A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data

Peak load reduction is one of the most essential obligations and cost-effective tasks for electrical energy consumers. An isolated microgrid (IMG) system is an independent limited capacity power system where the peak shaving application can perform a vital role in the economic operation. This paper presents a comparative analysis of a categorical variable decision tree algorithm (CVDTA) with the most common peak shaving technique, namely, the general capacity addition technique, to evaluate the peak shaving performance for an IMG system. The CVDTA algorithm deals with the hybrid photovoltaic (PV)—battery energy storage system (BESS) to provide the peak shaving service where the capacity addition technique uses a peaking generator to minimize the peak demand. An actual IMG system model is developed in MATLAB/Simulink software to analyze the peak shaving performance. The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. Actual variable load data and PV generation data are considered to conduct the simulation case studies which are collected from a real IMG system. The simulation result exhibits the effectiveness of the CVDTA algorithm which can minimize the peak demand better than the capacity addition technique. By ensuring the peak shaving operation and handling the economic generation dispatch, the CVDTA algorithm can ensure more energy savings, fewer system losses, less operation and maintenance (O&M) cost, etc., where the general capacity addition technique is limited.

Experimental study of an internal combustion engine fueled by a low-calorific value producer gas

This paper describes an experimental study of the operation of an internal combustion engine of fueled by a low-calorific value gas. The main operating parameters of low-power ICE were determined. Efficiency was also evaluated when the ICE was converted to operate on producer gas. In the experiment, it was shown that the engine reached a stable operating mode under load and data on the temperature and exhaust gases composition were obtained. According to our estimates, in the steady-state operation of the internal combustion engine with a load, the efficiency factor was about 22 %. When using the model gas, the from generator output power, was about 30-40 % of the nominal value, under variable load conditions. However, it was found that in steady-state operation, the power of the internal combustion engine was 40-55% of the nominal value.

Constant stress arches and their design space

It is generally accepted that an optimal arch has a funicular (moment-less) form and least weight. However, the feature of least weight restricts the design options and raises the question of durability of such structures. This study, building on the analytical form-finding approach presented in Lewis (2016. Proc. R. Soc. A 472 , 20160019. ( doi:10.1098/rspa.2016.0019 )), proposes constant axial stress as a design criterion for smooth, two-pin arches that are moment-less under permanent (statistically prevalent) load. This approach ensures that no part of the structure becomes over-stressed under variable load (wind, snow and/or moving objects), relative to its other parts—a phenomenon observed in natural structures, such as trees, bones, shells. The theory considers a general case of an asymmetric arch, deriving the equation of its centre-line profile, horizontal reactions and varying cross-section area. The analysis of symmetric arches follows, and includes a solution for structures of least weight by supplying an equation for a volume-minimizing, span/rise ratio. The paper proposes a new concept, that of a design space controlled by two non-dimensional input parameters; their theoretical and practical limits define the existence of constant axial stress arches. It is shown that, for stand-alone arches, the design space reduces to a constraint relationship between constant stress and span/rise ratio.

Development of a Digitally Controlled Inductive Power Transfer System with Post-Regulation for Variable Load Demand

Inductive Power Transfer (IPT) is an emerging technology enabling a contactless charging process in manifold applications such as electric vehicles, wearable and portable devices, or biomedical applications. Such technology can be profitably used to develop enhanced electronic solutions in the framework of smart cities, homes and smart workplaces. This paper presents the development and realization of a series–series compensated IPT System (IPTS) followed by a post-regulator implemented by means of a DC–DC converter. Such a system is modeled through a first harmonic approximation method, and a sensitivity analysis of the IPTS performance is carried out with respect to the variations of the primary inverter switching frequency and phase-shift angle. As an element of novelty of this work, the bias points are determined which allow the efficiency maximization while ensuring system controllability. An enhanced dynamic modeling of the system is then performed by means of a coupled mode theory, including the inverter phase-shift modulation and extending its validity to whatever operating frequency. A digital control of the post-regulator is implemented by means of a commercial low-cost microcontroller enabling the output voltage regulation under both fixed and variable load conditions through a voltage mode control technique. An IPTS prototype is eventually realized, which is able to correctly perform the output voltage regulation at the desired nominal value of 12 V for static resistive loads in the range [5,24] Ω, yielding the output power in the range [6, 28.8] W and the experimental efficiencies going from 72.1% (for 24 Ω) to 91.7% (for 5 Ω). The developed system can also be effectively used to deliver up to 35 W output power to variable loads, as demonstrated during the battery charging test. Finally, an excellent output voltage regulation is ascertained for load transients between 5 Ω and 24 Ω, with limited over- and undershoot amplitudes (less than 3% of the nominal output voltage), thus enabling the use of the proposed system for both fixed and variable loads in the framework of smart homes and workplaces applications.

Research and Experimental Analysis of Hydraulic Cylinder Position Control Mechanism Based on Pressure Detection

This paper studies the precise position control of the hydraulic cylinder in the hydraulic support. The aim of this paper is to develop a method of hydraulic cylinder position control based on pressure and flow coupling, which takes the coupling feedback of load and flow into account, especially in the scene of cooperative control under the condition of multiple actuators and variable load. This method solves the problems of slow movement and sliding effect of hydraulic support in the traditional time-dependent hydraulic position control, as well as better realizes the intelligent and unmanned development of the fully mechanized mining face. First, based on the flow continuity equation and Newton Euler dynamic equation, the flow and stroke control model with the input and output pressure of hydraulic cylinder is established. Then, the effectiveness and correctness of the control model are verified by the comparison between the hydraulic system simulation software, AMESim, and the experiment. Finally, a test system is built. When the system pressure is large than 10 MPa, the error between the data determined by the fitting algorithm and the actual detection data is within 5%, which verifies the effectiveness of the theory and simulation model.

Experimental-theoretical studies of hydrotechnical angular-type retaining walls

Relevance. Retaining walls are common structures that are part of waterworks. They have the characteristic features of hydraulic structures, such as large dimensions, low percentages of reinforcement (up to 1.0%), horizontal interblock joints. The listed features determine the nature of the work and the stress-strain state of the retaining walls. The main loads on the rear faces of the retaining walls are loads from the action of the backfill soil. The incomplete consideration of the design features and the nature of the loads action in the design of a number of retaining walls that are in the stage of long-term operation has caused the need to strengthen them. One of the reinforcement methods was to install reinforcement rods in drilled inclined holes in the zones of horizontal interblock joints. It was necessary to conduct experimental studies of reinforced concrete retaining walls under the action of various loads, in particular conside- ring the reinforcement by inclined rods. The aim of the experimental research was to study the effect of variable load on the stress-strain state of these structures, among others with due regard to inclined reinforcement installed in the zones of horizontal interblock joints. When solving the set tasks, proven experimental methods of researching reinforced concrete structures of hydrotechnical structures were used. Results. Experimental data from the study of models of retaining walls, including those with reinforcement by inclined reinforcement, at different locations of the resultant load on rear faces of models were obtained. An experimental substantiation of the reinforcement of reinforced concrete structures of retaining walls with an inclined reinforcement crossing horizontal construction joints has been carried out.

Dynamic Modelling and Validation of an Air-to-Water Reversible R744 Heat Pump for High Energy Demand Buildings

This paper presents a reversible heat pump based on CO2 as the refrigerant, able to provide heating, cooling, and domestic hot water to high energy demand buildings. The unit was developed and tested under the EU H2020 project MultiPACK, which has the main goal of assuring the market about the feasibility, reliability, and energy efficiency of CO2 integrated systems for heating and cooling and promoting a fast transition to low environmental impact solutions. Within the project, the confidence raising was performed by installation and monitoring of fully integrated state-of-the art CO2 systems in the Southern European Climate. With the aim of predicting the unit behaviour under variable load and boundary conditions, a dynamic model of the entire unit was developed with commercial software, considering actual components and the implemented control system and it was validated with experimental data, collected at the factory’s lab before commissioning. The validation against experimental data collected during operation as a heat pump demonstrated a maximum percentage difference between the experimental and predicted value of gas–cooler heat flow rate equal to +5.0%. A preliminary comparison with the experimental data in chiller configuration is reported, however further development was required to achieve a satisfactory validation. Lastly, the numerical model was utilized to simulate a typical operation in heat pump configuration with the system coupled with a hot water tank storage for the production of domestic hot water and space heating; the model predicts higher COP when operating in domestic hot water operation due to the lower water inlet temperature.

Vibration characteristics of the gear shaft-bearing system with compound defects under variable operating conditions

Due to the variable working conditions, there are compound defects in the gear shaft-bearing system easily, vibration signals are very complex, and the fault diagnosis of the system becomes more difficult. Thus, a 36 degrees of freedom (36-DOFs) dynamic model is established for discussing the vibration characteristics of the gear shaft-bearing system, the gear pair spalling defect is considered, there are localized defects on the inner raceway and outer raceway of the supporting bearing, the work conditions contain variable speed, variable load, speed fluctuation, and load fluctuation. The obtained vibration signal is processed by the short-time Fourier transform for the time–frequency distribution map. When the gear shaft-bearing system with compound defects operates under variable conditions, roller passing outer raceway frequency, roller passing inner raceway frequency, gearing meshing frequency, and the relative harmonic frequencies can also be found. The defect frequencies and frequency amplitude are increasing with the speed while the system makes the accelerated movement. While the load acting on the system increases, the defect frequencies remain unchanged, but the frequency amplitude becomes larger. If there are fluctuations of the speed and load, the apparent defect frequency fluctuation and amplitude fluctuation is generated. The mathematical model and the analysis results are verified by the experiment, which will provide the theoretical basis for the fault diagnosis of the gear shaft-bearing system.

Bearing Fault Diagnosis under Variable Working Conditions Based on Deep Residual Shrinkage Networks and Transfer Learning

Nowadays, deep learning has made great achievements in the field of rotating machinery fault diagnosis. But in the practical engineering scenarios, when facing a large number of unlabeled data and variable operating conditions, only using a deep learning algorithm may reduce the performance. In order to solve the above problem, this paper uses a method of combining transfer learning with deep learning. First, the deep shrinkage residual network is constructed by adding soft thresholds to extract the characteristics of bearing vibration data under noise redundancy. Then, the joint maximum mean deviation (JMMD) criterion and conditional domain adversarial (CDA) learning domain adapting network are used to align the source and target domains. At the same time, adding transferable semantic augmentation (TSA) regular items improves alignment performance between classes. Finally, the proposed model is verified by three experiments: variable load, variable speed, and variable noise, which overcomes the shortcomings of traditional deep learning and shallow transfer learning algorithms.