uncertainty levels. The numerical results demonstrate the promising performance and the efficiency of the proposed method. The results also verify the effectiveness of the proposed method VPP with various combinations of renewable energy sources, energy storage systems, and loads.

Optimization and economic assessment of renewable energy sources and their combinations for Central Europe

The article deals with the economic evaluation of investment and optimization of the renewable energy sources for family houses. For example, from the point of view of solar systems, the optimal solution is based on the specific application of it. The design is dependent on the location of the panels and ration between active aperture area and real daytime consumption. Common calculations according to actual standards often give overstated results, which also reflected in the value of the investments. The article shows the research of optimal parameters of the thermal solar system for preparing of domestic hot water. A combination of related standards and software TRNSYS are used to find optimal parameters. Thanks to created and verified simulation models, it is possible to design parameters so as to avoid under-dimensioning or over-dimensioning of the each system. Energy price is another factor affects the payback period of investments. This is affected by the used energy sources and their combination. For example, buildings that use electricity to heat water or heating have different energy charges than a building that uses natural gas. So, the aim is to find optimal solution of the combination of renewable energy sources.

Designing a Model for the Global Energy System—GENeSYS-MOD: An Application of the Open-Source Energy Modeling System (OSeMOSYS)

This paper develops a path for the global energy system up to 2050, presenting a new application of the open-source energy modeling system (OSeMOSYS) to the community. It allows quite disaggregate energy and emission analysis: Global Energy System Model (GENeSYS-MOD) uses a system of linear equations of the energy system to search for lowest-cost solutions for a secure energy supply, given externally defined constraints, mainly in terms of CO2-emissions. The general algebraic modeling system (GAMS) version of OSeMOSYS is updated to the newest version and, in addition, extended and enhanced to include e.g., a modal split for transport, an improved trading system, and changes to storages. The model can be scaled from small-scale applications, e.g., a company, to cover the global energy system. The paper also includes an application of GENeSYS-MOD to analyze decarbonization scenarios at the global level, broken down into 10 regions. Its main focus is on interdependencies between traditionally segregated sectors: electricity, transportation, and heating; which are all included in the model. Model calculations suggests that in order to achieve the 1.5–2 °C target, a combination of renewable energy sources provides the lowest-cost solution, solar photovoltaic being the dominant source. Average costs of electricity generation in 2050 are about 4 €cents/kWh (excluding infrastructure and transportation costs).

Selection of Appropriate Combination of Renewable Energy Sources for Electricity Conservation by using Analytical Hierarchy Process

Selection of Appropriate Combination of Renewable Energy Sources for Electricity Conservation by using Analytical Hierarchy Process

Designing a Global Energy System Based on 100% Rwables for 2050: GENeSYS-MOD: An Application of the Open-Source Energy Modelling System (OSeMOSYS)

This paper develops a path for the global energy system up to 2050, presenting a new application of the open source energy systems model OSeMOSYS to the community. It allows quite disaggregate energy and emission analysis: GENeSYS-MOD (Global Energy System Model) uses a system of linear equations of the energy system to search for lowestcost solutions for a secure energy supply, given externally defined constraints, mainly in terms of CO2-emissions. The General Algebraic Modeling System (GAMS) version of OSeMOSYS is updated to the newest version and, in addition, extended and enhanced to include e.g. a modal split for transport, an improved trading system, and changes to storages. The model can be scaled from small-scale applications, e.g. a company, to cover the global energy system. The paper also includes an application of GENeSYS-MOD to analyze decarbonization scenarios at the global level, broken down into 10 regions. Its main focus is on interdependencies between traditionally segregated sectors: electricity, transportation, and heating. Model calculations suggests that in order to achieve the 1.5°-2° C target, a combination of renewable energy sources provides the lowest-cost solution, solar photovoltaic being the dominant source. Average costs of electricity generation in 2050 are about 4 €cents/kWh (excluding infrastructure and transportation costs).