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.

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.

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.

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.

Distribution,exploitation,and utilization of intermediate-to-deep geothermal resources in eastern China

The part of China,east of the Hu Huanyong Line,is commonly referred to as eastern China.It is characterized by a high population density and a well-developed economy;it also has huge energy demands.This study assesses and promotes the large-scale development of geothermal resources in eastern China by analyzing deep geological structures,geothermal regimes,and typical geothermal systems.These analyses are based on data collected from geotectology,deep geophysics,geothermics,structural geology,and petrology.Determining the distribution patterns of intermediate-to-deep geothermal resources in the region helps develop prospects for their exploitation and utilization.Eastern China hosts superimposed layers of rocks from three major,global tectonic domainsd namely Paleo-Asian,Circum-Pacific,and Tethyan rocks.The structure of its crust and mantle exhibits a special flyover pattern,with basins and mountains as well as well-spaced uplifts and depressions alternatively on top.The lithosphere in Northeast China and North China is characterized by a thin,low density crust and mantle,whereas the lithosphere in South China has a thin,low density crust and a thick,high density mantle.The middle and upper crust contain geobodies with high conductivity and low velocity,with varying degrees of development that create favorable conditions for the formation and enrichment of geothermal resources.Moderate-to-high temperature geothermal resources are distributed in the MesozoiceCenozoic basins in eastern China,although moderate temperature geothermal resources with low abundance dominate.Porous sandstone reservoirs,karstified fractured-vuggy carbonate reservoirs,and fissured granite reservoirs are the main types of geothermal reservoirs in this region.Under the currently available technical conditions,the exploitation and utilization of geothermal resources in eastern China favor direct utilization over large-scale geothermal power generation.In Northeast China and North China,geothermal resources could be applied for large-scale geothermal heating purposes;geothermal heating could be applied during winter along parts of the Yangtze River while geothermal cooling would be more suitable for summer there;geothermal cooling could also be applied to much of South China.Geothermal resources can also be applied to high value-added industries,to aid agricultural practices,and for tourism.

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.

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.

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.

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.

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.

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.

Fuzzy stochastic long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive honey bee mating optimization

This paper presents a novel modified inter- active honey bee mating optimization （IHBMO） base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources （DERs）. The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting, A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduc- tion in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power orDERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

Data-driven distribution network topology identification considering correlated generation power of distributed energy resource

This paper proposes a data-driven topology identification method for distribution systems with distributed energy resources(DERs).First,a neural network is trained to depict the relationship between nodal power injections and voltage magnitude measurements,and then it is used to generate synthetic measurements under independent nodal power injections,thus eliminating the influence of correlated nodal power injections on topology identification.Second,a maximal information coefficient-based maximum spanning tree algorithm is developed to obtain the network topology by evaluating the dependence among the synthetic measurements.The proposed method is tested on different distribution networks and the simulation results are compared with those of other methods to validate the effectiveness of the proposed method.

Optimal Design of Distributed Energy Resource Systems under Uncertainties Based on Two-Stage Robust Optimization

Distributed energy resource(DER)systems are widely used owing to their excellent economic and environmental performance.However,uncertainties in the system generate difficulties in the optimal design of DER systems.In practice,the distribution of uncertain parameters is generally unknown.In this work,a two-stage robust optimization(RO)model was proposed for the optimal design of DER systems considering uncertainties in renewable energy intensity,energy prices,and load demands.Three uncertainty sets(i.e.,the box,ellipsoid,and convex-hull uncertainty sets)were adopted to describe the distribution of uncertain parameters,and the proposed two-stage RO problem was solved using affine decision rules.A typical hospital in Lianyungang,Jiangsu Province,China,was selected as the case study object,and the effectiveness of the model was verified.The case study results showed that uncertainties in energy prices and load demands have a significant impact on system configuration and economic performance,and mainly affect the installed capacities of gas boilers,absorption chillers,and storages.Uncertainty set will affect the optimization results and an appropriate uncertainty set should be adopted to describe uncertainties precisely and increase accuracy of results.

Availability, Performance and Reliability Evaluation for PV Distributed Generation

Nowadays, renewable energy resources play an important role in replacing conventional energy resources such as fossil fuel by integrating solar, wind and geothermal energy. Photovoltaic energy is one?of?the very promising renewable energy resources which grew rapidly in the past few years, it can be used to produce electric energy through photovoltaic process. The primary objective of the research proposed in this paper is to facilitate the increasing penetration levels of PV systems in the electric distribution networks. In this work, the PV module electrical model is presented based on the mathematical equations and was implemented on MATLAB to simulate the non-linear characteristics I-V and P-V curves with variable input parameters which are irradiance and temperature based on Riyadh region. In addition, the reliability evaluation of distribution networks, including distributed generators of solar photovoltaic (PV) with varying output power capacity is presented also. The Monte Carlo simulation algorithm is applied to test the distribution network which is RBTS Bus 2 and the same has been conducted on the original case of distribution network substation 7029 which is located at KSA Riyadh. The two distribution networks have been modified to include the PV’s distributed generators. The distributed generators contribute to supply a part of the load during normal mode and supply the entire load during component failure or failure of grid operation supply. The PV stochastic models have been used to simulate the randomness of these resources. Moreover, the study shows that the implementation and integration of renewable resources as distributed generations have improved the reliability of the distribution networks.

Development strategy of efficient bio-methane system by focused utilization of distributed biomass

Bio-methane,as a promising renewable green energy,the component and thermal value of which are very close to that of natural gas,indicates an enormous resource potential and could be employed as the alternative of fossil energy through the development of agro-industrial integration and efficient bio-methane system. Establishment of high efficient agro-industrial integrated bio-methane system is an important component of the renewable energy system and also a significant way of emission reduction.