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.

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.

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.

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.

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.

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.

Protection coordination in distribution systems with and without distributed energy resources-a review

Emission of greenhouse gases and depletion of fossil fuel reserves are two key drivers,which are forcing the mankind to generate the future energy demand from the renewable energy resources.These resources are generally distributed in nature and are directly integrated at distribution levels.Increasing penetration of the distributed energy resources in distribution power networks creates additional operational and control issues.These are mostly regulatory,economical load dispatching,power quality and protection issues.Generally power distribution systems are protected with the help of dedicated over current based protection schemes.But increasing share of distributed energy resources penetration in electric utilities poses a serious threat to the existing protection coordination schemes of the distribution systems.Distributed energy resources connected distribution networks become interconnected in nature and protection coordination schemes,which are designed for unidirectional flow of fault currents become ineffective/non-functional.Therefore,new protection coordination schemes are required for providing the adequate protection coordination for distributed energy resources connected electric power networks.In the available literature,the protection coordination schemes for radial distribution systems and developments in the area of protection coordination are discussed in detail.A thorough review for all these protection coordination schemes for distribution systems with and without distributed energy resources is done in this review article.It includes the analytical and artificial intelligence based techniques application for coordination of protective relays in the distribution systems.The limitations and research gaps in the area of protection coordination schemes are also presented in this review article.The aim of this research paper is to bring all the available research in the area of relay coordination on one platform,so that it will help the emerging researcher to identify the future scope of relay coordination application for distributed energy resources connected distribution systems.

Will auctioning promote the renewable energy generation in China?

Renewable energy generation,as part of the global effort to mitigate climate change,will play a central role in reducing greenhouse gas emissions and achieving China's goal of carbon emissions peak before 2030 and carbon neutral before 2060.However,the impact of carbon quota auctions on renewable energy generation has not been sufficiently discussed.The main purpose of this study is to investigate whether China can rely on quota auctions to increase renewable energy generation in the short term,and to demonstrate which is more effective in promoting renewable energy development,policy enforcement or auction constraints?The improved neo-trans-log production model,the multiobjective linear programming model and the dispatch heuristic were used to predict additional emission reduction cost,optimized power mix with different auctioning rates,with economic development,technological progress and the unique characteristics of China's power generation industry being taken into consideration.The results show that the auctioning rate will have little influence on the optimized energy production structure,especially on the share of renewable energy resources;when the total on-grid electricity generation ranges from 7625 to 7926 billion kW h and the auctioning rate ranges from 0% to 5%,policy enforcement will influence the generation of renewable energy to a greater extent than auctioning in the near future.

Situation of China's solar water heater industry,related national standards,testing and the Golden Sun certification program

China is the largest solar water heater producer and market in the world.Despite the fast growth and an installed capacity that accounts for the majority of the global gross,China's per capita solar hot water capacity is still very low,implying a huge margin of market potential;and the recognition of the industry in the global market is handicapped by the scattered scale of production and inconsistent product quality.To ensure continued growth of China's solar water heating(SWH) industry,Chinese Government has established a series of national SWH standards,three national testing centers,and a certification program to lay the foundation for the development of the Golden Sun product labeling system.China General Certification Center(CGC) developed the Golden Sun product certification and labeling system on a pass/fail basis evaluating with established criteria.The system was designed to help manufacturers acclimate to explicit consistent requirements and to identify and fix the deficiencies in the design and execution of the program itself.Timely revision and integration of the national standards are recommended to accommodate the test procedures and requirements to new technologies and the evolving SWH market.Strict implementation of the Golden Sun certification and labeling system are suggested to avail improving the quality control and forging internationally reputable brands of Chinese solar water heating products.

Future of Architecture: Buildings as Power Plants

After the energy crisis in 1970s,buildings began to be used as a platform for the elements which produce energy from renewable energies to return them into energy producing power plants.This is a safe,clean and economic way to produce energy since the energy is produced where it is needed and they use renewable energy resources.So,it promises hope for the future energy production.Therefore,the aim of this study is to examine buildings which produce electricity by using renewable energy resources and to show that this is one of the safest,cleanest and most economic ways to be used to produce energy in the future.This is done by describing power plants and how buildings are used as power producing stations by the use of renewable energy resources or other energy producing materials,then by examining case studies which are constructed and already being used,case studies which are just a design that have not yet been constructed,and by making projections to the future energy producing techniques that are just a proposal in 2021.In the conclusion,buildings are proposed as the future power plants,either here on earth or on another planet like Mars.

Assessment of renewable energy:Status,challenges,COVID-19 impacts,opportunities,and sustainable energy solutions in Africa

Today’s more focus and efforts are being put by all the energy leaders towards power generation using renewable energy resources.Fortunately,these resources are becoming affordable to facilitate a swift shift towards green and clean energy.Possible strategic assets are an add-on for all the developing nations in terms of economy.The technological advancement and power market revolution resulting in an adequate reduction of renewable energy cost and affordability.This paper mainly focusing on Covid-19 impacts in the African energy sector.Also,analyzing recent developments in African renewable energy generation that holds the immense capacity for im-provisation.This paper highlighting the recommendations in response to the COVID-19 pandemic for the African renewable energy sector.This paper is a result of rigorous analysis based on major issues governing sustainable solutions for Africa.This review paper comes up with effective conclusions to address the challenges in the cur-rent pandemic situation.In Africa abundance of resources is found with huge potential for the generation of power.But still,Africa undergoing a phase of serious crises because they are not able to tap its huge capital of renewable energies.There is a subsequent need for power grid restructuring,energy storage technologies,and parallel mitigation of environmental factors with seasonal variations.Proposed review analysis bringing a better opportunity for all issues towards sustainable solutions,that will ease the renewable energy status in Africa.It is observed that there is an inevitable need to focus on having strong government policy frameworks and proper regulations.The various recommendations are required to swing towards renewable energy development.Com-bined efforts are required in luring foreign investments and to address feasible issues like setting-up targets.This paper demonstrated a smart energy system using a proposed machine learning-based framework for enhancing the PV forecasting and up-gradation in available technologies.

Provision of Ramp-rate Limitation as Ancillary Service from Distribution to Transmission System:Definitions and Methodologies for Control and Sizing of Central Battery Energy Storage System

The variability of the output power of distributed renewable energy sources(DRESs)that originate from the fastchanging climatic conditions can negatively affect the grid stability.Therefore,grid operators have incorporated ramp-rate limitations(RRLs)for the injected DRES power in the grid codes.As the DRES penetration levels increase,the mitigation of high-power ramps is no longer considered as a system support function but rather an ancillary service(AS).Energy storage systems(ESSs)coordinated by RR control algorithms are often applied to mitigate these power fluctuations.However,no unified definition of active power ramps,which is essential to treat the RRL as AS,currently exists.This paper assesses the various definitions for ramp-rate RR and proposes RRL method control for a central battery ESS(BESS)in distribution systems(DSs).The ultimate objective is to restrain high-power ramps at the distribution transformer level so that RRL can be traded as AS to the upstream transmission system(TS).The proposed control is based on the direct control of theΔP/Δt,which means that the control parameters are directly correlated with the RR requirements included in the grid codes.In addition,a novel method for restoring the state of charge(So C)within a specific range following a high ramp-up/down event is proposed.Finally,a parametric method for estimating the sizing of central BESSs(BESS sizing for short)is developed.The BESS sizing is determined by considering the RR requirements,the DRES units,and the load mix of the examined DS.The BESS sizing is directly related to the constant RR achieved using the proposed control.Finally,the proposed methodologies are validated through simulations in MATLAB/Simulink and laboratory tests in a commercially available BESS.

Bi-level Energy Trading Model Incorporating Large-scale Biogas Plant and Demand Response Aggregator

Increasing intermittent renewable energy sources(RESs)intensifies the imbalance between demand and generation,entailing the diversification of the deployment of electrical energy storage systems(ESSs).A large-scale biogas plant(LBP)installed with heating devices and biogas energy storage(BES)usually exhibits a storage-like characteristic of accommodating an increasing penetration level of RES in rural areas,which is addressed in this paper.By utilizing the temperature-sensitive characteristic of anaerobic digestion that enables the LBP to exhibit a storage-like characteristic,this paper proposes a bi-level energy trading model incorporating LBP and demand response aggregator(DRA)simultaneously.In this model,social welfare is maximized at the upper level while the profit of DRA is maximized at the lower level.Compared with cases only with DRA,the results show that the proposed model with the LBP improves the on-site accommodation capacity of photovoltaic(PV)generation up to 6.3%,18.1%,and 18.9%at 30%,40%,and 50%PV penetration levels,respectively,with a better economic performance.This nonlinear bi-level problem is finally recast by a single-level mathematical program with equilibrium constraints(MPEC)using Karush-Kuhn-Tucker(KKT)conditions and solved by the Cplex solver.The effectiveness of the proposed model is validated using a 33-bus test system and a sensitivity analysis is provided for analyzing what parameter influences the accommodation capacity most.

Stochastic processes in renewable power systems: From frequency domain to time domain

With the increasing penetration of renewable energy resources(RESs), the uncertainties of volatile renewable generations significantly affect the power system operation. Such uncertainties are usually modeled as stochastic variables obeying specific distributions by neglecting the temporal correlations. Conventional approaches to hedge the negative effects caused by such uncertainties are thus hard to pursue a trade-off between computation efficiency and optimality. As an alternative, the theory of stochastic process can naturally model temporal correlation in closed forms. Attracted by this feature, our research group has been conducting thorough researches in the past decade to introduce stochastic processes within renewable power systems. This paper summarizes our works from the perspective of both the frequency domain and the time domain, provides the tools for the analysis and control of power systems under a unified framework of stochastic processes, and discusses the underlying reasons that stochastic process-based approaches can perform better than conventional approaches on both computational efficiency and optimality. These work may shed a new light on the research of analysis, control and operation of renewable power systems.Finally, this paper outlooks the theoretic developments of stochastic processes in future’s renewable power systems.

Optimal configuration analysis for a campus microgrid—a case study

The foremost issues of 21st century are challenging demand of electrical energy and to control the emission of Green House Gases(GHG)emissions.Renewable energy resources based sustainable microgrid emerges as one of the best feasible solution for future energy demand while considering zero carbon emission,fossil fuel independency,and enhanced reliability.In this paper,optimization and implementation of institutional based sustainable microgrid are discussed based on cost analysis,carbon emission,and availability of energy resources.Various microgrid topologies are considered for addressing the most ideal solution.The metrological data such as irradiance is acquired from solar satellite data of NASA(National Aero Space Agency)while the data for wind speed is taken from synergy enviro engineer’s site.HOMER®simulation tool is used for modelling and optimization purpose.