Battery Energy Storage System and Demand Response Based Optimal Virtual Power Plant Operation

With certain controllability of various distribution energy resources (DERs) such as battery energy storage system (BESS), demand response (DR) and distributed generations (DGs), virtual power plant (VPP) can suitably regulate the powers access to the distribution network. In this paper, an optimal VPP operating problem is used to optimize the charging/discharging schedule of each BESS and the DR scheme with the objective to maximize the benefit by regulating the supplied powers over daily 24 hours. The proposed solution method is composed of an iterative dynamic programming optimal BESS schedule approach and a particle swarm optimization based (PSO-based) DR scheme approach. The two approaches are executed alternatively until the minimum elec-tricity cost of the whole day is obtained. The validity of the proposed method was confirmed with the obviously decreased supplied powers in the peak-load hours and the largely reduced electricity cost.

A Two-Layer Active Power Optimization and Coordinated Control for Regional Power Grid Partitioning to Promote Distributed Renewable Energy Consumption

With the large-scale development and utilization of renewable energy,industrial flexible loads,as a kind of loadside resource with strong regulation ability,provide new opportunities for the research on renewable energy consumption problem in power systems.This paper proposes a two-layer active power optimization model based on industrial flexible loads for power grid partitioning,aiming at improving the line over-limit problem caused by renewable energy consumption in power grids with high proportion of renewable energy,and achieving the safe,stable and economical operation of power grids.Firstly,according to the evaluation index of renewable energy consumption characteristics of line active power,the power grid is divided into several partitions,and the interzone tie lines are taken as the optimization objects.Then,on the basis of partitioning,a two-layer active power optimization model considering the power constraints of industrial flexible loads is established.The upper-layer model optimizes the planned power of the inter-zone tie lines under the constraint of the minimum peak-valley difference within a day;the lower-layer model optimizes the regional source-load dispatching plan of each resource in each partition under the constraint of theminimumoperation cost of the partition,so as to reduce the line overlimit phenomenon caused by renewable energy consumption and save the electricity cost of industrial flexible loads.Finally,through simulation experiments,it is verified that the proposed model can effectively mobilize industrial flexible loads to participate in power grid operation and improve the economic stability of power grid.

Progress and prospects of innovative coal-fired power plants within the energy internet

The development of electrical engineering and electronic, communications, smart power grid, and ultra-high voltage transmission technologies have driven the energy system revolution to the next generation: the energy internet. Progressive penetration of intermittent renewable energy sources into the energy system has led to unprecedented challenges to the currently wide use of coal-fired power generation technologies. Here, the applications and prospects of advanced coal-fired power generation technologies are analyzed. These technologies can be summarized into three categories:(1) large-scale and higher parameters coal-fired power generation technologies, including 620/650/700 oC ultra-supercritical thermal power and double reheat ultra-supercritical coal-fired power generation technologies;(2) system innovation and specific, highefficiency thermal cycles, which consist of renewable energy-aided coal-fired power generation technologies, a supercritical CO_2 Brayton cycle for coal-fired power plants, large-scale air-cooling coal-fired power plant technologies, and innovative layouts for waste heat utilization and enhanced energy cascade utilization;(3) coal-fired power generation combined with poly-generation technologies, which are represented by integrated gasification combined cycle(IGCC) and integrated gasification fuel cell(IGFC) technologies. Concerning the existing coal-fired power units, which are responsible for peak shaving, possible strategies for enhancing flexibility and operational stability are discussed. Furthermore, future trends for coal-fired power plants coupled with cyber-physical system(CPS) technologies are introduced. The development of advanced, coal-fired power generation technologies demonstrates the progress of science and is suitable for the sustainable development of human society.

Clean Coal &High Carbon Efficiency Energy Engineering

Today we live in a world of Hydrocarbon Energy Carriers, where Carbon is always used as a Carrier for Hydrogen 1) Biomass (CH1.44O0.66 or C6H12O6);2) Natural Gas [NG] (CH4);3) Water Gas [C+H2O];4) Gasoline (C6H12, C7H18, C8H18, etc.);5) Kerosene (C17H36, C18H38, C19H40, C20H42, C21H44, C22H46, etc.) and;6) Crude Oil. The Carbon aggregates are all storable and have worthwhile, logistically manageable energy densities. But whenever recovering Energy from the Carbon molarities, CO2 gets emitted into the atmosphere, while separate use of Hydrogen Energy contents carried by the Carbon moieties would just generate water vapor. Hydrogen is also the most important intermediary in Refineries, hydrogenating lower grade Hydrocarbons into higher potencies, or for removing Sulfur by the formation of Hydrogen Sulfur, that can be dissociated after its segregation from the Hydrocarbon products. But most of the internal Hydrogen yields in Refineries today is used for onsite production of Ammonia as a basis for Energy fertilizers in high performance agriculture. Because Hydrogen is awkward to store and transport, most of it is currently used captive within large size centralized plants as a reactant for producing Hydrocarbon energy carriers, using the Carbon as a carrier for the Hydrogen moieties, to then be distributed over big enough areas for consumption of the such large scale plants’ volumes. With recently proven achievements of Hydrogen production from excess Wind & Solar Power by electrolysis, Hydrogen could become available in abundant quantities, to be distributed locally within the coverage area of the transmission grid such Wind & Solar installations are feeding into. In combination with Carbon as a reactant such abundant Hydrogen could also be synthesized into Hydrocarbon Energy Carriers and substitute fossil commodities.

Cloud-Model-Based Feature Engineering to Analyze the Energy-Water Nexus of a Full-Scale Wastewater Treatment Plant

Wastewater treatment plants(WWTPs)are important and energy-intensive municipal infrastructures.High energy consumption and relatively low operating performance are major challenges from the perspective of carbon neutrality.However,water-energy nexus analysis and models for WWTPs have rarely been reported to date.In this study,a cloud-model-based energy consumption analysis(CMECA)of a WWTP was conducted to explore the relationship between influent and energy consumption by clustering its influent’s parameters.The principal component analysis(PCA)and K-means clustering were applied to classify the influent condition using water quality and volume data.The energy consumption of the WWTP is divided into five standard evaluation levels,and its cloud digital characteristics(CDCs)were extracted according to bilateral constraints and golden ratio methods.Our results showed that the energy consumption distribution gradually dispersed and deviated from the Gaussian distribution with decreased water concentration and quantity.The days with high energy efficiency were extracted via the clustering method from the influent category of excessive energy consumption,represented by a compact-type energy consumption distribution curve to identify the influent conditions that affect the steady distribution of energy consumption.The local WWTP has high energy consumption with 0.3613 kW·h·m^(-3)despite low influent concentration and volumes,across four consumption levels from low(I)to relatively high(IV),showing an unsatisfactory operation and management level.The average oxygenation capacity,internal reflux ratio,and external reflux ratio during high energy efficiency days recognized by further clustering were obtained(0.2924-0.3703 kg O_(2)·m^(-3),1.9576-2.4787,and 0.6603-0.8361,respectively),which could be used as a guide for the days with low energy efficiency.Consequently,this study offers a water-energy nexus analysis method to identify influent conditions with operational management anomalies and can be used as an empirical reference for the optimized operation of WWTPs.

Stability Enhancement of Small-Scale Power Grid with Renewable Power Sources by Variable Speed Diesel Power Plant

This paper proposes a power control method to improve a stability of a small-scale power grid with renewable energy sources. In an isolated small- scale power grid such as an island, diesel power plant is main power source which has an environmental burden and expensive running cost due to high priced fossil fuel. Thus, expanding installation of the renewable energy sources such as a wind power is strongly desirable. Such fluctuating energy sources, however, harm power quality of the small-scale power grid, and in addition, conventional power plant in the small-scale power grid cannot, in general, stabilize the grid system with such fluctuating power sources. In this study, Variable Speed Doubly-Fed Induction Generator (VS-DFIG) is proposed to be in-stalled at a diesel power plant instead of a conventional Fixed Speed Synchronous Generator (FS-SG), because quick control of a power balance in the small-scale power grid can be achieved by using the inertial energy of VS-DFIG. In addition, utilization of a Battery Energy Storage System (BESS) is also considered to assist cooperatively the VS-DFIG control. As a result of the simulation analysis by using the proposed method, it is verified that frequency fluctuations due to renewable energy source can be effectively reduced by quick power control of the VS-DFIG compared to the conventional FS-SG, and further control ability can be obtained by utilizing BESS. Moreover, the transient stability of a small-scale power grid during a grid fault can also be enhanced.

Experimental study of power consumption, local characteristics distributions and homogenization energy in gas–liquid stirred tank reactors

In this paper, the power consumption, the vertical local void fraction and the local gas–liquid interfacial area are investigated in the aerated stirred tank reactors(STRs) equipped with a rigid-flexible impeller. Meanwhile, the regressive correlation based on power consumption and interfacial area is proposed. Then a novel homogenization energy(HE = RSDPtm) expression based on power consumption and local interfacial area is redefined and used to indicate the mixing efficiency. The optimal operating mode is selected based on the change of the HE value. This paper can provide research ideas for structural optimization of stirred reactors.

Virtual Power Plants for Grid Resilience: A Concise Overview of Research and Applications

The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.

Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Optimal Scheduling Strategy for Energy Consumption Minimization of Hydro-Thermal Power Systems

A comparison analysis based method for computing the water consumption volume needed for electric energy production of optimal scheduling in hydro-thermal power systems is presented in this paper. The electric energy produced by hydroelectric plants and coal-fired plants is divided into 4 components: potential energy, kinetic energy, water-deep pressure energy and reservoir energy. A new and important concept, reservoir energy, is proposed, based on which is divided into a number of water bodies, for example 3 water bodies, and a reservoir is analyzed in a new way. This paper presents an optimal scheduling solution of elec-tric energy production of hydro-thermal power systems based on multi-factors analytic method, in which some important factors, such as load demand, reservoir in-flow, water consumption volume increment rate of hydroelectric plants or converted from coal-fired plants, and so on are given to model the objective function and the constraints. A study example with three simulation cases is carried out to illustrate flexibility, adapta-bility, applicability of the proposed method.

Study on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm

Coal consumption curve of the thermal power plant can reflect the function relationship between the coal consumption of unit and load, which plays a key role for research on unit economic operation and load optimal dispatch. Now get coal consumption curve is generally obtained by least square method, but which are static curve and these curves remain unchanged for a long time, and make them are incompatible with the actual operation situation of the unit. Furthermore, coal consumption has the characteristics of typical nonlinear and time varying, sometimes the least square method does not work for nonlinear complex problems. For these problems, a method of coal consumption curve fitting of the thermal power plant units based on genetic algorithm is proposed. The residual analysis method is used for data detection;quadratic function is employed to the objective function;appropriate parameters such as initial population size, crossover rate and mutation rate are set;the unit’s actual coal consumption curves are fitted, and comparing the proposed method with least squares method, the results indicate that fitting effect of the former is better than the latter, and further indicate that the proposed method to do curve fitting can best approximate known data in a certain significance, and they can real-timely reflect the interdependence between power output and coal consumption.

A Sustainable Energy Efficiency Solution in Power Plant by Implementation of Perform Achieve and Trade (PAT) Mechanism

An enhanced energy efficiency scheme, “Perform, Achieve and Trade” (PAT) is explored in relation to the existing carbon market in India, particularly the Clean Development Mechanism, Renewable Energy Certification and possible Nationally Appropriate Mitigation Actions. The PAT scheme incentivises energy-intensive large industries and facilities for Enhance Energy Efficiency, through technology upgrade and improvement in process. The PAT scheme currently identified 478 designated consumers from eight energy intensive industrial sectors namely, thermal power plants, iron and steel, cement, textiles, chlor-alkali, aluminum, fertilisers and pulp & paper. The threshold limit in thermal power plant sector to become a PAT designated consumer is 30,000 tonne of oil equivalent annual energy consumption. In the first PAT cycle, run through 2012 to 2015, total 144 designated consumers from various states have been identified with individual target. Thermal power plant sector has been categorized on the basis of their fuel input into three subsectors i.e. gas, oil and coal based plants. This paper reviews the state of the art in PAT mechanism design and operational features for implementation on thermal power plant sector. The possibility of implementing an Emission Trading Scheme (ETS) in India is explored from political and institutional perspectives.

Peer-to-Peer Energy Trading Method of Multi-Virtual Power Plants Based on Non-Cooperative Game

The current electricity market fails to consider the energy consumption characteristics of transaction subjects such as virtual power plants.Besides,the game relationship between transaction subjects needs to be further explored.This paper proposes a Peer-to-Peer energy trading method for multi-virtual power plants based on a non-cooperative game.Firstly,a coordinated control model of public buildings is incorporated into the scheduling framework of the virtual power plant,considering the energy consumption characteristics of users.Secondly,the utility functions of multiple virtual power plants are analyzed,and a non-cooperative game model is established to explore the game relationship between electricity sellers in the Peer-to-Peer transaction process.Finally,the influence of user energy consumption characteristics on the virtual power plant operation and the Peer-to-Peer transaction process is analyzed by case studies.Furthermore,the effect of different parameters on the Nash equilibrium point is explored,and the influence factors of Peer-to-Peer transactions between virtual power plants are summarized.According to the obtained results,compared with the central air conditioning set as constant temperature control strategy,the flexible control strategy proposed in this paper improves the market power of each VPP and the overall revenue of the VPPs.In addition,the upper limit of the service quotation of the market operator have a great impact on the transaction mode of VPPs.When the service quotation decreases gradually,the P2P transaction between VPPs is more likely to occur.

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.

ANALYSIS OF HYDRAULIC POWER SOURCES DISPOSITION AND ENERGY CONSUMPTION FOR HYDRAULIC DRILL RIG

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Solar Power Plant Network Packet-Based Anomaly Detection System for Cybersecurity

As energy-related problems continue to emerge,the need for stable energy supplies and issues regarding both environmental and safety require urgent consideration.Renewable energy is becoming increasingly important,with solar power accounting for the most significant proportion of renewables.As the scale and importance of solar energy have increased,cyber threats against solar power plants have also increased.So,we need an anomaly detection system that effectively detects cyber threats to solar power plants.However,as mentioned earlier,the existing solar power plant anomaly detection system monitors only operating information such as power generation,making it difficult to detect cyberattacks.To address this issue,in this paper,we propose a network packet-based anomaly detection system for the Programmable Logic Controller(PLC)of the inverter,an essential system of photovoltaic plants,to detect cyber threats.Cyberattacks and vulnerabilities in solar power plants were analyzed to identify cyber threats in solar power plants.The analysis shows that Denial of Service(DoS)and Manin-the-Middle(MitM)attacks are primarily carried out on inverters,aiming to disrupt solar plant operations.To develop an anomaly detection system,we performed preprocessing,such as correlation analysis and normalization for PLC network packets data and trained various machine learning-based classification models on such data.The Random Forest model showed the best performance with an accuracy of 97.36%.The proposed system can detect anomalies based on network packets,identify potential cyber threats that cannot be identified by the anomaly detection system currently in use in solar power plants,and enhance the security of solar plants.

Optimal Energy Management for Virtual Power Plant with Renewable Generation

The nature of variable and uncertainty from renewable energy sources (RESs) makes them challenging to be integrated into the main grid separately. A Virtual Power Plant (VPP) is proposed to aggregate the capacities of RESs and facilitate the integration and management in a decentralized manner. In this paper, a novel framework for optimal energy management of VPP considering key features such as handling uncertainties with RESs, reducing operating costs and regulating system voltage levels is proposed, and a two-stage stochastic simulation is formulated to address the uncertainties of RESs generation and electricity prices. Simulation result show that the framework can benefit from ensuring the energy balance and system security, as well as reducing the operation costs.

Energy and Exergy Analysis of Moist Air for Application in Power Plants

In this study an energy and exergy analysis is made of moist air, it is used the psychometrics charts. A Visual Basic program is used to generate psychometrics charts. These charts are used to analyze the air thermodynamic behavior, considering the environmental variations, pressure, temperature and relative humidity. Also, the available energy in the cooling processes at constant enthalpy, humidification at constant temperature and heating with constant relative humidity is analyzed. For example, we obtained that the enthalpy and exergy in a thermodynamic state, with conditions, Patm = 1.013 bar, Tatm = 25oC and Φatm=50%, are h = 50.56 kJ/kga and ε =11.5 kJ/kga;and for Patm= 0.77 bar to the same conditions of Tatm and Φatm, the enthalpy and exergy increases in a 14% and 20%, respectively.

Design of Steam Turbine for Electric Power Production Using Heat Energy from Palm Kernel Shell

The steam turbine is a prime mover that converts kinetic energy in steam into rotational mechanical energy through the impact or reaction of the steam against the blades. The aim of this study is to design a steam turbine for a small scale steam power plant with target of producing electricity. The turbine is driven by the heat energy from palm kernel shells as a renewable energy source obtained at a lower or no cost. The study was concentrated on design of turbine elements and its validation using computer packages. Specifically, the microturbine design was limited to design, modeling, simulation and analysis of the rotor, blades and nozzle under the palm kernel shell as fuel for the micro power plant. In blade design, stress failures, efficiency and blade angle parameters were considered. In casing volume design, the overall heat transfer and mean temperature, and different concepts were applied. The thermal distribution on stator and rotor was considered in order to determine its level of tolerance. The design software packages used for design validation were Solidworks and Comsol Multiphysics for analysis. Simulation results showed that the designed steam turbine can adequately tolerate change in stress/load, torsion/compression, temperature and speeds.