Energy Generation Units Research Articles

Research into the recovery of exhaust gases from ice using an expansion machine and fuel conversion

We have devised a scheme for the energy-generating unit based on the internal combustion engine 1Ch 6.8/5.4 with a spark ignition and a two-stage system for the recovery of heat from the exhaust gases. The basic elements for the first and second stages of the heat recovery system have been selected. A first stage involves a rotary piston expansion machine while a second stage employs the fuel conversion.We have studied effective parameters for the engine 1Ch 6.8/5.4 with a system of the deep two-stage recovery of heat from exhaust gases under different modes of operation. The dependences were established for change in the specific effective fuel consumption on the power of the energy-generating installation using only the conversion of fuel and in a combination with the expansion machine.The dependences have been derived for the operational parameters of a rotary piston engine on consumption of a working body. We have determined temperatures of the working bodies in a reactor and the heat capacity of exhaust gases depending on the load on the engine, as well as the necessary amount of energy to convert ethanol into synthesis gas. The dependences have been obtained of the degree of ethanol conversion on the reaction temperature and the mass flow rate through the reactor. We have established the dependence of specific heat of the chemical reaction on the degree of conversion.It was established that when reaching full conversion in line with the reaction of decomposition the entire liquid ethanol is completely converted into combustible synthesis gas, whose main components are hydrogen, carbon monoxide, and methane. The estimated specific lower combustion heat of the synthesis gas is 28.79 MJ/kg. Obtaining 1 kg of synthesis gas requires 4.0 MJ of thermal energy.It was determined that under condition of applying the conversion of fuel and, accordingly, the addition of synthesis gas, the specific effective ethanol flow rate, depending on the mode of engine operation, decreases by up to 12 %. The amount of energy that needs to be used in the reactor for obtaining synthesis gas is 50…65 % of the heat released with the exhaust gases under a given mode of operation.It has been established that the application of a rotary-piston expansion machine that acts as the first stage in the recovery of heat from exhaust gases has made it possible to gain an increase in the capacity of the energy-generating unit of 27 %.It has been found that the use of two stages of heat recovery leads to a decrease in the specific effective fuel consumption by 29 %

Enabling and Evaluation of Inertial Control for PMSG-WTG Using Synchronverter With Multiple Virtual Rotating Masses in Microgrid

With the ever-increasing penetration level of renewable energy generation units and the replacement of traditional synchronous generators, the issues associated with the deteriorated performance of power system frequency regulation and potential grid frequency instability become more significant. In this paper, the inertial control algorithm using a synchronverter is enabled for variable-speed wind turbines. Besides, the type-4 permanent magnet synchronous generator wind turbine generator using synchronverter inertial control is modeled and the comprehensive analysis and comparison are conducted between frequency-based inertial control and synchronverter inertial controls. Aiming to address the compromised ability of a synchronverter with desirable inertial response to deal with fast changing wind condition, a synchronverter with multiple virtual rotating masses is proposed in order to improve the active power tracking performance as well as to boost inertial control of the synchronverter. The performance of inertial controls is verified in the modified 10MVA IEEE 14 bus microgrid system. The assessment of the simulation results provides a deep insight into different inertial control methods while demonstrating the applicability of synchronverter on wind power generation systems.

Smart Integration Based on Hybrid Particle Swarm Optimization Technique for Carbon Dioxide Emission Reduction in Eco-Ports

The increasing daily rate of environmental pollution, due to electrical power generation from fossil fuel sources in different societies, urges the researchers to study alternative solutions. These solutions can be summarized into either finding other clean, renewable sources or managing the available sources optimally. This research represents smart electrical interconnection management between some of the Egyptian seaports for optimal operation, with a clean sustainable environment as the target. The optimum ports’ commitment operation works through certain technical constraints to attain optimal economic and environmental factors. One of the main objectives of this study is the reduction of carbon dioxide (CO2) emission, which is released from the electrical power generation that covers the seaports demands. It is progressed through the green port smart commitment, by incorporating unpolluted and renewable energy resources. This study depends on the redesign of some Egyptian seaports to be green ports with eco-friendly electrical construction. According to the new electrical design, two out of the six studied seaports can be considered as renewable energy generation units consisting of Photovoltaic (PV) electrical generation resources. The new design of the seaports electrical network can be considered as a hybrid network, collecting both fossil fuel electrical power generation and PV sources. To gain benefits from the diversity in geographical behaviors, ports on the red sea and Mediterranean sea are integrated into the network cloud. Connecting ports on red and Mediterranean seas construct a network cloud, which supports the operation of the whole network under different conditions. Hybrid (weighted-discrete) Particle Swarm Optimization Technique (HPSOT) is an effective optimization technique which is applied to provide the optimum interconnection management between the eco-ports. It is developed based on some technical constraints which are the availability of the network buses interconnection, the voltage and frequency levels, and deviations due to the smart unit interconnection and the re-direction of the power flow. The HPSOT is targeted to minimize the economical cost and the harmful environmental impact of the seaport electrical network, while covering the overall network load. The HPSOT is programmed utilizing the Matlab program. It is tested on the six Egyptian seaports network that consists of El Dekheila, Alexandria, and Damietta on the Mediteranean and Port Said, Suez, and Sokhna port on the Suez canal and Red sea. It verifies its accurateness and efficiency in decreasing the combined cost function involving costs of CO2 emission. CO2 emission is reduced to 6% of its previous value for the same consumed electrical energy, that means it has a positive impact on retarding the greenhouse effect and climate change.

Performance analysis of micro-grid designs with local PMSG wind turbines

Micro-grids are small-scaled power grids, with local clean energy generation and intelligent management units. Micro-grids equipped with PV panels, wind turbines and batteries are known as hybrid power systems. Since these systems are a promising solution to build the future smart city, different designs were proposed and implemented. The present study compares two micro-grid-connected PMSG designs, with PV panels and batteries, based on system performance and power quality. In the first design, the wind turbine is connected to the common DC bus through a rectifier, while in the second configuration, it is connected to the 3-phase AC circuit via a transformer. The comparison is carried-out under different weather and system conditions. According to simulation results, the first design is less affected by voltage harmonics and has a better power quality, while the second design is robust to inverter or transformer failures and supports more loads.

An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results

This paper presents a holistic innovative solution for the transformation of the current district heating and cooling systems to automated more efficient systems. A variety of technological advancements have been developed and integrated to support the effective energy management of future district heating and cooling sector. First, we identify and discuss the main challenges and needs that are in line with the EU objectives and policy expectations. We give an overview of the main parts that our solution consists of, with emphasis on the forecasting tools and an advanced control system that addresses unit commitment and economic load dispatch problems. The proposed control approach employs distributed and scalable optimisation algorithms for optimising the short-term operations of a district heating and cooling plant subject to technical constraints and uncertainties in the energy demand. To test the performance and validate the proposed control system, a district heating plant with multiple energy generation units and real-life heat load data were used. Simulation experiments were also used to evaluate the benefits of using thermal storage units in district heating systems. The results show that the proposed method could achieve significant cost savings when energy storage is employed. The proposed control strategy can be applied for both operating optimally district heating plants with storage and supporting investment planning for new storage units.

Transparent Luminescent Solar Concentrators Using Ln3+-Based Ionosilicas Towards Photovoltaic Windows

The integration of photovoltaic (PV) elements in urban environments is gaining visibility due to the current interest in developing energetically self-sustainable buildings. Luminescent solar concentrators (LSCs) may be seen as a solution to convert urban elements, such as façades and windows, into energy-generation units for zero-energy buildings. Moreover, LSCs are able to reduce the mismatch between the AM1.5G spectrum and the PV cells absorption. In this work, we report optically active coatings for LSCs based on lanthanide ions (Ln3+ = Eu3+, Tb3+)-doped surface functionalized ionosilicas (ISs) embedded in poly(methyl methacrylate) (PMMA). These new visible-emitting films exhibit large Stokes-shift, enabling the production of transparent coatings with negligible self-absorption and large molar extinction coefficient and brightness values (~2 × 105 and ~104 M−1∙cm−1, respectively) analogous to that of orange/red-emitting organic dyes. LSCs showed great potential for efficient and environmentally resistant devices, with optical conversion efficiency values of ~0.27% and ~0.34%, respectively.

Propagating Uncertainty in Power System Dynamic Simulations Using Polynomial Chaos

Quantifying the uncertainty of the renewable energy generation units and loads is critical to ensure the dynamic security of next-generation power systems. To achieve that goal, the time-consuming Monte Carlo simulations are usually used, which is not suitable for online dynamic analysis of large-scale power systems. To circumvent this difficulty, two uncertainty quantification approaches using polynomial-chaos-based methods are proposed and investigated. The first approach is the generalized polynomial chaos method that is able to reduce the computing time by three orders of magnitude compared with Monte Carlo methods while achieving the same accuracy. We find that this approach is very useful for short-term power system dynamic simulations, but it may produce unreliable results for long-term simulations. To address the weakness of that approach, we present the second method, namely the multi-element generalized-polynomial-chaos method. It is seen that this method is more accurate and more numerically stable than the generalized polynomial chaos method. Since the uncertainties of the renewable energy generation units and loads can follow very different distributions, we extend the Stieltjes’ recursive procedure that allows us to derive the orthogonal basis functions for any assumed probability distribution of the input random variables. Extensive simulations carried out on the WECC 3-machine 9-bus system and the New England 10-machine 39-bus system reveal that our proposed approaches are able to produce comparable accuracy as the Monte Carlo based method while achieving significantly improved computational efficiency for both stable and unstable power system operating conditions.

Efficient wind energy generation within Arctic latitudes

The paper addresses approaches to increasing the efficiency of wind turbines operating in autonomous mode in Arctic regions. Such type of wind turbine operation is related to fluctuations of the generated power, that negatively affects grid power quality. The increase of wind turbines efficiency is achieved by the utilization of current reserve of power converter, which is a necessary part of megawatts-sized wind energy generation unit. The developed Simulink model of the wind turbines, built according to two of the most suitable for megawatts-level power generation topologies, was used to determine their power output depending on the wind turbine’s rotor speed and the wind speed. Obtained power profile was then used to determine the amount of free current reserve depending on the wind speed, which has verified the ability of both wind turbine topologies to efficiently improve grid power quality, therefore leading to reduction or absence of the necessity to install additional power equipment for the compensation purpose.

Nonlinear Multi-Agent Optimal Load Frequency Control Based on Feedback Linearization of Wind Turbines

Large scale power systems have distributed structure since power generation units are distributed in the network. In such systems, where the communications are sometimes imperfect, centralized control structures have concerns to be applied. For such inherently distributed systems, multi-agent control structures are more appropriate. On the other hand, power systems have nonlinear dynamics. When all generation units are synchronous generators, linear approximation of swing equation of generators is a common choice. However, by penetration of renewable energy generation units, those have highly nonlinear dynamics, nonlinear control approaches should be applied. In this paper, a nonlinear multi-agent feedback linearization approach is adopted for optimal load frequency control of a power system with wind generation units. Multiagent controllers with both distributed and decentralized structures are proposed. Centralized feedback controller is also applied for comparison purposes. The parameters of the controllers are optimized using gray wolf optimization algorithm to improve time response of the system and reduce generation costs. IEEE 30-bus system with six synchronous generators and four wind turbines is considered as a test system. Simulation results verify the inefficiency of centralized controller and show that distributed control structure can produce a balanced performance in terms of time response and is better from the cost reduction view point than the decentralized controller.

Robust Multi-Objective Control of Power System Stabilizer Using Mixed H2/H∞ and µ Analysis

<p>In order to study the dynamic stability of the system, having a precise dynamic model including the energy generation units such as generators, excitation system and turbine is necessary. The aim of this paper is to design a power stabilizer for Mashhad power plant and assess its effects on the electromechanical fluctuations. Due to lack of certainty in the system, designing an optimized robust controller is crucial. In this paper, the establishment of balance between the nominal and robust performance is done by the weight functions. In the frequencies where the uncertainty is high, in order to achieve to the robust performance of the controller, μ analysis is more profound, otherwise, in order to achieve to nominal performance, robust stability, noise reduction and decrease of controlling signal, the impact of the controller H2/H∞ is more profound. The results of the simulation studies represent the advantages and effectiveness of the suggested method.</p>

Direct quantification of multiple-source energy flexibility in a residential building using a new model predictive high-level controller

This article presents a new energy management system (EMS) for a variety of energy flexibility conversion, routing and storage options in buildings. The EMS uses an efficient nonlinear optimization-based model-predictive control (MPC) method, which achieves low computational complexity by utilizing successive linear programming (SLP) for continuous approximations of discrete (two-level) control problems. Whole-year simulation runs demonstrate that the method is applicable to a residential building system that has multiple energy generation, conversion and storage units with significant nonlinear interactions. Both qualitative and quantitative comparison of the simulation results with a rule-based reference control showed strong dependencies between cost and CO2 emission flexibility goals, energy selling prices and forecasting accuracy. This study shows that significant cost savings can be obtained by taking advantage of energy price fluctuations, increasing the average coefficient of performance (COP) of the heating system, and reducing passive losses in heat storage. In the simulated case study the EMS was able to improve the average COP of a heating system from 2.20 to 2.43–2.74, depending on energy cost assumptions, when compared against a rule-based control (RBC). With a performance bound of perfect forecasting the EMS was able to improve net economic outcome by 38–168%, or by 21–75% of the cost of imported electricity.

A design and experimental investigation of a large-scale solar energy/diesel generator powered hybrid ship

Due to the increasing demand for energy conservation and the reduction of emissions, renewable energy applications for ships have attracted a great deal of attention. In this paper, a 5000-vehicle space pure car and truck carrier (PCTC) is selected as the research object. Then, on the basis of the existing power system, a unified grid-tied/stand-alone solar system is designed with a built-in battery energy storage system. The system includes a solar energy generation unit, a battery storage system, a diesel generating set, grid-tied/stand-alone controlled inverters, a battery management system (BMS) and an energy management system. According to an analysis of the experimental data, it can be concluded that the use of solar energy hybrid power, in theory, can reduce fuel consumption by 4.02% and carbon dioxide (CO2) emissions by 8.55% a year.

Allocation factors in Combined Heat and Power systems – Comparison of different methods in real applications

The planning and operation of multi-generation units needs to be properly addressed, to guarantee a correct assessment of their performance with respect to standard energy generation units. Performance indicators are defined to compare energy conversion units, and in presence of multiple outputs an allocation methodology is required. There is currently no single method to allocate input resources and impacts in cogeneration and multi-generation systems, as the number of aspects that are involved leads to different approaches. Each method provides specific advantages related to the target for which it has been defined, but attention must be paid on the entire range of boundary conditions that could affect the results. This paper evaluates the current methodologies for allocation factors calculation in Combined Heat and Power plants, to present an indication of the strengths and the limits of each approach. The methods are applied to multiple case studies, by considering the operation data from existing natural gas plants of different size, technology and conversion efficiency. The use of real data allows to consider actual situations in which the choice of the method could lead to different indications. The results show the significant variability of the allocation factors, the main drivers being the choice of the methodology itself, the conversion technology and the reference efficiency values that are set for separate production of heat and power. A discussion is proposed on the importance of defining proper methods and reference parameters, with particular attention to the applications for which the allocation factors need to be calculated and the potential effects on energy policies and regulations.

Feasibility study on the low temperature district heating and cooling system with bi-lateral heat trades model

A Novel low temperature district heating and cooling system with auxiliary heat storage pipe system is proposed for reflecting new features of bi-lateral energy trades effectively in emerging energy prosumer based new energy business platform. The newly proposed district heating and cooling system can provide more favorable operating conditions to implement bi-lateral heat trades system between the heat supplier and the prosumers, who operating their own distributed energy generation unit such as a cogeneration etc., connected to the network being able to utilize low-exergy level of waste heats available in consumer side. In this study, the appropriate system configuration for reliable operation, the optimal operation rules, the functionality of auxiliary heat storage pipe on bi-lateral heat trades and its operating characteristics etc. are analyzed extensively by developing simplified simulation models of the DHC network using Matlab/Simulink without any support by experiment or field measurement. The simulation results show that the newly suggested low temperature DHC system with auxiliary heat storage pipe can add improved rooms of operating flexibility to maintain stable supplying temperature conditions and is superior to conventional system in handling bi-lateral heat trades model. It is also shown that the new concept of DHC system can alleviate the inefficiency arising from mismatching of heat demand and supply in consumer side significantly, not to mention of the heat losses during the operation.

LMI based robust load frequency control for time delayed power system via delay margin estimation

The employment of communication channels inevitably result in the advent of time delays in load frequency control (LFC) schemes. The existence of such time delays exerts potential threats on the stability of power systems. This paper aims to study a three-area time delayed power system and propose a linear matrix inequality (LMI) based robust LFC scheme with delay margin estimation. Analytic form of the delay margin is subsequently provided. Following that, LMI based robust controller design procedure is proposed based on delay margin estimation, wherein the robust performance index (RPI) is introduced. The robust controller gains are ultimately obtained with the estimated delay margin and a binary search technique which aims to find the minimum value of RPI. Simulations are conducted to evaluate performance of the proposed scheme: the effectiveness of the DME process is verified under an ideal power system condition; a second simulation incorporating the effects on GRC and GDB is conducted to further validate the rightness of DMC; parameter perturbations are considered in the next simulation; a comparative study which compares the proposed approach with other three existing methods is initialized in the fourth simulation test; at last, the impact of a micro grid comprises wind and solar energy generation units is incorporated to test the performance of the novel method. The simulation results indicate that the delay margin estimation procedure is effective and the proposed control scheme is robust and has superior performance over conventional LMI based robust control schemes.

Intelligent control strategy for a grid connected PV/SOFC/BESS energy generation system

In this paper, an intelligent control strategy for a grid connected hybrid energy generation system consisting of Photovoltaic (PV) panels, Fuel Cell (FC) stack and Battery Energy Storage System (BESS) is proposed. Firstly, the dynamic modeling of the electrical energy resources is carried out. Then, the local controllers of DC-DC power converters are designed to regulate the operating points of the energy generation units. An online-trained Elman Neural Network (ENN) based controller is developed to perform the tracking of the optimal operating point of the PV source. Moreover, a Takagi-Sugeno-Kang based fuzzy gain tuner is adopted for the adjustment of the PI parameters of the FC and BESS controllers. Besides, the Virtual Flux Oriented Control (VFOC) scheme based on neuro-fuzzy gain tuners is adopted to control the power flow between the hybrid system, the local loads and the utility grid. Furthermore, a centralized power supervisor is established to determine the levels of the power references for the local controllers according to the supply and demand conditions. The simulation results obtained in the Matlab/Simulink environment demonstrate the efficiency of the proposed control scheme.

Power in the loop real time simulation platform for renewable energy generation

Nowadays, a large scale of renewable energy sources has been connecting to power system and the real time simulation platform is widely used to carry out research on integration control algorithm, power system stability etc. Compared to traditional pure digital simulation and hardware in the loop simulation, power in the loop simulation has higher accuracy and degree of reliability. In this paper, a power in the loop analog digital hybrid simulation platform has been built and it can be used not only for the single generation unit connecting to grid, but also for multiple new energy generation units connecting to grid. A wind generator inertia control experiment was carried out on the platform. The structure of the inertia control platform was researched and the results verify that the platform is up to need for renewable power in the loop real time simulation.

Sizing of Photovoltaic-Wind-Battery Hybrid System for a Mediterranean Island Community Based on Estimated and Measured Meteorological Data

Deploying renewable energy systems (RES) to supply electricity faces many challenges related to cost and the variability of the renewable resources. One possible solution to these challenges is to hybridize RES with conventional power systems and include energy storage units. In this study, the feasibility analysis of a grid-connected photovoltaic (PV)-wind-battery hybrid system is presented as a microgrid for a university campus-scale community on a Mediterranean island. Models for PV and wind turbine systems are presented to estimate energy production, and net present cost (NPC) and levelized cost of electricity (LCOE) are used as economic metrics. A parametric study is performed with hourly time-steps to determine the sizes of energy generation and storage units to minimize the NPC for a small community as the case study. Two alternate configurations with and without storage are proposed. In both cases, the resulting LCOE is 0.15 USD/kWh while the current electricity tariff for the analyzed location was 0.175 USD/kWh in 2015. This lower unit cost of electricity leads to a lower NPC considering a 25-year lifetime. Different estimated and measured solar irradiance and wind speed data sets are used to evaluate the performance of the designed microgrid. Sensitivity analysis on different available weather data sets shows that the uncertainty in wind resource estimations is much higher than the uncertainty in solar resource estimations. Moreover, the results show that solar and wind resources could be utilized synergistically for the studied location.

Feasible use of microbial fuel cells for pollution treatment

Abstract The microbial fuel cells (MFC) can directly transform chemical energy in feed substance to electricity by anodic aspiration pathways. This mini review provides an order-of-magnitude argument that MFC has much lower catalyst density at electrode surface and much higher diffusional resistance for substrates than the chemical fuel cell, the former should not be used as an energy generation unit; rather, it should be applied in low power density level applications such as biofilm wastewater treatment. The literature studies using MFC for pollution treatment are discussed.

Experimental study of nanofluid effects on heat transfer in closed cycle system in shell and tube heat exchangers at Isfahan power plant

The present study investigated the effect of distilled-water/ silver nanofluid on heat transfer in a closed cooling system of one of the electrical energy generation units at Isfahan power plant. The difference between this study and previous researches refers to silver properties which have a high thermal conductivity and is non-toxic, hydrophilic and eco-friendly. Distilled water/ silver nanofluid with 20 nm average diameter and 0.1% volume fraction was purchased from Iranian nanomaterials’ Pishgaman company. The volume fractions 0.01%, 0.025%, 0.05%, 0.075% were prepared in the laboratory and thermophysical properties were practically measured in the laboratory. Nanofluids with flow rates from 0.14 to 0.26 kg/s and volume fraction from 0.01% to 0.1% passed through the tubes of heat exchanger and were evaluated in the Reynolds number range of 1500 to 4000. This study was aimed to achieve the overall heat transfer coefficients and pressure drop of the system. According to the system performance index, the results showed that nanofluid can be used to increase the efficiency of heat exchangers and, as an appropriate method, to reduce the dimensions of the exchangers. The results showed that nanofluid increased heat transfer coefficient by 16%. Pressure drop of nanofluid, however, have no significant change compared with the pressure drop of pure water.