Despite their obvious benefit in terms of energy efficiency and their potential benefit on pollutant emissions, Flue Gas Condensers (FGCs) are still not widely spread in biomass combustion plants. Although their costs have significantly decreased during the last decade, the economic viability of FGC retrofits is not straightforward and their return on investments is mainly dependent on the temperature of the available heat sink and the moisture content of the fuel. Based on a new techno-economic model of a FGC validated with recent industrial data, this paper presents a methodology to assess the economic viability of an FGC retrofitting in a medium-scale biomass combustion plant. The proposed methodology is applied to the case of a typical District Heating plant for which real data was collected. For the first time, the usual assumptions of constant process data generally used are challenged by considering the variability of the return temperature and heat demand over the year. Further... [more]

Solving the Unit Commitment problem is an important step in optimally dispatching the available generation and involves two stages—deciding which generators to commit, and then deciding their power output (economic dispatch). The Unit Commitment problem is a mixed-integer combinational optimization problem that traditional optimization techniques struggle to solve, and metaheuristic techniques are better suited. Dragonfly algorithm (DA) and particle swarm optimization (PSO) are two such metaheuristic techniques, and recently a hybrid (DA-PSO), to make use of the best features of both, has been proposed. The original DA-PSO optimization is unable to solve the Unit Commitment problem because this is a mixed-integer optimization problem. However, this paper proposes a new and improved DA-PSO optimization (referred to as iDA-PSO) for solving the unit commitment and economic dispatch problems. The iDA-PSO employs a sigmoid function to find the optimal on/off status of units, which is the mi... [more]

Nowadays, wireless sensor networks (WSNs) are becoming increasingly popular due to the wide variety of applications. The network can be utilized to collect and transmit numerous types of messages to a data sink in a many-to-one fashion. The WSNs usually contain sensors with low communication ability and limited battery power, and the battery replacement is difficult in WSNs for large amount embedded nodes, which indicates a balanced routing strategy is essential to be developed for an extensive operation lifecycle. To realize the goal, the research challenges require not only to minimize the energy consumption in each node but also to balance the whole WSNs traffic load. In this article, a Shortest Path Tree with Energy Balance Routing strategy (SPT-EBR) based on a forward awareness factor is proposed. In SPT-EBR, Two methods are presented including the power consumption and the energy harvesting schemes to select the forwarding node according to the awareness factors of link weight. F... [more]

Electric vehicles (EVs) are envisaged to be the future transportation medium, and demonstrate energy efficiency levels much higher than conventional gasoline or diesel-based vehicles. However, the sustainability of EVs is only justified if the electricity used to charge these EVs is availed from a sustainable source of energy and not from any fossil fuel or carbon generating source. In this paper, the challenges of the EV charging stations are discussed while highlighting the growing use of distributed generators in the modern electrical grid system. The benefits of the adoption of photovoltaic (PV) sources along with battery storage devices are studied. A multiport converter is proposed for integrating the PV, charging docks, and energy storage device (ESD) with the grid system. In order to control the bidirectional flow between the generating sources and the loads, an intelligent energy management system is proposed by adapting particle swarm optimization for efficient switching betw... [more]

The optimal reactive power dispatch (ORPD) problem represents a noncontinuous, nonlinear, highly constrained optimization problem that has recently attracted wide research investigation. This paper presents a new hybridization technique for solving the ORPD problem based on the integration of particle swarm optimization (PSO) with artificial physics optimization (APO). This hybridized algorithm is tested and verified on the IEEE 30, IEEE 57, and IEEE 118 bus test systems to solve both single and multiobjective ORPD problems, considering three main aspects. These aspects include active power loss minimization, voltage deviation minimization, and voltage stability improvement. The results prove that the algorithm is effective and displays great consistency and robustness in solving both the single and multiobjective functions while improving the convergence performance of the PSO. It also shows superiority when compared with results obtained from previously reported literature for solvin... [more]

This paper puts forward a new mathematical model, which is a coal damage-heat-fluid-solid multi-field coupling theory, in order to reveal the mechanical mechanism of the increase of coal-bed methane recovery through thermal stimulation, and to evaluate its effect. The strain field is introduced to define the damage of coal by considering of the effects of temperature, gas pressure, and mining stress of the coal seam. It is used to quantitatively describe the degree of coal rupture and damage. Additionally, the elastic and damage constitutive equation of coal and rock mass, the governing equation of the temperature field, and the coupling equation of gas diffusion and seepage are established. Based on these equations, the finite element source program is redeveloped by using the FORTRAN language, and a multi-field coupling analysis program is compiled. This program takes the temperature, the gas seepage, and the damage and deformation of coal and rock mass into consideration. The effect... [more]

Overcapacity in China’s coal industry has serious negative impacts on the rational allocation of coal resources and stable operation of the national economy. Since 2016, the Chinese government has implemented a series of de-capacity policies to optimise coal production capacity. Timely policy effect assessment is of great significance to the government to guide high-quality development of the coal industry. This paper first reviews the dilemma encountered by China’s coal industry prior to 2016, and then analyses the progress and effect of coal industry de-capacity. The main results are as follows: (1) The capacity reduction is mainly distributed in the central and southwestern regions. Most of the coal mines are state-owned, and there is a prominent worker resettlement problem. (2) The capacity optimisation policy has accelerated the implementation of the overall spatial planning of China’s coal supply. China’s coal production centre has shifted from the central and eastern regions to... [more]

The Energetic Transition Law in Mexico has established that in the next years, the country has to produce at least 35% of its energy from clean sources in 2024. Based on this, a proposal in this study is the cogeneration between the principal thermal power plants along the Mexican states of the Gulf of Mexico with modeled wind farms near to these thermal plants with the objective to reduce peak electricity demand. These microscale models were done with hourly MERRA-2 data that included wind speed, wind direction, temperature, and atmospheric pressure with records from 1980−2018 and taking into account roughness, orography, and climatology of the site. Wind speed daily profile for each model was compared to electricity demand trajectory, and it was seen that wind speed has a peak at the same time. The amount of power delivered to the electric grid with this cogeneration in Rio Bravo and Altamira (Northeast region) is 2657.02 MW and for Tuxpan and Dos Bocas from the Eastern region is 319... [more]

Fossil fuels have been heavily exploited since the Industrial Revolution. The resulting carbon emissions are widely regarded as being the main cause of global warming and climate change. Key mitigation technologies for reducing carbon emissions include carbon capture and storage (CCS) and renewables. According to recent analysis of the International Energy Agency, renewables and CCS will contribute more than 50% of the cumulative emissions reductions by 2050. This paper presents a new mathematical programming model for multi-footprint energy sector planning with CCS and renewables deployment. The model is generic and considers a variety of carbon capture (CC) options for the retrofit of individual thermal power generation units. For comprehensive planning, the Integrated Environmental Control Model is employed in this work to assess the performance and costs of different types of power generation units before and after CC retrofits. A case study of Taiwan’s energy sector is presented t... [more]

This investigation was carried out to highlight the influence of the variation of permeability of the porous media with respect to the injection orientations during enhanced gas recovery (EGR) by CO2 injection using different core samples of different petrophysical properties. The laboratory investigation was performed using core flooding technique at 1300 psig and 50 °C. The injection rates were expressed in terms of the interstitial velocities to give an indication of its magnitude and variation based on the petrophysical properties of each core sample tested. Bandera Grey, Grey Berea, and Buff Berea sandstone core samples were used with measured permeabilities of 16.08, 217.04, and 560.63 md, respectively. The dispersion coefficient was observed to increase with a decrease in permeability, with Bandera Grey having the highest dispersion coefficient and invariably higher mixing between the injected CO2 and the nascent CH4. Furthermore, this dispersion was more pronounced in the horiz... [more]

The aim of this study was to develop a mathematical regression model for predicting end-use energy consumption in the residential sector. To this end, housing characteristics were collected through a field survey and in-depth interviews with residents of 71 households (15 apartment complexes) in Seoul, South Korea, and annual data on end-use energy consumption were collected from measurement systems installed within each apartment unit. Based on the data collected, correlativity between the field-survey data and end-use energy consumption was analyzed, and effective independent variables from the field-survey data were selected. Regression models were developed and validated for estimating six end uses of energy consumption: heating, cooling, domestic hot water (DHW), lighting, electric appliances, and cooking. Regression analysis for ventilation was not applied, and instead a calculation formula was derived, because the energy-consumption proportion was too low. The adj-R2 of the esti... [more]

This paper presents a mixed receding horizon control (RHC) strategy for the optimal scheduling of a battery energy storage system (BESS) in a hybrid PV and wind power plant while satisfying multiple operational constraints. The overall optimisation problem was reformulated as a mixed-integer linear programming (MILP) problem, aimed at minimising the total operating cost of the entire system. The cost function of this MILP is composed of the profits of selling electricity, the cost of purchasing ancillary services for undersupply and oversupply, and the operation and maintenance cost of each component. To investigate the impacts of day-ahead and hour-ahead forecasting for battery optimisation, four forecasting methods, including persistence, Elman neural network, wavelet neural network and autoregressive integrated moving average (ARIMA), were applied for both day-ahead and hour-ahead forecasting. Numerical simulations demonstrated the significant increased efficiency of the proposed mi... [more]

A method is proposed to fit parameters of Power System Stabilizer controllers in electromechanical multimachine power systems. The use of the Non-dominated Sorting Genetic Algorithm II heuristic method and Tabu search is considered to be initial search criteria. These methods give an approximation of the values that define the controllers. Then, the stochastic approach was used to evaluate the behavior of the parameters found when considering the system’s response to the presence of random and self-sustained in-time disturbances that affect the response of the system under steady state. The stochastic approach allows the evaluation of the system’s response through the calculation of the cost of energy loss under steady state. The method is applied to two systems: a three-machine nine-busbar system, and the Interconnected System of the Greater North (Sistema Interconectado del Norte Grande) in Chile. For these systems, the proposed methodology effectively optimized the controllers and T... [more]

One of the main power quality issues that can affect variable speed drives (VSDs) is the occurrence of voltage sags on their AC power supply. Voltage sags can affect the inverter nominal operation, leading to a malfunction of the AC motor. This paper presents an inverter with resilient capability to voltage sags. The topology consists of two conventional three-phase bridge inverters arranged to require just a single DC source. This inverter is also characterized by a voltage multilevel operation, providing the full advantages of multilevel converters without the need for level balancing. Associated with this AC motor driver, a control system based on a field-oriented controller with a vector voltage modulator that will enable voltage sag ride-through capability is proposed. The proposed control system does not require any changes in the occurrence of voltage sags. To verify the characteristics of the proposed drive and control system, simulation tests are provided. Simulation results c... [more]

During biomass storage, some gases can be produced and reach dangerous levels to human health. Among them, carbon monoxide is especially worrying, due to its potentially lethal effects and its contribution to the greenhouse effect. High levels of this gas could be reached, depending on many factors, such as unsuitable ventilation in storage areas or raw material characteristics. The aim of this research study was to assess the levels of CO produced during pellet storage at a laboratory scale, depending on the ventilation conditions (changing the amount of sample and frequency), the pellet characteristics (eucalyptus and cork residue pellets), and variables that influence CO levels. A greater number of pellets (when not ventilated) increased CO levels and discontinuous ventilation did not reduce these levels once the space was isolated again. Cork samples provoked higher CO emissions, possibly due to its higher fat content and surface area, which promotes the interaction between air and... [more]

Wind power, one of renewable energy resources, is a fluctuating source of energy that prevents its further participation in the power market. To improve the stability of the wind power injected into the power grid, a short-term wind speed predicting model is proposed in this work, named VMD-P-(ARIMA, BP)-PSOLSSVM. In this model, variational mode decomposition (VMD) is combined with phase space reconstruction (P) as data processing method to determine intrinsic mode function (IMF) and its input−output matrix in the prediction model. Then, the linear model autoregressive integrated moving average model (ARIMA) and typical nonlinear model back propagation neural network (BP) are adopted to forecast each IMF separately and get the prediction of short-term wind speed by adding up the IMFs. In the final stage, particle swarm optimization least squares support vector machine (PSOLSSVM) uses the prediction results of the two separate models from previous step for the secondary prediction. For... [more]

In this study, the thermal behavior of the coaxial and double U borehole heat exchangers was investigated using numerical simulations in both the long- and short-term. As a reference for borehole heat exchanger specifications, the existing coaxial and double U probes of a geothermal heat pump installed within the Horizon 2020 research project named “Cheap GSHPs” were considered. Nine years of simulations revealed that when borehole heat exchangers are subjected to a balanced thermal load, and intermittent operating modes of the ground source heat pump system are set, the coaxial pipes’ configuration provides better thermal performance due to the higher thermal capacitance of the heat-carrier fluid and the lower borehole thermal resistance. The analysis was conducted considering two different types of ground with different thermal conductivity values. As result, the more conductive ground type highlights the higher yield of the coaxial probe.

Urban heat island effects (UHIE) are becoming increasingly widespread, thus, there is an urgent need to address thermal comfort, which significantly influences the daily lives of people. In this study, a means of improving the thermal environment by spatial analysis of heat was implemented to ensure basic thermal comfort in future smart cities. Using Seoul as the study site, the relationship between sensible heat and land cover type was used to identify heat islands in this city. Thereafter, k-means clustering was employed to extract unfavourable and favourable thermal areas. High sensible heat indicates locations where environmental heat needs to be mitigated. Sensible heat distribution data were used for spatial typification to formulate an effective land cover factor to mitigate the UHIE. In-situ net radiation data measured at six sites were utilised to confirm the spatial typification of the thermal environment. It was found that expanding the green space by 1% reduces the sensible... [more]

The applications of surfactants in Enhanced Oil Recovery (EOR) have received more attention in the past decade due to their ability to enhance microscopic sweep efficiency by reducing oil-water interfacial tension in order to mobilize trapped oil. Surfactants can partition in both water and oil systems depending on their solubility in both phases. The partitioning coefficient (Kp) is a key parameter when it comes to describing the ratio between the concentration of the surfactant in the oil phase and the water phase at equilibrium. In this paper, surfactant partitioning of the nonionic surfactant Alkylpolyglucoside (APG) was investigated in pre-critical micelle concentration (CMC) and post-cmc regimes at 80 °C to 106 °C. The Kp was then obtained by measuring the surfactant concentration after equilibration with oil in pre-cmc and post-cmc regimes, which was done using surface tension measurements and high-performance liquid chromatography (HPLC), respectively. Surface tension (ST) and... [more]

The inverter of an energy storage system, which plays an important role in maintaining the voltage of a stand-alone microgrid, can shut down in response to external or internal abnormal conditions. Such a protective measure can cause the microgrid to blackout. A redundant inverter can be configured to respond upon failure of the main inverter to ensure higher stability of the stand-alone microgrid. However, the microgrid may experience several to tens of blackout cycles when the main inverter fails owing to a time delay in the operation of the sub inverter. To overcome this limitation, we propose an LCpL filter for suppressing any sudden changes in the microgrid during the transition period between the main and sub inverters. In addition, this study also describes a control method for the sub inverter to prevent system blackouts. A 100 kW microgrid system consisting of two 100 kW inverters with LCpL filters and loads was used to demonstrate the efficacy/utility of the proposed method.

As the penetration of intermittent renewable energy increases and unexpected market behaviors continue to occur, new challenges arise for system operators to ensure cost effectiveness while maintaining system reliability under uncertainties. To systematically address these uncertainties and challenges, innovative advanced methods and approaches are needed. Motivated by these, in this paper, we consider an energy integrated system with renewable energy and pumped-storage units involved. In addition, we propose a data-driven risk-averse two-stage stochastic model that considers the features of forbidden zones and dynamic ramping rate limits. This model minimizes the total cost against the worst-case distribution in the confidence set built for an unknown distribution and constructed based on data. Our numerical experiments show how pumped-storage units contribute to the system, how inclusions of the aforementioned two features improve the reliability of the system, and how our proposed d... [more]

In order to reduce the energy consumption of deep-sea self-sustaining profile buoy (DSPB) and extend its running time, a stage quantitative oil draining control mode has been proposed in this paper. System parameters have been investigated including oil discharge resolution (ODR), judgment threshold of the floating speed and frequency of oil draining on the energy consumption of the system. The single-objective optimization model with the total energy consumption of DSPB’s ascent stage as the objective function has been established by combining the DSPB’s floating kinematic model. At the same time, as the static working current of the DSPB can be further optimized, a multi-objective energy consumption optimization model with the floating time and the energy consumption of the oil pump motor as objective functions has been established. The non-dominated sorted genetic algorithm-II (NSGA-II) has been employed to optimized the energy consumption model in the ascent stage of the DSPB. The... [more]

The movement and deposition of particles that occur during their natural circulation in supercritical water exercise an important impact on the safe and stable operation of a supercritical water reactor (SCWR). When supercritical water flows in pipelines, a large number of corrosive particles may be generated due to pipeline corrosion or the purity of the fluid itself. The presence of particulate matter affects the heat transfer efficiency of the pipeline, increasing flow resistance and easily promoting heat transfer deterioration. ANSYS-CFX numerical analysis software was used to simulate the natural circulation loop of supercritical water, and micron particles were added in the initial flow field. The effects of heating power, particle concentration and particle diameter on particle deposition were obtained. Through this analysis, it can be concluded that the heating of the pipeline has a certain inhibitory effect on the deposition of particles. The rise in both initial particle conc... [more]

The oil and gas industry faces numerous problems, from the exploration to the production phase. One of the most common problems faced by the industry is the formation of gas hydrates in the pipeline during the deep-water operation. The advancement of kinetic hydrate inhibitors (KHIs) has been rapid. However, as the natural degradation of conventional KHIs, such as polyvinylpyrrolidone (PVP) and polyvinylcaprolactam (PVCap), is challenging, there is a need to develop environmental-friendly KHIs with enhanced biodegradability to improve possible environmental risks. Thus, green inhibitors have been developed as a new class of KHIs. Research for enhancement of green hydrate inhibitors, as an alternative for existing low dosage hydrate inhibitors (LDHIs), has increased. In this paper, the effect of induction time with presence of cassava peels on the formation of methane hydrate was studied and compared with commercialized inhibitor, PVP. The performance of cassava peels as a kinetic hydra... [more]

With the Paris Agreement entering into full force, South Korea must submit its target greenhouse gas emissions for commercial buildings by 2030 to the United Nations Framework Convention on Climate Change. To determine this target, the annual energy demands must be forecasted through appropriate models; the development of these models is the focus of our study. We developed a system to calculate energy demand forecasts by searching for suitable methods. We built distinct energy forecast models for petroleum, city gas, electricity, heat, and renewable energies. The results show that the most appropriate variable for the petroleum energy model is energy trend. Moreover, the annual increase rate of petroleum energy demand from 2019 to 2030 was forecasted to be −1.7%. The appropriate variable for city gas energy model was the floor area of commercial buildings, which was forecasted to increase at an annual average growth rate of 0.4% from 2019 to 2030. According to the forecast results of... [more]