Inclusion Of Renewable Energy Research Articles

Comparative Analysis of Congestion Management Methods with Integrated Renewable Energy Generation

Inclusion of renewable energy in power grid at micro and macro level has imposed numerous challenges in the recent years. Occurrence and managing congestion in the power transmission line due to unpredictable and stochastic nature of Renewable Energy Source (RES) integration has become a challenging task to the grid operators. Transmission lines operate at bottlenecks during a congestion episode adding to the extra congestion cost and risk in grid stability which becomes burden to the generation as well as end users. Different methodologies are applied to detect and manage the congestion to eliminate the congestion cost factor and maintain grid stability. The presented analysis compares conventional methodology Linear Sensitivity Factors (LSF) and Heuristic methodology Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) methods for congestion management in power transmission lines with integrated RES (wind and solar) system. For comparative analysis, a modified standard IEEE 30 Bus system is chosen which is integrated with real time RES generation. Optimal locations of RES generation with minimized congestion cost and percentage of RES curtailment are chosen as objective function for comparison of the methodologies.

A New Self-Learning Optimization Management Scheme for Smart Grid Systems

This paper presents a new energy optimization management scheme for the smart grid system (SGS), which not only considers the inclusion of renewable energy in energy management, but also considers the feedback sale of redundant renewable energy to the grid, so as to obtain better optimization management results and avoid energy waste. A new performance index function is constructed, which aims to save users’ electricity costs and protect energy storage batteries. We construct a periodic iterative self-learning method based on the characteristics that the relevant data of SGS is approximately periodic. The proposed self-learning optimization method is based on adaptive dynamic programming (ADP). The initial iterative control law is obtained by pre-training, and the designed method can be realized by neural networks. Simulation experiments are carried out by using the relevant data of SGS for four weeks. The experimental results show that the new energy management scheme can help users save a lot of electricity costs, and is more effective than some common methods.

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This paper presents a new energy optimization management scheme for the smart grid system (SGS), which not only considers the inclusion of renewable energy in energy management, but also considers the feedback sale of redundant renewable energy to the grid, so as to obtain better optimization management results and avoid energy waste. A new performance index function is constructed, which aims to save users’ electricity costs and protect energy storage batteries. We construct a periodic iterative self-learning method based on the characteristics that the relevant data of SGS is approximately periodic. The proposed self-learning optimization method is based on adaptive dynamic programming (ADP). The initial iterative control law is obtained by pre-training, and the designed method can be realized by neural networks. Simulation experiments are carried out by using the relevant data of SGS for four weeks. The experimental results show that the new energy management scheme can help users save a lot of electricity costs, and is more effective than some common methods.

Reinvestigate the significance of STRIPAT and extended STRIPAT: An inclusion of renewable energy and trade for gulf council countries

The rapid growth experienced by the Gulf Council countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) has placed significant strain on their ecological footprint due to extensive energy consumption. Consequently, it becomes necessary to examine the factors contributing to the high ecological footprint and explore potential solutions for its reduction. This study aims to analyze the key factors influencing the ecological footprint in the GCC countries from 1995 to 2020. Through an extensive review of existing literature, it is evident that economic growth, urbanization, and trade can disturb ecological balance, while environmental technology and renewable energy offer potential remedies for environmental challenges. Thus, these variables have been selected as independent factors for investigation. The results obtained from advanced panel techniques emphasize the significance of adopting environmental technologies and increasing the utilization of renewable energy sources in order to decrease the ecological footprint. Conversely, economic growth, urbanization, and trade are identified as crucial drivers of environmental degradation. Considering that the GCC countries heavily rely on oil and petroleum exports, as well as non-renewable energy sources for their economic activities, the positive relationship between economic growth and trade is to be expected. The results propose multifold recommendations: (i) providing incentives for renewable energy and (ii) prioritizing the implementation of clean technology over traditional technologies.

Integration of Renewable Energy in Green Hydrogen Generation

The inclusion of renewable energies, especially photovoltaic energy in the green hydrogen production is a very promising idea in the field of energy. However, these sources are unstable and susceptible to a variety of atmospheric influences, including temperature and illumination, for this reason, we must address these issues before we can adopt renewable energy as a major source in hydrogen production. Using Matlab software, we will construct an autonomous photovoltaic system that uses a DC-DC boost converter to link the PV array to the load. To improve the efficiency of the photoelectric power, we will utilize the perturbation and observation MPPT approach.

Scenario Analysis of an Electric Power System in Colombia Considering the El Niño Phenomenon and the Inclusion of Renewable Energies

This paper develops and analyzes four energy scenarios for Colombia that consider the El Niño phenomenon and the inclusion of renewable energies in the energy generation matrix for the period 2020–2035. A comparative analysis is presented between the results of the different scenarios proposed. The most relevant finding is the use of the reserve margin as an indicator of system reliability. A scenario which included 7214 MW of large-scale non-conventional renewable energy, 10,000 MW of distributed generation, and 12,240 MW of hydroelectric power was assumed, with a reserve margin of over 50%. Additionally, it was found that for the scenarios in which a generation capacity with non-conventional renewable energies of less than 10,000 MW in 2034 was assumed, the reserve margin of the system in the seasons of the El Niño phenomenon will be less than historical records of the system. Alternatively, it was found that the scenarios in which the inclusion of at least 9600 MW of the electric power generation capacity of non-conventional renewable energies proposed by 2034 offer benefits in the reduction in greenhouse gas (GHG) emissions, which contributes to the achievement of the emission reduction objectives of the Paris Agreement.

Margarethenhöhe goes towards low-carbon area - sustainable concepts for energy-efficient built heritage

Within the framework of a project funded by the Federal Ministry of Economics and Energy (BMWi) in Germany, it is being examined how, with different approaches, even historic buildings can contribute to an energy-efficient heritage district. Five partners are investigating the legal, structural and technical conditions for improving the building envelope in line with the preservation order, modernizing the buildings and providing a future-oriented energy supply. The inclusion of renewable energies and the digital networking of all components is of particular importance. For this all suitable measures will be adapted in five buildings for demonstration. Then, on basis of an extensive monitoring, the theoretically elaborated model approaches and the results obtained by means of numerical simulations can be validated. The joint project started in 2016. The IWB of University of Stuttgart as coordinator, the Margarethe Krupp Foundation as owner, the Gas and Heat Institute Essen e.V. and two institutes of the RWTH Aachen University, the Institute for Integrated Analog Circuits and the Institute for Building and Climate Technology, are partners in the research network.

Innovative Energy Technologies for Powering Buildings

This paper makes a technical analysis of the methods that can be used to provide Energy to Residential Buildings. The paper firstly describes the legislative framework for increasing the efficiency in the building sector and building certification. The key for improving the energy efficiency of buildings is ‘Nearly Zero-Energy Buildings(nZEB)‘. The main research in nZEB is described in section three and the technologies for increasing the energy performance of buildings, in summary, are presented in section four. A case study of the integration of renewable sources in the energy supply of residential buildings describes the calculation methodology of required energy, the specific consumption, and energy performance of building after inclusion of renewable energy for powering the building. The results of this analysis show that the energy uses in nZEB buildings are influenced by the building location, their architecture, energy system design, and level of renewable energy production.

Optimal planning, design and operation of a regional energy mix using renewable generation. Study case: Yucatan peninsula

ABSTRACT Planning and operation of smart energetic projects have increased in complexity and requires a deeper analysis. The inclusion of renewable energy and distributed generation sources lead to an inherent difficulty to define appropriate models for decision-making. Nowadays, decisions in planning and operation are made level by level due to a disarticulation of information within the electrical sector and the stakeholders. Therefore, here is proposed an architectural decision model of multilevel-multiobjective to solve this problem. In this scheme, the problem of energetic assets sizing is on the upper level, while the problem of operation and dispatch of unit power is on the lower level. Both levels are related through quantitative tools (key performance indicators (KPI)) and qualitative tools (quality function deployment (QFD) and hierarchical analytical process (AHP)). This model was applied in the Yucatán peninsula. As a result, an integral solution with a lower cost and better environmental factor than the baseline for the region was obtained.

Modeling and Simulation using MATLAB to Mitigate Technical Challenges & Also for Scalability of Pilot Project of Clustered Solar Agricultural Feeder

The inclusion of renewable energy in India’s electricity mix has been increased dramatically in the past several years. From an environmental, energy security and long-term cost standpoint, this evolving trend is undoubtedly welcome. Solar energy has rapidly emerged as a reliable, affordable and clean solution for meeting India’s fast growing energy demand and supply to all. But connecting PV plant DC power with the AC grid is difficult because of tripping, not properly synchronizing. In this paper the development of PV array model, their integration, power quality assessment and Simulink implementation are described. Modeling concept presented in this paper can easily be extended and used for scalability purpose. System consist of solar arrays, MPPT, IGBT inverter and transformer. First, the field parameters has been measured and analyzed by using Fluke Power Analyzer, then exact field modeling and simulation of cluster model of 1.6 MW grid (agricultural feeder)connected PV based solar power plant using MATLAB Simulink R2019A is made in which Maximum Power Point Tracking technique(MPPT) for obtaining maximum possible power output is used, and in MPPT we have used Perturb and Observe method. The ideal values getting from MATLAB Simulation and the real time values of the PV Plant measured by fluke power analyzer are compared and analyzed, then an efficient systems can be modeled for proper synchronization with the grid.

Is the environmental Kuznets Curve in Europe related to the per-capita ecological footprint or CO2 emissions?

Abstract The nexus between environment-economic development has been investigated for a long time. Many empirical studies have measured environmental degradation by CO2 emissions and ignored the possibility that the use of such metric as environmental degradation indicator may be invalid in some cases when it comes to resource stocks. This paper focuses on two indicators of environmental degradation including ecological footprint (EF) and CO2 emissions as target variables to provide new insights into the ongoing discussions of whether the environmental Kuznets Curve (EKC) hypothesis is related to the indicators of environmental pressure used. Estimating a heterogeneous panel model with data on 14 European countries over the period 1990–2014, we provide evidence for the sensitivity of the EKC hypothesis to the type of environmental degradation proxy used. Furthermore, we provide new insights regarding the relevance of EF as an appropriate environmental tool that fits the EKC prediction in contrast to CO2 emissions. Regarding the explanatory variables, the results show that renewable energy is an environmentally friendly source while fossil fuels contribute to environmental degradation. The inclusion of renewable energy and fossil fuel does not alter the behavior of economic growth in all environmental degradation indicators. The empirical results demonstrate the need to implement environmental management policies that encourage the production/supply of renewable energy and to reduce reliance on fossil fuel consumption. This paper is expected to provide policy makers with a set of policy proposals to achieve sustainable environmental and economic development.

Thermodynamic and economic evaluation of an innovative electricity storage system based on thermal energy storage

One of the main issues concerning the inclusion of renewable energies as a way to produce electricity is the fluctuation of the production. This explains why there is a need for efficient solutions which will allow to store the energy when there is no need for it and release it when renewable energies are not able to sustain the production. This work concerns a Power-to-Power solution based on thermal energy storage at high temperature (around 900 °C). It relies on a simple heating loop to convert electrical energy into heat, and a thermodynamic cycle such as a gas cycle or a combined cycle to convert heat into electricity. One of the questions raised by this system is how it can be profitable from the economic point of view. Indeed a lot of studies have been conducted on energy storage, but very few propose solutions which can be relevant in terms of global costs and payback time. The aim of this study is to investigate if this system could be competitive in the European, and more specifically, French energy market. To look further into this topic, the system architecture and its components are defined. A thermodynamic model is also built to represent the behavior of the cycle. Finally, an economic discussion is performed using cost functions from the literature. The results show that the system does not accumulate enough running hours to justify high investment costs and should rely on simple technologies to insure its profitability. Furthermore, while the high capital expenditures of the whole system could be challenging, the thermal storage itself is not a big expense when compared to the cost of a natural gas fired power plant.

Study of the harmonic and interharmonic content in electrical signals from photovoltaic generation and their relationship with environmental factors

The inclusion of renewable energies is associated with harmonic and interharmonic contamination due to the use of power inverters. Thus, several international standards have been developed to establish the admissible distortion levels associated with spectral contamination. However, these standards present limitations: interharmonics are not considered and only present limits for current signals and voltage are dismissed. This work assesses the spectral content introduced by photovoltaic generation in low voltage grids considering the existence of voltage harmonics and interharmonics. Additionally, a multiple linear regression analysis quantifies the effect of sun irradiance and photovoltaic cell temperature on harmonic and interharmonic distortion. The analysis is performed in real signals from a photovoltaic generation plant considering different weather conditions. The results prove that the spectral content in photovoltaic generation is variable throughout the day, and environmental factors can reasonably describe the behavior of harmonic and interharmonic distortion.

The Why of Adaptive Protections in Modern Electrical Networks

Electrical networks are evolving and taking on more challenges as the inclusion of renewable energy and distributed generation units increase, specially at distribution levels. Big trends of generating electricity with alternative and renewable resources has promoted the formation of distribution networks subsystems or micro grids, capable of supplying their own electric demand and to export energy to the interconnected system, if necessary. However, the effects of these generation units into the network and into the microgrid as well are many, as harmonic distortion, voltage flickers and especially in electrical protections.This paper provides an overview about implementation of renewable energy and distributed generation worldwide, as well as an introduction to microgrids concept and its main impacts and challenges into the electric systems. Finally, the main impacts of microgrid on protection equipments are presented at a distribution level, being adaptive protections one of the solutions to the dynamic changes of the electric system.

Development of a Bike-Sharing System Based on Pedal-Assisted Electric Bicycles for Bogota City

The lack of sustainable solutions to mobility and transportation is a major problem in Latin American cities and requires prompt solutions. The main issues in Latin America are the high-cost of solutions, no inclusion of renewable energies, poor energy management, the use of foreign systems not adapted to local contexts, ineffective regional legislation and politics, among others. In this paper the main technical issues concerning the implementation of a bike-sharing system using pedaling-assisted (PAS) electric bicycles for Bogota City are discussed and a solution is proposed. To solve such problems, a methodology to design a tailored solution well suited to Bogota citizen’s needs is developed. Such methodology starts with the development of an on-board-computer (OBC) in order to characterize bike-users by collecting a rider’s data in real-time. Furthermore, the proposed solution develops a low-cost middle-drive (mid-drive) propulsion system for the PAS in the electric bike using brushless-DC (BLDC) motors and by implementing a field-oriented controller (FOC). The reported bike-sharing system also includes the development and implementation of two charging-stations that enable charging the battery on the electric bikes exclusively by using photovoltaic energy. Experimental results are presented and discussed.

The deployment of the first tidal energy capture system in Taiwan

As government policies of energy resources shift towards the inclusion of renewable energy, the ocean resources have become great potential. One of the ocean energies is tidal current energy which can be used to drive underwater turbine and generator. A study on harvesting ocean is done in this integrated project with six subprojects which are investigated by the researchers of cross-disciplinary including mechanical, electrical, ocean, environmental engineering, underwater technology and marine science. The horizontal-axis turbine is attached to a magnetic generator and is installed in a square nozzle and diffusor duct which is semi-submerged and floated. The floating capture system is mooring by steel chains and the anchoring system is concrete gravity blocks. The deployment of the first NSYSU energy capture system is made in 2013 at Penghu Island and the system was safety approved in storm wave condition since it was passed by Teinping Typhoon attacked. A maximum power take off (PTO) nearly equal to 5 kW is monitored which is the largest tidal current PTO in Taiwan and also is the first on-site successful ocean deployment in Taiwan.

Constructing A Multi-Microgrid with the Inclusion of Renewable Energy in Oman's Rural Power System

This paper investigates the possibility of constructing multi-microgrids by interlinking the rural area systems in the Al Wusta governorate of the Sultanate of Oman, which are currently being supplied by diesel generators. It is proposed to enhance the rural system under study by switching off small diesel stations and replacing them with wind turbines. The microgrids formed in this way are then interlinked together to create multi-microgrids. The paper studies the interlinked multi-microgrids under different scenarios; in terms of voltage profiles and power flow using the ETAP software package. This study contributes to the feasibility study of retiring some diesel power plants and using renewable energy resources in rural Oman.

Reducing uncertainty accumulation in wind-integrated electrical grid

Abstract Implementing microgrids has become a major trend in the electric power industry to move toward energy sustainability. One approach for implementing microgrids is to introduce renewable energy. With the inclusion of renewable energy in a microgrid, an appropriate energy storage capacity is needed to cope with uncertainty variation resulting from renewable energy generation fluctuation. This study proposes a probability-based dispatch strategy for determining energy storage capacity with consideration of wind and load fluctuation. The wind and load models are constructed based on their trends and uncertainty variations. The wavelet packet analysis method and the moving average technique are used to extract the trends of wind energy and load. Log-normal and extreme value distributions are used to model the uncertainties from wind speed and load. This research improves an existing method with reduced uncertainty accumulation, resulting in a more suitable battery size. To validate the proposed method, a real-time operating simulation is used to observe the behavior of a wind-integrated electrical grid. Results show that the proposed method can reduce the effects of uncertainty variation caused by wind and load. A smaller energy storage capacity with higher reliability is also obtained through optimization.

Using CPS Enabled Microgrid System for optimal power utilization and supply strategy

Because the power grid experiences dynamic variations in energy generation and demand, inclusion of renewable energy alone will not assure self-sustainability of the grid system. Energy sustainability can be achieved by developing Cyber Physical System enabled smart buildings capable of dynamic energy management. In this research work, we propose the architecture for CPS enabled sustainable buildings integrated with Distributed Energy Generators (DEG). We have developed three algorithms, namely, Equipment Classification Algorithm (ECA), Context Aware Room Energy Utilization (CAREU), and Availability based Management Algorithm (AMA), for dynamic energy management to attain energy sustainability of smart buildings, and optimization models for profit maximization in smart buildings. Prototype of the smart buildings are developed with features such as realtime energy monitoring, renewable energy integration, dynamic rescheduling and reallocation of energy utilization of equipments to attain energy sustainability. The results show that the proposed method provides energy sustainability compared to the current state-of-the-art methods.

Developing a new optimization framework for power generation expansion planning with the inclusion of renewable energy—A case study of Iran

The current paper proposes a new hybrid framework to consider the tangible and intangible factors besides the conventional power generation expansion planning problem. It aims at approximating the results to the real world and determining the long term electricity generation expansion plan of Iran from 2016–2035. In addition, it focuses on promoting the shares of renewable energy resources by utilizing the sustainable development approach. The proposed framework includes two stages. In the first stage, the detailed evaluation of technologies is carried out using a hybrid fuzzy analytic network process and benefits, opportunities and risks analysis. In the second stage, a multi-objective model is developed for the optimization of a generation expansion plan. Two objective functions are considered in the model: maximizing the total preference weight of the plan and minimizing the total costs, which includes investment, operation and maintenance, generation, emission, and unmet demands costs. The applicability and efficiency of the proposed framework are surveyed by applying it for Iran's power industry. The mathematical model is solved using the NSGA-II algorithm and sensitivity analysis is performed for the key parameters. The results show the increasing shares of renewable resources in the planning horizon. Furthermore, it shows that the fossil power plants would play a significant role in the future of Iran's electricity supply. The natural gas combined cycle power plants would be the most preferred alternative among the fossil power plants and would have the most installed capacity share during the planning horizon.