A SOLVABLE ONE-DIMENSIONAL ALLOCATION DECISION MODEL OF RENEWABLE RESOURCES

In the paper, the determinate atlecation decision model and the probabilistic allocation decision model of a kind of renewable resource are separatly studied by means of dynamic programming, and the optimal allocation policy is given under some special conditions.

OPTIMAL DYNAMICAL BALANCE HARVESTING FOR A CLASS OF RENEWABLE RESOURCES SYSTEM

An optimal utilization problem for a class of renewable resources system is investigated. Firstly, a control problem was proposed by introducing a new utility function which depends on the harvesting effort and the stock of resources.Secondly, the existence of optimal solution for the problem was discussed. Then, using a maximum principle for infinite horizon problem, a nonlinear four-dimensional differential equations system was attained. After a detailed analysis of the unique positive equilibrium solution, the existence of limit cycles for the system is demonstrated. Next a reduced system on the central manifold is carefully derived, which assures the stability of limit cycles. Finally significance of the results in bioeconomics is explained.

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.

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.

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.

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.

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.

Comparative Analysis of Reaction to Fire and Flammability of Hemp Shives Insulation Boards with Incorporated Microencapsulated Phase Change Materials

Nowadays buildings contain innovative materials,materials from local resources,production surpluses and rapidly renewable natural resources.Phase Change Materials(PCM)are one such group of novel materials which reduce building energy consumption.With the wider availability of microencapsulated PCM,there is an opportunity to develop a new type of insulating materials,combinate PCM with traditional insulation materials for latent heat energy storage.These materials are typically flammable and are located on the interior wall finishing yet there has been no detailed assessment of their fire performance.In this research work prototypes of low-density insulating boards for indoor spaces from hemp shives using carbamide resin binder and cold pressing were studied.Bench-scale cone calorimeter tests were conducted to evaluate fire risk,with a focus on assessing material flammability properties and the influence of PCM on the results.In this research,the amount of smoke,heat release rate,effective heat of combustion,specific extinction coefficient,mass loss,carbon dioxide yield,specific loss factor,ignition time of hemp straws samples and samples of hemp straws with 10%and without PCM admixture were compared.There is a risk of flammability for PCM and their fire reaction has not been evaluated when incorporating PCM into interior wall finishing boards.The obtained results can be used by designers to balance the potential energy savings of using PCM with a more complete understanding and predictability of the associated fire risk when using the proposed boards.It also allows for appropriate risk mitigation strategies.

Virtual Power Plants for Grid Resilience: A Concise Overview of Research and Applications

The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.

Energy Economic Dispatch for Photovoltaic-Storage via Distributed Event-Triggered Surplus Algorithm

This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices.This method integrates features including photovoltaic(PV)systems,energy storage coupling,varied energy roles,and energy supply and demand dynamics.The systemmodel is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously.To strike a balance between optimality and feasibility,renewable energy resources are modeled with considerations for forecasting errors,Gaussian distribution,and penalty factors.Furthermore,this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production costs.Rooted in surplus theory and finite time projection,the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality constraints.The algorithm greatly reduces the communication burden through event triggering mechanism.Finally,both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm.

Status of Renewable Energy Applications in the Malaysian Energy Mix

Demand for power in Malaysia is projected to double the current demand in 2030. The current fuel mix for power generation is heavily dependent on fossil fuels. This has created energy supply and environmental sustainability concerns to the industry. Furthermore, at the recent United Nations Climate Change Conference 2009-15th Conference of Parties （COP15）, Malaysia had given the commitment to voluntary reduction of up to 40% in terms of emissions intensity of GDP by the year 2020 compared to 2005 levels. Renewable energy （RE） provides the best alternative in addressing these issues. In 2001, RE was regarded as the fifth fuel in the new Five Fuel Strategy of the National Energy Policy. Small Renewable Energy Program （SREP） was launched with the main objective of supporting the government＇s strategy to intensify the development of RE as the fifth fuel resource. Biomass, the largest amongst the main RE resources available, can be used for heat and power generation. With optimum utilization, the value ofbiomass resources in Malaysia is estimated to be more than RM 500 billion （USD 156 billion） over the next 20 years. Malaysia has the capacity to use renewable energy resources to address the national energy agenda.

Study of the development road map of China’s renewable energy

Renewable energy (RE) has been attached high attention around the world due to its carbon-free and indigenous production in a sustainable way. China enjoys plenty of renewable energy resources, particularly the wind, solar, hydro- and biomass energy, which could be a sound basis for a large-scale exploitation. This report examines the current status of RE technology and industry, analyzes the challenges of promoting RE in China. In order to pave the way for a long-term development of RE, this paper outlines the basic principles and priorities for individual RE technology. In line with these, the paper puts forward the RE targets and further describes the RE road map by 2020, 2030 and extend to 2050, taking consideration of China’s RE resources, industrial basis and energy demand etc. At last, this paper provides some recommendations to ensure the achievements of the RE targets.

Study on the Possibility of Raw Seawater into Beverage—Using Ethanol as a Renewable Resource

In COVID-19 pandemic in the world, alcohol (ethanol) can be listed as a sterilizing disinfectant. It absolutely played a Messianic function on the sterilization effect. And it is said that it has one more function called “salinity reduction” but that function is not widely known. The two functions (Sterilization & Salinity Reduction) mentioned above are extremely important regarding the theme of “raw seawater into beverage” in this study. It is thought that if the two functions are achieved other water quality items such as NO-2 and other items can be cleared with comparative ease. To put briefly the feature of modern waterworks in a word, it can be said that “source of water is river water and its sterilization is chlorine”. In this study, we set up it with a completely new sanitization method (great reset), that is, “source of water is mixtures (seawater and rainwater) and its sterilization is ethanol”. And it can be also expected that the capture and storage of ethanol as a renewable resource is basically possible by utilizing sunlight as a natural power. Therefore, we think that this resolves itself into a question of the choice (sense of value/culture) of the users. It means that how users finally balance out with three factors, i.e., cost, risk (safety) and benefit. Based on the viewpoint mentioned above, we examined the possibility of raw seawater into beverage using ethanol as a renewable resource to create humankind’s wisdom to the settlement (breakthrough) of the water scarcity in the world including Asia and Africa. As a result, we have obtained the new findings that suggest the possibility of raw seawater into beverage using ethanol as a renewable resource.

Optimizing Decision-Making of A Smart Prosumer Microgrid Using Simulation

Distributed renewable energy sources offer significant alternatives for Qatar and the Arab Gulf region’s future fuel supply and demand.Microgrids are essential for providing dependable power in difficult-to-reach areas while incorporating significant amounts of renewable energy sources.In energy-efficient data centers,distributed generation can be used to meet the facility’s overall power needs.This study primarily focuses on the best energy management practices for a smart microgrid in Qatar while taking demandside load management into account.This article looked into a university microgrid in Qatar that primarily aimed to get all of its energy from the grid.While diesel generators are categorized as a dispatchable distributed generation with energy storage added to handle solar radiation from the sun and high grid power operating costs in the suggested scenario,wind turbines and solar Photovoltaic(PV)are classified as non-dispatchable distributed generators.The resulting linear math issues are assessed and displayed in MATLAB optimization software using a mixed-integer linear programming(MILP)strategy.According to the simulation results,the suggested energy management strategy reduced the university microgrid’s grid power costs by 38.8%,making it an affordable solution which is somehow greater than the prior case scenario’s 23%savings.The installed solar system capacity’s effects on the economy,society,and finances were also assessed,and it became clear that the best option for the smart microgrid was determined that would be 325 kW of solar PV,25 kW of wind turbine,and 600 kW of diesel generators,respectively.Given the current situation,university administrators are urged to participate in distributed generators and adopt cutting-edge designs for energy storage technologies due to the significant environmental and financial benefits.

Graphene-Based Active Tunable Metasurfaces for Dynamic Terahertz Absorption and Polarization Conversion

Simultaneous broadband absorption and polarization conversion are crucial in many practical applications,especially in terahertz communications.Thus,actively tunable metamaterial systems can exploit the graphene-based nanomaterials derived from renewable resources because of the flexible surface conductivity and selective permeability of the nanomaterials at terahertz frequencies.In this paper,we propose a graphene-based active tunable bifunctional metasurface for dynamic terahertz absorption and polarization conversion.The graphene ring presents a certain opening angle(A)along the diagonal of the xoy plane.When A=0°,the proposed metasurface behaves as a broadband absorber.Numerical results show the feasibility of achieving this polarization-insensitive absorber with nearly 100%absorptance,and the bandwidth of its 90%absorptance is 1.22 THz under normal incidence.Alternatively,when A=40°after optimization,the proposed metasurface serves as a broadband polarization convertor,resulting in robust broadband polarization conversion ratio(PCR)curves with a bandwidth surpassing 0.5 THz in the reflection spectrum.To tune the PCR response or the broad absorption spectrum of graphene,we change the Fermi energy of graphene dynamically from 0 to 0.9 eV.Furthermore,both the broadband absorption and the linear polarization conversion spectra of the proposed metasurface exhibit insensitivity to the incident angle,allowing large incident angles within 40°under high-performance operating conditions.To demonstrate the physical process,we present the impedance matching theory and measure electric field distributions.This architecture in the THz frequency range has several applications,such as in modulators,sensors,stealth,and optoelectronic switches.THz wave polarization and beam steering also have broad application prospects in the field of intelligent systems.

Studies on the Evolutionary Laws and Maintaining Mechanism of Renewability of the Yellow River's Water Resources

The Yellow River has a vast catchment area and historically it is the mother river of the Chinese nation. Now it serves as one of the main theatres for the on-going national campaign to develop China's western hinterland.……

Stochastic Security-constrained Unit Commitment Considering Electric Vehicles, Energy Storage Systems, and Flexible Loads with Renewable Energy Resources

In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming(MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency.

Optimal Day-ahead Dynamic Pricing of Grid-connected Residential Renewable Energy Resources Under Different Metering Mechanisms

Nowadays,grid-connected renewable energy resources have widespread applications in the electricity market.However,providing household consumers with photovoltaic(PV)systems requires bilateral interfaces to exchange energy and data.In addition,residential consumers’contribution requires guaranteed privacy and secured data exchange.Dayahead dynamic pricing is one of the incentive-based demand response methods that has substantial effects on the integration of renewable energy resources with smart grids and social welfare.Different metering mechanisms of renewable energy resources such as feed-in tariffs,net metering,and net purchase and sale are important issues in power grid operation planning.In this paper,optimal condition decomposition method is used for dayahead dynamic pricing of grid-connected residential renewable energy resources under different metering mechanisms:feed-intariffs,net metering,and net purchase and sale in conjunction with carbon emission taxes.According to the stochastic nature of consumers’load and PV system products,uncertainties are considered in a two-stage decision-making process.The results demonstrate that the net metering with the satisfaction average of 68%for consumers and 32%for the investigated electric company leads to 28%total load reduction.For the case of net purchase and sale mechanism,a satisfaction average of 15%for consumers and 85%for the electric company results in 11%total load reduction.In feed-in-tariff mechanism,in spite of increased social welfare,load reduction does not take place.

Covalent modification of multiwalled carbon nanotubes with a low molecular weight chitosan

Covalent modification of shortened multiwalled carbon nanombes （MWNTs） with a natural low molecular weight chitosan （LMCS） was accomplished by the nucleophilic substitution reaction. The LMCS modified MWNTs （MWNT-LMCS） were characterized by FTIR, solid-state ^13C NMR, and XPS spectroscopies, thermogravimetric analysis, and transmission electron microscopy. The results revealed that amino and primary hydroxyl groups of the LMCS participated mainly in the formation of the MWNT-LMCS conjugates. The MWNT-LMCS consists of 58 wt.% LMCS, and about four molecular chains of the LMCS were attached to 1000 carbon atoms of the nanotube sidewalls. As a novel derivative of the MWNTs, the MWNT-LMCS not only solved in DMF, DMAc and DMSO, but also in aqueous acetic acid solution.

Homogeneous modification of carbon nanotubes with cellulose acetate

An efficient strategy that comprised shorten, chain extension, active groups introducing and homogeneous reaction tactics, was adopted to modify multiwalled carbon nanotubes （MWNTs） with cellulose acetate （CA）. Specially, by utilizing 2,4,6-trichloro- 1,3,5-triazine, a reactive intermediate of the MWNTs （MWNT-triazine） was obtained. Suitable solubility of the MWNT-triazine helps make the homogeneous modification become reality. Detailed characterizations further verified that reaction between chloride atoms in the MWNT-triazine and hydroxyl groups in the CA had contributed to the formation of MWNT-CA conjugates. The novel MWNT-CA consists of carbon （76.3%）, oxygen （18.4%） and nitrogen （5.3%）. With a nanotube-attached CA content of 42.8 wt%, the MWNT-CA is readily soluble in DMSO, NMP, DMF and DMAc. Confirmation of the CA-based modification route might lead to studies aiming for specific sorption and isolation.