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.

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.

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.

Spatiotemporal characteristics of wind energy resources from 1960 to 2016 over China

In the paper,daily near-surface wind speed data from 462 stations are used to study the spatiotemporal characteristics of the annual and seasonal mean wind speed(MWS)and effective wind energy density(EWED)from 1960 to 2016,through the methods of kriging interpolation,leastsquares,correlation coefficient testing,and empirical orthogonal function(EOF)analysis.The results show that the annual MWS is larger than 3 m s-1 and the EWED is larger than 75 W m-2 in northern China and parts of coastal areas.However,the MWS and EWED values in southern China are all smaller than in northern China.Over the past 50 years,the annual and seasonal MWS in China has shown a significant decreasing trend,with the largest rate of decline in spring for northern China and winter for coastal areas.The annual MWS in some areas of Guangdong has an increasing trend,but it shows little change in southwestern China,South China,and west of Central China.Where the MWS is high,the rate of decline is also high.The main spatial distributions of the annual MWS and the annual EWED show high consistency,with a decreasing trend year by year.The decreasing trend of wind speed and wind energy resources in China is mainly related to global warming and land use/cover change.

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.

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.

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.

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.

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.

Evaluation Method for Offshore Wind Energy Resources Using Scatterometer and Weibull Parameters

The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaWinds-derived Weibull mean wind speed and energy density by considering uncertainties inherent in SeaWinds wind speed estimates. In this study, 1159 SeaWinds-derived wind speeds covering the KEO buoy are used for estimating two Weibull parameters, scale and shape. On the other hand, observed wind speeds from 2004 to 2008 at the KEO buoy are used for simulating three kinds of wind speeds in order to quantify some uncertainties inherent in SeaWinds-derived wind speeds. It is found that uncertainties associated with wind speed estimates （operational wind speed range, sampling time） show small differences in scale, shape and Weibull mean wind speed except energy density among the simulated datasets. Furthermore, the upper and lower bounds of 90% confidence interval corresponding to SeaWinds number of observations indicate 4-2.5% error of Weibull mean wind speed and 4-6.8% error of energy density, respectively.

Reinforcement Learning with Enhanced Safety for Optimal Dispatch of Distributed Energy Resources in Active Distribution Networks

As numerous distributed energy resources(DERs)are integrated into the distribution networks,the optimal dispatch of DERs is more and more imperative to achieve transition to active distribution networks(ADNs).Since accurate models are usually unavailable in ADNs,an increasing number of reinforcement learning(RL)based methods have been proposed for the optimal dispatch problem.However,these RL based methods are typically formulated without safety guarantees,which hinders their application in real world.In this paper,we propose an RL based method called supervisor-projector-enhanced safe soft actor-critic(S3AC)for the optimal dispatch of DERs in ADNs,which not only minimizes the operational cost but also satisfies safety constraints during online execution.In the proposed S3AC,the data-driven supervisor and projector are pre-trained based on the historical data from supervisory control and data acquisition(SCADA)system,effectively providing enhanced safety for executed actions.Numerical studies on several IEEE test systems demonstrate the effectiveness and safety of the proposed S3AC.

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.

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.

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.

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.

Wind energy and wave energy resources assessment in the East China Sea and South China Sea

In this paper, the third-generation wave model WAVEWATCH-Ⅲ （WW3） was used to simulate the wave field of the East China Sea and South China Sea from January 1988 to December 2009, with wind input of CCMP wind field. Then, the wind energy density and wave energy density were calculated by using the simulated 22-years＇ wave-field data and CCMP data. By synthetically considering the size of energy density, the frequency of energy level and the stability of energy density, the resources of wind energy and wave energy in the East China Sea and South China Sea were analyzed and regionalized. The result can be a guide to searching location of wind ＆ wave power plant.

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.