Energy Generation Units Research Articles

Coordinated LVRT Support for a PMSG-Based Wind Energy Conversion System Integrated into a Weak AC-Grid

In a grid, the choice of the point of common coupling (PCC) does not solely rely on the voltage level alone but also conjointly depends on the grid strength for many explicit purposes. Nowadays, the affinity of low SCR grid connections has become a crucial thought once it involves the integration of wind generation plants (WPPs). Since the quality of wind resources is a critical issue, these plants are usually placed in remote areas with a sophisticated potential of wind flow. These remote areas are typically less inhabited, where the grid does not perpetually always have to be sturdy. Moreover, the exceeded power demand loading and higher wind penetration affect the generation, transmission, and distribution utilities by permitting the flow of unbalanced voltages and currents in the power system. Therefore, the quality of transmitted power is becoming a crucial facet of distributed energy generation units. In this paper, a permanent-magnet synchronous generator (PMSG) based wind energy conversion system (WECS) is presented. It discusses a solution, which provides the low voltage ride through (LVRT) provision by the suppression of DC link overvoltage and active power limitation during an asymmetrical grid fault. With improved back-to-back converter control, the machine side converter (MSC) is employed to control the DC-link voltage. Furthermore, the grid side converter (GSC) is used to implement the active/reactive current injection according to the outlined limits. The need for external hardware is eventually avoided, which is typically required to dissipate the additional energy generated during a grid fault. Hence, it is proven to be an affordable solution.

Hierarchical Honeycomb-Structured Electret/Triboelectric Nanogenerator for Biomechanical and Morphing Wing Energy Harvesting

HighlightsCreate a hierarchical honeycomb-inspired triboelectric nanogenerator (TENG) with excellent transparency, compactness, lightweight and deformability.Amplify capacitance variation by dividing large hollow space into numerous energy generation units with porous honeycomb architecture.Demonstrate self-powered insole plantar pressure mapping applications by the self-sustained elastic nature of the h-TENG device.Integrate the h-TENG into the morphing wing of small-unmanned aerial vehicles for converting flapping motions into electricity for the first time.

Design and analysis of fuel cell vehicle-to-grid (FCV2G) system with high voltage conversion interface for sustainable energy production

This study proposes the more effective use of fuel cell (FC) vehicles by providing vehicle-to-grid (V2G) technologies that provide the integration of transportation and electricity networks. The main objective of the current study is to develop an FCV2G system with a high voltage conversion interface for the integration of low voltage FC energy units to utility-grids. To transfer the energy from the fuel cell vehicle (FCV) to the grid/homes with high efficiency, a single-switch high voltage conversion DC-DC converter is proposed, designed and implemented in the FCV2G system. The FCV2G with the proposed converter is analyzed for different operating modes in order to validate the smooth energy transfer with maximum power extraction capability. In the performance section, an FC in the rating of 20 kW (based on Pininfarina Sintesi model) is located in the energy generation unit of FCV2G, and a dynamic load profile is operated for 24 h period. The generated energy from FCV is supplied to consumer loads and electric grids in the rating of 220 Vrms/50 Hz. In the analysis section, during low load consumption, the FCV both meets the energy need of the load, and the excess energy is supplied into the grid. In cases where the homes' energy consumption is higher than the power rating produced by the FCV, the load absorbs the maximum power generated by the FCV and meets the power difference needing from the grid. In the designed model, FCV supplies a 44.06 kW h energy to consumer loads/grids per a day. After the system analysis, economic aspects are supported through energy and profit analysis of the FCV2G system. The results verify that the purchased price from grid-electricity significantly reduces to lower values for daily operation.

Research on AC/DC hybrid system real-time simulation progress improvement

In order to improve the accuracy of real-time simulation of power electronic transformers, all models are based on FPGA modeling, and a mathematical model of power electronic transformers suitable for FPGA operations has been established. Aiming at the simulation error caused by multi-rate simulation, this paper analyzes the source of simulation error, proposes a step wave average communication algorithm, which improves the oscillation and jitter of simulation results. The simulation platform is connected to the real controller of power electronics and the real controller of new energy generation unit. The real-time simulation verification is carried out for the dynamic characteristics, control performance and stability of AC / DC system. The simulation results verify the reliability and practicability of the simulation platform.

ViPSN: A Vibration-Powered IoT Platform

In this article, we introduce a vibration-powered sensing node (ViPSN), a programmable Internet-of-Things (IoT) platform for the development of vibration-powered or motion-powered sensing and transmitting systems. It leverages the exploitation and utilization of ambient vibration energy by using a piezoelectric transducer. The roles and relations of six necessary modules, including energy generation unit (EGU), energy transduction unit (ETU), energy enhancement unit (EEU), energy management unit (EMU), energy user unit (EUU), and edge demonstration unit (EDU) are discussed in detail. In particular, an enhanced EMU is proposed by making necessary complements to an extensively used off-the-shelf integrated circuit (IC) solution for piezoelectric transducers. It provides more comprehensive energy storage indicating signals, such that the sensing, computing, and transmitting tasks can be carried out more robustly by keeping a good awareness of the remaining energy. Owing to the enhanced EMU design, vibration energy in various forms, such as intermittent and transient ones, can be more effectively harvested and utilized. The performance of ViPSN is evaluated, in terms of its lifetime and Quality of Service (QoS), under different vibration scenarios. The inclusive design and affiliated opensource project of ViPSN help build a new ecosystem for the research and development of vibration- or motion-powered IoT systems.

Optimisation of solar/wind/bio-generator/diesel/battery based microgrids for rural areas: A PSO-GWO approach

The suitability of microgrids depends upon the balance between the size, cost-efficiency and reliability of the system. The work involves optimal planning of microgrid taking a case of three locations in the Indian state of Bihar. A combination of Solar/Wind/Bio-generator energy generation units along with diesel generation and the battery is implemented for this purpose. The tradeoff between Cost Of Electricity (COE) and Deficiency of Power Supply Probability (DPSP) has been analysed and an objective function is defined as a combination of the two with a bound of Renewable Factor (RF). A hybrid Particle Swarm Optimisation-Grey Wolf Optimiser (PSO-GWO) is implemented for optimisation. The performance of the algorithm is compared with numerous others using 13 classical benchmark test functions and 10 CEC-06 2019 benchmark functions. The obtained microgrids are analysed to supply at an average Cost of Electricity of 0.17($/kWh) meeting at least 93% of the demand. Besides, an average renewable factor of 0.93 makes the system environmental friendly. The work also includes a sensitivity analysis of Cost of Electricity. The results are compared with those using other previously used algorithms in the literature and the effectiveness of the implemented algorithm is established.

New Energy Generation Converter Harmonic Evaluation Based on Operation Data

The research on the harmonic mechanism and features of new energy generation units is crucial for ensuring safe and stable operation of new energy generation. In this paper, a big data analysis method suitable for the operation data of new energy power plant is used to analyse the harmonics generated by PWM modulation and dead zone effect of switching devices and the interharmonics generated by DC side voltage fluctuation. The simulation analysis verifies the harmonic characteristics of new energy power converter, the model basis of new energy power generation operation evaluation and power grid connection certification.

Systematic Categorization of Optimization Strategies for Virtual Power Plants

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.

A novel air separation unit with energy storage and generation and its energy efficiency and economy analysis

Air separation units (ASUs), as a single industrial equipment item, accounted for a considerable proportion (4.97%) of China’s national total power consumed. Therefore, combining with energy storage technology and implementing demand side management on ASUs can balance the demand on a power grid and bring economic benefits to various enterprises. Air liquefaction is a facet of air separation technology, however, stand-alone liquid air energy storage (LAES) has still issues such as the need for signification investment and a long payback period. To address these issues, we propose a novel air separation unit with energy storage and generation (ASU-ESG) which integrates an ASU, a liquid air storage unit, and an energy release and generation unit. It not only meets the product purity and yield requirements for ASUs, but also realizes the large-scale storage with only one type of device, using a single technology. To assess the performance of ASU-ESG, energy efficiency and economic analyses are conducted, and its effects on power grid balancing are discussed. When no external energy used in ASU-ESG, its electrical round-trip efficiency reaches 53.18%, the electricity cost saves 4.58~6.84% compared with the conventional internal compression ASUs, and the payback period for the LAES system is 2.8~4.2 years. If the ASU-ESG is implemented in China’s ASUs, the annual reduction in the average peak-valley ratio (25.98%) in China is 6.4~7.3%. Considering the widespread application of such ASUs’, for any country and region, its implementation will be of great practical significance to improving the economic benefits of ASUs and balancing the power demand.

Optimal sizing of grid-connected hybrid renewable energy systems without storage: a generalized optimization model

ABSTRACT In this study, a weighted multi-objective mixed-integer linear programming (WMO-MILP) model considering both economic and environmental factors is proposed for the optimal sizing of the grid-connected hybrid renewable energy systems without storage (HRES-WS). The proposed model is capable of designing the system including several different types of renewable energy generation units to meet the demands of various consumption points. One of the significant values of the model is that it holistically combines the operational, technical, physical and/or capacity constraints which are rarely considered in an integrated way in the literature. Another contribution of the model is its ability to evaluate the tradeoff between the cost-related and CO2 related conflicting objectives by allocating them various weights resembling the decision-maker’s cost-based, environmental-based, or partially cost- and environmental-based priorities. A case study is utilized to demonstrate the value of the model. In order to take into consideration the stochastic nature of the modeling environment, the Monte Carlo simulation is used to predict weather data and load demand based on the historical data. The findings indicate that the combined effect of environmental and cost-related objectives influences the demand to be met by RES at acceptable cost and CO2 emission level. For example, focusing only on the environmental objective, the annual amount of CO2 emission decreases by 14% and the total installed capacity increases by 41%, and therefore the system cost increases by 205% as compared to the base case in which the weight of each objective function is assumed to be equal. The proposed model has the potential to significantly support decision-making process when evaluating a grid-connected HRES-WS both economically and environmentally.

Zero-sequence current injection based power flow control strategy for grid inverter interfaced renewable energy systems

ABSTRACT This paper deals with an energy management issue for the grid-connected renewable energy sources connected with unbalanced loads. In the grid-connected energy systems, conventional energy management methods are used to manage balanced active power supplied from energy units to grids/loads. However, unbalanced load groups, like single-phase loads, parallel rectifiers, and three-winding transformers tied to the electric networks, cause zero-sequence currents and impair the power stability at the grid-side. For this purpose, in this study, an improved power flow controller method with zero-sequence current injection is proposed in order to compensate zero-sequence currents and ensure phase equilibrium at grid-side. Therefore, it is tested in a photovoltaic/fuel cell-based hybrid energy system with unbalanced loads, including zero-sequence. Instead of the conventional abc/dq frame used in energy management control, the proposed method makes use of triple αβ transforms and implemented in each phase to be controlled separately under designed unbalanced load groups. Hence, it abolishes the weakness of the conventional abc/dq frame method that generates the undesirable mean reference for zero-sequence situations. In addition, the designed system cannot only mitigate the grid-side zero-sequence currents but also supply active powers to three-phase loads/grids. The optimization of energy systems is also provided through a maximum power point tracking algorithm. In the performance testing, the energy generation units are performed under three states, which produce different supplied currents at the output. In the performance section, it is obvious that zero-sequence components at grid-side currents are significantly reduced via the proposed power flow controller-based system. Also, the results are compared to the conventional method in order to verify the validity of the proposed approach under the designed load groups.

Chance Constrained Optimization for Energy Management in Electric Vehicles

E-powertrain of future electric vehicles could consist of energy generation units (e.g., fuel cells and photovoltaic modules), energy storage systems (e.g., batteries and supercapacitors), energy conversion units (e.g., bidirectional DC/DC converters and DC/AC inverters) and an electric machine, which can work in both generating and motoring modes [1- 6]. An energy management system is responsible to operate the above-mentioned components in a way that the technical constraints are satisfied. This task should be accomplished by solving an optimization problem, which could aim at minimizing the total operation costs [5]. The optimization problem has been widely addressed by deterministic approaches [7], which take into account the forecasted values of active-reactive load profile. However, as shown in Figure 1 (a), it is impossible to accurately forecast the values, meaning that the solutions coming from deterministic approaches could lead to infeasible operations (i.e., constraint violations). Therefore, stochastic optimization approaches [8] should be utilized to fi nd optimal solution strategies while considering uncertain parameters.

Multi-objective co-optimization of power and heat in urban areas considering local air pollution

This paper suggests a novel framework to co-optimize the power and heat in smart cities considering the local air pollution from energy generation units and traffic fumes. To achieve the aim, a smart city comprised of power and heat generation units is addressed. The energy system of the smart city can be connected to the main grid or be operated as a stand-alone power system. Connecting to the main grid, the city trades power in the wholesale electricity market with price uncertainty. In order to co-optimize the operation cost of energy units and to control the pollution levels of the urban area, a Combined Economic Pollution Dispatch Problem (CEPDP) is developed. The CEPDP is optimized under air pollution constraints from both energy generation units and traffic fumes. Increasing the applicability of the suggested approach, pollution density is addressed using the Box model while the wind speed and surface roughness influence on it. To solve the CEPDP, a multi-objective Non-Dominated Sorting Genetic Algorithm (NSGA II) is proposed. The suggested approach is implemented in a virtually-designed smart city located in the center of Iran. The results show that although the use of distributed generation decreases the global emission all over the world, it transmits the air pollution from suburban areas to cities increasing the local pollution. The two conflict objectives, i.e. global and local pollutions, may change the operation of distributed generation to meet the local environment requirements of cities.

Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method

The large-scale renewable energy power plants connected to a weak grid may cause bus voltage fluctuations in the renewable energy power plant and even power grid. Therefore, reactive power compensation is demanded to stabilize the bus voltage and reduce network loss. For this purpose, time-series characteristics of renewable energy power plants are firstly reflected using K-means++ clustering method. The time group behaviors of renewable energy power plants, spatial behaviors of renewable energy generation units, and a time-and-space grouping model of renewable energy power plants are thus established. Then, a mixed-integer optimization method for reactive power compensation in renewable energy power plants is developed based on the second-order cone programming (SOCP). Accordingly, power flow constraints can be simplified to achieve reactive power optimization more efficiently and quickly. Finally, the feasibility and economy for the proposed method are verified by actual renewable energy power plants.

The calculation method of optimized AC choppers capacity in islanded MMC-HVDC system

In order to ensure the safety of renewable energy generation integration system through islanded MMC-HVDC, the AC choppers with the same capacity as sending end converter station are equipped in current projects. However, considering the actual operation needs, it is not necessary to equip so many AC choppers. The optimal capacity of the AC choppers can be calculated according to the most serious fault. The calculated capacity can meet two requirements. One is the renewable energy generation units just start to cut off when the DC voltage reaches the overvoltage limit value. Another one is to minimize the cost and floor area of the AC choppers. It can ensure that the converter station devices is not be damaged in the condition of lowest economic cost. A three-terminal and a four-terminal renewable energy generation integration system through islanded MMC-HVDC are built in PSCAD, which verifies the correctness of the theoretical analysis.

Fault Detection of a Medium Voltage Cable Joint using Support Vector Machine Algorithm

Fault detection of the cable joints is one of significant problems in the electrical utilities and industrial companies to increase the network stability as the system interruption can make side effects for both power generation units, renewable energy generation units and other power sources beside of the costumers. In this paper, fault detection of a 20kV XLPE cable joint had been studied using the measured partial discharge (PD) signals and also support vector machine algorithm. In this study, the measured data had been classified based on proposed features as the indices of data classification and they had been used in the classifier algorithm to determine fault based on measured signals and the corresponding obtained features. The results show that the proposed features and applied algorithm could determine the faults in the cable joints with an appropriate range of accuracy. This study could develop the previous studies on a widely used cable joint. This research can be helpful for the electrical utilities to increase network stability.

A Comprehensive Review and Technical Guideline for Optimal Design and Operations of Fuel Cell-Based Cogeneration Systems

The need for energy is increasing from year to year and has to be fulfilled by developing innovations in energy generation systems. Cogeneration is one of the matured technologies in energy generation, which has been implemented since the last decade. Cogeneration is defined as energy generation unit that simultaneously produced electricity and heat from a single primary fuel source. Currently, the implementation of this system has been spread over the world for stationary and mobile power generation in residential, industrial and transportation uses. On the other hand, fuel cells as an emerging energy conversion device are potential prime movers for this cogeneration system due to its high heat production and flexibility in its fuel usage. Even though the fuel cell-based cogeneration system has been popularly implemented in research and commercialization sectors, the review regarding this technology is still limited. Focusing on the optimal design of the fuel cell-based cogeneration system, this study attempts to provide a comprehensive review, guideline and future prospects of this technology. With an up-to-date literature list, this review study becomes an important source for researchers who are interested in developing this system for future implementation.

Quantification of Efficiency Improvements from Integration of Battery Energy Storage Systems and Renewable Energy Sources into Domestic Distribution Networks

Due to the increasing use of renewable, non-controllable energy generation systems energy storage systems (ESS) are seen as a necessary part of future power delivery systems. ESS have gained research interest and practical implementation over the past decade and this is expected to continue into the future. This is due to the economic and operational benefits for both network operators and customers, battery energy storage system (BESS) is used as the main focus of this research paper. This paper presents an analytical study of the benefits of deploying distributed BESS in an electrical distribution network (DN). The work explores the optimum location of installing BESS and its impact on the DN performance and possible future investment. This study provides a comparison between bulk energy storage installed at three different locations; medium voltage (MV) side and low voltage (LV) side of the distribution transformer (DT) and distributed energy storage at customers’ feeders. The performance of a typical UK DN is examined under different penetration levels of wind energy generation units and BESS. The results show that the minimum storage size is obtained when BESS is installed next to the DT. However, the power loss is reduced to its minimum when BESS and wind energy are both distributed at load busbars. The study demonstrates that BESS installation has improved the loss of life factor of the distribution transformer.

Damping of low-frequency oscillation in power systems using hybrid renewable energy power plants

Global warming, increase in environmental pollution, and high cost of electrical power generation using fossil fuels are considered the most important reasons for the application of renewable energy power plants (REPPs) around the world. In recent years, a new generation of REPPs called hybrid renewable energy power plants (HREPPs) has been implemented in order to have higher efficiency and reliability than conventional REPPs such as wind power plants and photovoltaic power plants. The HREPPs include two or more renewable energy generation units such as wind turbine generation units, and PV generation units. In case of high penetration of these types of power plants, the most common tasks of synchronous generators should be supported by them. One of these tasks is the ability to reduce the low-frequency oscillation (LFO) risk through power oscillation damper such as the power system stabilizers of synchronous generators. In this paper, a novel method is proposed for LFO damping by HREPPs, which is based on the design of an optimal power oscillation damper (OPOD) implemented in the generic HREPP controller model. The structure of the proposed OPOD is a 2nd-order single-input lead-lag controller, and its performance is investigated in a modified two-area test system. The simulation results show the proper performance of the HREPP for LFO damping using the proposed OPOD in the various loading levels and different short circuit ratio values.

Integrated flywheel and spiral spring triboelectric nanogenerator for improving energy harvesting of intermittent excitations/triggering

Triboelectric nanogenerators (TENGs) have attracted extensive attention for converting mechanical energy in our living/working environment into electric energy. However, many types of mechanical motions in daily life are intermittent, causing the harvester to give a non-continuous but pulsed output. Here, an integrated flywheel and spiral spring TENG (FSS-TENG) is reported that improves energy harvesting of intermittent excitations/triggering by storing the energy in the form of a continuous rotational energy of a flywheel as well as the potential energy of a spiral spring, which are expected to produce a constant energy output even after the excitation. Transmission unit of FSS-TENG is mounted on the box to convert intermittent motion into rotational motion. With the stored energy, the flywheel provides long running time. The energy-generating unit between the flywheel and the shell continuously outputs electric energy. The effect of each component on output performance is systematically studied. Under a single excitation, the maximum running time of FSS-TENG is over 20 s. In the high-performance mode, FSS-TENG generates 38.4 mJ of electric energy. The maximum load voltage and short-circuit current are 680 V and 33.5 μA, respectively. The FSS-TENG easily drives more than 2000 light emitting diodes (LEDs), power thermostats, and potentially has broader applications in environmental energy harvesting.