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Demand response (DR) is one of the most cost-effective and logical smart grid terms for power systems that can be used during peak load hours, whereas load shedding (LS) is the last and most expensive solution in emergency grid situations. The aim of them is to satisfy equilibrium constraints between consumption and generation and restore the power system frequency to normal bounds at the least possible time. The rapid increase in power grid costs and limitations on electricity generation resources have resulted in the increasing need for industrial customers' participation as an alternative solution to peak load spikes. Therefore, this paper considers the estimation of imbalance active power in a smart strategy to introduce a critical DR (CDR) in heavy industries (pulp and paper, cement, and medium density fibreboard (MDF)) based on direct load control (DLC) technique in order to reduce the need for LS in frequency restore. To evaluate the proposed model, a real case study including the typical pulp and paper, cement, and MDF industries processes with actual power consumption data is considered. The numerical and graphical results confirm that the proposed CDR can be used as an inexpensive solution to replace the costly spinning reserves and avoid load shedding. [ABSTRACT FROM AUTHOR]

SUMMARY Previous studies by the authors have shown that energy savings in pulp and paper mills offer opportunities for increased electricity production on-site or wood fuel export. The energy export implies reductions in CO2 emissions off-site, where fossil fuel or fossil-fuel-based electricity is replaced. To assess this potential and the related profitability for a future situation, four energy market scenarios were used. For a typical Scandinavian mill, the potential for CO2-emission reductions was 15-140 kton year−1 depending on the scenario and the form of energy export. Extrapolated to all relevant mills in Sweden, the potential was 0.4-3.1 Mton year−1, which is in the order of percent of the Swedish CO2 emissions. Wood fuel export implies larger reduction in CO2 emissions in most scenarios. In contrast, electricity export showed better economy in most of the cases studied; with annual earnings of 5-6 M€, this is an economically robust option. In the market pulp mill investigated, the wood fuel export was in the form of lignin. Lignin could possibly be valued as oil, regarding both price and potential for CO2-emission reduction, making lignin separation an option with good profitability and large reductions of CO2 emissions. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The application of renewable energies such as wind and solar has become an inevitable choice for many countries in order to achieve sustainable and healthy economic development [[1]]. The paper "Steady-State Analysis and Output Voltage Minimization Based Control Strategy for Electric Springs in the Smart Grid with Multiple Renewable Energy Sources" by Y. Zou et al. presented a general steady-state analysis and minimal compensating voltage control scheme for the second generation of electric springs in the power system with substantial penetration of intermittent renewable energy sources. The paper "Parallel LSTM-Based Regional Integrated Energy System Multienergy Source-Load Information Interactive Energy Prediction" by B. Wang et al. proposed an energy prediction strategy for multienergy information interaction in regional integrated energy systems from the perspective of horizontal interaction and vertical interaction. [Extracted from the article]

The continuous expansion of the scale of power grid construction has led to the emergence and development of the uninterrupted operation of the unmanned aerial vehicle (UAV) distribution network. However, in the actual power production process, due to the limitations of operating conditions and environment, power safety accidents are inevitable. With the support of intelligent technology, the monitoring effect and application level of the safety monitoring system for the uninterrupted operation of the UAV distribution network have been improved. Unified planning and scheduling were carried out throughout the job implementation process. The efficiency of equipment safety management has been strengthened, which is of great practical significance to the safe production of electric power. Based on the analysis of the environmental characteristics and implementation difficulties of the unmanned aerial vehicle distribution network, this paper studied the safety monitoring system and method by combining the high intelligence and high-efficiency characteristics of the learning control robot technology. The designed unmanned aerial vehicle distribution network safety monitoring system and method were tested. In order to understand the effect of the system intuitively, this paper analyzed from three aspects: system sensitivity, anti-interference, and data acquisition and management. It also contrasted with traditional monitoring systems. The test data showed that the sensitivity test value of the traditional monitoring system in the R1 circuit with the lowest voltage intensity was 71.3%. In the R4 circuit with the strongest voltage intensity, the test value only reached 84.4%. The test values of the system in this paper in the two types of circuits were 85.6% and 93.3%, respectively. In the data acquisition and management test, the acquisition and management rates under the highest numerical information could reach more than 97%. It can be seen that it has strong feasibility in actual operation. [ABSTRACT FROM AUTHOR]

This paper performs a technoeconomic analysis of the wind power potential and evaluates the cost of wind power generation in Evodoula, comparing two methods, the conventional method and the uncertainty method based on a comparative spatiotemporal approach using the geographic information system (GIS) software tool. This study is based on satellite wind data measured at 10 m above ground level (AGL) over a 40-year period (1980-2019), by the meteorological service NASA (National Aeronautics and Space Administration)/Goddard Space Flight Center (GSFC). The main objectives are to obtain an appropriate design for a proven optimal location and to assess the viability of wind power at Evodoula. For this type of study, there is little literature available. The optimization of an onshore wind farm and deployment in the wind energy development interest area (ZIDEE) is carried out to obtain a minimum and parsimonious discounted cost production unitary (CPU) of the electricity produced. The results showed that in Okok, a location with a large energy deficit, an onshore wind farm with an electricity generation capacity of 12.5 MW with 5 NORDEX N100-2.5MW wind turbines would have a total energy production (TEP) of about 64.0254825 TWh and a selling price of electricity that would be 0.0034 CAD$/kWh, which is very low compared to the utility price (about 98% cheaper). The total cost of the wind farm would be about $11 million, with a net present cost of about $218 million. The annual profit generated by the wind farm would be over $6 billion. The return on investment (ROI) of the project is estimated at 2880.882%. The constructed onshore wind farm would avoid CO2 emission at over 11 Mt CO 2 , eq /year as the energy generated is from the atmosphere. The wind farm would realize an average annual cash flow estimated at nearly $30 million after 20 years of operation. These savings would allow the installation of CO2 capture systems in conventional power plants. In addition, the analysis of uncertainties and risks was identified and quantified to estimate the confidence levels of the project development results. The risks have been assessed, and we recommend that the total uncertainty of the project is around 15%. The energy values in P 75 and P 90 are 10.08% and 19.22%, respectively, lower than the energy value in P 50 of 11.60 GWh/An. Finally, the main policy recommendations for an inclusive design process are highlighted. The contribution of this study is to assist policy makers in making appropriate decisions in the development and implementation of energy and environmental policy in Cameroon and in many continental areas. [ABSTRACT FROM AUTHOR]

New energy (NE) power generation technology has become an important means to solve the problems of global energy demand and environmental governance due to its sustainability and cleanliness. However, restricted by climate and other factors, the instability of its power generation capacity has a serious impact on the voltage multimedia quality evaluation of small microgrids, which even causes damage to important equipment. This paper proposed a multimedia quality evaluation method in the new energy power generation system relying on intelligent robot numerical control technology. According to the state characteristics of different units, the expanded representation models of conventional units, wind turbines, and photovoltaic units were established, respectively. Based on intelligent robot numerical control technology, a multimedia quality monitoring model of the new energy power generation system in random production simulation was established. The planned outage condition of the unit, which was ignored by the current stochastic simulation method, has been fully considered to ensure the rationality of the simulation of intelligent robot numerical control technology. The intelligent robot numerical control technology was used to explore the expected production power change of the unit and to improve the calculation speed and accuracy. In this paper, an appropriate wind and solar power generation model was constructed based on the output characteristics of wind and solar. Secondly, the influence of random faults between units on the subsequent loading rate was studied through probability calculation. The start-stop factors of conventional units were comprehensively analyzed. Then, the expected value of unit start-stop times was obtained. The average relative error of the expected value of the power shortage of the new energy electricity generation system (EGS) was 2.45%, and the error was lower than 2.98%. In the intelligent robot numerical control technology in this paper, the planned outage condition of the unit was considered, which showed the correctness and superiority of the multimedia quality evaluation of the proposed model. [ABSTRACT FROM AUTHOR]

The use of decentralized renewable energy systems will continue to play a significant role in electricity generation especially in developing countries where grid expansion to most remote areas is uneconomical. The income levels of these off-grid communities are often low, such that there is a need for the delivery of cost-effective energy solutions through optimum control and sizing of energy system components. This paper aims at minimizing the net present cost (NPC) and the levelised cost of energy (LCOE). The study presents a hybrid power system involving a hydroelectric, solar photovoltaic (PV), and battery system for a rural community in Cameroon. The optimization of the system was done using HOMER Pro and validated using a meta-heuristic algorithm known as genetic algorithm (GA). The GA approach was programmed using the MATLAB software. After the HOMER simulation, the optimal power capacity of 3 kW solar PV, 334.89 Ah battery, and 32.2 kW microhydropower was used to meet the load. The village load profile had a daily energy usage of 431.32 kWh/day and a peak power demand of 38.49 kW. The optimized results showed an NPC and LCOE of $90,469.16 and 0.0453 $/kWh, respectively. The system configuration was tested against an increase in hydropower capacity, and it was observed that increasing the hydropower capacity has the ability to significantly reduce the LCOE as well as the battery and solar PV size. A comparative analysis of the two approaches showed that the optimization using GA was more cost-effective than HOMER Pro with the least LCOE of 0.0344 $/kWh and NPC of $86,990.94 as well as a loss of power supply probability (LPSP) of 0.99%. In addition, the GA method gave more hydropower generation than HOMER Pro. This supports the fact that stochastic methods are more realistic and economically viable. They also accurately predict system operation than deterministic methods. [ABSTRACT FROM AUTHOR]

Summary: Many electricity consumers around the world are billed electric peak load charges. In the United States, these demand charges can contribute up to 70% of a consumer's electricity bill. Research has shown that the financial impact of these charges to the consumers can be reduced by acting on the intelligence provided by peak electric load day (PELD) forecasts. Unfortunately, published research detailing PELDs forecasting methodologies for facilities adopting behind the meter renewable electricity generation (BTMREG) is non‐existent. This paper contributes: (a) a PELD forecasting methodology applicable to consumers with BTMREG. A case study demonstrates the methodology's ability to achieve 93% of the potential savings in kW, translating to demand charge reductions of approximately US$ 142 129 per year. (b) The first side‐by‐side performance comparisons of electric load and PELD forecasting models for scenarios with and without BTMREG. (c) The first PELD forecasting model savings comparison for scenarios with and without BTMREG. Experimental results suggest that counterintuitively, BTMREG adoption can translate into higher peak load savings for electricity consumers. [ABSTRACT FROM AUTHOR]

Summary: Burning fossil fuel like coal, diesel, and so on, for electricity generation is environmentally hazardous and cause increased CO2 emissions worldwide. To meet the ever‐growing energy demand, solar energy remains top and considered to be most promising one that grabbed global attention recently, especially, in the areas of rural electrification and water pumping. Moreover, the solar photovoltaic (PV) system is advantageous and highly preferred. Thus, this paper attempts to review various components of solar‐powered water‐pumping systems, its configuration, characteristics, and performance. Also, comparison of water‐pumping system with and without maximum power point tracking (MPPT), motor and pumps selection based on water flow rate, optimal converter selection, and effective controller performance is studied. Furthermore, PV pumps behavioral study at various geographical locations is also made. Critical analysis on PV water pumping with limitation and suggestions is also highlighted. Hence, it is envisaged that the data presented in this review paper will be useful to the researchers in the selection of suitable PV techniques, pumps, motors, MPPT, and controllers for the effective design, control, and better performance of solar water‐pumping system. [ABSTRACT FROM AUTHOR]

We live in a world that is completely dependent on energy; thus, humankind can no longer live without power. With electricity being the main form of energy today, this has increased the complexity of our life today. In Uganda, electricity generation is mainly through hydropower, which puts the country in the bottleneck of overdependence on one source of energy. There are many energy systems out there that the country can use to diversify its electricity generation. Therefore, the need to understand the level of development and utilization of various energy systems has been the underlying question for this present study. A comprehensive literature survey was conducted using electronic databases, including ScienceDirect, Wiley, Sage, Scopus, Taylor & Francis, and Google Scholar. The publications in the form of reports, conference papers, working papers, discussion papers, journal articles, book sections, and textbooks were considered in this study. In total, 11 energy systems, including human and animal energy, solid biomass (firewood), hydropower, wind, geothermal, solar, nuclear, peat, coal, petroleum, and nonsolid biomass (methanol, hydrogen, ethanol, biodiesel, and biogas), are described. The current and future development and utilization of these energy systems have been described. The challenges for developing and utilizing these systems were elaborated on, and the solutions for their challenges were presented. Hydropower from the Nile River, being the main river for large hydropower plant construction, is the dominant energy system in Uganda. Nuclear energy will be the salvation for the country's electric energy supply in the near future. Therefore, Uganda needs to bet big on nuclear energy. [ABSTRACT FROM AUTHOR]

The increased electricity demand amidst inadequate electricity generation in South Africa has plunged the country into frequent power outages and load shedding. However, the country still has the lowest electricity transmission and distribution losses in sub-Saharan Africa. Despite low losses, there is still an opportunity to reduce losses further and reduce power outages and load shedding. This study examines the determinants of electricity transmission and distribution losses in South Africa. The results will inform policymakers on avoiding higher electricity transmission losses to alleviate the current electricity shortfall. Using the time-series data from 1971–2020 and the autoregressive distributed-lag (ARDL) bounds testing approach to cointegration, the study confirmed a long-run relationship between electricity transmission, distribution losses, and income, price, investment, political regime, and economic integration. Regression analysis from the ARDL methods revealed that investments, political administration, and economic integration positively influence electricity transmission and distribution losses. At the same time, income reduces electricity transmission and distribution losses in the long run. However, income, price, and economic integration minimize electricity transmission losses in the short run while the remaining variables maintained their positive effects. The implication is that without proper checks in place, an expansion in South Africa's economic integration, investment, and democracy may negatively affect the electricity sector of the country through an increase in electric power losses, while higher income will help the industry via lower electric power losses. The paper, among other things, recommends building a robust economy to ensure lower levels of electricity transmission and distribution losses. [ABSTRACT FROM AUTHOR]

In recent years, renewable resources have widely been used to provide necessary energy due to the increasing fossil fuel prices, environmental pollution concerns, and the necessity to meet the growth in energy demands. The output of renewable resources especially solar and wind energies is associated with meteorological parameters, so their reliability creates many challenges for the energy sector. The consumption peak of the gas network is taken into account to adjust the frequency of the microgrid (MG). Both gas network load and electric load distributions are adjusted at the same time. In a multicarrier network, the frequency is regulated in a nonlinear manner. Meanwhile, new necessary loads for production and electric vehicles have imposed new loads on the power network; if proper management is not performed to respond to these new loads, the increase of network frequency deviations may lead the network to fail and even break down. In this paper, a network of various sources including the wind turbine, solar panel, storage (battery and flywheel), electric vehicle (EV), diesel generator (DG) electric power generation, and multicarrier energy hub (MCEH) with combined heat and power (CHP) was designed to examine vehicle-to-grid (V2G) electric vehicles. The ANFIS adaptive fuzzy control method was used to provide a fine-tuning frequency of the network. A comparison between the suggested approach and a fuzzy controller system was carried out to examine the superiority of the introduced approach to the frequency control. The simulations were obtained using MATLAB/SIMULINK software. The simulation outcomes indicated that the SMART controller can achieve good efficiency in frequency regulation and reliable output power in the examined microgrid. Further comparison in terms of effective (RMS) values and maximum frequency deviation indicates the superior performance of the proposed method over the fuzzy method. [ABSTRACT FROM AUTHOR]

Most field scientific observation and research stations are located at the end of power grids which are usually not extended to such areas. Consequently, the power supply of equipment in field observation stations cannot be guaranteed. Meanwhile, regions with poor ecosystem stability are relatively sensitive to environmental changes and thus prone to degradation and succession due to external interference. In this paper, the photovoltaic (PV) power generation system of a grassland ecohydrological field scientific observation and research station was taken as the research object. Two kinds of distributed PV power generation systems were simulated and analyzed by use of PVsyst software. The total power of laboratory equipment, PV power generation efficiency, and system cost of the field observation station were calculated and analyzed. The design scheme and scale of PV power generation systems suitable for field observation stations were determined. Finally, a PV power generation test system was set up, and PV power generation data were sorted out. The feasibility of the design scheme of PV power generation systems was verified by analyzing the relationship between the simulated and actual power generation of systems and that between the daily energy use proportions of field observation stations. Besides, the environmental benefits of PV systems were analyzed, and their amount of energy saving and emission reduction was calculated. This study can solve the issue of the low power supply guarantee rate of field observation stations, provide a design basis and beneficial reference for the construction of environment-friendly field laboratory stations, and realize green energy saving and the sustainable use of energy while protecting the ecosystem from being destroyed. [ABSTRACT FROM AUTHOR]

Low-emission environmental protection concept once it replaced the low-carbon energy transformation concept, to a certain extent, disrupted the core direction of energy transformation. This paper takes the green development of electric power as the research direction, the thermal power unit is the green source control point of electricity, and the green production of the thermal power unit is the research target; based on the actual research data and the actual data, the comprehensive evaluation of the green production of a thermal power generating unit in a city is carried out by means of ANP, matter-element extension model, and principal component analysis. This paper not only reflects the quantification of green benefits in each year, but also achieves the comparison of green achievements and the analysis of increasing losses in the data years. Furthermore, the indexes of annual increase and loss of the index system are analyzed and filtered. The indexes of strong contribution index and short board of barrel are found out, and the dimension reduction management of green production of thermal power unit is realized. [ABSTRACT FROM AUTHOR]

The energy sector of today's Rwanda has made a remarkable growth to some extent in recent years. Although Rwanda has natural energy resources (e.g., hydro, solar, and methane gas, etc.), the country currently has an installed electricity generation capacity of only 226.7 MW from its 45 power plants for a population of about 13 million in 2021. The current national rate of electrification in Rwanda is estimated to 54.5% (i.e.; 39.7% grid-connected and 14.8% off-grid connected systems). This clearly demonstrates that having access to electricity is still a challenge to numerous people not to mention some blackout-related problems. With the ambition of having electricity for all, concentrated solar power (CSP) and photovoltaic (PV) systems are regarded as solutions to the lack of electricity. The production of CSP has still not been seriously considered in Rwanda, even though the technology has attracted significant global attention. Heavy usage of conventional power has led to the depletion of fossil fuels. At the same time, it has highlighted its unfriendly relationship with the environment because of carbon dioxide (CO2) emission, which is a major cause of global warming. Solar power is another source of electricity that has the potential to generate electricity in Rwanda. Firstly, this paper summarizes the present status of CSP and PV systems in Rwanda. Secondly, we conducted a technoeconomic analysis for CSP and PV systems by considering their strengths, weaknesses, opportunities, and threats (SWOT). The input data of the SWOT analysis were obtained from relevant shareholders from the government, power producers, minigrid, off-grid, and private companies in Rwanda. Lastly, the technical and economical feasibilities of CSP and PV microgrid systems in off-grid areas of Rwanda were conducted using the system advisor model (SAM). The simulation results indicate that the off-grid PV microgrid system for the rural community is the most cost-effective because of its low net present cost (NPC). According to the past literature, the outcomes of this paper through the SWOT analyses and the results obtained from the SAM model, both the CSP and PV systems could undoubtedly play a vital role in Rwanda's rural electrification. In fact, PV systems are strongly recommended in Rwanda because they are rapid and cost-effective ways to provide utility-scale electricity for off-grid modern energy services to the millions of people who lack electricity access. [ABSTRACT FROM AUTHOR]

Summary: The uncertainties related to renewable energy resources (RERs) and energy markets have a direct impact on the scheduling of hybrid microgrids and stand as a challenge in renewable‐based systems. Due to this, many mathematical methods are employed for modeling uncertainties, but applying a suitable approach is important for reaching accurate results. This paper presents the chance‐constrained programming technique to model the fluctuations in renewable outputs and electricity market prices to effectively deliberate the probabilistic nature of them. In this respect, the transactive energy concept is used to provide the energy sharing possibility for hybrid microgrids with a high portion of renewables for clean electricity generation. The interaction between the electrical and gas network as a result of using the gas‐fired devices in each microgrid, is also included in this study. To test the effectiveness of the suggested framework, the IEEE‐10 bus case study with five commercial hybrid microgrids is selected and the scheduling of microgrids is carried out in the interconnected electricity and gas networks. The different impacts of the proposed method are analyzed by considering two cases: optimal scheduling of hybrid microgrids without uncertainty modeling (Case I) and with it (Case II). In Case I and II, numerical results indicated $22 378.067 expected operation cost for Case II in comparison with $26 014.359 for Case I, which proves the effectiveness of the proposed model in probabilistic modeling of the system as well as achieving the economic benefits for hybrid microgrids. Highlights: Optimal chance‐constrained DA scheduling of hybrid microgrids is effectively conducted.The CCP method is used for probabilistic evaluation of the problem in the presence of RERs.Transactive energy technology is employed for managing energy trading in the system.LHS and FFS methods are applied for scenario generation and reduction, respectively.The interactions between electricity and gas networks are effectively modeled. [ABSTRACT FROM AUTHOR]

This paper estimates the maximum integration level of residential rooftop solar photovoltaic (PV) capacity within the power network of the Duke Energy Progress (DEP) and Duke Energy Carolinas (DEC) under two scenarios embodying different assumptions about the flexibility of nuclear power plant (NPP) operations. A mixed-integer optimization model was constructed and simulated to find out the maximum solar penetration level under each scenario and to calculate the expected total system's electricity generation costs, energy mix, atmospheric emission reductions, and emission abatement costs. Analysis reveals that improving NPP operation maneuverability would increase the maximum solar PV penetration level in the DEP and DEC power networks by 39%, from 8.9% to 12.4% of the total system's electricity generation. Consequently, it would further improve the electricity generations' unit costs and CO2 emission reductions by 3% and 8% points, respectively. On the other hand, increasing the solar PV penetration limit under high flexible NPP operation scenario leads to increase in the CO2 emission abatement costs by 8% points. The results of the study indicate that the flexibility of existing power system resources may present a barrier for a large uptake of solar energy. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) output power has regularity, volatility, and randomness. First of all, this paper carried on a metrological analysis to PV system data. Then, this paper analyzed the relationship between PV historical data, PV power forecasting model, and forecast error. By spectrum analysis of PV power, the PV power is decomposed into periodic components, low frequency residual components, and high frequency residual components. Making a specific analysis of these three components determines the minimum modeling error value, which reflects the unpredictable part of the PV power. Determining the minimum modeling error for PV forecasting not only objectively evaluates the quality of the PV forecasting model but also can determine the prediction accuracy standard according to different PV power generation targets. The examples given in this paper illustrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a techno‐economic analysis of photovoltaic mini‐grid systems (PMs), using a group of remote houses in 3 locations in Nigeria, as case studies. It uses a worst‐case users' load demand approach for the design and analysis of the proposed energy system, according to international technical standards. It presents detailed capacity, yield and losses, battery state of charge (SoC), reliability, users' load demand increase (Ldi), and life cycle economic analyses by using the Hybrid Optimisation for Electric Renewables (HOMER) simulation tool. The effect of 25% Ldi is also considered in the paper. The study can be used to develop a practical energy model to address the poor energy situation in those locations when they are implemented. Results indicate that PMs of 68, 76, and 61 kW can meet the users' demand of ~63 500 kWh/year with an availability of 99.2% for the locations, respectively. By including a 30‐kVA diesel generator to the PMs' model, an availability of 100% was obtained, demonstrating that the issue of loss of energy supply for several days in the year due to users' Ldi and the cloudy days is being addressed. The results further show that although the hybrid energy systems have relatively higher initial capital, total life cycle and replacement costs, and the cost of energy, they achieve a higher reliability compared with the proposed PMs. The research can be useful for planning solar PV infrastructure for remote locations around the world. [ABSTRACT FROM AUTHOR]

This work estimates the annual energy that could be generated from a concentrated solar power (CSP) plant. The optimal location used for this analysis was selected based on a set of multicriteria decision-making (MCDM) methods employed in an earlier research. The paper also determines the financial viability of implementing a CSP plant within the selected location. A 100MW CSP plant for the said location was modelled and simulated using the System Advisor Model (SAM) software with data from the online database of the National Renewable Energy Lab (NREL) available from the SAM software. Using a solar multiple of 2.0 with a TES of 6 hours, the plant generated an estimated annual energy of 306.850GWh with a capacity factor of 35.10% and gross-to-net conversion of 89.10%. The months with the highest generation were from November to March while July to September had the least generation. Generation begins from 8 am, rising to a peak around 12 pm to 4 pm and gradually declines into the night. Results from the financial analysis produced a net present value (NPV) of USD 156,287,433.72 after the plant life of 25 years, indicating profitability of the project. Results from the sensitivity analysis showed that the project NPV became negative only when the base case capital cost, electricity price, and revenue were, respectively, increased by 15%, reduced by 10%, and reduced by 13%. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a comparative study of novel energy integrations between Multiple‐Effect Desalination (MED) and Organic Rankine Cycle (ORC) systems for the simultaneous production of desalinated water and electric power. Two new MED/ORC configurations are proposed, where part of the sensible and/or latent heat of condensation of the ORC is used to potentiate the generation of steam in the last effect of the MED, taking advantage of the temperature levels present in the MED. A simulator of the proposals was developed and validated with experimental results reported in the literature. These configurations are compared energetically with the MED and ORC systems working individually and against another previously proposed configuration, also considering the impact of the integrations on the heat transfer area required by the systems. The results show a decrease in the thermal energy requirements for the activation of the MED system with the new integrations. The energy requirements of the MED are reduced by 28% when integrated into the first effect with the ORC evaporator. The utilization of the sensible heat of condensation of the ORC in configuration 3 did not present a considerable energy decrease compared to configuration 2, due to the limited sensible heat available for its recovery, of approximately 22 kW. The usage of the latent heat of condensation of the ORC in configuration 4 implies that increasing the condensation temperature and pressure of the ORC, decreases its efficiency by 1.8% and increasing the energy required by 221 kW provides the two services simultaneously. [ABSTRACT FROM AUTHOR]

Summary: Electric‐driven heat pumps are one of the most encouraging systems that could support the raising of renewables contribution in civil sector energy consumption, especially with reference to the Countries with a high contribution of renewable energy sources in electricity generation mix. However, the evaluation of the effective energy and environmental performance of an electric heat pump meeting the space heating and cooling requests of a building has to consider several factors that affect the results. Among them great attention should be given to the variability of weather conditions in which the system operates, the changeability of the efficiency and environmental indicators of power grid. The analysis becomes more complex if the variation of these parameters is considered in terms of time and geographic location but it leads to the actual evaluation of the energy conversion system performance that is neglected by European Regulations. This paper presents an energy and environmental analysis of an electric‐driven air‐source heat pump providing the space heating and cooling needs of the same building located in two different geographical locations by means of a dynamic simulation performed in TRNSYS 17. The analysis is carried out considering the average and time‐dependent values of the carbon dioxide emission factors for electricity and the power grid efficiency indicators evaluated by means of the real electricity generation data. In addition, the paper proposes the evaluation of the average and hourly energy and environmental parameters referred only to the electricity market zones in which the buildings are located. These indices are considered in the analysis too. The results have highlighted that the assessment based on average and high‐resolution parameters, as well the evaluation based on indicators referred to electricity market zones only, could return very different outcomes leading to a significant overestimation or underestimation of the energy and environmental performance of the system based on the electric‐driven heat pump. Finally, a further analysis has been carried out to determine how the results can vary considering the average value of the electric efficiency indicator suggested by Italian Regulations and that of other European Countries. [ABSTRACT FROM AUTHOR]

Summary: In the existent paper, the performance of thermal storage hybrid buildings exploiting the latent heat of phase change materials (PCMs) for thermal refrigeration and heating of the contemporary period has been investigated. The conventional buildings consume a large amount of electricity, primarily for the heating and cooling applications. Electricity generation primarily relies on coal‐based thermal power plants. The emissions from these establishments pose a serious threat to the environment. Moreover, conventional heating/cooling units rely on exorbitant energy cost. The usage of any kind of thermal storage system is an efficacious way of stockpiling thermal energy and utilizing it when needed. This paper gives a comprehensive overview of the available thermal storage units incorporating PCMs. The various segments of the buildings, viz, ceiling, window, wall, and floor have been analyzed in details. The results are quite promising in terms of load reduction and overall energy saving. Indoor surface temperature reduction of up to 7oC has been achieved. The energy saving of up to 40% can be realized by employing PCM. A comprehensive list of the PCMs is also tried to build up for end users according to their temperature requirement. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a comparative life cycle assessment of two types of H2 carriers, methanol and ammonia, using GaBi 10 software. Two types of H2 carriers that is, methanol and ammonia are compared from coal, natural gas and renewables, respectively. The full supply chain is considered in the carbon footprint evaluation, which contains production, storage, transportation, and utilization phase. The energy analysis results show that H2 carrier produced from natural gas has higher energy efficiency than that from renewables, which can be attributed to the high energy consumption during H2 generation in the latter. Carbon footprint evaluation indicates that solar PV‐based ammonia production route has the lowest GWP in all scenarios, with a value of 43.9 g of CO2‐Equation MJ−1 of ammonia. In addition, electricity has been found as the key factor affecting GHG emissions in the routes of fuels produced from renewable H2 through sensitivity analysis. By optimizing electricity generation and expanding the carbon capture scale of power plant, the GHG emissions level of CCU‐based methanol production route and solar PV‐based ammonia production route can be further reduced. [ABSTRACT FROM AUTHOR]

Summary: In addition to directly burning in firepower plants, coal can be alternatively gasified into gaseous carbon monoxide and then fed into solid oxide fuel cells for efficient power generation. Carbon monoxide solid oxide fuel cells (CO‐SOFCs) not only avoid the drawbacks of expensive hydrogen fuel but also facilitate carbon dioxide's separation and enrichment. In this paper, an integrated system is first presented to efficiently recycle the waste heat released from CO‐SOFCs via alkali metal thermoelectric converters (AMTECs) for additional electricity generation. Key performance indicators such as power density and energy efficiency are mathematically expressed by including the heat‐transfer losses between heat sources and AMTEC. The maximum power density of the integrated system gains 18% improvement compared with that of the sole CO‐SOFC. The maximum efficiency can reach 60.84%. The optimum ranges of the current density, efficiency, and power density for the whole integrated system are determined. Furthermore, the influences of the fuel cell temperature on the optimum ranges are also studied. The correlations between the critical parameters and the maximum power density and efficiency of the system are revealed. The maximum power density and efficiency as well as the corresponding parameters are calculated numerically. The findings show that waste heat can be recycled efficiently by employing AMTECs. Novelty Statement: A numerical model of the CO‐SOFC/AMTEC integrated system is established.The maximum efficiency of the hybrid system can reach 60.84%.The optimum ranges of key parameters are determined and discussed. [ABSTRACT FROM AUTHOR]

SUMMARY How to decide the location and the capacity of distributed generators (DGs) in the distribution network is a complex and hard work. In this paper, several technical indexes involving energy loss, voltage quality and stability, and line loadability are considered to optimize DG capacity and location. It is an optimization problem wherein both discrete and continuous variables are involved, and cloud theory adapted genetic algorithm (CAGA) is employed to avoid search exploration and long time search. The weights of the indexes are decided by judgment matrix. DGs in a 28-node distributed network are employed to be optimized quickly to improve the indexes aforementioned to demonstrate the CAGA developed in this paper. Meanwhile, the optimization results are compared with traditional GA. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The integration of solar photovoltaic (PV) power generation technology into electric vehicle (EV) charging systems is of great significance, and it is very important to analyze the influencing factors of vehicle operating parameters on the generation power of vehicle PV system. In this paper, a model is developed to predict the power generated by vehicle PV system through a combination of a Fluent simulation study and Simulink modeling. Then the generation power of vehicle PV system under 7 different vehicle speeds in different months in Northeast China is analyzed. Through the Spearman correlation analysis and multilevel function fitting of the data, the mathematical model of a vehicle PV system power is proposed. Its variation with vehicle speed is obtained, as affected by solar radiation intensity and ambient temperature. According to the mathematical model analysis, the relevant vehicle characteristics and rules for vehicle PV systems were obtained. The simulation results show that the generation power of vehicle PV system in Northeast China increases significantly with the increase of vehicle speed in summer, but does not change significantly with the increase of vehicle speed in winter. [ABSTRACT FROM AUTHOR]

The floating photovoltaic (FPV) system is a revolutionary power production technology that has gotten a lot of interest because of its many benefits. Aside from generating electricity, the technology can also prevent the evaporation of water. The electrical and mechanical structures of FPV power stations must be studied to develop them. Much research on FPV technologies has already been undertaken, and these systems have been evaluated from many perspectives. Many problems, including environmental degradation and electricity generation, fertile soils, and water management, are currently limiting societal growth. Floating photovoltaic (PV) devices save a great of land and water resources and have a greater energy conversion efficiency than standard ground power systems. A performance investigation of photovoltaic (PV) installations set on a moving platform is carried out. The paper presents and discusses various design alternatives for boosting the profitability and efficiency of floating photovoltaic (FPV) systems. Especially, FPV systems that take advantage of increasing capabilities like monitoring, conditioning, and attention were included. Although researchers have agreed on the benefits of floating systems, there has been little in-depth research on the parameters of floating photovoltaic systems. The results of this research tests were performed, and these reveal that the beneficial monitoring and conditioning impacts result in a significant gain in performance. The effects of using flat reflections on improvements are also investigated. As a result, this research examines the evolution of photovoltaic systems, then investigates the power generation capacity of floating photovoltaic systems, and then examines the benefits and possibilities of floating PV systems in depth. The concept of developing an integrated air storage system using a floating building on waters is discussed. [ABSTRACT FROM AUTHOR]

This paper presents the development of a wind power forecasting model based on gene expression programming (GEP) for one of the major wind farms in Sri Lanka, Pawan Danavi. With the ever-increasing demand for renewable power generation, Sri Lanka has started harnessing electricity from wind power. Though the initial establishment cost of wind farms is high, the analyses clearly showcased the economic sustainability of wind power generation in long term. In this context, forecasting the wind power generation at Sri Lankan wind farms is important in many ways. However, limited research has been carried out in Sri Lanka to predict the wind power generation against the changing climate. Therefore, to overcome this research gap, a model was developed to forecast wind power generation against two climatic factors, viz. on-site wind speed and ambient temperature. The results showcased the robustness and accuracy of the proposed GEP-based forecasting model (with R2 = 0.92, index of agreement = 0.98, and RMSE = 259 kW). Moreover, the results of the study were compared against three different forecasting models and found comparable in terms of the model accuracy. The GEP-based model is advantageous over machine learning techniques due to its capability in deriving a mathematical expression. As an acceptable relationship was found between wind power generation and climatic factors, the proposed model facilitates the future projection of wind power generations with forecasted climatic factors. Though the application of GEP in the field of wind power generation is reported in a few research publications, this is the first research in which GEP is employed to model the power generation with respect to weather indices. The proposed prediction model is advantageous than machine learning models as the relationship between the wind power and the weather indices can be expressed. [ABSTRACT FROM AUTHOR]

When it comes to large-scale renewable energy plants, the future of solar power forecasting is vital to their success. For reliable predictions of solar electricity generation, one must take into consideration changes in weather patterns over time. In this paper, a hybrid model that integrates machine learning and statistical approaches is suggested for predicting future solar energy generation. In order to improve the accuracy of the suggested model, an ensemble of machine learning models was used in this study. The results of the simulation show that the proposed method has reduced placement cost, when compared with existing methods. When comparing the performance of an ensemble model that integrates all of the combination strategies to standard individual models, the suggested ensemble model outperformed the conventional individual models. According to the findings, a hybrid model that made use of both machine learning and statistics outperformed a model that made sole use of machine learning in its performance. [ABSTRACT FROM AUTHOR]

In deregulated electricity markets, generation companies (GENCO) try to maximize their economic benefits considering the electricity demand, transmission network condition, and other participants' behaviors. The increasing penetration of renewable sources such as wind power generation with intermittent nature poses several challenges to the participation of GENCOs in the electricity market. Thus, this paper presents a stochastic bilevel optimization model to determine the coordinated bidding strategy of a wind-thermal GENCO with the aim of maximizing its profit in the day-ahead and real-time balancing market. Herein, the model aims to maximize the profit of GENCO in the day-ahead and the balancing market in the upper-level problem while minimizing the operation cost of the system in the lower-level problem. The uncertainties of wind power generation and electricity demand are modeled by defining a set of scenarios considering their mutual correlation using the copula technique. Additionally, incorporating AC power flow constraints in the proposed optimization model offers a better solution to the coordinated bidding strategy of the wind-thermal GENCO. Further, the nonlinear AC power flow equations are linearized using the piecewise approximation technique to reduce the computational complexity and enhance the accuracy of the optimal solution. In the end, the developed algorithm is implemented on the IEEE 24-bus RTS, and the simulation results are provided to validate the efficiency and applicability of the proposed coordinated bidding strategy model. The results advocate that the participation of the thermal unit along with the wind farm might mitigate the risk of uncertainties, but it causes an intense increase in the locational marginal price of the system. Importantly, the simulation results indicate the computational efficiency of the model by developing an exact AC power flow model without compromising the results. Notably, it has been found that the profit of the wind-thermal GENCO would be increased by 35.2% employing the copula technique to model the mutual correlation of uncertain parameters. [ABSTRACT FROM AUTHOR]

This paper mainly studied the solid oxide fuel cell (SOFC)-micro gas turbine (MGT) hybrid power system. The key parameters that greatly influence the overall system performance have been studied and optimized. The thermodynamic potential of improving the hybrid system performance by integrating SOFC with the advanced thermal cycle system is analyzed. The optimization rules of main parameters of SOFC-MGT hybrid power system with the turbine inlet temperature (TIT) of MGT as a constraint condition are revealed. The research results show that TIT is a key parameter that limits the electrical efficiency of hybrid power system. With the increase of the cell number, both the power generation efficiency of the hybrid cycle power system and TIT increase. Regarding the hybrid system with the fixed cell number, in order to get a higher electrical efficiency, the operating temperature of SOFC should be enhanced as far as possible. However, the higher operating temperature will result in the higher TIT. Increasing of fuel utilization factor is an effective measure to improve the performance of hybrid system. At the same time, TIT increases slightly. Both the electrical efficiency of hybrid power system and TIT reduce with the increase of the ratio of steam to carbon. The achievements obtained from this paper will provide valuable information for further study on SOFC-MGT hybrid power system with high efficiency. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The method of determination of the control variables for a system controller, which controls the electric power output of a solid-polymer-membrane (PEM) fuel cell system during electric power load fluctuations, was considered. The operation was clarified for the response characteristics of electric power generation for setting the control variables of proportional action and integral action considered to be the optimal for the system controller. The power load pattern of an individual house consists of loads usually moved up and down rapidly for a short time. Until now, there have been no examples showing the characteristics of the power generation efficiency of a system that follows a load pattern that moves up and down rapidly. Therefore, this paper investigates the relation of the control variables and power generation efficiency when adding change that simulates the load of a house to PEM fuel cell cogeneration. As a result, it was shown that an operation, minimally influenced by load fluctuations, can be performed by changing the control variables using the value of the electric power load of a system. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, the Darcy–Forchheimer laminar thin film flow with MHD and heat transfer on an unsteady horizontal stretched surface is investigated. The impact of thermal radiation and viscous dissipation is also considered for thin film flow. The analysis of heat source with thermal radiation in a boundary layer flow can play a great role in manufacturing engineering procedures such as the production of electric power, solar energy modernization, and astrophysical flow. By using similarity transformation, the system of PDEs is converted to ODEs. Then HAM is applied for the solution of the problem. Moreover, the velocity and temperature profile for various embedded variables are discussed through graphs while the numerical solution of concerned physical quantities such as skin friction and Nusselt number are discussed through tables. The analysis shows that velocity profile is reducing function of M , K 1 , S , and F 1 . The temperature profile is an increasing function S and E c while a reducing function of Pr and R. The overall behavior of the proposed system is highlighted analytically. [ABSTRACT FROM AUTHOR]

The major concern of power utilities is to maintain, in all situations, the supply of electrical power to all its customers without any failure. However, because of a recent phenomenon such as demand power increase, insufficient power generation and other economical and environmental factors, most power system utilities operate with its equipment very close to their limits. This situation implies that events such as voltage instability and voltage collapse become more likely to occur. The static synchronous compensator, a shunt-connected Flexible AC Transmission Systems device capable of regulating the voltage level, is an important tool in order to prevent these occurrences from happening. In this paper, an approach to the problem of where these devices have to be inserted and what size should they have in order to enhance the voltage stability margin to a specified level is introduced in the form of metaheuristic approach. The approach was developed using the continuation power flow method to calculate the point of maximum loadability of the power system and using the particle swarm optimization concept to find the optimal combination of locations and sizes of a group of static synchronous compensator units. This is a known approach to the problem, but a new design of the objective function, which seeks to attain a pre-specified desired voltage stability margin, instead of maximizing it, is presented as an original contribution of the paper. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper investigates the application of a robust method to solve the problem of Daily Hydrothermal Generation Scheduling (DHGS). The Unit Commitment is implemented in restructured power systems by Independent System Operators to obtain an economic hourly generation schedule intended for the daily-ahead market. The application of Mixed-Integer Non-Linear Programming to deal with the DHGS problem has been discussed in this paper using Information Gap Decision Theory (IGDT) to assess a robust strategy for Independent System Operator. It is noted that the problem's uncertainty is due to load demand characterized using an IGDT method. The IGDT's concept is to model the uncertainty as an unbounded gap in the available information. Besides, this paper presents a model for risk-constrained DHGS to minimize the cost under uncertain load. This approach optimizes the robustness of decision-making strategy. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Object detection-based deep learning by using the looking and thinking twice mechanism plays an important role in electrical construction work. Nevertheless, the use of this mechanism in object detection produces some problems, such as calculation pressure caused by multilayer convolution and redundant features that confuse the network. In this paper, we propose a self-recurrent learning and gap sample feature fusion-based object detection method to solve the aforementioned problems. The network consists of three modules: self-recurrent learning-based feature fusion (SLFF), residual enhancement architecture-based multichannel (REAML), and gap sample-based features fusion (GSFF). SLFF detects objects in the background through an iterative convolutional network. REAML, which serves as an information filtering module, is used to reduce the interference of redundant features in the background. GSFF adds feature augmentation to the network. Simultaneously, our model can effectively improve the operation and production efficiency of electric power companies' personnel and guarantee the safety of lives and properties. [ABSTRACT FROM AUTHOR]

Summary: Conventional energy systems in both developed and developing economies are currently run by fossil‐fueled power plants. Many of them are ageing and are now being considered for the replacement to reduce the carbon intensity in electricity generation. One of the main routes to achieve this goal is by scaling‐up the deployment of the renewable energy system (RES). However, the increasing share of variable RES tends to affect the electrical grid operation. Hence, the need for reliable and flexible energy sources has emerged to cope with the variability in electricity and energy markets. Small modular reactors (SMRs) are emerging as alternatives to baseload fossil fuel systems and retiring large nuclear plants, primarily due to their small capacity and less‐capital intensive characteristics. The intermittency of power generation in the grid with a higher share of RES can be coped with in synergetic and effective way by adopting SMRs that form a nuclear‐renewable synergy in fulfilling the electricity demand. Furthermore, SMRs are designed to operate in load‐following mode adjusting the power output as demand of electricity fluctuates. SMRs feature modularity intended to enable enhanced constructability and phased‐deployment, adapting to the increased share of renewable energy in a distributed energy system, as energy demand increases. This paper will highlight the main outcomes of miscellaneous recent studies on the integrated energy systems carried out by international experts under the aegis of the International Atomic Energy Agency. The final publication of the study discusses the potential synergy of SMRs with RES for electric power production, as well as for other clean‐energy applications including seawater desalination, district heating, and hydrogen production. [ABSTRACT FROM AUTHOR]

High-temperature steam electrolysis (HTSE) consists of the splitting of steam into hydrogen and oxygen at high temperature in solid oxide electrolyzers. Performing the electrolysis process at high temperatures offers the advantage of achieving higher efficiencies as compared to the conventional water electrolysis. Furthermore, this allows the direct use of process heat to generate steam. This paper is related to the FCH JU (Fuel Cells and Hydrogen Joint Undertaking) project ADEL (ADvanced ELectrolyser For hydrogen Production with Renewable Energy Sources), which investigates different carbon-free energy sources to be coupled to the HTSE process. Renewable energy sources are able to provide the high-temperature steam electrolysis (HTSE) process with heat and power. This paper investigates the capability of Concentrating Solar Power (CSP) technologies to provide the HTSE process with the necessary energy demand. The layout of the plant is shown in the following figure. The design of commercial-scale high-temperature steam electrolysis has been carried out. The HTSE plant is coupled to an air cooled solar tower. The configuration and the operating parameters of the solar tower are based on those of the solar tower of Jülich (Germany), which is operated by DLR. This paper presents the results of process analysis performed to evaluate the hydrogen production from a HTSE plant coupled to an 80MWth air solar tower. Additionally, the dynamic behavior of the system during energy fluctuations has been analyzed. The receiver-to-hydrogen efficiency (based on the Higher Heating Value of hydrogen) is 26% at a hydrogen production rate of 680 kg/h in steady-state operation. The overall solar-to-hydrogen efficiency is calculated to be at 18%. Moreover, the analysis under transient conditions shows that a steady-state operation of the plant is only possible for 8 h. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: A novel model for superconductor magnetic energy storage (SMES) system as distributed generation system is proposed in this paper. Three‐level–bidirectional current fed chopper and 3‐level diode clamp inverter are used, and a novel switching strategy is proposed for control. Two cases are defined as the connected mode and islanded mode from the power grid that the SMES operation is considered and studied for both cases, for local load supplying and active/reactive power control. However, voltage controller in the islanded case and power controller in the connected case are designed. Proposed model and its associated control approaches have been verified through simulations by MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

This paper presents a method to control the rotor speed of wind turbines in presence of gearbox efficiency fault. This kind of faults happens due to lack of lubrication. It affects the dynamic of the principal shaft and thus the rotor speed. The principle of the fault tolerant control is to find a bloc that equalizes the dynamics of the healthy and faulty situations. The effectiveness decrease impacts on not only the dynamics but also the steady state value of the rotor speed. The last reason makes it mandatory to add an integral term on the steady state error to cancel the residual between the measured and operating point rotor speed. The convergence of the method is proven with respect to the rotor parameters and its effectiveness is evaluated through the rotor speed. [ABSTRACT FROM AUTHOR]

Summary: Most of the rural villages throughout the world are isolated from rest of the regions in accessibility to the electricity that considerably affects the sustainable development of this region. Low generation capacity addition, accessibility, and affordability of electrical power in the remote area are the major causes responsible for such situations. This long‐standing problem can be addressed through user friendly power supply from renewable power generation system with microgrid topology. In this paper a solar photovoltaic‐augmented, cogeneration‐based wind power generation scheme has been proposed for remote rural area power supply. This stand‐alone hybrid‐microgrid‐based power generation scheme will provide uninterrupted power to the under privileged village peoples at minimum cost unlike the existing utility supply. Considering, the complementary nature of the available wind and solar power, this paper also presents a coordinated control mechanism that ensures the automatic power exchange facility within the microgrid effectively. The scheme has been simulated by using MATLAB Simulink‐2016 simulation tool and practically implemented using a dSPACE CP1104 interfacing device, and the results are found satisfactory. [ABSTRACT FROM AUTHOR]

This paper discusses adding a spatial dimension to the design of community microgrid projects in the interest of expanding the existing discourse related to energy performance optimization measures. A multidimensional vision for designing community microgrids with higher energy performance is considered, leveraging urban form (superstructure) to understand how it impacts the performance of the system’s distributed energy resources and loads (infrastructure). This vision engages the design sector in the technical conversation of developing community microgrids, leading to energy efficient designs of microgrid-connected communities well before their construction. A new generation of computational modeling and simulation tools that address this interaction are required. In order to position the research, this paper presents a survey of existing software packages, belonging to two distinct categories of modeling, simulation, and evaluation of community microgrids: the energy infrastructure modeling and the urban superstructure energy modeling. Results of this software survey identify a lack in software tools and simulation packages that simultaneously address the necessary interaction between the superstructure and infrastructure of community microgrids, given the importance of its study. Conclusions represent how a proposed experimental software prototype may fill an existing gap in current related software packages. [ABSTRACT FROM AUTHOR]

The accuracy of energy management system for renewable microgrid, either grid-connected or isolated, is heavily dependent on the forecasting precision such as wind, solar, and load. In this paper, an improved fuzzy prediction horizon forecasting method is developed to address the issue of intermittence and uncertainty problem related to renewable generation and load forecast. In the first phase, a Takagi-Sugeno type fuzzy system is trained with many evolutionary optimization algorithms and established coverage grade indicator to check the accuracy of interval forecast. Secondly, a wind, solar, and load forecaster is developed for renewable microgrid test bed which is located in Beijing, China. One day and one step ahead results for the proposed forecaster are expressed with lowest RMSE and training time. In order to check the efficiency of the proposed method, a comparison is carried out with the existing models. The fuzzy interval-based model for the microgrid test bed will help to formulate the energy management problem with more accuracy and robustness. [ABSTRACT FROM AUTHOR]

For large-scale commercialized wind turbines, using the speed-torque lookup table is a traditional strategy to achieve optimum tip-speed ratio tracking. Due to the constraint of the minimum grid-connected generator speed and the rated generator speed, the strategy can only use the slashes to describe these 2 transition zones. This affects the smoothness of the output power, shrinks the optimum tip-speed range, and loses the generating energy. Based on an analysis of the nonlinear aerodynamics of the wind turbine, this paper presents a strategy of realizing optimal power generation control that dynamically updates the output torque limit value of the controller. The strategy solves the problems of unmeasurable wind speed and inability to track wind speed and achieves the target of maximum wind energy capture below rated wind speed. Simulation and field test results proved the correctness of the algorithm. [ABSTRACT FROM AUTHOR]

SUMMARY This paper describes the problem of short-term wind power production forecasting based on meteorological information. Aggregated wind power forecasts are produced for multiple wind farms using a hybrid intelligent algorithm that uses a data filtering technique based on wavelet transform (WT) and a soft computing model (SCM) based on neural network (NN), which is optimized by using particle swarm optimization (PSO) algorithm. To demonstrate the effectiveness of the proposed hybrid intelligent WT + NNPSO model, which takes into account the interactions of wind power, wind speed, wind direction, and temperature in the forecast process, the real data of wind farms located in the southern Alberta, Canada, are used to train and test the proposed model. The test results produced by the proposed hybrid WT + NNPSO model are compared with other SCMs as well as the benchmark persistence method. Simulation results demonstrate that the proposed technique is capable of performing effectively with the variability and intermittency of wind power generation series in order to produce accurate wind power forecasts. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Aiming at the high demand for the torque response speed and torque pulsation of the all-terrain vehicle (ATV) Electric Power Steering (EPS) system, this paper proposes to apply the Model Predictive Current Control to the all-terrain vehicle EPS system. A Novel Three-Vector Model Predictive Current Control (N3V-MPCC) is proposed in this paper to reduce the current ripple and reduce the calculation load. Two effective voltage vectors and a zero vector are selected in the control period through only six times of prediction and application of the Sector Vector Selection method. The duration of each voltage is calculated and output to the Voltage Source Inverter (VSI). Simulation and experimental results show that, compared with PID cascade Field Oriented Control (PI-FOC), N3C-MPCC can effectively reduce the ripple current of the d-axis and the q-axis. In the simulated electric power mode, the q-axis current ripple of the N3V-MPCC is reduced by 66.67%. Experimental results show that the current ripple of the motor is reduced by 60%, and the torque pulsation is reduced by 62.5%. Therefore, N3V-MPCC has a faster current response speed and smooth steering torque. [ABSTRACT FROM AUTHOR]

Summary: Growth in global energy demand, with major fossil fuel consumption, has induced detrimental environmental and social impacts. Therefore, in recent years, technologies focused on renewable energy utilization, including biomass energy, have evolved to meet the energy requirements. Bioenergy‐based power generation systems are among the best‐unutilized configurations to diminish reliance on fossil fuels. However, it is difficult to select a biomass‐based configuration for economical, sustainable, and reliable power generation. Understanding different possible configurations of biomass‐based energy systems, design parameters, system research gaps, and integration challenges in biomass‐based energy systems are important for further development and propagation. This paper presents a critical review of biomass‐based different hybrid configurations with solar, wind, fuel cell, micro‐hydro, geothermal, and diesel generator, and various designing parameters, challenges, and gaps with future scope. To restrict the scope of the review, only the gasification and anaerobic digestion related biomass electricity generation systems are considered. The analysis indicates that the biomass‐based hybrid energy systems can provide an eco‐friendly and cost‐effective solution, especially for off‐grid rural electrification. The solar radiation, load demand, fuel price, capacity shortage, interest rate, wind speed, biomass quantity, and electricity rate are among the most critical designing parameters in biomass‐based energy systems. The study provides valuable information to designers, researchers, and policy makers on the latest design constraints and relevant policies relating to biomass‐based hybrid energy systems. [ABSTRACT FROM AUTHOR]

Summary: Backgroud: The uncertainty associated with renewable generation and loads imposes various challenges for the economic operation of microgrids. On the residential side, energy storage systems are implemented with high expectations to enhance photovoltaic power consumption and electricity price arbitrage. Aims: This paper proposes an expectation‐oriented stochastic model for optimal energy management of household batteries to cope with the uncertain electricity generation and consumption. Materials & Methods: The exact cost expectation of daily operation is formulated as an alternative to the conventional scenario‐based average approximation. A predictive control‐based battery scheduling mechanism is developed further to apply the proposed model to intraday energy storage management. Results: Simulation results validate the convexity of the proposed model. Discussion: Although nonlinear in nature, the resultant optimization problem is proven to be convex, which ensures computable global optimal solutions for the proposed model. Conclusion: Simulation results demonstrate the effectiveness of the proposed scheduling strategy compared with existing methods. [ABSTRACT FROM AUTHOR]