Types Of Renewable Energy Systems Research Articles

A Comparative Study of Data Mining Methods for Solar Radiation and Temperature Forecasting Models

Photovoltaic (PV) energy systems are a leading type of renewable energy systems globally. Predicting PV energy production accurately is crucial for maintaining efficient energy grids, making informed decisions in the energy market, and reducing maintenance costs. To ensure high accuracy and optimal production, it is essential to monitor and analyze these variables regularly. Solar radiation and temperature are two meteorological variables that directly affect the quantity of PV energy generated in PV facilities. The Performance Ratio (PR) is a critical parameter for assessing PV plant performance. A comprehensive model was constructed in this study to forecast solar radiation and temperature using multiple machine learning methods, including Instance-Based K-Nearest Neighbor Algorithm (IBK), Linear Regression, Random Forests, Random Tree, Multilayer Perceptron (MLP), and MLP Regression. Moreover, we used time series approaches, such as Simple Exponential Smoothing (SES), Error-Trend-Seasonality (ETS), Autoregressive Integrated Moving Average (ARIMA) and Holt Winter's Seasonal Method (HWES) models for PV systems prediction. Initially, we conducted daily forecasts as well as 1-step ahead forecasts at 5-minute intervals for both solar radiation and temperature. It is crucial to subject both variables to the same methodology in order to construct precise models for forecasting PV. Secondly, we compared the predicted values of solar radiation and temperature with the actual energy yield of the power plant to calculate energy production. Subsequently, a relative analysis of data mining models and time series models have been performed depending on the statistical error criteria like RMSE, MAPE, MABE, MAE, MSE, and direction accuracy (DAC). 

Advanced Rapid Predictive and Modulation Model for PV System

In the real-time case of the power management system, renewable energy improves power generation to reduce demand. Since this type of renewable energy system is not sufficient to generate power to the load with controlled energy in grid systems and other related high-power applications. The existing models refer to the static parameters to control the regulation factor of the DC converter. This leads to a delay in step response and the other related features which will affect the output power with noise and surge peaks. In this work, a novel model of the optimal controlling model was proposed to improve the switching activities of the converter circuit. In this, the DC–DC converter design needs to enhance for reducing the noise at converted DC output. The controller tunes gain the parameters according to the feedback signal dynamically to reduce the step response time. For this process, a rapid model predictive and modulation-based controller with maximum power point tracking analyzer are used to estimate operating point of the PV system and control the switching devices accordingly. This improves the high-frequency switching activities to reduce the noise level in DC output. This can also reduce the noise at DC output. The inverter was connected at the output terminal of DC–DC converter for the AC load components. The space vector pulse width modulation technique was used for driving the inverter switches to reduce the total harmonic distortion from the output waveform to the load terminal. The simulation result and the experimental result show the performance of the proposed controller comparing with traditional controlling models.

Problems and Opportunities for Cost-Effective Photovoltaic Systems for Private Use

The climate changes, rising world tensions, soaring energy prices and fossil fuel dependencies require an affordable green power solution to be found and applied. The PV systems seem to be such solution, but there are still many obstacles standing on their way, especially in Bulgaria. An analysis concerning the cost-effectiveness of PV systems is done. The results are that they are cost-effective for companies, but not so much for private users yet. There are already breakthroughs in battery technology that are expected to open wide the doors for many types of renewable energy systems. The Bulgarian regulation process is one of the main obstacles standing on the way of PV systems.

Environmental Impact of Ground Source Heat Pump Systems: A Comparative Investigation From South to North Europe

Ground Heat Exchangers (GHEs), buried in the ground either horizontally or vertically (in a borehole), are coupled with a heat pump to form a Ground Source Heat Pump (GSHP) system, which is a type of Renewable Energy System that exploits geothermal energy for space heating and cooling. GSHP systems are proposed as an alternative to conventional Air Source Heat Pumps (ASHPs) as they exhibit a higher efficiency. In this study, this difference in efficiency is tested in order to determine how the systems perform in terms of environmental impact. Three types of GSHP systems (with different GHE configuration), each compared to ASHPs, undergo a Life Cycle Analysis using the ReCiPe method from both mid-point and end-point perspectives. The heating and cooling loads required for a single residential building of area 220 m2, with nearly Zero Energy Building technical characteristics, is used as a Functional Unit, for seven cases (locations/countries) from South to North Europe. Additionally, a Simple Payback Period method is employed to investigate the CO2 payback time for the GSHPs. It is concluded that the use of GSHP systems in residential buildings, even with nZEB (nearly Zero Energy Buildings) characteristics of low heating/cooling demand, can be a more environmentally friendly solution than that of an ASHP system, depending on the factors affecting the system, namely the ground thermal characteristics, the heating/cooling demand, the heating/cooling peak loads and electricity mix.

Control of the Hybrid Renewable Energy System with Wind Turbine, Photovoltaic Panels and Battery Energy Storage

The aim of the paper is the study of the Hybrid Renewable Energy System, which is consisted of two types of renewable energy systems (wind and sun) and is combined with storage energy system (battery). The paper presents the classification and review of architectures of Hybrid Renewable Energy Systems. The considered Hybrid Renewable Energy System was designed as a multi-converter system with gearless Wind Turbine driven Permanent Magnet Synchronous Generator and with a Photovoltaic Array and Battery Energy System. The mathematical models of individual elements of a complex Hybrid Renewable Energy System were described. In the control of both systems of Wind Turbine with Permanent Magnet Synchronous Generator and Photovoltaic array, the algorithms of Maximum Power Point Tracking have been implemented for higher efficiency of energy conversion. The energy storage in the battery has been managed by the control system of a bidirectional DC/DC converter. For the control of the Machine Side Converter and Wind Turbine with Permanent Magnet Synchronous Generator, the vector control method has been implemented. In the control system of the Grid Side Converter, the advanced method of Direct Power Control has been applied. The energy management strategies for optimal flows of electrical energy between individual systems of considered hybrid renewable energy system are developed and described. In order to determine the operation of proposed control systems, the simulation studies have been performed for different conditions of operation of individual elements of the complex hybrid system. The considered control methods and energy management strategies were tested thorough simulation studies for different wind speed variations, different sun irradiations, and different local load demands. The performed simulations are of practical importance in terms of proper operation requirements, design selection of components and energy management of Hybrid Renewable Energy Systems.

Reliability assessment of power systems considering renewable energy sources

Various types of renewable energy systems can make vulnerable the reliability of the system because of initiating noteworthy degrees of uncertainty and availability despite of their good effects on the system operation cost and global concerns. The difficulty can be removed with using special renewable energy sources with have complimentary in natures. This paper presents the reliability assessment of wind and solar energy based power system at different levels. The optimization problem is to increase the reliability of the system with both solar and wind energy systems. First, the system is developed by taking the effect of uncertain nature of wind and solar energy sources, the probability of the top event and failure rate of different components. The model predictive method is used to take the different future value of the daily data. For this investigation, total 11 cases are taken and reliability indices are considered for every case. Data of each basic event of solar-wind energy system components are taken from the old research. Further, the gamma model is used to obtain the system model and different reliability indices are evaluated. The top event probability for case 1, case 2, case 3, case 4, case 5, case 6, case 7, case 8, case 9, case 10 are 0.0234, 0.0245, 0.0256, 0.0263, 0.0267, 0.0268, 0.273, 0.0278, 0.0286 and 0.0288 respectively. The helpfulness of the proposed technique is provided through different evaluation data.

IDENTIFYING THE BEST DECENTRALIZED RENEWABLE ENERGY SYSTEM FOR RURAL ELECTRIFICATION IN NEPAL

Access to electricity is generally recognized as an important factor for economic and social development. Moreover, the world energy consumption depends on the use of limited resources like fossil fuels that induce adverse impact on the environment and society. As an alternative, renewable energies turn into crucial alternative energy ensuring sustainable energy needs and taking care of society, economy and the environment. In order to combat such issues, the United Nations has declared universal access to affordable, reliable and modern energy for by 2030. In many cases, different types of renewable energy systems are being developed to serve energy need without considering the best alternative. Thus, this paper tries to prioritize the installed Decentralized Renewable Energy (DRE) systems for rural electrification in Nepal by analyzing nineteen sustainability indicators related to four sustainability dimensions - technical, social, economic and environmental. An Analytical Hierarchy Process-Online Software (AHP-OS) model is used for ranking various DRE systems. Suitable goals, criteria, sub-criteria, and alternatives are developed after reviewing pertinent literature and consultation of the experts. The results reveal that micro-hydropower is the best electrification option followed by the solar home system, solar mini-grid, and wind-solar hybrid for decentralized electrification in Nepal. Biomass is found to be the least prioritized alternative in Nepal. The outcome of the research can help the policy-makers and decision-makers in shaping energy policies, plans, and programs, and foster sustainable energy development in the country. Similarly, the relevant stakeholders will be benefited by improving their products and services in the future.

Deep Belief Network with Seasonal Decomposition for Solar Power Output Forecasting

Solar power is a type of renewable energy system that uses solar energy to produce electricity, and is regarded as one of the most important power sources in Taiwan. Since sunshine duration affects the amount of energy that can be generated by a solar power, the seasons of the year are important factors that should be considered for accurate solar power prediction. In the last decade, the use of artificial intelligence for forecasting systems have been quite popular, and the deep belief network (DBN) models started getting more attention. In this study, a seasonal deep belief network (SDBN) was developed to forecast monthly solar power output data. The SDBN was constructed by combining seasonal decomposition method and DBN. Further, this study used monthly solar power output data from the Taiwan Power Company. The results indicated that the proposed forecasting system demonstrated a superior performance in terms of forecasting accuracy. Also, the performance of autoregressive integrated moving average (ARIMA), generalized regression neural network (GRNN), and DBN obtained from a separate study were compared to the performance of the proposed SDBN model and showed that the latter was better than the other three models. Thus, the SDBN model can be used as an alternative method for monthly solar power output data forecasting.

Optimal Decision-Making of Renewable Energy Systems in Buildings in the Early Design Stage

Renewable energy systems (RES) in buildings should be designed carefully, not only because of the need for an optimal design, but also to comply with related laws. Therefore, the design of RES in the buildings requires close collaboration between architects and engineers from the beginning of the design process. To support such collaboration, this study proposes a simplified design method for RES in buildings during the early design stage. By using the proposed design method, design alternatives that meet the required energy standards as suggested by law are first generated. Further designs are made to evaluate the performance and cost of the design alternatives and to find the optimal types of RES for the building. The study also uses a case study to verify the applicability of the design method to the early design stage. Although the performance and cost of the different design alternatives are similar, the implementation of each type of RES in each design alternative is different. Nonetheless, by analyzing performance patterns and the cost ratio of each type of RES in each design alternative, the study allows the most suitable type of RES to be chosen for the building.

LMI-based robust voltage tracking control for a class of renewable energy systems

ABSTRACTThis paper introduces a method of robust voltage tracking control for a class of renewable energy systems, which uses a linear matrix inequality (LMI)-based approach. A remodeling method is introduced where the nonlinear model of the renewable energy system is represented as a nonlinear combination of linear subsystems with state-dependent parameters (the so-called linear state-dependent parameter system model, LSDPM). Next, the remodeling method is applied to a boost converter, a photovoltaic (PV) system, and a wind energy conversion system as examples. A robust output voltage tracking approach is proposed based on the LSDPM. Using Lyapunov’s direct method, controller stability analyses are expressed as LMI formulations. Powerful numerical toolboxes then solve for the controller gains. The advantages of this approach include: i) the generalized remodeling technique is applicable to a wide variety of renewable energy systems; ii) it creates a unified LMI-based design framework for multiple control objectives; iii) it provides numerically solved control gains; and iv) it provides robust tracking control for the multiple objectives of renewable energy systems. Using an LMI-based robust voltage tracking controller is an accurate and effective method of control for many types of renewable energy systems. Finally, practical DSP-based experiments are carried out using the buck converter as an example. The satisfactory results of these experiments verify the theoretical derivations for this control method.

Renewable Energy Systems to Enhance Buildings Thermal Performance and Decrease Construction Costs

Renewable energy systems can be used to improve the buildings thermal performance and to design sustainable buildings. To achieve maximum thermal comfort inside the housing test modules for all weather conditions without using any form of energy from fossil fuels which could be obtained from renewable energy systems.Different modules type (Cavity Brick (CB), Insulated Cavity Brick (InsCB), Insulated Brick Veneer (InsBV) and Insulated Reverse Brick Veneer (InsRBV)) with the type of renewable energy systems is performed to determine which type could provide the greatest energy savings with the least cost. InsCB the best performing module but it cost more to build while InsBV module cost less but with lower thermal performance which can be compensated by using Photovoltaic systems (PV) to enhance the thermal performance with the least cost.

Simulated annealing-chaotic search algorithm based optimization of reverse osmosis hybrid desalination system driven by wind and solar energies

Small reverse osmosis (RO) based desalination plants driven by wind and solar energies are attractive options to meet the requirements of autonomous areas. The complexity of these systems requires proper optimization of the solar and wind energy generation with storage needs. The main contribution of this study is a design optimization method of a hybrid reverse osmosis desalination plant powered by solar and wind energy. There are many investigations based on hybrid energy systems but the investigation of a useful model and effective methods are rarely found. Here, the possibility of three autonomous hybrid arrangements, namely, solar-wind-battery-RO desalination, solar-battery-RO desalination, and wind-battery-RO desalination, are investigated. Integer and continuous variables in the optimization model of the hybrid schemes for an autonomous region of Iran are considered. The main optimization function of minimizing the life cycle cost is used to evaluate different types of renewable energy systems for powering reverse osmosis desalination. Also, the probability of power interruption is used to measure the reliability of the hybrid schemes. For this aim, a new hybrid search algorithm is developed for simulating annealing and chaotic system. The results are compared with those from original chaotic search and simulated annealing algorithms. The simulation results show that the relative error in the hybrid scheme between the best performances of the hybrid search algorithm and the simulated annealing algorithm is 47.75%, and 4.08% for the hybrid search algorithm and chaotic search algorithm. In overall terms, the results demonstrate that the hybrid search algorithm provided the best performance between the original simulated annealing and the chaotic search algorithm. Additionally, the hybrid renewable energy system decreases system cost and increases system reliability for increasing fresh water availability and meeting the electricity load demands.

Dynamic response and power production of a floating integrated wind, wave and tidal energy system

Abstract This study deals with the hydro-aero-mooring coupled dynamic analysis of a new offshore floating renewable energy system, which integrates an offshore floating wind turbine (OFWT), a wave energy converter (WEC) and tidal turbines. The primary objective is to enhance the power production and reduce the platform motions through the combination of the three types of renewable energy systems. Simulation results show that the combined concept achieves a synergy between the floating wind turbine, the wave energy converter and the tidal turbines. Compared with a single floating wind turbine, the combined concept undertakes reduced surge and pitch motions. The overall power production increases by approximately 22%–45% depending on the environmental conditions. Moreover, the power production of the wind turbine is more stable due to the reduced platform motions and the combined concept is less sensitive to the transient effect induced by an emergency shutdown of the wind turbine.

Review on the Recent Developments of Photovoltaic Thermal (PV/T) and Proton Exchange Membrane Fuel Cell (PEMFC) Based Hybrid System

Photovoltaic Thermal (PV/T) system emerged as one of the convenient type of renewable energy system acquire the ability to generate power and thermal energy in the absence of moving parts. However, the power output of PV/T is intermittent due to dependency on solar irradiation condition. Furthermore, its efficiency decreases because of cells instability at high temperature. On the other hand, fuel cell co-generation system (CGS) is another technology that can generate power and heat simultaneously. Integration of PV/T and fuel cell CGS could enhance the reliability and sustainability of both systems as well as increasing the overall system performance. Hence, this paper intended to present the parameters that affect performance of PV/T and Proton Exchange Membrane Fuel Cell (PEMFC) CGS. Moreover, recent developments on PV/T-fuel cell hybrid system are also presented. Based on literates, mass flow rate of moving fluid in PV/T was found to affect the system efficiency. For the PEMFC, when the heat is utilized, the system performance can be increased where the heat efficiency is similar to electrical efficiency which is about 50%. Recent developments of hybrid PV/T and fuel cell show that most of the studies only focus on the power generation of the system. There are less study on the both power and heat utilization which is indeed necessary in future development in term of operation strategy, optimization of size, and operation algorithm.

Inventory compilation for renewable energy systems: the pitfalls of materiality thresholds and priority impact categories using hydropower case studies

This paper explores the potential to simplify the life cycle assessment (LCA) process for a hydropower (HP) system, without significantly compromising the accurate representation of environmental burdens. Taking five HP case studies, two questions were addressed: (i) Does a 1 % materiality threshold capture at least 95 % of the key environmental burdens from cradle-to-operation? (ii) What is the effect of applying a materiality threshold based on the global warming potential (GWP) indicator for capturing other environmental impacts? A comprehensively detailed inventory database was developed for five modern small- and micro-HP case studies (50–650 kW), representing run-of-river and water supply infrastructure installations from the UK and Ireland. Following ISO 14040 standards, the environmental burdens were quantified for these HP projects. Normalised results were compared against a natural gas combined cycle power plant (NG-CCP) reference system for marginal grid electricity generation. The adoption of a 1 % materiality threshold as advised by some guidelines led to cumulative omissions of up to 7.5 % of the total project burdens for some HP installations, contravening the 95 % inclusion target. The number of project components differed between the two types of HP projects and target exceedances were more likely for projects with more components. Using a lower materiality threshold of 0.2 or 0.5 % ensured that the 95 % target was achieved for all HP projects. Considering GWP as an indicator burden for assessing materiality thresholds led to significant omissions for other environmental burdens, e.g. abiotic resource depletion potential (ARDP). Omitting a number of small components with low-carbon contributions (e.g. copper wiring) led to a 19 % underestimation for contributors to the resource-based (GWP) impact categories. A simplified methodology may not capture all environmental burdens for a hydropower system or fossil fuel-based power plant. Basing a 1 % materiality threshold on contribution to a single burden, such as GWP, can lead to omissions of significant contributory components for that burden, and larger omissions for other burdens. ARDP is a particularly important impact category for renewable energy systems and appears to be particularly sensitive to materiality thresholds. It is important that practitioners take care with materiality thresholds when evaluating the environmental performance of all types of renewable energy systems through LCA. Including a materiality threshold to draw practicable system boundaries is necessary; however, reducing the threshold contribution to 0.5 % would be more likely to ensure that at least 95 % of environmental burdens are accounted for.

Multi-objective optimal design of a solar absorption cooling and heating system under life-cycle uncertainties

SACH systems, as a type of renewable energy systems, meet building cooling and heating demand through solar energy and therefore can reduce energy consumption and, in turn, mitigate the environmental impacts associated with building operation. Many researchers have evaluated and optimized the design of SACH systems under deterministic schemes; however, deterministic approach is subject to uncertain parameters in the evaluation or objective functions such as energy prices in the future and the results subsequently may not hold true. To enhance the design robustness and validate the use of deterministic approaches, a stochastic multi-objective optimization (SMOO) model is developed that incorporates these uncertainties. In this paper, a SACH system is optimized with respects to life-cycle energy, economic, and environment performance. The uncertain parameters considered include the life span of SACH systems and the fluctuations of energy markets and financial conditions. A case study follows to investigate the relationship among uncertainty and different designs. The comparison between deterministic and stochastic optimization shows that deterministic optimization can be used by designers who are moderate or not risk-averse at all.

Assessment of renewable energy technologies for charging electric vehicles in Canada

Electric vehicle charging by renewable energy can help reduce greenhouse gas emissions. This paper presents a data-intensive techno-economic model to estimate the cost of charging an electric vehicle with a battery capacity of 16 kW h for an average travel distance of 65 km from small-scale renewable electricity in various jurisdictions in Canada. Six scenarios were developed that encompass scale of operation, charging time, and type of renewable energy system. The costs of charging an electric vehicle from an off-grid wind energy system at a charging time of 8 h is 56.8–58.5 cents/km in Montreal, Quebec, and 58.5–60.0 cents/km in Ottawa, Ontario. However, on integration with a small-scale hydro, the charging costs are 9.4–11.2 cents/km in Montreal, 9.5–11.1 cents/km in Ottawa and 10.2–12.2 cents/km in Vancouver, British Columbia. The results show that electric vehicle charging from small-scale hydro energy integration is cost competitive compared charging from conventional grid electricity in all the chosen jurisdictions. Furthermore, when the electric vehicle charging time decreases from 8 to 4 h, the cost of charging increases by 83% and 11% from wind and hydro energy systems, respectively.

English

The process of Evolving the renewable generation technologies has many challenges, such as realize reduction in the capital costs and improving energy efficiencies of the different types of renewable energy systems, such as wind, solar PV, solar thermal, and tidal. Significant evolution is desirable in large-scale energy storage technologies. For consistent integration of renewable resources in a grid, the challenges of high penetration levels will have to be addressed in power system planning and operation, and in grid connection. The aspirants of power and energy engineering careers need to be educated so that they can foresee and evolve new approaches and technologies to maintain reliability and economy of grids intact. The challenges of integrating high penetrations of renewable energy technologies into the grid are seldom taken up as they need interdisciplinary innovations in areas as power systems analysis, communications, power electronics, economics, operations research, and industrial organization. In this paper some of the challenges in Integrating Renewable Technologies are discussed.

GIS-based site selection methodology for hybrid renewable energy systems: A case study from western Turkey

Renewable energy sources are presently being considered as alternatives to fossil fuels, because they are perpetual, environmentally friendly, and release negligible amounts of greenhouse gases to the atmosphere while producing energy. A disadvantage of renewable energy systems, however, is that continuous energy generation is not possible by using only one type of renewable energy system, since renewable energy resources depend on climate and weather conditions. Two or more renewable energy systems can be integrated into a hybrid system to overcome this problem so that when one resource is not available, the other can continue producing energy. Another disadvantage of renewable energy sources is that they are not available at every geographic location. Their use is mostly advantageous at remote locations that often are of high ecological value. Thus, identification of preferable locations for renewable energy systems is a decision-making problem that requires evaluation of the potential of the resource together with economic and environmental limitations. This paper introduces a methodology for site selection of hybrid wind solar–PV renewable energy systems. First, environmental acceptability and economic feasibility objectives are identified through a comprehensive review of the literature, current Turkish laws and legislations, and interviews with the General Directorate of Electrical Power Resources Survey and Development Administration of Turkey. Second, viable locations in terms of environmental acceptability and economic feasibility are determined through a fuzzy decision-making procedure that uses ordered weighted averaging algorithm for aggregating multiple objectives. Then, priority sites are identified separately for wind and solar energy systems by using Geographic Information System (GIS) and finally associated maps are overlaid to obtain the most feasible locations for hybrid wind solar–PV systems.

Grid-connectivity of remote isolated islands—A proposition in Indian context

This paper has analyzed the cases of Moushuni Island at Sundarban of 24 Parganas South of West Bengal, India. The proposition is to find out the possibility of grid-connectivity of isolated remote islands which is under rural electrification scheme by hybrid renewable energies under Jawaharlal Nehru National Solar Mission of India. In these rural electrification program, grid extension can be the best option if the grid is reliable, the rural community rather big and in proximity to the grid. In many circumstances, a strong case for mini-grids based on hybrid systems can be made. Scattered communities and isolated houses are well served by solar and small hydro (where available) or small wind energy systems. By feeding renewable electricity to the utility grid through grid-connected hybrid renewable energy system, during time of peak demand, sufficient electrical loads can be shed to prevent turning on a coal or natural gas-fired plant and therefore save CO2 emissions and potentially energy import costs, replacing fossil fuels. But there is a barrier for grid-connectivity for isolated island, which can be overcome by feed-in-tariff policy implementation for renewables. Also, feed-in-tariff for mini-grids is a promising approach for linking off-grid and grid-connected renewable energy support. Also, most intelligent controller for grid interactive operation of solar photovoltaic-wind-bio hybrid energy system at Moushuni Island is proposed. This intelligent controller will switch from various renewable resources like solar-wind-biomass through change over switch panel to find out optimized hybrid renewable energy system. Malda district of West Bengal, India is a vision towards smart-grid city towards sustainable future, where rural consumers can upgrade their quality of life through solar energy resource. This paper also illustrated the socio-economic and environmental benefits and social costing of adopting renewables future for India. Cost proposition for integrating distributed renewable energy sources-solar energy to electricity grid has been analyzed along with the feasibility studies for factors responsible for cost/unit reduction. The feasibility studies for social, economic, and environmental benefits of renewables have been discussed along with justifications for hybrid renewable vs stand alone-photovoltaic and other types of renewable energy systems along with the comparative analysis of economic costing of installation of various types of renewable energy systems.