Research on the Impact of New and Renewable Energy Replacing Fossil Energy Resource under Constraint of Carbon Emissions

For studying new and renewable energy as a substitute for fossil energy in primary energy consumption and its impact on carbon emissions to cope with economic uncertainties, a multi-sector DSGE model was employed to simulate the dynamic impact on carbon emissions and macroeconomic development. The structural adjustment of energy consumption and the carbon emissions mitigation policy were considered in the model. The simulation results showed that using new and renewable energy instead of fossil energy is an optimal choice for the firms to comply with the regulations of carbon emission mitigation policy. Structural adjustment of energy consumption is the best route to achieve the dual goal of economic development and carbon emission reduction. Unexpected sharp fall in free carbon quota has a negative impact on the economy.

Hybrid Ensemble-Learning Approach for Renewable Energy Resources Evaluation in Algeria

In order to achieve a highly accurate estimation of solar energy resource potential,a novel hybrid ensemble-learning approach,hybridizing Advanced Squirrel-Search Optimization Algorithm(ASSOA)and support vector regression,is utilized to estimate the hourly tilted solar irradiation for selected arid regions in Algeria.Long-term measured meteorological data,including mean-air temperature,relative humidity,wind speed,alongside global horizontal irradiation and extra-terrestrial horizontal irradiance,were obtained for the two cities of Tamanrasset-and-Adrar for two years.Five computational algorithms were considered and analyzed for the suitability of estimation.Further two new algorithms,namely Average Ensemble and Ensemble using support vector regression were developed using the hybridization approach.The accuracy of the developed models was analyzed in terms of five statistical error metrics,as well as theWilcoxon rank-sum and ANOVA test.Among the previously selected algorithms,K Neighbors Regressor and support vector regression exhibited good performances.However,the newly proposed ensemble algorithms exhibited even better performance.The proposed model showed relative root mean square errors lower than 1.448%and correlation coefficients higher than 0.999.This was further verified by benchmarking the new ensemble against several popular swarm intelligence algorithms.It is concluded that the proposed algorithms are far superior to the commonly adopted ones.

An Overview on Advanced Grid-connected Inverters Used for Decentralized Renewable Energy Resources

并网逆变器是分散式可再生能源接入配电网的重要接口,随着分布式可再生能源渗透率的不断提高,并网逆变器在传统配电网中的地位越发突出。为了高效完成可再生能源分散式并网,并有效降低并网逆变器对电网的冲击,一些在装置上、结构上和功能上更加先进的并网逆变器成为了迫切的需求。针对现有的一些先进并网逆变器进行比较、分析和研究,从装置级、功能级和控制级的角度对现有先进并网逆变器进行综述。给出一些在结构上能更加灵活地将可再生能源分散接入配电网的硬件电路。研究一些适用于可再生能源分散接入的,使并网逆变器能虚拟同步发电机完成自治运行、电能质量治理、系统阻抗检测、网络阻抗控制等辅助控制功能。同时还对并网逆变器的并网同步算法和电流跟踪控制策略进行了探讨。最后,提出一个适合于可再生能源分散并网的先进并网逆变器框架。

Multi-objective planning model for simultaneous reconfiguration of power distribution network and allocation of renewable energy resources and capacitors with considering uncertainties

This research develops a comprehensive method to solve a combinatorial problem consisting of distribution system reconfiguration, capacitor allocation, and renewable energy resources sizing and siting simultaneously and to improve power system's accountability and system performance parameters. Due to finding solution which is closer to realistic characteristics, load forecasting, market price errors and the uncertainties related to the variable output power of wind based DG units are put in consideration. This work employs NSGA-II accompanied by the fuzzy set theory to solve the aforementioned multi-objective problem. The proposed scheme finally leads to a solution with a minimum voltage deviation, a maximum voltage stability, lower amount of pollutant and lower cost. The cost includes the installation costs of new equipment, reconfiguration costs, power loss cost, reliability cost, cost of energy purchased from power market, upgrade costs of lines and operation and maintenance costs of DGs. Therefore, the proposed methodology improves power quality, reliability and security in lower costs besides its preserve, with the operational indices of power distribution networks in acceptable level. To validate the proposed methodology's usefulness, it was applied on the IEEE 33-bus distribution system then the outcomes were compared with initial configuration.

Collaborative optimization model of renewable energy development considering peak shaving costs of various flexibility resources

China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of new energies is the limited flexibility of regulations on power system resources,resulting in insufficient consumption capacity.Thus,the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered.In this study,a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system,comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost,and combining renewable energy output characteristics,load forecasting,grid development,and other factors.For the optimization of various flexible resource utilization methods,a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources.A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation,safety,and environmental protection was proposed.Finally,a certain area of Gansu Province was used as an example to perform detailed analysis and calculation,which demonstrated that the model has an optimal effect.This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations.

Energy Efficient Resource Allocation Approach for Renewable Energy Powered Heterogeneous Cellular Networks

In this paper,maximizing energy efficiency(EE)through radio resource allocation for renewable energy powered heterogeneous cellular networks(HetNet)with energy sharing,is investigated.Our goal is to maximize the network EE,conquer the instability of renewable energy sources and guarantee the fairness of users during allocating resources.We define the objective function as a sum weighted EE of all links in the HetNet.We formulate the resource allocation problem in terms of subcarrier assignment,power allocation and energy sharing,as a mixed combinatorial and non-convex optimization problem.We propose an energy efficient resource allocation scheme,including a centralized resource allocation algorithm for iterative subcarrier allocation and power allocation in which the power allocation problem is solved by analytically solving the Karush-Kuhn-Tucker(KKT)conditions of the problem and a water-filling problem thereafter and a low-complexity distributed resource allocation algorithm based on reinforcement learning(RL).Our numerical results show that both centralized and distributed algorithms converge with a few times of iterations.The numerical results also show that our proposed centralized and distributed resource allocation algorithms outperform the existing reference algorithms in terms of the network EE.

Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and wind.Energy resources are vital for all countries in terms of their economies and politics.As a result,selecting the optimal option for any country is critical in terms of energy investments.Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming.In the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous data.This study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp numbers.The hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective characteristics.The best-suited renewable energy alternative is discovered using the approach presented.

Hybrid Renewable Energy Resources Management for Optimal Energy Operation in Nano-Grid

Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment,unlike non-renewable energy resources.However,they often fail to meet energy requirements in unfavorable weather conditions.The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load.In this paper,an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure.An actual data set comprising information about the load and demand of utility grids is used to evaluate the performance of the proposed nanogrid energy management system.The objective function is formulated to manage the nanogrid operation and implemented using a variant of Particle Swarm Optimization(PSO)named recurrent PSO(rPSO).Firstly,rPSO algorithm minimizes the installation cost for nanogrid.Thereafter,the proposed NEMS ensures cost efficiency for the post-installation period by providing a daily operational plan and optimizing renewable resources.State-of-the-art optimization models,including Genetic Algorithm(GA),bat and different Mathematical Programming Language(AMPL)solvers,are used to evaluate the model.The study’s outcomes suggest that the proposed work significantly reduces the use of diesel generators and fosters the use of renewable energy resources and beneficiates the eco-friendly environment.

China puts more money in renewable energy resources

In 2010, over 300 billion yuan ($47.31 billion) are invested in renewable energy sources in China, outranking every other country. Hence, China has become one of the world’s biggest investors in renewable energy sources.

Tapping Renewable Energy Resources -with A Combined Capacity of 1236 MW as Target for the Year 2000

China began the research and development of renewable energy generation since 1970s, in particular in the Eighth Five-year Plan period, the State made closer attention to the research and development of renewable energy, therefore the technical level, application scale and economic, social benefits have seen greater progress. The combined capacity of renewable energy generation reached 100 MW at the end of 1994. And it is planned a combined capacity of 1236 MW will be targeted for the year 2000.

Counter-Rotating Type Pump-Turbine Unit Stabilizing Momentarily Fluctuating Power from Renewable Energy Resources

It is difficult for renewable energy resources to provide constant power with excellent quality for the grid system. This serial research proposes a power stabilization system with a pumped storage to guarantee power quality and capacity, while the outputs from the energy resources are at unstable and/or fluctuating conditions. The power stabilization system with a counter-rotating type pump-turbine unit was prepared and operated at the pumping and the turbine modes. The unit composed of the tandem impellers/runners connected to the inner and the outer armatures of the unique motor/generator. The experiments have verified that this type pump-turbine unit is reasonably effective to stabilize momentarily/instantaneously the fluctuating power from the renewable energy resources.

Intelligent Fractional-Order Controller for SMES Systems in Renewable Energy-Based Microgrid

An autonomous microgrid that runs on renewable energy sources is presented in this article.It has a supercon-ducting magnetic energy storage(SMES)device,wind energy-producing devices,and an energy storage battery.However,because such microgrids are nonlinear and the energy they create varies with time,controlling and managing the energy inside them is a difficult issue.Fractional-order proportional integral(FOPI)controller is recommended for the current research to enhance a standalone microgrid’s energy management and performance.The suggested dedicated control for the SMES comprises two loops:the outer loop,which uses the FOPI to regulate the DC-link voltage,and the inner loop,responsible for regulating the SMES current,is constructed using the intelligent FOPI(iFOPI).The FOPI+iFOPI parameters are best developed using the dandelion optimizer(DO)approach to achieve the optimum performance.The suggested FOPI+iFOPI controller’s performance is contrasted with a conventional PI controller for variations in wind speed and microgrid load.The optimal FOPI+iFOPI controller manages the voltage and frequency of the load.The behavior of the microgrid as a reaction to step changes in load and wind speed was measured using the proposed controller.MATLAB simulations were used to evaluate the recommended system’s performance.The results of the simulations showed that throughout all interruptions,the recommended microgrid provided the load with AC power with a constant amplitude and frequency.In addition,the required load demand was accurately reduced.Furthermore,the microgrid functioned incredibly well despite SMES and varying wind speeds.Results obtained under identical conditions were compared with and without the best FOPI+iFOPI controller.When utilizing the optimal FOPI+iFOPI controller with SMES,it was found that the microgrid performed better than the microgrid without SMES.

Lightweight innovation ADIs help development of renewable energy and new technology industries in China

The world is undergoing profound changes in energy and technology.Countries are vigorously developing new sustainable energy sources and technologies.Renewable energy sources encompass various technologies such as wind turbines,solar energy,nuclear energy,and bioenergy.Additionally,emerging technology fields include new energy vehicles,robots,and artificial intelligence devices,among others.The renewable energy industries and implementation of new technologies necessitate the development and adoption of new equipment and components.Austempered ductile iron(ADI)is renowned for its unique microstructure and superior properties.By utilizing ADI,lightweight and innovative castings can be designed to not only reduce weight but also save energy and decrease emissions.More importantly,these castings enhance the efficiency and reliability of new energy equipment and emerging technology installations.This paper describes the development,applications,and future prospects of lightweight and innovative ADI castings within sectors such as solar photovoltaic(PV),wind power generation,industry robots,and trucks in China.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Hydroelectric and Hydrogen Storage Systems for Electric Energy Produced from Renewable Energy Sources

Renewable energy sources are essential formitigating the greenhouse effect and supplying energy to resource-scarce regions.However,their intermittent nature necessitates efficient storage solutions to enhance system efficiency and manage energy costs.This paper investigates renewable and clean storage systems,specifically examining the storage of electricity generated from renewable sources using hydropower plants and hydrogen,both of which are highly efficient and promising for future energy production and storage.The study utilizes extensive literature data to analyze the impact of various parameters on the cost per kWh of electricity production in hybrid renewable systems incorporating hydropower and hydrogen storage plants.Results indicate that these hybrid systems can store electricity efficiently and cost-effectively,with production costs ranging from 0.126 to 0.3$/kWh for renewablehydropower systems and 0.118 to 0.42$/kWh for renewable-hydrogen systems,with expected cost reductions over the next decade due to technological advancements and increased market adoption.The novelty of this study lies in its comprehensive comparison of hybrid renewable systems integrating hydropower and hydrogen storage,providing detailed cost analysis and future projections.It identifies key parameters influencing the cost and efficiency of these systems,offering insights into optimizing storage solutions for renewable energy.Moreover,this research underscores the potential of hybrid systems to reduce dependency on fossil fuels,particularly during peak demand periods,and emphasizes the importance of seasonal and geographic considerations in selecting energy sources.The study highlights the importance of policy support and investment in hybrid renewable systems and calls for further research into optimizing these systems for different seasonal and geographic conditions.Overall,the integration of renewable energy sources with hydropower and hydrogen storage offers a promising pathway to a sustainable,economical,and resilient energy future.

Characteristics of Biopellets Manufactured from Various Lignocellulosic Feedstocks as Alternative Renewable Energy Sources

The increased valorization of renewable and cost-effective lignocellulosic feedstocks represents a viable,sustainable,and eco-friendly approach toward the production of biopellets as alternative energy sources.The aim of this research work was to investigate and evaluate the feasibility of using various lignocellulosic raw materials,i.e.,raru(Cotylelobium melanoxylon),mangrove(Rhizophora spp.),sengon(Paraserianthes falcataria),kemenyan toba(Styrax sumatrana),oil palm(Elaeis guineensis),manau rattan(Calamus manan),and belangke bamboo(Gigantochloa pruriens)for manufacturing biopellets with different particle sizes.The raw materials used were tested for their moisture content,specific gravity,ash,cellulose,and lignin content.In addition,thermal analyses,i.e.,calorific values,thermogravimetric analysis(TGA),and differential scanning calorimetry(DSC),were performed.The following properties of the biopellets produced were investigated:moisture content,volatile matter,ash content,fixed carbon,density,and thermal analyses.Based on an analysis of the raw materials,raru had the lowest moisture content(12%)and ash content(1.5%)and the highest specific gravity(1.2).Markedly,palm oil stem had the highestα-cellulose(55%)and lignin(37%)content.In accordance with the SNI 8675:2018 standard requirements,biopellets with optimal properties(moisture content of 1.4%,ash content of 0.79%,density of 1.09 g/m^(3),calorific value of 4672 cal/g,and TGA residue of 13.9%),were manufactured from raru wood.

Renewable Energy: Prospects and Challenges in Bangladesh

Among expert scientists and politicians, there is increasing agreement that it is absolutely necessary to reduce the emission of greenhouse gas (GHG) to lessen the severity of climate change. Although little, renewable energy sources currently reduce GHG that are being emitted from the energy industries. According to the majority of long-term energy estimates, renewable energy will be a substantial addition to the supply of energy worldwide by the end of this century, as capacity of renewable energy is gradually increasing in the early decades. However, developing nations like Bangladesh are largely reliant on pricey imported energy supplies (coal, gas, and oil) that lay a heavy weight on the country’s economy. Also, air pollution growing in importance as a national and international environmental issue. Regarding the development of clean and sustainable energy, renewable energy sources seem to be among the most practical and efficient alternatives, in both Bangladesh and globally. The geographic advantages of Bangladesh allow for widespread usage of the majority of such renewable energy sources. The comparative potential and use of fossil fuels against renewable energy sources globally and in Bangladesh is explored in this review.

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

Estimation of Landfill Gas and Its Renewable Energy Potential from the Polesgo Controlled Landfill Using First-Order Decay (FOD) Models

Methane generation in landfills and its inadequate management represent the major avoidable source of anthropogenic methane today. This paper models methane production and the potential resources expected (electrical energy production and potential carbon credits from avoided CH4 emissions) from its proper management in a municipal solid waste landfill located in Ouagadougou, Burkina Faso. The modeling was carried out using two first-order decay (FOD) models (LandGEM V3.02 and SWANA) using parameters evaluated on the basis of the characteristics of the waste admitted to the landfill and weather data for the site. At the same time, production data have been collected since 2016 in order to compare them with the model results. The results obtained from these models were compared to experimental one. For the simulation of methane production, the SWANA model showed better consistency with experimental data, with a coefficient of determination (R²) of 0.59 compared with the LandGEM model, which obtained a coefficient of 0.006. Thus, despite the low correlation values linked to the poor consistency of experimental data, the SWANA model models methane production much better than the LandGEM model. Thus, despite the low correlation values linked to the poor consistency of the experimental data, the SWANA model models methane production much better than the LandGEM V3.02 model. It was noted that the poor consistency of the experimental data justifies these low coefficients, and that they can be improved in the future thanks to ongoing in situ measurements. According to the SWANA model prediction, in 27 years of operation a biogas plant with 33% electrical efficiency using biogas from the Polesgo landfill would avoid 1,340 GgCO2e. Also, the evaluation of revenues due to electricity and carbon credit gave a total revenue derived from methane production of US$27.38 million at a cost of US$10.5/tonne CO2e.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.