Climate change has become a global phenomenon due to its threat to sustainable development. However, economic development plays a complementary role in both climate change and sustainability. Thus, ...the environmental Kuznets curve hypothesis is critical to climate change policy formulation and development strategies. Accordingly, this study examined the validity of environmental Kuznets curve hypothesis by investigating the relationship between economic growth, energy consumption, financial development, and ecological footprint for the period from 1977 to 2013 in 11 newly industrialized countries. For this purpose, the study employed both augmented mean group (AMG) estimator and heterogeneous panel causality method which are suitable for dependent and heterogeneous panels. The results of the estimator show that there is an inverted U-shaped relationship between economic growth and ecological footprint. According to the causality test results, it is concluded that there is bi-directional causality between economic growth and ecological footprint.
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•This study examines the validity of environmental Kuznets curve hypothesis.•There is bidirectional causality between economic growth and ecological footprint.•The study found a unidirectional causality from economic growth to energy consumption.
The use of Renewable Energy Resources (RER) is growing rapidly for energy generation and several studies indicate that these will have a huge contribution in the future. Selecting RER is a complex ...problem involving different criteria and alternatives. The first aim of the study is the development of an evaluation model to select the most appropriate RER in Turkey. Evaluation of RER alternatives can be seen as a multi criteria decision making (MCDM) problem that can be solved with flexible tools to handle complex situations and assist decision makers (DMs) in mapping out the situation. In this process, Group Decision Making (GDM) involves multiple DMs who have different goals or ways of thinking and can assess the decision process distinctively different from others. Linguistic interval fuzzy preferences with DEMATEL, ANP, TOPSIS integrated techniques are utilized to eliminate uncertainty and to better represent DMs' preferences. The originality of the paper comes from its ability to propose effective and comprehensive evaluation model for both Turkey and literature and apply to a real industrial problem to improve the RER selection process. Another contribution is to adapt integrated techniques including linguistic interval fuzzy preferences with DEMATEL, ANP, TOPSIS for the first time.
•Selecting RER is a complex problem involving different criteria and alternatives.•The aim of the study is the development of an evaluation model to select the most appropriate RER in Turkey.•Linguistic interval fuzzy preferences with DEMATEL, ANP, TOPSIS integrated techniques are utilized.•The proposed approach is applied to a real industrial problem to improve the RER selection process.
In this paper, the energy management of a microgrid including wind turbine, PhotoVoltaic (PV) modules, Combined Heat and Power (CHP) systems, fuel cells, power only units, heat only unit, Plug-in ...Electric Vehicles (PEVs), and thermal energy storage resources for supplying electrical and thermal loads is presented. For achieving a better management on demand side, both price-based and incentive-based Demand Response Programs (DRPs) have been used and their impacts on reducing the operational cost of microgrid in both grid-connected and island modes have been investigated. Also, the uncertainty of price, load, wind speed and solar radiation are taken into account in order to obtain more realistic results. By discretization of Probability Distribution Function (PDF) of each uncertain parameter, a set of scenarios is generated. Then, using a scenario reduction method based on mixed-integer linear optimization, the set of reduced scenarios is obtained. Two-stage stochastic programming approach is used to minimize the operational cost in microgrid energy management. The proposed method for microgrid energy management has been evaluated in three modes: grid-connected, grid-connected with DRPs, and island mode with DRPs.
•Microgrid energy management aimed at reducing the operational cost.•Using wind turbine, PV, CHP, fuel cell, power/heat only, heat buffer tank and PEV.•Using a scenario reduction method based on mixed-integer linear optimization.•The application of price- and incentive-based DRPs in order to manage demand side.
The intermittency introduced by the increasing integration of distributed renewable energy sources is challenging the efficient operation of residential distribution systems. A promising solution to ...tackle this challenge is the implementation of residential demand response through responsive household appliances such as heat pumps, refrigeration devices, and energy storage units. In this article, a peer-to-peer energy trading platform among residential houses is proposed to coordinate demand response schemes and level off potential generation/consumption disturbances in the hour-ahead intraday context. First, the day-ahead and intraday energy management models for residential houses are established considering the characteristics of responsive household appliances and energy storages. The discomfort and possible economic losses for performing demand responses are quantified with respect to the risk preferences of residential customers. The peer-to-peer energy trading platform is developed and a double-auction mechanism employed to promote the collaborative demand response schemes in the face of disturbances. An optimal bidding strategy of residential houses is also proposed. The feasibility of the proposed models and bidding strategy are verified through case studies. It is also illustrated that the residential demand response schemes and intraday peer-to-peer energy trading are effective in managing the uncertainties of load demand and renewable generation.
The electricity and transportation industries are the main sources of greenhouse gas emissions on Earth. Renewable energy, mainly wind and solar, can reduce emission from the electricity industry ...(mainly from power plants). Likewise, next-generation plug-in vehicles, which include plug-in hybrid electric vehicles (EVs) and EVs with vehicle-to-grid capability, referred to as "gridable vehicles" (GVs) by the authors, can reduce emission from the transportation industry. GVs can be used as loads, energy sources (small portable power plants), and energy storages in a smart grid integrated with renewable energy sources (RESs). Smart grid operation to reduce both cost and emission simultaneously is a very complex task considering smart charging and discharging of GVs in a distributed energy source and load environment. If a large number of GVs is connected to the electric grid randomly, peak load will be very high. The use of traditional thermal power plants will be economically and environmentally expensive to support the electrified transportation. The intelligent scheduling and control of GVs as loads and/or sources have great potential for evolving a sustainable integrated electricity and transportation infrastructure. Cost and emission reductions in a smart grid by maximum utilization of GVs and RESs are presented in this paper. Possible models for GV applications, including the smart grid model, are given, and results are presented. The smart grid model offers the best potential for maximum utilization of RESs to reduce cost and emission from the electricity industry.
Renewable energy (RE) is the key element of sustainable, environmentally friendly, and cost-effective electricity generation. An official report by International Energy Agency (IEA) states that the ...demand on fossil fuel usage to generate electricity has started to decrease since year 2019, along with the rise of RE usage to supply global energy demands. Researches on RE technologies are continuously growing in order to enhance the performance of RE generation, especially in term of energy conversion efficiency. The aim of this review paper is to understand and study further the current RE technologies such as solar energy, hydro energy, wind energy, bioenergy, geothermal energy, and hydrogen energy. Several hybrid RE technologies have been also studied and compared, to improve the overall performance of RE in generating electricity. Lastly, suggestions are provided for the purpose to solve and overcome the challenges and limitations of RE technologies in terms of economy, technical, and energy conversion efficiency.
•Comparison between the fossil fuel and renewable energy usage on electricity generation.•Review on current renewable energy technologies implementing in developed and developing countries.•Discuss the obstacles, challenges and policies of renewable energy usage in developing and developed countries.•Provide suggestions and opinions to avail the benefits of current renewable energy applications.
In this paper, optimal cooperative operational planning of distributed energy resources (DER) in an active distribution network (ADN) with soft open points (SOP) has been investigated. To do so, a ...new two-layer coordinated optimization framework ADN has been proposed considering SOP. In the upper layer, the location and sizing of the DERs and SOPs has been optimised. While inner layer executes simultaneous optimal functioning of volt/var control (VVC) devices, remote controlled switches (RCS), DERs, and SOPs. The main objective of proposed methodology is to reduce total investment cost of DERs and SOPs as well as operating costs of the system over the planning horizon. Besides, objective function considers the cost of energy not served (ENS), the cost of substation-purchased electricity, and the cost of carbon emissions. Meanwhile, a stochastic module has been employed to address high-level uncertainties associated to renewables and load demands. Besides, the effects of distribution network reconfiguration (DNR) and conservation voltage reduction (CVR) have been taken into account. For various instances, the suggested framework was implemented on an IEEE 119-bus distribution system and solved using a proposed hybrid optimization solver. The efficacy of proposed DER with SOP methodology has been validated on various cases and also tested on sudden external disturbances such as under voltage and over voltage problem conditions. When compared to standard planning schemes, the test results show that it is beneficial in boosting system efficiency, increasing reliability, and lowering the carbon footprint of distribution systems.
Throughout the world, the threat of climate change is pressing governments to accelerate the deployment of technologies to generate low carbon electricity or heat. But this is frequently leading to ...controversy, as energy and planning policies are revised to support new energy sources or technologies (e.g. offshore wind, tidal, bioenergy or hydrogen energy) and communities face the prospect of unfamiliar, often large-scale energy technologies being sited near to their homes. Policy makers in many countries face tensions between 'streamlining' planning procedures, engaging with diverse publics to address what is commonly conceived as 'NIMBY' (not in my back yard) opposition, and the need to maintain democratic, participatory values in planning systems.
This volume provides a timely, international review of research on public engagement, in contexts of diverse, innovative energy technologies. Public engagement is conceived broadly - as the interaction between how developers and other key actors engage with publics about energy technologies (including assumptions held about the methods used, such as the provision of financial benefits or the holding of deliberative events), and how individuals and groups engage with energy policies and projects (including indirectly through the media and directly through emotional and behavioural responses).
The book's contributors are leading experts in the UK, Europe, North and South America and Australia drawn from a variety of relevant social science disciplinary perspectives. The book makes a significant contribution to our existing knowledge, as well as providing interested professionals, policymakers and members of the public with a timely overview of the critical issues involved in public engagement with low carbon energy technologies.
•DERs are distributed generation, storage,electric vehicles, and demandresponses.•DERs aremodelledusingbothprobabilistic and deterministic methods.•DER optimisation mainly focusses on sizingand ...location toimprove the network.•DER integration commonly involves analysis on the IEEE test feeder.•DERs improve theresilience of the distribution network.
Distributed energy resources (DERs) have gained particular attention in the last few years owing to their rapid deployment in power capacity installation and expansion into distribution systems. DERs mainly involve distributed generation and energy storage systems; however, some definitions also include electric vehicles, demand response strategies, and power electronic devices used for their coupling with power grids. DERs challenge the entire operating system owing to their heterogeneous energy generation from renewable energy sources, the probabilistic nature of electric vehicle charging, and end-user exponential integration of power electronic devices. Research on DER integration has been conducted in the academic and industrial sectors. This study proposes a schematic literature review of DERs, including its modelling, description of deterministic and probabilistic power flow methods, power grid topologies for studies, and impacts of DERs on power grid operation. DERs are primarily modelled using probabilistic approaches. The most frequently optimized DER variables are sizing and location. Meanwhile, the most critical variables to analyse during their integration process to the power grid are voltage profile, frequency response, and charging of both lines and transformers, followed by less-proportional power quality indicators. Overall, DERs can improve the resilience of energy systems because they provide voltage and frequency support, reduce energy losses, enhance power quality indicators, and enhance energy recovery in extreme scenarios such as high-impact low-probability events.
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