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.

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.

Multi-agent Based Protection on Highly Dominated Distributed Energy Resources

Highly penetration of Distributed Energy Resources (DER) on the grid systems nowadays makes the systems grow dynamically. The system become more complex and the protection system become more complicated. The protection relay should accommodate the system changes according to the system conditions and topologies. As part of developmental aspect of Distributed Artificial Intelligent, Multi Agent System (MAS) is a challenging method for improving the intelligent properties of relay protection. This paper introduces the use of MAS approach on radial distribution system protection dominated with DER using dispersed adaptive rule-based protection supported by distributed database agent. The simulation results confirmed that the proposed algorithm can respond within 15.05 ms.

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.

An IEEE 1547-Based Power Conditioner Test System for Distributed Energy Resources

Power conditioner, that is responsible for electric power conversion, is a critical component used in many renewable energy power generation systems. Most of the electric power produced by distributed energy resources cannot directly import to utility network without power conversion. Meanwhile, power conversion may includes several different types, for example AC/DC, and DC/AC, which is realized by a variety types of power conditioners in the electric power system. Currently, many concerns are focused on the operation of these power conditioners used in distributed energy resources due to the worse designing may cause the terrible influence on safety and performance characteristic of distributed energy resources. The power quality and reliability of interconnected electric power network may be affected as well. In the view of this, IEEE standards board provides a uniform standard for interconnection of distributed resources with electric power systems. It provides requirements relevant to the performance, operation, testing, safety considerations, and maintenance of the interconnection. Based on the IEEE 1547 standard, this paper presents a test system for power conditioners that are used in distributed energy resources or other renewable energy applications. Some of the test items that described in IEEE 1547.1 relevant to interconnection issues can be realized by proposed test system.

Blockchain-assisted virtual power plant framework for providing operating reserve with various distributed energy resources

The paradigm shift from a coal-based power system to a renewable-energy-based power system brings more challenges to the supply-demand balance of the grid.Distributed energy resources(DERs),which can provide operating reserve to the grid,are regarded as a promising solution to compensate for the power fluctuation of the renewable energy resources.Small-scale DERs can be aggregated as a virtual power plant(VPP),which is eligible to bid in the operating reserve market.Since the DERs usually belong to different entities,it is important to investigate the VPP operation framework that coordinates the DERs in a trusted man-ner.In this paper,we propose a blockchain-assisted operating reserve framework for VPPs that aggregates various DERs.Considering the heterogeneity of various DERs,we propose a unified reserve capacity evaluation method to facilitate the aggregation of DERs.By considering the mismatch between actual available reserve capacity and the estimated value,the performance of VPP in the operating reserve market is improved.A hardware-based experimental system is developed,and numerical results are presented to demonstrate the effectiveness of the proposed framework.

Supply modes for renewable-based distributed energy systems and their applications:case studies in China

Distributed energy systems(DES),as an integrated energy system with coupled distributed energy resources,have great potential in reducing carbon dioxide emissions and improving energy efficiencies.Considering the background of urbanization and the energy revolution in China,the study investigates the renewable-based DESs supply modes and their application in China.A new method is proposed to classify DESs supply modes into three categories considering the renewable resource in domination,and their application domains are discussed.A comprehensive model is given for economic and environmental evaluation.Typical case studies show that the renewable-based DES systems can supply the energy in a cost-effective and environment-friendly way.Among them,the biomass waste dominated supply mode can not only achieve"zero"carbon emissions but also"zero"energy consumption,even though not yet economically attractive under the present policy and market conditions.Thus,recommendations are given to promote the further deployment of renewable-based DESs,regarding their supply modes,policy requirements,and issues to be addressed.

Collaborative Multiple Access And Energy-Efficient Resource Allocation in Distributed Maritime Wireless Networks

With the rapid increasing of maritime activities, maritime wireless networks(MWNs) with high reliability, high energy efficiency, and low delay are required. However, the centralized networking with fixed resource scheduling is not suitable for MWNs due to the special environment. In this paper,we introduce the collaborative relay communication in distributed MWNs to improve the link reliability, and propose an orthogonal time-frequency resource block reservation based multiple access(RRMA) scheme for both one-hop direct link and two-hop collaborative relay link to reduce the interference. To further improve the network performance, we formulate an energy efficiency(EE) maximization resource allocation problem and solve it by an iterative algorithm based on the Dinkelbach method. Finally, numerical results are provided to investigate the proposed RRMA scheme and resource allocation algorithm, showing that the low outage probability and transmission delay can be attained by the proposed RRMA scheme. Moreover,the proposed resource allocation algorithm is capable of achieving high EE in distributed MWNs.

Design and Analysis of a 24 Vdc to 48 Vdc Bidirectional DC-DC Converter Specifically for a Distributed Energy Application

The design of a bidirectional dc-dc power converter specifically for a distributed energy application is presented. The existing two different DC voltage battery bank of the distributed generation needs to interlink each other using a bi-directional dc-dc converter in order to minimize the unbalance of the output load currents of the three inverters connected to electric grid system. Through this connection, a current can flow from one system to another or vice versa depending on which systems need the current most. Thus, unbalanced currents of the grid line have been minimized and the reliability and performance of the DER grid connected system has been increased. A detailed mathematical analysis of the converter under steady state and transient condition are presented. Mathematical models for boost and buck modes are being derived and the simulink model is constructed in order to simulate the system. Moreover, the model has been validated on the actual operation of the converter, showing that the simulated results in Matlab Simulink are consistent with the experimental ones.

Comparative Analysis for Evaluating Wind Energy Resources Using Intelligent Optimization Algorithms and Numerical Methods

Statistical distributions are used to model wind speed,and the twoparameters Weibull distribution has proven its effectiveness at characterizing wind speed.Accurate estimation of Weibull parameters,the scale(c)and shape(k),is crucial in describing the actual wind speed data and evaluating the wind energy potential.Therefore,this study compares the most common conventional numerical(CN)estimation methods and the recent intelligent optimization algorithms(IOA)to show how precise estimation of c and k affects the wind energy resource assessments.In addition,this study conducts technical and economic feasibility studies for five sites in the northern part of Saudi Arabia,namely Aljouf,Rafha,Tabuk,Turaif,and Yanbo.Results exhibit that IOAs have better performance in attaining optimal Weibull parameters and provided an adequate description of the observed wind speed data.Also,with six wind turbine technologies rating between 1 and 3MW,the technical and economic assessment results reveal that the CN methods tend to overestimate the energy output and underestimate the cost of energy($/kWh)compared to the assessments by IOAs.The energy cost analyses show that Turaif is the windiest site,with an electricity cost of$0.016906/kWh.The highest wind energy output is obtained with the wind turbine having a rated power of 2.5 MW at all considered sites with electricity costs not exceeding$0.02739/kWh.Finally,the outcomes of this study exhibit the potential of wind energy in Saudi Arabia,and its environmental goals can be acquired by harvesting wind energy.

GRU-integrated constrained soft actor-critic learning enabled fully distributed scheduling strategy for residential virtual power plant

In this study,a novel residential virtual power plant(RVPP)scheduling method that leverages a gate recurrent unit(GRU)-integrated deep reinforcement learning(DRL)algorithm is proposed.In the proposed scheme,the GRU-integrated DRL algorithm guides the RVPP to participate effectively in both the day-ahead and real-time markets,lowering the electricity purchase costs and consumption risks for end-users.The Lagrangian relaxation technique is introduced to transform the constrained Markov decision process(CMDP)into an unconstrained optimization problem,which guarantees that the constraints are strictly satisfied without determining the penalty coefficients.Furthermore,to enhance the scalability of the constrained soft actor-critic(CSAC)-based RVPP scheduling approach,a fully distributed scheduling architecture was designed to enable plug-and-play in the residential distributed energy resources(RDER).Case studies performed on the constructed RVPP scenario validated the performance of the proposed methodology in enhancing the responsiveness of the RDER to power tariffs,balancing the supply and demand of the power grid,and ensuring customer comfort.

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.

Decoding the Einstein-Type Formula for Reducing Energy Conversion to Carbon Emissions in Renewables Systems

This article explores the role of distributed energy resources such as efficient solar cells that drive carbon neutrality within the solar energy. For example, the perovskite solar cells offer high efficiency and potential for low-cost production. A novel theoretical model is discovered in distributed energy resources for power emissions and cost. The smart carbon neutrality approaches are analyzed in both theory and experiments. The advantages, current challenges, and future prospects of the related solutions are discussed methodically. By addressing stability and scalability issues, these approaches can contribute significantly to reducing carbon emissions and promoting sustainable energy solutions.

智能营销研究概述(四)——DER带来的变革

分布式能源(DER)的快速发展和大规模应用将给智能营销带来新的机遇和挑战。基于智能电网技术路线提出DER发展展望,引入计及分布式发电单元的3级控制信息管理、电量消纳原理、虚拟营销、需求侧引导等全新概念,重点阐述其对智能营销带来的变革。最后针对我国智能电网发展愿景、能源利用等热点问题对DER参与下的智能营销做深入思考,提出其建模、接入权等问题,探讨了包含DER框架下的智能营销发展前景和研究方向。

基于IEC 61850-7-420标准的DER通信及控制通用接口设计与实现

为了提高分布式能源通信及控制功能的扩展性与互操作性,针对分布式能源的信息模型构建与信息交互,提出了一种基于IEC 61850-7-420标准的分布式能源通信及控制通用接口,给出了通用接口具体的设计与实现方法。开发了通用接口实际的智能电子设备,并基于构建的多分布式能源集成测试平台,对分布式能源通信及控制功能进行了相应的实验测试。研究结果表明,通用接口的设计与实现方法切实可行,分布式能源在其状态信息、设置、控制以及测量/计量值等方面能够实现快速、准确的信息交互,为分布式能源系统集成提供有效的技术手段和解决方案。

基于序电流故障分量的含DER点状网络逆功率保护新方法

点状网络具有较高的供电可靠性,且有利于分布式电源(distributed energy resource,DER)接入;但DER宽限接入后会引起中压馈线频繁出现功率倒送,现有的点状网络逆功率保护无法适应,限制了DER接入容量。根据DER出力波动性与点状网络故障引起的电流变化特征,提出了基于序电流故障分量及其功率方向的逆功率保护新方法。分析了点状网络中不同位置发生各种短路故障时的序分量特征,利用序电流突变量作为启动元件判断系统运行状态,通过序功率方向确定故障位置,在保证保护动作性能的基础上突破对DER接入容量限制;给出了序电流突变量启动定值以及各序功率方向的动作区间。建模仿真结果证明,该保护方法能够实现高供电可靠性与DER友好接入的有机统一。

考虑风光不确定性的虚拟电厂合作博弈调度及收益分配策略

虚拟电厂(virtual power plant,VPP)通过先进的控制技术高效聚合容量小、数量多的分布式能源(distributed energy resource,DER)参与电力市场交易。随着DER数量的增加,其出力的波动性以及聚合后的收益问题需要解决。基于此,提出一种在日前电力市场下,多类型DER聚合于VPP的协同博弈调度模型。首先,提出多类型DER聚合于VPP的运营框架。其次,由于风光出力的不确定性严重影响系统的运行,建立基于变分模态分解(variational modal decomposition,VMD)和改进的双向多门控长短期记忆(bidirectional multi gated long short-term memory,Bi-MGLSTM)网络的组合预测模型。然后,同类型DER形成联盟,并以售电收益最大化为目标,构建VPP多联盟的合作博弈调度模型,为实现联盟及成员间收益分配的公平性,设计多因素改进shapley值法和基于奇偶循环核仁法的两阶段细化收益分配方案。最后,算例结果表明,所提方法能有效提高风光功率的预测精度,实现VPP内联盟间合作互补运行,保证了多个主体间收益分配的公平性与合理性。

分布式能源利用的经济性与环境影响研究——基于DER-CAM模型

分布式供能系统是一种先进的供能系统,具有高效、环保、经济等特点,在降低建筑能耗方面潜力巨大。采用DER-CAM模型模拟我国不同气候区的商业建筑分布式能源的经济性与环境影响,得到多技术集成优化能有效减排降本、政策引导与经济刺激会促进分布式能源技术应用等启示,为我国能源合理规划、适宜技术选择以及提升能源效率及经济性提供参考。

GEOTHERMAL RESOURCES ASSESSMENT AND NUMERICAL SIMULATION IN TUANBO REGION

This paper mainly deals with the reservoir on the heat and mass transfer and mass and energy balance in a geothermal field.On the basis of briefing the general characteristics of the reservoir and the supposition of the reservoir modeling,the paper emphasizes the mathematical descriptions of hydra thermal transportation and convection by two methods according to the different models,such as lumped parameter model and distributed parameter model.It is effective to use these models in simulating the heterogeneous,and anisotropical fracture reservoir for the designed lifetime of 15 years.

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.