Wave Energy Resource Availability Assessment in the Philippines Based on 30-Year Hindcast Data

With the goal of evaluating the wave and wave energy conditions in the Philippines,the simulated wave nearshore(SWAN)model was used to estimate the wavefield using 30 years of cross-calibrated multi-platform(CCMP)wind field data(1987-2016).The spatiotemporal patterns of annual and monthly averaged significant wave heights and wave energy in the Philippines were analyzed based on the simulated data.Results showed that they had similar values;in particular,significant wave heights and wave energy were smaller in the south and southwest and higher in the north and northeast.A total of 12 representative points along the Philippine coast were selected to draw wave and wave energy roses.A directional analysis showed that the dominant wave was in the north north-east(NNE),northeast(NE),and east north-east(ENE)directions.Wave energy was mainly distributed in regions with an energy period between 1 and 10 s and significant wave heights between 0 and 4 m.To better utilize wave energy data in the Philippines,this paper studied the available and rich area of wave energy and analyzed the annual and monthly variability index of wave energy in the country.Moreover,the available significant wave heights of wave energy conversion devices(WECs)were set as 0.5-4 m,and the maximum annual average available wave energy occurred in the eastern Philippine Sea area,reaching 13 kW m^(-1).For the safety of WECs,extreme typhoon-induced wave conditions must be considered.Furthermore,the results showed that the maximum significant wave height and mean period over the 50-year return period reached 18 m and 15 s,respectively.

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.

Distribution Network Optimization Model of Industrial Park with Distributed Energy Resources under the Carbon Neutral Targets

Taking an industrial park as an example,this study aims to analyze the characteristics of a distribution network that incorporates distributed energy resources(DERs).The study begins by summarizing the key features of a distribution network with DERs based on recent power usage data.To predict and analyze the load growth of the industrial park,an improved back-propagation algorithm is employed.Furthermore,the study classifies users within the industrial park according to their specific power consumption and supply requirements.This user segmentation allows for the introduction of three constraints:node voltage,wire current,and capacity of DERs.By incorporating these constraints,the study constructs an optimization model for the distribution network in the industrial park,with the objective of minimizing the total operation and maintenance cost.The primary goal of these optimizations is to address the needs of DERs connected to the distribution network,while simultaneously mitigating their potential adverse impact on the network.Additionally,the study aims to enhance the overall energy efficiency of the industrial park through more efficient utilization of resources.

Prediction of Sedimentary Microfacies Distribution by Coupling Stochastic Modeling Method in Oil and Gas Energy Resource Exploitation

In view of the problem that a single modeling method cannot predict the distribution of microfacies, a new idea of coupling modeling method to comprehensively predict the distribution of sedimentary microfacies was proposed, breaking the tradition that different sedimentary microfacies used the same modeling method in the past. Because different sedimentary microfacies have different distribution characteristics and geometric shapes, it is more accurate to select different simulation methods for prediction. In this paper, the coupling modeling method was to establish the distribution of sedimentary microfacies with simple geometry through the point indicating process simulation, and then predict the microfacies with complex spatial distribution through the sequential indicator simulation method. Taking the DC block of Bohai basin as an example, a high-precision reservoir sedimentary microfacies model was established by the above coupling modeling method, and the model verification results showed that the sedimentary microfacies model had a high consistency with the underground. The coupling microfacies modeling method had higher accuracy and reliability than the traditional modeling method, which provided a new idea for the prediction of sedimentary microfacies.

An assessment of global ocean wave energy resources over the last 45 a

Against the background of the current world facing an energy crisis,and human beings puzzled by the problems of environment and resources,developing clean energy sources becomes the inevitable choice to deal with a climate change and an energy shortage.A global ocean wave energy resource was reanalyzed by using ERA-40 wave reanalysis data 1957–2002 from European Centre for Medium-Range Weather Forecasts（ECMWF）.An effective significant wave height is defined in the development of wave energy resources（short as effective SWH）,and the total potential of wave energy is exploratively calculated.Synthetically considering a wave energy density,a wave energy level probability,the frequency of the effective SWH,the stability and long-term trend of wave energy density,a swell index and a wave energy storage,global ocean wave energy resources were reanalyzed and regionalized,providing reference to the development of wave energy resources such as wave power plant location,seawater desalination,heating,pumping.

A wave energy resource assessment in the China's seas based on multi-satellite merged radar altimeter data

Wave energy resources are abundant in both offshore and nearshore areas of the China＇s seas. A reliable assessment of the wave energy resources must be performed before they can be exploited. First, for a water depth in offshore waters of China, a parameterized wave power density model that considers the effects of the water depth is introduced to improve the calculating accuracy of the wave power density. Second, wave heights and wind speeds on the surface of the China＇s seas are retrieved from an AVISO multi-satellite altim-eter data set for the period from 2009 to 2013. Three mean wave period inversion models are developed and used to calculate the wave energy period. Third, a practical application value for developing the wave energy is analyzed based on buoy data. Finally, the wave power density is then calculated using the wave field data. Using the distribution of wave power density, the energy level frequency, the time variability indexes, the to-tal wave energy and the distribution of total wave energy density according to a wave state, the offshore wave energy in the China＇s seas is assessed. The results show that the areas of abundant and stable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, southeast of Taiwan in the China＇s seas; the wave power density values in these areas are approximately 14.0–18.5 kW/m. The wave energy in the China’s seas presents obvious seasonal variations and optimal seasons for a wave energy utilization are in winter and autumn. Except for very coastal waters, in other sea areas in the China＇s seas, the energy is primarily from the wave state with 0.5 m≤Hs≤4 m, 4 s≤Te≤10 s whereHs is a significant wave height andTe is an energy period; within this wave state, the wave energy accounts for 80% above of the total wave energy. This characteristic is advantageous to designing wave energy convertors （WECs）. The practical application value of the wave energy is higher which can be as an effective supplement for an energy con-sumption in some areas. The above results are consistent with the wave model which indicates fully that this new microwave remote sensing method altimeter is effective and feasible for the wave energy assessment.

The temporal and spatial patterns and potential evaluation of China＇s energy resources development

The issue of China＇s energy supply security is not only the key problem which af- fects China＇s rapid and sustainable development in the 21st century, but also the one which international attention focuses on. Based on the notable characteristic of spatial imbalance between energy production and consumption in China, this paper takes the evolution of China＇s primary energy resources development（excluding hydropower） from 1949 to 2007 as the study object, with the aim to sum up the evolutive characteristics and laws of China＇s energy resources development in the past nearly 60 years. Then, based on comprehensive considerations of coal＇s, oil＇s and natural gas＇s basic reserves, qualities, geological conditions production status, and ecological service function of every province, this paper adopts development potential index （DP）to evaluate the development potential of every province＇s en- ergy resources, and divide them into different ranks. Conclusions are drawn as follows： （1） Generally speaking, China＇s gross energy production was increasing in waves from 1949 to 2007. From the viewpoint of spatial patterns, China＇s energy resources development has shown a characteristic of ＂concentrating to the north and central areas, and evolving from linear-shaped to ＂T-shaped＂ pattern gradually since 1949. （2） The structure evolution of China＇s energy resources development in general has shown a trend of ＂coal proportion is dominant but decreasing, while oil and gas proportions are increasing＂ since 1949. （3） At the provincial scale, China＇s energy resources development potential could be divided into large, sub-large, general and small ranks, four in all. In the future, the spatial pattern of China＇s energy production will evolve from ＂T-shaped＂ to ＂R-shaped pattern＂. These conclusions will help to clarify the temporal and spatial characteristics and laws of China＇s energy resources development, and will be beneficial for China to design scientific and rational energy development strategies and plans, coordinate spatial imbalance of energy production and consumption, ensure national energy supply, avoid energy resources waste and disorderly development, and promote regional sustainable development under the globalization back-ground with changeful international energy market.

Gini Coefficient-based Task Allocation for Multi-robot Systems With Limited Energy Resources

Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.

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.

Discussion on the Assessment Method of Wind Energy Resources by Using Regional Meteorological Data

The exploitation status of wind energy resources was analyzed, and the distribution of wind energy resources and regional meteorological stations were introduced, and then the assessment method of wind energy resources by using data from regional meteorological station was studied taking Huangjin Regional Meteorological Station in Xinning County in Hunan Province for example, besides, corresponding software was compiled. By means of SQL database and program, the method was used simply and easily and had positive meaning for the development of wind energy resources and excavation of wind farm in inland region.

Study on wave energy resource assessing method based on altimeter data——A case study in Northwest Pacific

Wave energy resource is a very important ocean renewable energy. A reliable assessment of wave energy resources must be performed before they can be exploited. Compared with wave model, altimeter can provide more accurate in situ observations for ocean wave which can be as a novel method for wave energy assessment.The advantage of altimeter data is to provide accurate significant wave height observations for wave. In order to develop characteristic and advantage of altimeter data and apply altimeter data to wave energy assessment, in this study, we established an assessing method for wave energy in local sea area which is dedicated to altimeter data.This method includes three parts including data selection and processing, establishment of evaluation indexes system and criterion of regional division. Then a case study of Northwest Pacific was performed to discuss specific application for this method. The results show that assessing method in this paper can assess reserves and temporal and spatial distribution effectively and provide scientific references for the siting of wave power plants and the design of wave energy convertors.

Evaluation of shallow geothermal energy resources in the Beijing-Tianjin- Hebei Plain based on land use

To discover the characteristics,distribution and potential of shallow geothermal energy in the Beijing-Tianjin-Hebei Plain area.This paper,based on a large amount of data collection and field investigations,evaluateed the shallow-layer geothermal energy in the study area through the analytic hierarchy process and comprehensive index method.Based on suitability zoning results superimposed with 1:100000 land use data,the study area is divided into encouraged,controlled,restricted and prospective mining areas regarding the development of shallow geothermal energy,and the economic availability of shallow geothermal energy in the encouraged and controlled areas are evaluated.The results show that the shallow geothermal energy in the Beijing-Tianjin-Hebei Plain can meet the heating and cooling demand of 6×10^(8) m2 of buildings,equivalent to 1.15×10^(7) t of standard coal,thus reducing carbon dioxide emissions by 2.73×10^(7) t and reducing sulfur dioxide emissions by 1.95×10^(5) t.According to the development and utilization mode,the energy demand level and the Beijing-Tianjin-Hebei coordinated development plan,the development and utilization of geothermal resources in the plain area has two types:Urban concentrated mining areas and rural scattered mining areas.The scale and level of intensive utilization of regional geothermal resources are of great significance.

Spectroscopy framework and review of characterization of energy resource sites

Site characterization and rapid reliable identification of energy resources play a key role for future efficient energy production.Over the last several decades,many laboratory and in-situ techniques were developed to qualitatively and quantitatively characterize the sites and minerals.Despite the advancements,there are still many challenges associated with exploration,rapid detection,and spatial interpolation of the energy resources within a site.Spectroscopy techniques offer solutions to the current ongoing efforts on site characterization,exploration and collection of resources,quality control monitoring during production,and reclamation of the production sites due to environmental contamination.Spectral analysis has shown great promise in providing in-situ measurements that are comparable to arduous laboratory physio-chemical analysis.Spectroscopy is a fairly new technology in some sectors and has seen limited use but has shown great potential in exceeding the minimum standards implemented.This paper presents review of the current spectroscopy techniques that have been used in the agriculture,landfill,nuclear power,mining,and ground contamination industries with respect to the production of energy.A general overview of how spectral analysis techniques are being used to benefit each of these sectors along with some of the drawbacks associated with each is presented.Three frameworks including basic process,operation flowchart,minimum number of tests to be performed,and information on spatial interpolation analysis are presented.These frameworks along with the basic processes can be implemented for characterization of energy resource sites。

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.

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.

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.

Impact of Cascade Disconnection of Distributed Energy Resources on Bulk Power System Stability:Modeling and Mitigation Requirements

This work presents a new approach to establishing the minimum requirements for anti-islanding protection of distributed energy resources(DERs)with focus on bulk power system stability.The proposed approach aims to avoid cascade disconnection of DERs during major disturbances in the transmission network and to compromise as little as possible the detection of real islanding situations.The proposed approach concentrates on the rate-of-change of frequency(RoCoF)protection function and it is based on the assessment of dynamic security regions with the incorporation of a new and straightforward approach to represent the disconnection of DERs when analyzing the bulk power system stability.Initially,the impact of disconnection of DERs on the Brazilian Interconnected Power System(BIPS)stability is analyzed,highlighting the importance of modeling such disconnection in electromechanical stability studies,even considering low penetration levels of DERs.Then,the proposed approach is applied to the BIPS,evidencing its benefits when specifying the minimum requirements of anti-islanding protection,without overestimating them.

Modeling and management performances of distributed energy resource for demand flexibility in Japanese zero energy house

Zero-energy buildings(ZEBs)can contribute to decarbonizing building energy systems,while the energy mismatch between energy demand and on-site stochastic generation in ZEBs increases the need for energy flexibility.This study proposed mixed-integer linear programming energy management schemes for optimizing the flexible scheduling of distributed energy resources,including battery energy storage,heat pump,and building thermal mass as a passive thermal energy storage system.With optimally designed objectives,this study used case studies to evaluate the flexibility potential provided by the demand-side management,considering dynamic characteristics of the process.The results showed that the proposed demand-side management for battery storage offers significant potential in increasing photovoltaic(PV)self-consumption and reducing operational costs.Cost reduction ratios of flexible dispatch of combined PV and battery storage systems exceed 15%.Flexible coupling of PV and heat pump systems for meeting hot water demand can reduce energy cost by more than 20%.The flexible coupling of the heat pump and PV system also had a significant impact on the power consumption pattern of domestic heat pumps,the load-shifting potential highly depends on the available PV generation and hot water demand.The optimal trade-off between thermal energy use and thermal comfort violation may not reduce the total energy used for space heating,the increased PV consumption helped reduce grid imports.The study provides insights into the energy flexibility behavior and efficiency of the proposed demand-side management for ZEBs,which is expected to provide guidelines for exploring demand-side flexibility.

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.