This study focuses on the sizing and optimization of a micro-grid with storage, which is destined to supply the load of an economic activity zone (EAZ) in Sidi Bouzid, Tunisia. To solve this problem, a genetic algorithm is established and programmed into MATLAB. The objective functions are considered by providing three minimums, namely Greenhouse Gas emissions (GHG), Life Cycle Cost (LCC) and Embodied Energy (EE), for three values of loss of power supply probability (LPSP) previously fixed. The sizing and optimization results are found and evaluated using a time series exchange of energy during a year to determine the optimal component size of a photovoltaic/wind/battery system (PV/WT/Bat). The simulation results show that the lowest ratio of LPSP values corresponds to the higher GHG, EE, LCC, photovoltaic panels area (APV), battery storage capacity (Cn), wind turbines area (AWT) and vice versa. This means that demanding higher energy reliability leads to higher energy cost and polluti... [more]

Pipe height in cylindrical neutron moderator is an important factor to flow pattern, temperature distribution and even the neutron characters. In this paper, the steady-state thermal analysis of cold neutron moderator is carrying out with different heights, conjugated heat transfer method and one-way coupled with a neutron transfer software. The different pipe heights, which is the jet-to-surface distances (H/D = 0.5~6), were compared using a 2D moderator model. The results show that vortex size and velocity gradient from container wall to vortex center vary with H/D, the center of recirculation zone nearly remain constant, and heat transfer effect is weakened on the target bottom surface. With H/D increasing, the velocity at bottom target surface is progressively decreased, and cooling effect is poor, leading to the rise in temperature. The optimal range cooling performance is (H/D) = 0.5~1 at Re = 1.7 × 105, and the enhancement of beam power further strengthens the thermal deposition... [more]

In the last decade, China has sharply tightened the monitoring values for wastewater treatment plants (WWTPs). In some regions with sensitive discharge water bodies, the values (24 h composite sample) must be 1.5 mg/L for NH4-N and 10 mg/L for total nitrogen since 2021. Even with the previously less strict monitoring values, around 50% of the wastewater treatment plants in China were permanently unable to comply with the nitrogen monitoring values. Due to the rapid changes on-site to meet the threshold values and the strong relation to energy-intensive aeration strategies to sufficiently remove nitrogen, WWTPs do not always work energy-efficiently. A Chinese WWTP (450,000 Population equivalents or PE) with upstream denitrification, a tertiary treatment stage for phosphorus removal and disinfection, and aerobic sludge stabilisation was modelled in order to test various concepts for operation optimisation to lower energy consumption while meeting and undercutting effluent requirements. F... [more]

This study concerns the use of the critical chain method to schedule the construction of renewable energy facilities. The critical chain method is recognized as a useful project management tool, transforming a stochastic problem of uncertainty in activity durations into a deterministic one. However, this method has some shortcomings. There are no clear principles of grouping non-critical activities into feeding chains. Another ambiguity is sizing the feeding buffers with regard to the topology of the network model and the resulting dependencies between activities, located in different chains. As a result, it is often necessary to arbitrarily adjust the calculated sizes of feeding buffers before inserting them into the schedule. The authors present the new approach to sizing the time buffers in the schedule, enabling a quick assessment of the quality of a given solution variant and finding a solution that best meets the established criteria, conditions, and constraints. The essence of t... [more]

With the increasing penetration of intermittent renewable energy generation, there is a growing demand to use the inherent flexibility within buildings to absorb renewable related disruptions. Heat pumps play a particularly important role, as they account for a high share of electricity consumption in residential units. The most common way of quantifying the flexibility is by considering the response of the building or the household appliances to external penalty signals. However, this approach neither accounts for the use cases of flexibility trading nor considers its impact on the prosumer comfort, when the heat pump should cover the stochastic domestic hot water (DHW) consumption. Therefore, in this paper, a new approach to quantifying the flexibility potential of residential heat pumps is proposed. This methodology enables the prosumers themselves to generate and submit the operating plan of the heat pump to the system operator and trade the alternative operating plans of the heat... [more]

This article presents a two-stage optimization model aiming to determine optimal energy mix in distribution networks, i.e., battery energy storage, fuel cell, and wind turbines. It aims to alleviate the impact of high renewable penetration on the systems. To solve the proposed complex optimization model, a standard variant of the dragonfly algorithm (DA) has been improved and then applied to find the optimal mix of distributed energy resources. The suggested improvements are validated before their application. A heuristic approach has also been introduced to solve the second stage problem that determines the optimal power dispatch of battery energy storage as per the size suggested by the first stage. The proposed framework was implemented on a benchmark 33-bus and a practical Indian 108-bus distribution network over different test cases. The proposed model for energy mix and modified DA technique has significantly enhanced the operational performance of the network in terms of average... [more]

Grid-connected microgrids consisting of renewable energy sources, battery storage, and load require an appropriate energy management system that controls the battery operation. Traditionally, the operation of the battery is optimised using 24 h of forecasted data of load demand and renewable energy sources (RES) generation using offline optimisation techniques, where the battery actions (charge/discharge/idle) are determined before the start of the day. Reinforcement Learning (RL) has recently been suggested as an alternative to these traditional techniques due to its ability to learn optimal policy online using real data. Two approaches of RL have been suggested in the literature viz. offline and online. In offline RL, the agent learns the optimum policy using predicted generation and load data. Once convergence is achieved, battery commands are dispatched in real time. This method is similar to traditional methods because it relies on forecasted data. In online RL, on the other hand,... [more]

The Algerian economy and electricity generation sector are strongly dependent on fossil fuels. Over 93% of Algerian exports are hydrocarbons, and approximately 90% of the generated electricity comes from natural gas power plants. However, Algeria is also a country with huge potential in terms of both renewable energy sources and industrial processes waste heat recovery. For these reasons, the government launched an ambitious program to foster renewable energy sources and industrial energy efficiency. In this context, steam and organic Rankine cycles could play a crucial role; however, there is a need for reliable and time-efficient optimization tools that take into account technical, economic, environmental, and safety aspects. For this purpose, the authors built a mathematical tool able to optimize both steam and organic Rankine units. The tool, called Improved Rankine Cycle Plant Designer, was developed in MATLAB environment, uses the Genetic Algorithm toolbox, acquires the fluids th... [more]

The increasing penetration of renewable energy sources in power grids highlights the role of battery energy storage systems (BESSs) in enhancing the stability and reliability of electricity. A key challenge with the renewables’, specially the BESSs, integration into the power system is the lack of proper dynamic models and their application in power system analyses. The control design strategy mainly depends on the system dynamics which underlines the importance of the system accurate dynamic modeling. Moreover, control design for the power system is a complicated issue due to its complexity and inter-connectivity, which makes the application of distributed control to improve the stability of a large-scale power system inevitable. This paper presents an optimal distributed control design for the interconnected systems to suppress the effects of small disturbances in the power system employing utility-scale batteries based on existing battery models. The control strategy is applied to t... [more]

The adjustment of rail traffic in the event of an electrical infrastructure disruption presents an important decision-making process for the smooth operation of the network. Railway systems are complex, and their analysis relies on expensive simulations, which makes incident management difficult. This paper proposes the use of sensitivity analysis in order to evaluate the influence of different traffic adjustment actions (e.g., spacing between trains and speed reduction) on the train supply voltage, which must never drop below the critical value prescribed by technical standards. Three global sensitivity analysis methods dedicated to black box, multivariate, nonlinear models are considered: generalized Sobol indices, energy distance-based indices, and regional sensitivity analysis. The three methods are applied to a simple traffic rescheduling test case and give similar results, but at different costs. Regional sensitivity analysis appears to be the most suitable method for the present... [more]

The intermittent nature of renewable sources, such as solar and wind, leads to the need for a hybrid renewable energy system (HRES) that can provide uninterrupted and reliable energy to a remote and off-grid location with the use of a biogas generator and battery. In the present study, conventional PV panels have been integrated with phase change material (PCM) for power enhancement. In addition, various configurations (i. PV-Wind-Battery system, ii. PV-PCM-Wind-Battery, iii. PV-Wind-Biogas-Battery and iv. PV-PCM-Wind-Biogas-Battery) have been compared for the hot and humid climatic location of Chennai, India. Optimization has been carried out to minimize the cost of energy and the net present cost has also been computed. It has been found that the integration of PCM with the PV-Wind-Biogas-Battery-based off-grid system results in savings of USD 0.22 million in terms of net present cost and reduces the cost of energy from USD 0.099/kWh to USD 0.094/kWh. Similarly, for another off-grid... [more]

In recent years, a growing number of enterprises have taken different steps to reduce the energy consumption and carbon emissions of information and communication technology (ICT) assets. Because of the expansion of digitalization and the need for rapid access to information, enterprises have been compelled to optimize the location and utilization of their ICT hardware. In this context, this paper presents a novel method based on a mixed-integer linear programming approach for optimizing the physical location and task allocation of printing devices in office floor plans considering the power usage of the ICT assets, the costs related to the purchase and service of the individual devices, operating costs, and distance between employees and printing devices. The applicability of the proposed model is illustrated using the case study of a company with 100 functional departments located in several office buildings across Poland. The results reveal that the model guarantees the execution of... [more]

To meet the demand of multiple power requirements, and enhance power utilization, a new type of dual-element electricity unit is designed in this study, which is a permanent magnet piston mechanical electric engine. Based on the analysis method of traditional internal combustion engines and linear generators, the working principle of the engine and the magnetic field distribution in the electrodynamic structure are analyzed, the machine dynamics model and electrodynamics model of the engine are established, then the theoretical evaluation is additionally established using finite elements. Based on this, an optimization model is constructed with the electrodynamic shape dimension as the optimization variable, with the intention of growing the output power. The optimization of the engine electrodynamic shape is executed via the use of the finite aspect approach and the NLPQL optimization algorithm integrated. The results show that the optimized engine output electricity expanded to 8.40... [more]

In the Global South, pico- and micro-hydropower turbines are often made by local workshops. Despite several advantageous features, e.g., a high power density and capacity to handle silt, there is no commonly available Turgo turbine design appropriate for local manufacture. Technological developments including the internet, CAD, and additive manufacturing increase the opportunity to precisely transfer designs around the world. Consequently, design improvements can be shared digitally and used by manufacturers in their local context. In this paper, a rationalised CFD approach was used to guide simple design changes that improve the efficiency of a Turgo turbine blade. The typical manufacturing capacity of the micro-hydropower industry in Nepal was used to rationalise the variation of potential design changes. Using the geometry and operational parameters from an existing design as a benchmark, a two-blade, homogenous, multiphase model was developed and run using the commercial code ANSYS... [more]

An internal combustion engine (ICE) is a highly nonlinear dynamic and complex engineering system whose operation is constrained by operational limits, including emissions, noise, peak in-cylinder pressure, combustion stability, and actuator constraints. To optimize today’s ICEs, seven to ten control actuators and 10−20 feedback sensors are often used, depending on the engine applications and target emission regulations. This requires extensive engine experimentation to calibrate the engine control module (ECM), which is both cumbersome and costly. Despite these efforts, optimal operation, particularly during engine transients and to meet real driving emission (RDE) targets for broad engine speed and load conditions, has still not been obtained. Methods of model predictive control (MPC) have shown promising results for real-time multi-objective optimal control of constrained multi-variable nonlinear systems, including ICEs. This paper reviews the application of MPC for ICEs and analyzes... [more]

The role of a pre-cooler is critical to the sCO2-BC as it not only acts as a sink but also controls the conditions at the main compressor’s inlet that are vital to the cycle’s overall performance. Despite their prime importance, studies on the pre-cooler’s design are hard to find in the literature. This is partly due to the unavailability of data around the complex thermohydraulic characteristics linked with their operation close to the critical point. Henceforth, the current work deals with designing and optimizing pre-cooler by utilizing machine learning (ML), an in-house recuperator and pre-cooler design, an analysis code (RPDAC), and a cycle design point code (CDPC). Initially, data computed using 3D Reynolds averaged Navier-Stokes (RANS) equation is used to train the machine learning (ML) model based on the deep neural network (DNN) to predict Nusselt number (Nu) and friction factor (f). The trained ML model is then used in the pre-cooler design and optimization code (RPDAC) to ge... [more]

This paper utilises a two-stage demand response-enabled energy management algorithm for a typical Turkish self-sufficient living space. The proposed energy management model provides an additional gain in line with the goal of self-sufficiency by scheduling flexible loads and energy storage systems at home according to a static time of use tariff. The impact of load scheduling and battery optimisation were evaluated in the scope of self-sufficiency, economic gain and return on investment performances. According to the results, the proposed two-stage structure provided a net saving increase of 9.5% in the one-battery scenario, and it rises to 14% in the design with three batteries. On the other hand, when we inspect the energy management scenarios with the return on investment (ROI) calculations, we see that the single battery system has a higher ROI than the two or three battery systems due to the increased battery cost. Moreover, the ROI value, 13.9% without optimisation, increased to... [more]

The purpose of this study was to apply new methods of econometric models to the Life Cycle Assessment (LCA) of physical assets, by integrating investments such as maintenance, technology, sustainability, and technological upgrades, and to propose a means to evaluate the Life Cycle Investment (LCI), with emphasis on sustainability. Sustainability is a recurrent theme of existing studies and will be a concern in coming decades. As a result, equipment with a smaller environmental footprint is being continually developed. This paper presents a method to evaluate asset depreciation with an emphasis on the maintenance investment, technology depreciation, sustainability depreciation, and technological upgrade investment. To demonstrate the value added of the proposed model, it was compared with existing models that do not take the previously mentioned aspects into consideration. The econometric model is consistent with asset life cycle plans as part of the Strategic Asset Management Plan of t... [more]

Due to the substantial amounts of money involved and the complex interactions of a number of different factors, managers of oil and gas companies are faced with significant challenges when making investment decisions that will increase business efficiency and achieve competitive advantages, especially through cost control. Due to the various uncertainties of the current period, optimal investment strategies are difficult to determine. Thus, through an economic analysis that includes data analysis, quantitative risk analysis scenarios, modelling and simulations, a work framework, in the form of a generic algorithm, is proposed with the aim of generating a complex procedure for optimizing investment decisions in oil field development. A complex set of elements is considered in the analysis: costs (operational expenditures (OPEX) and capital expenditures (CAPEX), daily drilling rig costs), prices (oil, gas, separation and water injection preparation), production profiles, different types... [more]

Hydrogen used as an energy carrier can provide an important route to the decarbonization of energy supplies, but realizing this opportunity will require both significantly increased production and transportation capacity. One route to increased transportation capacity is the shipping of liquid hydrogen, but this requires an energy-intensive liquefaction step. Recent study work has shown that the energy required in this process can be reduced through the implementation of new and improved process designs, but since all low-temperature processes are affected by the available heat-sink temperature, local ambient conditions will also have an impact. The objective of this work is to identify how the energy consumption associated with hydrogen liquefaction varies with heat-sink temperature through the optimization of design parameters for a next-generation mixed refrigerant based hydrogen liquefaction process. The results show that energy consumption increases by around 20% across the coolin... [more]

Regenerative braking can significantly improve the energy efficiency of hybrid and electric vehicles, and many studies have been carried out in order to improve and optimize the energy recovery of the braking energy. In the paper, the optimization of regenerative braking by means of braking force modulation is analysed, with specific application to the case of cars converted into Through-the-road (TTR) hybrid vehicles, and an optimal modulation strategy is also proposed. Car hybridization is an emerging topic since it may be a feasible, low-cost, intermediate step toward the green transition of the transport system with a potential positive impact in third-world countries. In this case, the presence of two in-wheel-motors installed on the rear axle and of the original mechanical braking system mounted on the vehicle can result in limited braking energy recovery in the absence of proper braking management strategies. A vehicle longitudinal model has been integrated with an algorithm of... [more]

This paper proposes the algorithm to control the current ratio of the transmitting (Tx) coils for proper power distribution to the two receiving (Rx) coils in wireless power transfer (WPT) system. The proposed algorithm assumes that each Rx coil appears at different times to consider the situation where multiple users request power transmission as practically as possible. That is, suppose the second Rx coil enters the charging space later than the first Rx coil. When each coil enters the charging space, only the Tx coil is used to obtain the value required for calculation. Using the obtained result, the optimized Tx coil current is calculated by the proposed algorithm and proper power distribution to both Rx coils is achieved. Three Tx coils and two Rx coils are constructed using the ANSYS MAXWELL simulation tool. As a result of applying the proposed algorithm, it was confirmed that a similar level of power was transmitted between 40∼60%, respectively. The sum of the power transmitted... [more]

The propagation of hybrid power systems (solar−diesel−battery) has led to the development of new energy management system (EMS) strategies for the effective management of all power generation technologies related to hybrid microgrids. This paper proposes two novel EMS strategies for isolated hybrid microgrids, highlighting their strengths and weaknesses using simulations. The proposed strategies are different from the EMS strategies reported thus far in the literature because the former enable the real-time operation of the hybrid microgrid, which always guarantees the correct operation of a microgrid. The priority EMS strategy works by assigning a priority order, while the optimal EMS strategy is based on an optimization criterion, which is set as the minimum marginal cost in this case. The results have been obtained using MATLAB/Simulink to verify and compare the effectiveness of the proposed strategies, through a dynamic microgrid model to simulate the conditions of a real-time oper... [more]

High penetration levels of Plug-in Electric Vehicles (PEVs) could cause stress on the network and might violate the limits and constraints under extreme conditions, such as exceeding power and voltage limits on transformers and power lines. This paper defines extreme conditions as the state of a load or network that breaks the limits of the constraints in an optimization model. Once these constraints are violated, the optimization algorithm might not work correctly and might not converge to a feasible solution, especially when the complexity of the system increases and includes nonlinearities. Hence, the algorithm may not help in mitigating the impact of penetrating PEVs under extreme conditions. To solve this problem, an original algorithm is suggested that is able to adapt the constraints’ limits according to the energy demand and the energy needed to charge the PEVs. Different case scenarios are studied for validation purposes, such as charging PEVs under different state of charge l... [more]

The establishment of the concept of sustainable, decentralised, multi-carrier energy systems, together with the declining costs of renewable energy technologies, has proposed changes in off-grid electrification interventions towards the development of integrated energy systems. Notwithstanding the potential benefits, the optimal capacity planning of such systems with multiple energy carriers—electricity, heating, cooling, hydrogen, biogas—is exceedingly complex due to the concurrent goals and interrelated constraints that must be relaxed. To this end, this paper puts forward an innovative new optimal capacity planning method for a first-of-its-kind stand-alone multiple energy carrier microgrid (MECM) serving the electricity, hot water, and transportation fuel demands of remote communities. The proposed off-grid MECM system is equipped with solar photovoltaic panels, wind turbines, a hydrogen-based energy storage system—including an electrolyser, a hydrogen reservoir, and a fuel cell—a... [more]