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The deregulation of the electricity market has been accompanied by the growing utilization of unpredictable renewable energy sources (RESs) such as solar, wind, and hydropower plants. Additionally, advancements in energy storage technologies and new energy demands have further contributed to this trend. As a result, the planning and operation of power systems are now surrounded by a higher level of uncertainty. In order to ensure the proper operation of power systems integrated with RESs, modern power systems are equipped with specific vital tools such as optimal power flow (OPF), which regulates generation and demand to achieve specific objectives. Hence, this paper conducts a comprehensive review of recently published research articles focusing on various solution strategies to address OPF problems in the presence of stochastic RESs and power demand. The review encompasses diverse solution methodologies, objective functions, constraints, and distinct techniques to simulate the stochastic behavior of RESs and dynamic loads. Additionally, the paper explores fundamental challenges, identifies critical research gaps, and highlights unexplored areas pertaining to optimal power system operation in the future. This review is essential for system operators who need to assess and pre-plan flexibility competency for their power systems to ensure practical and cost-effective operation under high RESs penetration. [ABSTRACT FROM AUTHOR]

This paper proposes the Hybrid desalination and power generation through parabolic trough collectors. This study aims to examine the feasibility, performance optimization, and economic viability of power-generation plant and hybrid-desalination using multi-stage flash (MSF) and reverse osmosis (RO) technologies assessed by using the parabolic trough collectors (PTC). The objective is to discover the posibilities of this innovative approach in addressing water scarcity and clean energy demands. The studies usually focus on several key aspects. Firstly, it resolves the technical feasibility of integrating MSF and RO technologies with parabolic-trough-collectors to optimize energy efficiency and freshwater production. This involves evaluating the system design, heat transfer mechanisms, and operational parameters.Secondly, performance optimization is a key area of investigation. By optimizing these parameters the aim is to maximize freshwater production while minimizing energy consumption. Thirdly, the economic viability of the hybrid plant will be assessed. This involves considering capital investment, conducting a comprehensive cost analysis, maintenance costs, and operational expenses. The study also evaluates the potential for revenue generation through the sale of excess electricity produced by the system. The potential outcomes of this research include demonstrating the technical-feasibility as well as economic-viability of the hybrid desalination and power generation plant. The findings may indicate that this approach can effectively address water scarcity challenges while contributing to clean energy production. The study may also highlight the environmental benefits of integrating renewable energy sources (RESs) and decreasing greenhouse gas emissions compared to traditional desalination methods.The proposed method is executed in MATLAB platform and compared to various existing approaches. [ABSTRACT FROM AUTHOR]

Energy generation and pollutant emissions are two faces of the same coin, as the current energy sources i.e., fossil energy, are still considered to be major sources of greenhouse gases (GHG). Therefore, shifting to cleaner energy sources imposes itself as an inevitable solution to reduce this environmental cost. In this paper, a hybrid system based on the multi-agent approach and Long Short-Term Memory (LSTM) neural networks to forecast the energy production and its carbon dioxide (CO2) emissions and simulate the potential emission reduction in case of switching to renewable energy sources is presented. The proposed system's architecture consists of combining LSTM models with the agent-based technology, where multiple LSTM forecasting models were trained to forecast the production of each type of the studied energies and then estimate the equivalent emitted CO2 and calculate the influence of the renewable energy inputs on the carbon emissions and the fossil fuels consumption. The simulation process consists of two phases: firstly, each forecasting agent uses a specific LSTM model to forecast short-term energy production. Secondly, these agents send the forecasted values to the coordination agent who is responsible for calculating the total CO2 emissions and the benefits of the renewable energy inputs. [ABSTRACT FROM AUTHOR]

Due to the non-deterministic and probabilistic qualities of renewable energy resources (RER), integrating these resources has posed a challenge for energy companies and government policy planners. Hybrid power systems require frequent voltage regulation to address the changes in renewable generation and facilitate voltage management. This leads to an increment in the operating time of the tap changer in the power transformer, thus resulting in accelerated degradation of the on-load tap changer (OLTC) device. The primary focus of this paper is to optimally manage the penetration level of renewable generation while maintaining the minimum time for proper operation of voltage regulation devices. Accordingly, the major contribution of this paper is to address the switching cycle issues of the on-load tap-changing transformer. Initially, a framework is proposed to optimize the location and size of renewable power generation using a multi-objective cuckoo search optimization algorithm. The main goal here is to reduce power losses and tap changer operations while improving the system voltage profile under different levels of renewable energy penetration. The optimization problem takes into consideration the fluctuating nature of wind speed and solar irradiance for sunny and cloudy days over 24 h. The framework has been applied to the IEEE 57-bus and 118-bus systems with different load levels. The performance of the proposed approach has been benchmarked by comparing it with the genetic optimization algorithm to identify the higher potential buses for renewable generation allocation. The cuckoo search algorithm (CSA) shows outstanding results in reducing the number of switching cycles to about (37 – 43) % whereas the genetic algorithm (GA) only (17 – 18). In this sense, the number of changes in tap position when using the CSA is 1956 for sunny days and 1763 for cloudy days compared to GA 2558 for sunny days and 2547 for cloudy days. The voltage profiles for both algorithms are maintained in the range of (1.06 and 0.94) per unit. The results affirm the effectiveness of the proposed approach in determining the optimal placement and size of RER with voltage profile improvement and reduction in the switching cycles of OLTC. [ABSTRACT FROM AUTHOR]

The growing energy demand and the emerging environmental concerns across the globe caused increasing penetration of renewable energy sources (RESs) in distribution systems. One of the major issues faced by modern distribution systems with high RESs penetration is voltage instability. Generally, voltage instability can lead to voltage collapse, which is one of the key drivers for blackout incidents around the world. Under voltage load shedding (UVLS) schemes are usually executed as the final option to prevent a large-scale blackout or voltage collapse. But ever-increasing integration of RESs in distribution systems creates an additional threat to the existing UVLS schemes. Therefore, new UVLS methods are necessary to provide the appropriate corrective scheme for distribution systems, particularly when connected with RESs. This paper reviews and updates the recent UVLS methods emphasizing on distribution network application. In addition, the contributions and limitations of the conventional, adaptive, and computational intelligence techniques of UVLS are highlighted. Moreover, this paper provides an overview of the voltage stability indices applied for UVLS methods. Also, at the end of this review article, the further research directions to improve the safety of modern distribution systems during emergencies using UVLS are drawn as the conclusion. [ABSTRACT FROM AUTHOR]

The need for environmentally-friendly energy generation and massive exploitation of fossil fuels are leading to the increased demand for renewable energy sources like photovoltaic (PV) and wind energy, etc. The fluctuating behaviour of PV causes various disadvantages, of which the generation of Inter-harmonics is the major problem. The production of Inter-harmonics by the load-interfacing inverters is primarily due to the Maximum Power Point Tracking (MPPT) techniques employed in PV system. The requirement of multiple perturbations in tracking peak points is the primary cause behind the inter-harmonic generation. Since solar irradiation varies throughout a specific period, there can be situations, where the operating irradiance changes abruptly from one state to the other. These abrupt changes generate enormous fluctuations in the MPPT power output, resulting in an inter-harmonics generation. This paper proposes an evolved INter-HARmonic-Elimination (INHARE) algorithm for minimizing the PV fluctuating behaviour, leading to lower voltage ripple and settling time. The proposed INHARE algorithm is examined for a 0.52 kW PV system, where the Inter-harmonics content is reduced considerably in load current for the case of varying irradiances at a constant temperature. [ABSTRACT FROM AUTHOR]

There is a rapid increase in power demand which has led to an increase in the need for smaller grids all over the world. The microgrid is such a small power supply system that consists of loads, distributed energy resources, and energy storage systems. With the development of the internet, the power sector has started the development of the newest type of grids, involving a smart technology called smart grids. Smart grids have got smart integration and advanced storage, along with dynamic optimization of grid operation and resources, digital information and control, distributed resources, demand-side resources, energy efficiency resources, and smart metering systems. The developments in intelligent controllers reflect in power flow management also. This paper gives an idea of how to achieve power flow management through a tariff-based Fuzzy Logic Controller (FLC). The control algorithm used here is the k factor-based Icosϕ algorithm, which decides the amount of power shared by microgrids and the grid based on the load demand. The power forecasting of the microgrid with a solar source is performed using ANN. The regression plot and the error histogram obtained show the accuracy of the ANN controller. The simulation of power flow management of the smart microgrid system is tested and analyzed and the proposed system is compared with other existing research. The hardware implementation of the FLC controller with the Arduino interface which is analogous to real-time measurement is explained in detail to compare the simulation results obtained. [ABSTRACT FROM AUTHOR]

In recent times, the research in sustainable energy resources was integrated with the control approaches of various hybrid renewable energy systems for balancing the electricity generation. The accelerated hybrid energy storage systems and steadily growing energy consumption make the variability and the predictable behavior occur in the renewable energy sources, which requires an energy management system. This paper aims to control hybrid renewable energy systems for power management. The systems consist of photovoltaic (PV) arrays, diesel generators, wind systems with boost converter DC-DC, and inverters. The optimum of the real-time process is less due to prediction errors of multiple renewable sources, which track the output voltage and load current. Model predictive control (MPC) is proposed for problem-solving time operation to address this issue and compensate for the prediction error. The major impact factors, such as optimal split power, stability, reliability of energy, and desired dynamic responses, have been identified by applying the MPC technique. A simulation model has been constructed using MATLAB/Simulink environment to confirm the effectiveness of the MPC technique model. [ABSTRACT FROM AUTHOR]

Biogas has garnered increasing interest as a sustainable alternative to fossil fuels. However, due to the complexity of generating biogas, it is crucial to adopt adequate methodologies that aid planning, building, and running operations. Mathematical models have proven to be useful for assisting in the production of biogas, and they are applicable in different stages of the process. Therefore, the objective of this paper is to investigate how mathematical models can contribute to enhancing the efficiency and optimizing the biogas generation process. The Methodi Ordinatio methodology was used to conduct a systematic review of the literature. The VOSviewer software and the bibliometrix package in R were used to generate visual maps. The results revealed that mixed integer linear programming (MILP) models are the most common, accounting for 27% of the studies, followed by simulation models (SIM) with 14%, and hybrid models (HYB) and nonlinear programming models (NLP) in equal proportions, both at 13%. These models are useful for predicting and simulating biogas production. The analysis also revealed a significant trend toward integrating biogas production with the agricultural sector. Continuous advancements and applications of mathematical models are expected to increasingly facilitate biogas generation, thereby propelling global energy usage toward a sustainable energy source. [ABSTRACT FROM AUTHOR]

It is a known fact that fossil fuels will be depleted in the near future owing to the negative effects on the environment. The number of applications using renewable energy sources instead of fossil fuels to obtain energy has increased significantly. It is aimed to provide effective energy production with the proposed rotary energy system (RES) installation for regions with high wind energy and solar energy potential. In the paper, the design, manufacturing process, installation, and output power prediction of a novel RES are presented. In the proposed system, a hybrid system whose energy is derived from solar and wind energy is envisaged. The electrical characteristics of the solar panels with dimensions 140 × 60 × 2.5 mm mounted on the prototype are 6 V 100 mA. The prototype has been tested at different rotation speeds to evaluate the effect of wind energy. Moreover, the output power prediction based on Feedforward Neural Network (FFNN) and Particle Swarm Optimization trained Feedforward Neural Network (PSO-FFNN) has been performed with the data obtained from the prototype system. The three quantitative standard statistical performance evaluation measures, root mean square error (RMSE), mean absolute percentage error (MAPE) and Theil's inequality coefficient (TIC) are employed to compare the performances of these architectures. FFNN architecture, the RMSE, MAPE and TIC values are calculated as 0.0690, 0.0455 and 0.0278, respectively. For the PSO-FFNN architecture, RMSE, MAPE and TIC values are 0.0530, 0.0383, and 0.0213, respectively. It has been proved that it will be produced energy more effectively thanks to the hybrid RES in meeting energy demand. [ABSTRACT FROM AUTHOR]

Lignite is the most potential alternative energy source in the future. Due to its porous structure and spray dust reduction during the mining process, the lignite has a high moisture content, which leads to an increase in the energy consumption of dry distillation. Drying can effectively dewater it and improve the grade. In this paper, the dehydration and upgrading of wet low-grade lignite using a multi-layer reverse cross-flow drying bed were researched. The focus was on the change trend of the dehydration rate of the lignite in different beds. The distribution law of moisture content in the drying bed and the different drying function periods were determined and systematically analyzed. The influence of parameters such as drying temperature and smoke-coal ratio on drying characteristics was explored, at the same time, the significant influence of drying parameters on drying effect was analyzed and the optimal operating parameters were obtained (Rsc = 7.6, T = 200℃, t = 20 min). The test results show that: when the drying time t = 0-5 min, it is the fast drying period, and when t = 5-10 min, it is the constant-velocity drying period, and when t = 15-20 min, it is the slow drying period. When t = 10-15 min, it is accelerated drying period. With the increase of smoke-coal ratio (Rso), the dehydration rate of lignite increases first and then decreases. When the smoke-coal ratio Rsc = 7.6, the dehydration rate of lignite reaches the maximum value of ηcoal = 88.99%, and the dehydration effect is better at this time. After drying, the wet lignite has a moisture content of 2.95% and an ash content of 12.78%. The dehydration range of lignite of various density grades is obvious, realizing the efficient dehydration and upgrading of low-grade lignite. [ABSTRACT FROM AUTHOR]

Global energy demand has consistently increased in recent decades, owing to the rapid population increase. Energy consumption is higher than it has ever been, and most fossil supplies are on the verge of exhaustion with the current rate of exploitation. Facing the double pressure of meeting energy demands and reducing carbon emissions, the integration of renewable energy into different aspects of the energy ecosystem has become a unified agreement for all countries globally. Hybrid renewable energy systems that integrate multiple energy sources can effectively solve this problem. In the hybrid renewable energy system, optimizing the unit size is the key to achieving efficient utilization of renewable energy. Research trends show that artificial intelligence methods are gaining attention from researchers and can provide good system optimization in the absence of long-term weather data to provide good system optimization. While different studies have presented articles in this research domain, it is important to give a comprehensive collation/summary of the research trend while highlighting key models/methods utilized in this research domain. Hence, based on the published literature, this paper provides a comprehensive bibliographical review of the current trends/status of hybrid renewable energy systems research. Key research articles published in the Web of Science between the years 2000 and 2022 in this research domain have been reviewed. This paper describes the hybrid renewable energy systems, summarizes many different energy systems in existing literature, compares the differences between various energy systems, and analyzes the physical models of different systems, as well as the optimization methods and the optimization of the systems. Further, the uncertainty of electricity generation from renewable energy sources is analyzed in the literature review and the future challenges of hybrid renewable energy systems are summarized. [ABSTRACT FROM AUTHOR]

This research study presents the design of a mobile Android application which provides efficient PV sizing recommendations for residential users. The paper aims to promote the adoption of solar energy to meet energy demands for residential use, by providing accurate information to prospective renewable energy users via the development of an android application for the sizing of PV-battery systems. The study adopted a Design Science Research (DSR) methodology which employs models, techniques, and algorithms to create artifacts expected to meet specified sets of functional requirements. DSR provided stepwise processes for development of the application, validation, testing and evaluation. The evaluation of the android application's accuracy was presented in this paper, after extensive testing by experts and non-experts. Its performance showed that the feasibility of the application is suitable for potential users and professionals alike. The use of the developed mobile application could strengthen public-private partnerships that would promote widespread use of PV- battery system for residential applications. [ABSTRACT FROM AUTHOR]

In a DC microgrid, the main aim of power management is to maintain the balance of active power between renewable sources, storage batteries, loads, and distribution grid which can be represented by stable DC-link voltage. This paper proposes an adaptive strategy for power flow management of a stand-alone hybrid renewable energy system (HRES) consisting of a wind turbine generator, photovoltaic cell, battery energy storage (BES), and load by optimizing the gain of the PI controller in the battery storage system using the particle swarm optimization-based firefly algorithm (PSO-FA). A part of the PSO algorithm is utilized for improving velocity and attractiveness of the firefly algorithm thereby increasing the rate of convergence in the PI controller. This control technique improves gain constant by generating control pulses for charging and discharging of the BES system in order to make optimum use of renewable energy sources and to stabilize the voltage of the DC-link. From the simulations done in MATLAB/SIMULINK, it is observed that conventional trial- and error-based PI tuning produces high overshoot, whereas the proposed method produces better performance with less overshoot. Maintaining constant DC-link voltage, the instantaneous power generation under various conditions of generation and load consumption is managed by monitoring the state of charge of battery. This approach can be used as a complement for improving the performance of PI controllers designed by conventional methods. [ABSTRACT FROM AUTHOR]

Recently, there has been a noticeable contribution from renewable energy sources to enhance sources of electricity generation. The annual increase in energy consumption, the negative impacts of unsustainable energy sources, and the worldwide deterioration of fossil fuels like coal and oil are the causes of this. Solar and wind energy sources are the most often used renewable energy sources because of its minimal adverse environmental effects, negligible operating costs, and straightforward operational requirements. Simultaneously, renewable energy sources (RES) bring new challenges for protective measures. The dynamic response of RES, which is mostly controlled by inverters, is not taken into consideration while designing protection systems because rotating machines tend to behave dynamically as generating units. The magnitude and phase angle comparison, amount of negative-sequence, and short-circuit current level are all impacted by the RES, which presents difficulties for various pertinent transmission and distribution lines protection algorithms. This article is focused on 'Smart Grid Concept', known as the future power grid, which uses bidirectional flows of electricity and information to build an automated energy delivery network that is broadly distributed. Protection challenges and their feasible solutions for grid integrated RES are addressed in this review paper. [ABSTRACT FROM AUTHOR]

The past decade has seen an increase in renewable energy sources in the energy mix due to global environmental and supply security concerns. This paper aimed to investigate renewable energy effects on Gross Domestic Product (GDP) in the Southern African Power Pool (SAPP). The investigation is from 1988 to 2018, using the autoregressive distributed lag (ARDL), Nonlinear ARDL (NARDL), and fully modified OLS (FMOL) techniques. Based on empirical analyses of ARDL and FMOLS, it was found that both renewable and nonrenewable energies have a positive impact on economic growth in the Southern African power pool. However, the NARDL estimation indicates that neither renewable nor nonrenewable energy has a significant effect on economic growth in Southern African power pool. Therefore, based on the findings from both ARDL and FMOLS, the growth hypothesis is supported regarding the connection between renewable energy and economic growth in the Southern Africa power pool. Centered on the results, some policy implications were drawn for SAPP for sustainable economic growth, which includes measures to increase renewable energy in the energy mix, and also to encourage the optimization of cross-border connections where energy production from countries within SAPP that are not restricted by natural resources can be relied on to export sustainable energy. Additionally, building a more sustainable integrated power system in the region will assist SAPP with sustainable energy access and reduce the dependence on nonrenewable energy within the interconnected countries soon. [ABSTRACT FROM AUTHOR]

In this paper, we provide extensive modeling of fast-charging electric vehicle stations (FCEVS) allied to a grid integrated renewable energy sources (RES like hydro and solar) system considering an electric vehicle (EV) demand characteristics, state of charge (SOC), battery ratings, arrival, and departure time. This aids in maximizing the revenue and lowering the grid energy utilization. Investigations are carried with a novel meta-heuristic technique known as the emperor penguin optimization (EPO) algorithm, which is utilized to optimize the FCEVS parameters and maximize net present value (NPV). The investigations wih EPO has shown significant improvent of 1% with particle swarm optimization (PSO) and 1.25% with crow search algorithm (CSA). Also, studies are carried using a probabilistic demand distribution based on EV behaviors considering a sequential Monte-Carlo approach with hourly intervals. The acquired economic deliberations with EPO algorithm are compared with PSO, CSA, and EPO extracts maximum revenue. Simulations with FCEVS fed by grid, RES, and hybrid grid-RES reveal that FCEVS fed by hybrid grid-RES extracts the highest NPV. Further, 78.09% increase in NPV is observed with RES feeds the Grid over Grid feeds FCEVS alone, 25.23% hike of NPV is observed with both RES and battery storage system (BSS) over RES system, 10.56% increase with considering EVs arrival time and 2.3% increase with considering flow of EVs. Further, simulations with detailed modeling of FCEVS enhance NPV values over the hybrid grid-RES system. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric responses of renewable energy (RE) technology to globalization and economic growth shocks across the G7 countries using the Nonlinear Cointegrating Auto-Regressive Distributed Lag (NARDL) model. Our results indicate asymmetries across these countries and that positive shocks on globalization increase RE in Canada, Germany, the United Kingdom (UK), and the United States (US) while negative shocks decrease RE. However, both positive and negative globalization shocks promote RE consumption in Italy and Japan but decrease it in France. In contrast, both income shocks increase RE in France whilst positive income shocks increase RE in Canada, Germany, and Italy while negative shocks decrease RE. Positive income shock facilitates RE in the UK and the US while negative income shocks are detrimental to RE in Japan. Further analysis using panel cointegration, Fully Modified Ordinary Least Squares, and Panel Dynamic Ordinary Least Squares suggests that RE deployment in the G7 countries is mainly driven by positive shocks on income, globalization, and capital. We discuss the implications of the findings. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid fuzzy cascaded fractional order proportional integral-fractional order proportional derivative (FCFOPI-FOPD) controller improves the frequency regulation of a renewable energy source (RES) integrated power system. The frequency response characteristics of a two-area non-linear thermal-hydro-wind model under various operating situations are explored with an emphasis on the extensive usage of renewable energy sources (RES) in modern power systems. The power system in this study is developed using an innovative combination of a standard dynamic model of the steam turbine and the actual physical position of the generation rate constraint in the power plant model. The suggested FCFOPI-FOPD hybrid controller minimizes a power system's frequency deviation caused by specific differences in the pre-scheduled load. The effectiveness of a proposed FCFOPI-FOPD hybrid controller in alleviating system frequency variations under various perturbations was determined using MATLAB Simulink analysis. Comprehensive results show that the FCFOPI-FOPD hybrid controller outperforms the fuzzy-structured fractional order proportional integral and derivative (FOPID) and the proportional and integral controllers. The results also demonstrate that the proposed controller improves the settling time of frequency variations in area-1, area-2, and tie-line power deviation by 47%, 51%, and 66% compared to the responses obtained with the fuzzy FOPID controller. [ABSTRACT FROM AUTHOR]

To ensure the global energy demands and decarbonize the production of electricity, the expanded utilization of solar photovoltaics (PV) as a renewable energy resource has been increasing in recent decades, principally with the feasibility to be integrated with the conventional power grid. However, supplying clean power from PV grid-connected systems is often hampered by power quality (PQ) disturbances caused by the intermittent nature of solar radiation and other factors related to the grid, converters, and connected loads. To prevent deterioration of the power quality of the system, these disturbances must be mitigated. This paper technically studies some of these PQ issues, that is, the current total harmonic distortion (THD) which causes harmful effects on the whole connected power system and the linked loads. The case study works on a 5.5 kW grid-connected rooftop PV power system established at Benha Faculty of Engineering, Egypt, with the assistance of an installed weather station that boosts the validation of the research results. All aspects regarding the aforementioned small plant are presented including description and simulation of the whole system, review of current THD problems occurring at the point of common coupling (PCC), and a review of other disturbances observed by connected meters. A detailed examination of four techniques for harmonic mitigation, namely the on-off technique, LCL filter, active power filter, and hybrid active power filter is presented with a final comparison to assess the merits and demerits of each one. This research achieved a current harmonic limitation of 1.5%. [ABSTRACT FROM AUTHOR]

Residential sector is considered one of the largest consumers of primary energy in the world. The main part of total energy consumption in buildings refers to heating. The study presents a thermodynamic sustainability assessment of different energy sources for residential building heating. The paper presents universal methodology, which can be applied to energy and exergy analysis for all types of buildings. Various options of energy sources were studied, namely: coal, natural gas, electricity, district heating, air-water heat pump, biomass and district heating with a cogeneration. Energy and exergy analyses were conducted and appropriate efficiencies were determined. The calculation of an environmental impact factor and exergetic sustainability index for all types of considered energy sources was performed. The results showed that exergy efficiency was very low in all analyzed cases except for biomass, which leads to poor thermodynamic compatibility of energy quality from the supplied side and the energy used for building heating. It was shown that the highest exergy efficiency was in the case of biomass utilization (about 29%), due to the energy used from renewable energy sources. The minimum environmental impact factor (2.48) and maximum exergetic sustainability index (0.403) were found for the case of biomass utilization. [ABSTRACT FROM AUTHOR]

Microgrids are one of the best solutions to present energy crisis, where the expansions of distributed networks are not feasible. This is achieved with penetration of renewable energy sources along with suitable selection of Energy Storage Systems (ESS).The load demand can be supported with microgrid in the grid connected mode or autonomous mode by suitable sizing of DGs and BESS. Sizing of suitable ESS in terms of its capacity or discharge helps in shaving the peak demand and also maximizes the benefits related to their use. Various advantages to end-users can be provided by microgrid with ESS, like improvement in energy efficiency, minimizing overall energy consumption through distributed generations (DGs) and increasing reliability of power supply to the customers. All these advantages can be achieved by obtaining the optimal microgrid operating cost with ESS. One of the challenging tasks in Microgrids is obtaining optimal energy utilization of DGs to meet the load demand. This can be achieved through proper energy management in the microgrid by obtaining optimal power allocations of DGs and ESS. This paper presents an algorithm for microgrid operating cost minimization for 24 hrs time horizon with optimal power allocation of DGs considering randomness in DGs, with and without BESS. Accelerated particle swarm optimization (APSO), Jaya optimization (JAYA) technique and Linear programming based interior point algorithm (LP-IP) have been applied to minimize the operating cost of microgrid with optimal Energy management while selecting proper size of BESS. Simulation results obtained by PSO, APSO, JAYA and LP-IP solver based algorithms are compared for BESS size and microgrid operating cost for 24 hrs. Results of LP-IP solver based optimization algorithm are proved to be the most effective of all other algorithms in terms of cost reduction. Optimal sizing of BESS with energy management of DGs and BESS reduces the operating cost of microgrid meeting the load criteria. [ABSTRACT FROM AUTHOR]

The importance of renewable energy in the economic structures of countries is increasing and biomass is one of the most widely used renewable energy types. In this paper, the nexus between biomass energy consumption (BEC) and financial development (FD) for developing countries in the period between 1990 and 2018 has been investigated with Konya (2006) bootstrap panel causality tests, Westerlund (2006) panel cointegration with multiple breaks, CCE and AMG panel cointegration estimator are suitable for cross-section dependency and heterogenous panels. According to empirical findings, BEC and FD have cointegrated in the long-run and this relationship is positive. Moreover, the growth hypothesis is valid for Argentina, Bolivia, Mexico, Uruguay and El-Salvador; neutrality hypothesis is valid for Chile, Colombian, Peru, Turkey and Panama. [ABSTRACT FROM AUTHOR]

The increase of renewable energy generation and the integration with the grid brings some difficulties on the power network worldwide. The main problems on the energy providers are surplus or unregulated energy generation like in partially cloudy or fully sunny days. The main faults on the consumer side can be surplus or unregulated energy demand and in such cases, storage requirements exist for this energy to regulate the energy demand and thereby having a hybrid energy system. In this paper, the focus is on the active power control using a hybrid energy storage system (HESS) on the energy generation side by applying bidirectional power converters and maximum power point tracking (MPPT)control using a boost converter. Supercapacitor (SC) technology is proposed in such a hybrid storage system. A photovoltaic powered hybrid system storing the energy in a battery, and an SC is used to solve the big problems in the source and load side. The HESS is designed using bidirectional converters, and the working principles are given. Also, control algorithms for bidirectional converters are investigated with a detailed literature review to define the best solution for the proposed system. The HESS is designed in MATLAB/Simulink using bidirectional converters and simulated for resistive, battery, SC loads, and also combinations of these loads. Further, a newly proposed power-sharing method is investigated to increase the amount of energy stored with SC. Simulation results of the proposed system given and examined to verify the applicability of the idea. [ABSTRACT FROM AUTHOR]

The game theory concept has been adapted for energy management between energy producers and consumers in the presence of renewable energy sources (RES) and electric vehicles (EVs). The objective of the paper is to increase the penetration of renewable energy sources and EVs by the Stackelberg game theory model with real-time pricing. RES are the energy generation sources located near load centers to manage the demand of consumers. The primary objective of EV is transportation, but for managing the energy demand, EV participate in grid operations as a back up source of energy. EV are charged during off-peak hours and discharged to the grid during peak hours. Consumers benefited in terms of higher payoffs to supply energy during peak hours. To increase the payoffs, consumers can shift their appliance operation from high price duration to low price duration and create a new peak energy consumption. To maintain the balance between consumers and utility, an optimization tool is essential. The Stackelberg game theory model is a one leader and N followers' game, the leader first declares the energy price and the follower respond by selecting their best response for energy consumption. The leader can update its strategy again by considering the follower best response to obtain maximum benefits. The process to achieve the best response of the follower and leader is called the Stackelberg nash equilibrium. Objective of energy producers is to supply maximum energy through renewable energy sources and the use of EVs as storage units. The prime objective of consumers is to minimize energy tariff by scheduling the appliances. [ABSTRACT FROM AUTHOR]

Significant increments of energy demand and the need to decarbonize the existing energy systems motivate policymakers to utilize renewable energy resources. Accordingly, this paper suggests a hybrid electricity generation system that operates with wind and municipal solid waste biomass to generate monotonous currents and protect the environment by using a portion of the urban wastes. To select a hybrid power plant location, Z-number data envelopment analysis is employed considering economic, social, environmental, and strategic factors, in addition to reliability of fuzzy data. Furthermore, a routing problem is solved by the particle swarm optimization algorithm to calculate the optimal cost of urban waste gathering. As a case study, the model is applied to thirty-one cities in Iran; Shahrbabak, Meymeh, and Birjand are three cities selected as optimal hybrid power plant locations. Finally, the sensitivity analysis results indicate the importance of globally adopting land cost and distance from power distribution network factors. [ABSTRACT FROM AUTHOR]

This paper tackles the process of energy transition from a transactional perspective. It addresses the governance of energy transition by studying its local actualizations, moving beyond purely technical and normative readings. The paper shows that through the local socio-technological energy systems, sustainability governance filters down to the level of individual, everyday behavior, thus questioning the link between public and private spaces, especially regarding the issue of housing. Going beyond the results commonly yielded by transition studies, which favor large-scale analysis, it details how the discourse of citizen involvement, which often boils down to a mere call to control one's individual energy consumption, conceals environmental inequalities, confirming the socioeconomic divide materialized in deprived areas such as public housing estates or remote rural areas. From a methodological standpoint, the analysis is based on four case studies in Northeast France, in more or less privileged areas, and in both urban and rural environments: the renovation of a heating network in the public housing estate of Cité de l'Ill, north of Strasbourg; the solar energy systems designed for property owners in Plobsheim, a residential suburb of Strasbourg; the energy-efficient equipment set up in a public housing estate in the city of Saint-Dié, in the Vosges; and citizen participation in a cooperative program to finance wind turbines in the small Alsacian city of Saâles, in a mountain rural area. The paper draws on the results of these sociological investigations, carried out using field observations, questionnaires and interviews. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the effect of Energy Performance Certificates (EPCs) on the renovation of buildings. Thus, through the European project ENERFUND, 2 online web-based surveys were conducted in 12 countries of the European Union. It was shown that the results varied significantly both between countries and age groups and, that, on average, EPCs did play a role both in renovation decisions and whether to rent/buy a certain flat. In addition, this paper presents major key drivers and parameters related to energy renovation investment mobilisation and suggests actions that can contribute to the promotion of investments for deep energy renovation of buildings. Furthermore, it highlights potential benefits and effectiveness of using retrofitting online tools, such as the ENERFUND tool, pinpoints market failures in the building sector and provides suggestions on increasing the deep energy renovation market in Europe. [ABSTRACT FROM AUTHOR]

Promoting innovative renewable sources and reinforcing the wind energy market will contribute to preservation of the ecosystem by reducing emissions at global and local levels. The topic of the present paper is the analysis of the legal framework required for wind energy use in the Republic of Serbia. The paper discusses the harmonization of the domestic legislation with the global and European trends in this area as well as the obligations undertaken under international documents ratified within the European integration process. Wind energy use in the Republic of Serbia is far below the level which the country is expected to reach as one of the obligations under the Energy Community Treaty. The proposed measures that should be taken to increase the use of wind energy resources in the Republic of Serbia are legal and administrative measures, financial and investment measures, technology development, capacity building, human resources and infrastructure, awareness raising and education. [ABSTRACT FROM AUTHOR]

Biogas is an energy-efficient and environmentally beneficial technology used as an alternative to biomass energy sources. The objective of this study was to evaluate the traditional biomass energy system in Ethiopia and the National Biogas Program of Ethiopia (NBPE) as an alternative energy system. The study involved key informants, government legislation documents and strategy papers, bio-digester operating households and extensive literature reviews. The article provides a review of relevant literature in terms of both biogas technology and policy documents and related strategies in the Ethiopian context that support the NBPE. The literature review touches on both the technology itself and the policy aspects from within the country, sub-Saharan Africa and Asian countries. Furthermore, the article provides effective use and assessment of the findings for theory and policy of traditional biomass energy systems and biogas technology programmes. We argue that biogas technology is crucial as alternative sources of energy in Ethiopia, specifically for rural areas as it negates the disproportionate use of available traditional energy sources of firewood, cow dung, agricultural residues and charcoal. [ABSTRACT FROM AUTHOR]

This paper provides an empirical analysis of CO2emissions and economic growth, renewable energy consumption, and energy consumption over the period 1975–2014 in Germany. This paper uses the autoregressive distributed lag (ARDL) approach of cointegration test and vector error-correction models. The unit root and cointegration tests show that the long-run relationship between CO2emissions and its determinants. The empirical results show that the findings do not support the environmental Kuznets curve between real GDP and CO2emissions. To estimate the shocks of renewable energy consumptions, the study applies the dynamic test of Impulse Response Function (IRF) under the VAR method. The increasing portion of renewable energy consumption in electricity generation would have no impacts on the environment. However, the hikes of renewable energy sources would incur more cost to electricity producers and shrivel up the growth of economies through the expansionary effect of industry’s consumption and private capital spending in the Germany’s economy. [ABSTRACT FROM AUTHOR]

Sustainable management of energy resources is a challenge which our society faces at economic, environmental and political levels. Smart homes are central in recent technology; however, the smart buildings concept cannot stand on its own. Smart buildings need 'smart consumers', i.e. citizens who interact towards intelligent use of energy. Creating tools to enable citizens to become 'smart consumers' is one crucial factor for energy efficiency and rationalisation of energy and should be combined with promoting smart home initiatives. The paper presents a social-oriented 'meet-in-the-middle' scheme towards smart energy consumption in buildings and a roadmap to efficiently create tools for 'smart consumers'. The wider penetration of ICT tools will facilitate opportunities for citizens' empowerment to collaborate and promote better informed decision-making. [ABSTRACT FROM AUTHOR]

Intermittency in the output power of renewable and green energy sources (RGES) and low inertia of a standalone microgrid (SMG) result in large frequency deviations. Use of energy storage systems (ESSs) alleviate the SMG frequency deviations in an adorable manner but their high cost and low power density calls for alternative sources to balance the mismatch between power supply and demand. In recent years, utilization of the battery of an electric vehicle (EV) to minimize the frequency deviations has gained a lot of attention. Consequently, this paper proposes a robust and newly developed bio-inspired Salp Swarm Optimization (SSO) algorithm based PI-PD cascade controller for load frequency control (LFC) of the SMG integrated with the EVs. To demonstrate the efficacy of the proposed controller, its performance has been compared with other well-known controllers and algorithms considering diverse SMG operating scenarios. Simulation results distinctly prove the superiority of the proposed controller over the other controllers. Also, robustness of the proposed controller has been tested subject to ±50% variation in certain SMG parameters. Results clearly justify the robustness of the proposed controller. Additionally, operational stability of the SMG has been appraised through Eigenvalue and Bode diagram analysis for all the scenarios. [ABSTRACT FROM AUTHOR]

The paper aims to describe which barriers are encountered within the hotel sector with regards to implementing the use of renewable energy sources (RES) taking into account their expenses on energy as well as annual profits. The empirical analysis is based on binary logistic regression models employing data that influence hoteliers' decision for investing in RES. Results support that hoteliers consider economic, institutional and human-related factors as barriers for investing on RES. Policy-makers should consider that perceived barriers towards adopting RES differ between hotels with differing financial and energy performances. These variations are very important to consider in order to effectively address the barriers preventing the diffusion of renewable energy sources so as to reduce the impact of the hotel industry in environmental degradation attributed to energy consumption. [ABSTRACT FROM AUTHOR]

Solar Photovoltaics (PV) is considered a highly competitive technology supporting the transition towards a low-carbon energy system. However, increased shares of its deployment have caused a set of mainly regulatory and financial challenges which require solutions. This paper identifies key research challenges for the further development and deployment of Solar PV, aiming to bridge the gap between expressed market needs and scientific research inquiries. The findings revealed a heterogeneous landscape of Research Priorities and Research Needs focused around the issues of renewable energy sources' variability, the impacts of curtailment, material (re-)use and module efficiency, synergies with the cooling/heating sector, quality criteria and standardisation, as well as new support schemes and business models. These findings can be taken up by academic institutions or technology associations to shape further directions for research. Finally, a list of implications to guide potential end-users involved in the field of policy and practice is provided. [ABSTRACT FROM AUTHOR]

This paper examines long-run and short-run dynamics of renewable energy consumption on carbon dioxide (CO2) emissions and economic growth in the European Union. This study employs cointegration tests, Granger causality tests and vector error correction estimates to examine the direction of Granger causality, the long-run dynamics of economic growth and energy variables on carbon emissions. This study analyses time series data from the World Development Indicators over the period from1961 to 2012. The results of this study support a link between renewable energy consumption, economic growth, industrialization, exports and CO2 emissions in the long-run and short-run. The results support that the sign of the long-run dynamics from the endogenous variables to the CO2 emissions variable is negative and significant, which implies that the energy and environmental policies of the European Union aimed at curbing CO2 emissions must have been effective in the long-term. Furthermore, renewable energy consumption and exports have significant negative impact on CO2 emissions in the short-run. However, industrialization and economic growth have positive impact on CO2 emissions in the short-run. The results suggest that both economic growth and industrialization must have been achieved at the cost of harming the environment. The finding suggests that the increasing consumption of renewable energy tends to play an important role in curbing carbon emissions in the region. [ABSTRACT FROM AUTHOR]

Hydrogen is a clean energy source with a relatively low pollution footprint. However, hydrogen does not exist in nature as a separate element but only in compound forms. Hydrogen is produced through a process that dissociates it from its compounds. Several methods are used for hydrogen production, which first of all differ in the energy used in this process. Investigating the viability and exact applicability of a method in a specific context requires accurate knowledge of the parameters involved in the method and the interaction between these parameters. This can be done using top-down models relying on complex mathematically driven equations. However, with the raise of computational intelligence (CI) and machine learning techniques, researchers in hydrology have increasingly been using these methods for this complex task and report promising results. The contribution of this study is to investigate the state of the art CI methods employed in hydrogen production, and to identify the CI method(s) that perform better in the prediction, assessment and optimization tasks related to different types of Hydrogen production methods. The resulting analysis provides in-depth insight into the different hydrogen production methods, modeling technique and the obtained results from various scenarios, integrating them within the framework of a common discussion and evaluation paper. The identified methods were benchmarked by a qualitative analysis of the accuracy of CI in modeling hydrogen production, providing extensive overview of its usage to empower renewable energy utilization. [ABSTRACT FROM AUTHOR]

Global climate change mitigation action is hampered by systematic under-assessment of national ‘fair shares’, largely on the basis of perceived national interests. This paper aims to inform discussions centred on South Africa’s nationally determined contribution (NDC) by estimating (1) emissions reduction pathways for the country using the Climate Equity Reference Calculator (CERC) assuming a maximum 2°C aggregate warming target and (2) the likely economy-wide net mitigation costs or savings associated with reaching these pathways if known lower-cost mitigation measures, identified through the national mitigation potential analysis, are prioritised. The cumulative net savings associated with achieving the CERC ‘fair share’ emissions pathway, assuming the moderate use of low carbon power generation measures, would reach $5.3 billion by 2030. Net savings could be substantially greater reaching $46.8 billion by 2030 assuming power generation focuses on moving towards full decarbonisation. An unconditional commitment to the mitigation action implied by the ‘fair share’ emissions pathway therefore seems reasonable and prudent purely from the point of view of net country-wide savings. Only if power generation moves towards full decarbonisation would there be a reasonable chance of achieving the more ambitious CERC domestic emissions pathway. However, the significant additional cost associated with achieving the domestic emissions pathway should be conditional on international assistance. Key policy insights South Africa can only achieve its ‘fair share’ of the global mitigation effort if greater use is made of renewable energy options, and can realise significant net savings if it does so. Further emissions reductions would incur costs and require significant upscaling of the share of renewable energy and full implementation of all non-power generation mitigation measures available. Committing to this further mitigation action contingent on international finance would both strengthen the nation’s position in climate negotiations and support the provision of finance for those vulnerable developing nations that bear little or no responsibility for climate change. [ABSTRACT FROM AUTHOR]

In the past decade, district heat networks have emerged as a key strategy for the UK government to achieve its 2050 decarbonization targets. Reports and analyses have focused on the technical and economic challenges of introducing networked heat provision in a country where this is a relatively novel energy service. Meanwhile, there has been little emphasis on the spatial and physical aspects of heat provision and their influence on the spatial development of cities. In this paper, we contribute to current debates on urban energy transitions with insights on the implications of heat networks to cities including scale, density, mixed-use, and materiality. The study reveals the embeddedness of energy services and the emergence of new forms of local governance that combine spatial and energy planning to realize new urban energy landscapes. [ABSTRACT FROM AUTHOR]

This paper describes a methodology for applying geographical information systems (GIS) tools to site a photovoltaic (PV) park inside a sustainable community, in order, not only to meet all siting restrictions, such as environmental protection, but also to operate a PV park more efficiently reducing the shading effect erection and cabling cost. Additionally, the PV operation impact on the grid is investigated, integrating GIS maps into power systems analysis software, such as the PowerWorld®Simulator. In other words, this paper also stresses the importance of GIS for the design, installation and monitoring of power systems. A case study considering the Campus of the Technical University of Crete has been performed showing that siting properly a PV installation meeting 20% of the demand can gain significant savings in both peak and regular energy demands, especially on peak summer days. [ABSTRACT FROM PUBLISHER]

A tidal stream energy resource assessment can be achieved through direct measurements of tidal elevations or flow velocities, theoretical formulas, and numerical models. This paper first described the development of renewable energy in China. Then, the tidal stream energy resource in the Qiantang River Estuary was assessed. The present work established a 2D numerical model for calculating the power density in the estuary and validated it with in situ water level, tidal current, and suspended sediment concentration measurements. Three possible sites found near the Hangzhou Bay Bridge were selected for detailed resource assessment. The results indicated that if only 50 turbines are deployed to each site, the tidal stream energy output by all turbines would be 7.5 GWh/year. Finally, building a tidal stream power generation device into an existing bridge structure was proposed at the Qiantang River Estuary. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) processes allow fabrication of three-dimensional complex parts. Due to the exact amount of material used during the manufacturing step, these new manufacturing processes offer great opportunities for sustainable manufacturing. However, existing studies on these processes focus mainly on energy consumption and information about resources consumptions and waste flows are still lacking. This study aims to quantify with accuracy inventory data of AM processes during the manufacturing step of the life cycle of products. In order to accurately assess the environmental impact of a product, a generic method for acquisitions and characterisation of inventory data for parts made by AM processes is proposed. This methodology focuses not only on the electrical energy consumption but also on material consumption. This paper also describes the development of a parametric process model, which provides to an operator, an accurate estimation of the environmental performances of the fused deposition modelling process. [ABSTRACT FROM AUTHOR]

One of the most serious difficulties facing humanity is the need for a sustainable future. Maintaining nonrenewable energy resources for future generations is a main purpose of sustainability. However, for sustainable future, produced and consumed energy should support human development all social, economic and environmental dimensions. Problems related with environment and energy shortages have put all circles to the task of actively promoting education in energy conservation. Therefore, many countries have started to identify their responsibility for decreasing the unfavorable effect of high energy use on the environment. The primary contribution of this paper will be to ensure energy conservation policy advices to decrease climate change without effecting economic growth for a clean and sustainable energy future. [ABSTRACT FROM AUTHOR]

Thailand's economy is growing rapidly as seen in terms of GDP; according to Thailand is a developing country. So, in industrial sector and logistics are high cost. Around 36% of diesel is spent on the transportation sector, and the amount of oil imported is going up. The Thai government had launched a master plan to increase the stability of the energy situation. This paper studied the biodiesel policy in Thailand. Although the Thai government had launched a plan 8 years back, the plan could not meet its expected target. The policy was then extended to a 15-year plan. The goal is changed, using more biodiesel: 492.75 million liters in 2008 compared with 1642.5 million liters in 2022. The problems are politics, lack of raw materials, standard of specifications, no clear subsidized policy, and farmers' lack technology. [ABSTRACT FROM AUTHOR]

Europe has experienced fast-paced urbanization development over the past three decades. This paper empirically investigates the long-run equilibrium relationships and causal relationships among urbanization, renewable energy consumption, and CO2emissions, and this is important for EU countries’ future sustainable development. DOLS and FMOLS approaches are used for the period 1992–2014 . Granger causality results show that there is a unidirectional relationship from CO2emissions to urbanization, and there is no causality between renewable energy consumption and CO2emissions. The results have important implications for EU policymakers on the path toward a sustainable society. Urbanization can have negative impacts on the natural environment with the net effect being hard in EU countries. [ABSTRACT FROM PUBLISHER]

Oil price hikes can have disruptive effects on the current account balances of oil-importing developing countries, which largely depend on external energy sources for domestic output. Nonetheless, the relation between oil prices and current account has been analyzed only in a limited number of studies for the developing countries. This paper contributes to the literature by examining the dynamics of how oil prices impact the current account in Turkey for the period between 2004 and 2015. For this purpose, a rolling window analysis using an advanced resampling technique, namely maximum entropy boot-strap (meboot), for strongly dependent time series data was performed. The empirical results reveal that oil price fluctuations have considerable effects on Turkey's current account balance. In order to curtail the current account deficit, it is crucial that Turkey redesigns its energy policies and seeks alternative energy sources. [ABSTRACT FROM AUTHOR]

A marginal abatement cost curve (MACC) traces out the relationship between the quantity of pollution abated and the marginal cost of abating each additional unit. In the context of air quality management, MACCs are typically developed by sorting control technologies by their relative cost-effectiveness. Other potentially important abatement measures such as renewable electricity, energy efficiency, and fuel switching (RE/EE/FS) are often not incorporated into MACCs, as it is difficult to quantify their costs and abatement potential. In this paper, a U.S. energy system model is used to develop a MACC for nitrogen oxides (NOx) that incorporates both traditional controls and these additional measures. The MACC is decomposed by sector, and the relative costeffectiveness of RE/EE/FS and traditional controls are compared. RE/EE/FS are shown to have the potential to increase emission reductions beyond what is possible when applying traditional controls alone. Furthermore, a portion of RE/EE/FS appear to be cost-competitive with traditional controls. Implications: Renewable electricity, energy efficiency, and fuel switching can be cost-competitive with traditional air pollutant controls for abating air pollutant emissions. The application of renewable electricity, energy efficiency, and fuel switching is also shown to have the potential to increase emission reductions beyond what is possible when applying traditional controls alone. [ABSTRACT FROM AUTHOR]

Energy consumption of the water sector presents an increasing energy demand, contrary to GHG mitigation aims. As a result, research aimed at capturing emitted CO2and at developing treatment technologies with a low energy demand and increased renewable energy production has increased, leading to a surge in implementation of anaerobic digestion (AD). Valorization of the biogenic CO2emitted with biogas AD (estimated at over 1 MtCO2per annum for the UK water and organic waste sectors), presents an opportunity to further reduce carbon footprint and support energy supply decarburization. This paper reviews bioconversion of CO2into CH4in ADs (without addition of H2) as a means to valorize CO2emissions. The review has concluded this to be a promising solution to reduce carbon footprint and uplift renewable energy production. However, in order to increase readiness for implementation (1) the mechanisms of CO2utilization need to be elucidated, including the sources of additional H2needed, (2) studies need to report more thoroughly the conditions of CO2injection and (3) trials where ADs are integrated with gas to liquid mass transfer technologies need to be performed. [ABSTRACT FROM PUBLISHER]

This paper uses the vector error correction model (VECM) and Granger causality tests to investigate short and long-run relationships between per capita carbon dioxide (CO2) emissions, real gross domestic product (GDP), renewable and non-renewable energy consumption, trade openness ratio and agricultural value added (AVA) in Tunisia spanning the period 1980–2011. The Johansen-Juselius test shows that all our considered variables are cointegrated. Short-run Granger causality tests reveal the existence of bidirectional causalities between AVA and CO2emissions, and between AVA and trade. There are short-run unidirectional causalities running from non-renewable energy and GDP to AVA and to renewable energy, and running from CO2emissions to renewable energy. Interestingly, there are long-run bidirectional causalities between all considered variables. Our long-run parameters estimates show that non-renewable energy, trade and AVA increase CO2emissions, whereas renewable energy reduces CO2emissions. In addition, the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is not supported. Our policy recommendations are to increase international economic exchanges because this gives new opportunities to the agricultural sector to develop and to benefit from renewable energy technology transfer. Subsidizing renewable energy use in the agricultural sector enables it to become more competitive on the international markets while polluting less and contributing to combat global warming. [ABSTRACT FROM PUBLISHER]

This paper employs an integrated model for analysis of energy demand and MARKet ALlocation modelling framework for assessing different pathways for the development of energy systems of Nepal. Four energy scenarios are analysed with the time horizon from 2010 to 2030. With high electrification and energy efficiency and demand-side management, the analysis reveals that all three major goals of sustainable energy for all can be achieved by 2030, but that the total discounted systems costs required account for three times the costs of the reference scenario. In the policy scenario, net fuel import costs and greenhouse gas emissions will decline by 20% and 35%, respectively and the share of renewable energy will increase from 3% in 2010 to 22% in 2030. The analysis provides insights for selecting a better pathway for the sustainable energy development and energy security of the country. [ABSTRACT FROM AUTHOR]