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This study presents a 100% renewable and diversified system taking advantage of the available energy potential of renewable energies in Mexico with a view to a planned energy transition in cooperation with the environment. The processes of change that are experienced worldwide in favor of the planet make us reflect and propose alternatives that break traditional schemes in the production of energy (for which reason Mexico cannot deviate from its current model). It is here that this research becomes a transcendental and important reference for decision-making and the transformation of the energy sector in Mexico. The current electrical system relies on fossil fuels that need to be replaced by renewable energy sources (and it is necessary to satisfy growing demands in the long term). The methodological process is carried out with the use of the 100% renewable energy market design tool EnergyPLAN, which puts the concept of intelligent energy into practice by 2050. Finally, after analyzing the results, it is concluded that a good energy mix for 2050 is 30% solar photovoltaic, 25% wind, 14.5% hydraulic, 13.8% CSP plants, and 16.7% other technologies. Surpluses may be sold to the United States and Central America through interconnection points. [ABSTRACT FROM AUTHOR]

The constant changes in the load power lead permanently to a power mismatch between the power generation and the power consumption. So, the system frequency due to the power imbalance deviates from the nominal value. Consequently, a control loop should be implemented to stabilize the system frequency whenever a load change occurs. This paper presents a new super‐twisting sliding mode control methodology for obtaining an optimal frequency performance in a multi‐pool system. The paper presents a three‐pool system for frequency deviation problems using an optimal gain Super Twisting Sliding Mode Controller (STSMC), which regulates the frequency change and the line power change to zero in a minimal time. The extent of the excellence of the study proposed is evaluated by comparing it with three Benchmark classical controllers, which are the Tilt‐Integral‐Derivative (TID), Proportional‐Integral‐Derivative (PID), and Fractional‐Order PID (FOPID). The parameters of the four controllers are determined by a proposed physical meta‐heuristic optimization technique called Transient Search Optimizer (TSO), inspired by the dynamic behaviour in the electrical circuits comprising storage elements such as capacitors and inductors during the switching actions. The system simulation is performed, and the STSMC proved overwhelming superiority over other controllers, as it deals better with the transient interval of the system response. Renewable Energy sources (RESs) like photovoltaic and wind energy systems are established, and the STSMC is tested with industrial and residential load models. Finally, energy storage devices such as batteries and superconducting magnetic energy storage are implemented to suppress the rapid fluctuations in the system response, and it succeeded in doing that as the system oscillations are greatly damped with the energy storage devices. [ABSTRACT FROM AUTHOR]

For the time being, renewable energy source (RES) penetration has significantly increased in power networks, particularly in microgrids. The overall system inertia is dramatically decreased by replacing traditional synchronous machines with RES. This negatively affects the microgrid dynamics under uncertainties, lowering the microgrid frequency stability, specifically in the islanded mode of operation. Therefore, this work aims to enhance the islanded microgrid frequency resilience using the virtual inertia frequency control concept. Additionally, optimal model predictive control (MPC) is employed in the virtual inertial control model. The optimum design of the MPC is attained using an optimization algorithm, the African Vultures Optimization Algorithm (AVOA). To certify the efficacy of the proposed controller, the AVOA-based MPC is compared with a conventional proportional–integral (PI) controller that is optimally designed using various optimization techniques. The actual data of RES is utilized, and a random load power pattern is applied to achieve practical simulation outcomes. Additionally, the microgrid paradigm contains battery energy storage (BES) units for enhancing the islanded microgrid transient stability. The simulation findings show the effectiveness of AVOA-based MPC in improving the microgrid frequency resilience. Furthermore, the results secure the role of BES in improving transient responses in the time domain simulations. The simulation outcomes are obtained using MATLAB software. [ABSTRACT FROM AUTHOR]

Storage systems and demand-response programs will play a vital role in future energy systems. Batteries, hydrogen or pumped hydro storage systems can be combined to form hybrid storage facilities to not only manage the intermittent behavior of renewable sources, but also to store surplus renewable energy in a practice known as 'green' storage. On the other hand, demand-response programs are devoted to encouraging a more active participation of consumers by pursuing a more efficient operation of the system. In this context, proper scheduling tools able to coordinate different storage systems and demand-response programs are essential. This paper presents a stochastic mixed-integer-lineal-logical framework for optimal scheduling of isolated microgrids. In contrast to other works, the present model includes a logical-based formulation to explicitly coordinate batteries and pumped hydro storage units. A case study on a benchmark isolated microgrid serves to validate the developed optimization model and analyze the effect of applying demand-response premises in microgrid operation. The results demonstrate the usefulness of the developed method, and it is found that operation cost and fuel consumption can be reduced by ~38% and ~82% by applying demand-response initiatives. [ABSTRACT FROM AUTHOR]

The electrical system performance can be improved considerably by controlling the reactive power flow in the system. The reactive power control can be achieved by optimal reactive power dispatch (ORPD) problem solution and optimal integration of the FACTS devices. With high penetration of renewable energy sources (RESs) and the load growth, the ORPD solution became a challenging and a complex task due to the stochastic nature of the RERs and the load growth. In this regard, the aim of this paper is to solve the stochastic optimal reactive power dispatch (SORPD) with optimal inclusion of PV units, wind turbines and the unified power flow controller (UPFC) under uncertainties of the load growth and the generated powers. An Adaptive Beluga Whale Optimization (ABWO) is proposed for solving the SORPD which is based on the Fitness-Distance Balance Selection (FDBS) strategy and the territorial solitary males' strategy of the Mountain Gazelle Optimizer. The proposed ABWO is tested on IEEE 30-bus system and a comparison with other optimization techniques for solving the ordinary ORPD is presented for validating the proposed ABWO. The obtained results reveal that the TEPL is reduced from 5.3168 MW to 3.97985 MW with optimal integration of the RERs and UPFC. Likewise, the TEVD is reduced from 0.1794p.u. to 0.10689p.u. and the TVSI is decreased from 0.1289p.u. to 0.0476p.u. [ABSTRACT FROM AUTHOR]

Summary: Nowadays, microgrids are emerging as an invaluable framework for the integration of renewable energy sources and demand response programs. In such systems, energy storage facilities are also frequently deployed to properly manage surplus energy from renewable sources on pursuing more efficient management of the system. Hybrid storage systems in which various storage facilities are combined may result in a more effective solution than only considering one storage technology. This way, the good features of the different technologies may be jointly exploited while their drawbacks are minimized. Due to the large‐scale integration of renewable energies in this kind of grid, coping with uncertainties becomes a critical issue. Moreover, the operation of microgrids frequently deals with other kinds of uncertainties related to energy pricing from the upscale grid (in the case of grid‐connected mode) or local demand. This way, proper modeling of uncertainties is essential for adequately operating these systems. This paper contributes to this pool by developing a novel interval‐based formulation, for optimal scheduling of microgrids considering battery and pumped‐hydro storage systems. To achieve this goal, the optimal scheduling of a microgrid with pumped‐hydro and battery energy storage considering demand response is modeled, firstly. Then, the new interval‐based formulation is used to cope with the uncertainties. Finally, the suggested model is verified using simulations in various cases, and the results confirm the effectiveness of the novel interval‐based formulation for the optimal scheduling of microgrid with pumped‐hydro and battery energy storage under uncertainty. [ABSTRACT FROM AUTHOR]

This research presents a completely decarbonized system structured with renewable energies for the fragile ecosystem of the Galapagos Islands of Ecuador, with a horizon to the year 2050. The transition process begins with clear legal actions and allocating economic resources that clearly promote a change in the energy matrix and the transition would be achieved until the year 2050. The Galapagos Islands are the second largest marine reserve on the planet, declared a World Heritage Site in 1978 for UNESCO. The archipelago, a beautiful ecological attraction, has tourism as its main economic source. The biggest problem is in the supply of energy that mainly comes from fossil fuels, in addition to that, the smell of fuel in several places is out of tune with the harmonious nature and its species. The efforts began to be noticed when in the Archipelago the new implementations of renewable energy began to become a reality with the purpose of stopping using fossil fuels. In this sense, there is the potential to take advantage of the resources available in specific sites, especially the photovoltaic and wind solar considered in the National Plan All a Life. The change in the productive matrix from the national level also implies a change in demand, including at the transportation level with the use of electric vehicles and the use of electric stoves in homes. The purpose is that energy services in the Galapagos Islands progressively increase, on the one hand, replacing fossil fuels and on the other, supplying the growing demand with a view to 2050, taking advantage of renewable energies until reaching 100%. • The scenario outlined is 100% renewable energy by 2050 in the Galapagos Islands. •The Galapagos archipelago has great renewable energy potential. •The decarbonization in Galapagos will have a positive impact on the socioeconomic and environmental aspects. •Decarbonization is feasible by 2050 depending on the economic situation. •The electricity system of Galapagos will allow it to maintain its status as a Cultural Heritage of Humanity. [ABSTRACT FROM AUTHOR]

Nowadays, the penetration level of renewable energy sources (RESs) has increased dramatically in electrical networks, especially in microgrids. Due to the replacement of conventional synchronous generators by RESs, the inertia of the microgrid is significantly reduced. This has a negative impact on the dynamics and performance of the microgrid in the face of uncertainties, resulting in a weakening of microgrid stability, especially in an islanded operation. Hence, this paper focuses on enhancing the dynamic security of an islanded microgrid using a frequency control concept based on virtual inertia control. The control in the virtual inertia control loop was based on a proportional-integral (PI) controller optimally designed by the Manta Ray Foraging Optimization (MRFO) algorithm. The performance of the MRFO-based PI controller was investigated considering various operating conditions and compared with that of other evolutionary optimization algorithm-based PI controllers. To achieve realistic simulations conditions, actual wind data and solar power data were used, and random load fluctuations were implemented. The results show that the MRFO-based PI controller has a superior performance in frequency disturbance alleviation and reference frequency tracking compared with the other considered optimization techniques. [ABSTRACT FROM AUTHOR]

Bioenergy is one of the most important renewable-energy sources worldwide, accounting for more than two-thirds of the renewable-energy mix. Biomass accounted for 13–14% of the primary energy consumption in 2018, and by 2050, it is expected to account for 50% of the global primary energy consumption. This article studies the biomass potential in Iraq. The potential of this country to be one of the leading producers of bioenergy is discussed, remarking on the importance of agricultural crop waste. Nowadays, Iraq generates a great quantity of biomass every year. Unfortunately, instead of contributing to the energy industry and economic progress, these wastes are burned directly, potentially causing a slew of environmental issues. Based on earlier studies, the theoretical energy potential of Iraq agricultural wastes is assessed. It is concluded that 10 million tons of dry agricultural leftovers can create 115 PJ of energy per year. According to the findings of this study, 10 million heads of cattle in Iraq could generate 72 million m3 of biogas per day, with a total potential power of 946 TJ per year from animal wastes, mainly cattle dung. On the other hand, bioenergy potential is heavily reliant on the geographical distribution, availability, and accessibility of real waste. Wasit, Qadisiyah, and Mosul are the most feasible locations for this agricultural waste potential. This might lead to the development of a long-term economic plan for the successful and sustainable utilization of important accessible waste for bioenergy generation. [ABSTRACT FROM AUTHOR]

Renewable sources on islands seem to be the most attractive option to decarbonize and lower the price of electricity; currently, most islands do so by replacing their diesel generators with wind or solar sources, along with energy storage. The Galapagos Islands are no exception. This study presents a techno-economic analysis of hybrid renewable systems in the Galapagos Islands, considering the repowering of its renewable sources and reduction in the penetration of diesel generators. This study uses EnergyPlan software, where the best option is chosen based on technical, economic, and environmental indicators. Finally, several sensitivity analyses are done. The results show that by increasing the capacity of current wind and photovoltaic systems, the total annual cost reduces by 20% and 10.31%, respectively; this is a specific result of this study. Moreover, there is a reduction in CO2 emissions produced by diesel generators, up to 38.96%. [ABSTRACT FROM AUTHOR]

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Sustainable development reached a new energy paradigm in recent decades, by promoting renewable generation technologies. The present study performs a techno‐economic analysis of several hybrid energy systems that combine wind generators, photovoltaic systems, hydrokinetic turbines, lead acid batteries, and diesel generators in southern Ecuador. From real data, the sizing optimization of each renewable system was done under three proposed energy control algorithms. Then, the combinations of renewable systems are compared based on costs, energy, and environment. Additionally, this study includes several sensitivity analyzes varying the cost of the components and fuel, minimum state of charge in batteries, scaled electric load and time step to better understand the impact caused in each renewable hybrid system. The results show that a system composed of three renewable sources under load following and cycle charging energy controls, is cheaper and less polluting with respect to any combination of sources proposed. In addition to this, the systems that include photovoltaic systems and diesel generators present lower cost, 0.36 US$/kWh in the best case. To reduce the operability of the diesel generator, load following energy control is recommended. However, if diesel generator is removed, the resulting cost of 100% renewable systems increases considerably, reaching 0.88 US$/kWh. The results also show that, the variation in the capital cost of the components is directly proportional to the net present cost and cost of energy variation. Moreover, it is possible to reduce the cost of the system by discharging the batteries below their minimum state of charge. Finally, the results are more accurate when using a time step of 5 minutes. [ABSTRACT FROM AUTHOR]

• Developing a new stochastic-interval model for energy management in communities. • The developed model considers controllable demand, vehicle-to-grid and energy storage. • The developed model allows to adopt pessimistic or optimistic strategies. • Obtained results reveal the benefits on gathering prosumers on communities. • Community operation reduces the energy that must be acquired from the grid. With the advent of smart cities, residential consumers have evolved towards the concept of prosumers. This paradigm calls for new businesses like energy communities. Energy management of such frameworks is essential to maximize the collective welfare. This paper addresses this issue by developing an energy management framework that accounts for flexible demand, storage devices and electric vehicles. Its two-level structure allows to address the energy exchanging among prosumers in the 1st stage, while the 2nd stage focuses on optimally schedule the different collective assets. A novel stochastic-interval model is proposed to handle with uncertainties from demand, renewable generation, vehicles' behaviour and energy pricing. A case study is performed on a six-prosumer community. Results serve to validate the new tool and analyse the importance of smart devices. In addition, the new proposal allows to adopt different operating strategies. Actually, the total operating cost may increase by 90% if a pessimistic point of view is adopted while the importance of the vehicle-to-grid capability is marginal otherwise. Furthermore, the energy purchased could be reduced by 7% when adopting a community arrangement, supposing an improvement in the economy and environmental indicators of the network. Other relevant aspects are identified and discussed in depth. [ABSTRACT FROM AUTHOR]

In this article, the concept of a new simple neuro-fuzzy control scheme for a combined-cycle power plant is presented. Gasification technologies under development would enable the residual biomass to be used in gas turbines. Biomass conversion to a clean essentially ash-free form, usually by gasification and purification, is necessary to obtain high efficiency. This paper reports results of detailed full-load performance modeling of cogeneration systems based on gasifier/gas turbine technologies. [ABSTRACT FROM AUTHOR]

Biomass gasification is a technology that transforms solid biomass into gas. A gasifier is capable of converting wood into a gaseous fuel that is fed into a gas motor. The gas motor controller regulates both the gas motor and the gas motor generator. In this paper 2 fuzzy logic controllers have been developed using speed and mechanical power deviations, and a neural network has been designed to tune the gains of the fuzzy logic controllers based on the operating conditions of the biomass-based electric power plant. [ABSTRACT FROM AUTHOR]

The optimal reactive power dispatch (ORPD) problem is an important issue to assign the most efficient and secure operating point of the electrical system. The ORPD became a strenuous task, especially with the high penetration of renewable energy resources due to the intermittent and stochastic nature of wind speed and solar irradiance. In this paper, the ORPD is solved using a new natural inspired algorithm called the marine predators' algorithm (MPA) considering the uncertainties of the load demand and the output powers of wind and solar generation systems. The scenario-based method is applied to handle the uncertainties of the system by generating deterministic scenarios from the probability density functions of the system parameters. The proposed algorithm is applied to solve the ORPD of the IEEE-30 bus system to minimize the power loss and the system voltage devotions. The result verifies that the proposed method is an efficient method for solving the ORPD compared with the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

• Effects of different storage technologies on a hybrid renewable energy system. • Photovoltaic system, hydrokinetic system and diesel generator. • Five types of storage are considered. • The study is done in the HOMER Pro software. • Sensitivity analysis and variation of the minimum state of charge. This study analyzes the effects of different storage technologies on a hybrid renewable energy system composed of photovoltaic, hydrokinetic and diesel generator. Five types of storage are considered: lead acid, lithium ion, vanadium redox flow, hydrogen and hydrogen-vanadium redox flow. The analysis is mainly based on indicators such as Net Present Cost, Cost of Energy, unmet load and CO 2 emissions. HOMER software has been used in this paper with time-sampling models and sensitivity studies to determine the effects of each storage system. The results show that the vanadium redox flow batteries system presents a lower net present cost and cost of energy. The sensitivity analysis shows that the vanadium redox flow system presents a greater variation of the minimum state of charge (SOC) in relation to the net present cost. However, the system composed of hydrogen and fuel cell present the lowest variation. The two proposed strategies for energy control show the same performance. However, when using the Load Tracking Control, the variation of the minimum state of charge with respect to the net cost is greater than the variation obtained when applying the Load Cycle Control. [ABSTRACT FROM AUTHOR]

In this paper, a novel stochastic risk-averse mixed-integer linear programming (MILP) model is developed for optimal electricity procurement of hydrogen fuel stations (HFSs) with responsive hydrogen demands. In the developed model, HFS operator may procure its required electricity through day-ahead (DA) market, bilateral contracts, a contract with withdrawal penalty (CWP) and balancing market. The HFS is committed to inject a pre-specified volume of hydrogen into a natural gas network. In the developed stochastic model, the uncertainties in hydrogen demand and DA market prices are characterized as random variables and modeled as scenarios. The developed model is a two-stage model in which the decisions on transactions with bilateral contracts are the first-stage decision variables and the other decision variables belong to the second stage. The risk of suffering from high procurement costs is modeled using the Conditional Value at Risk (CVaR). The results confirm the efficiency of the proposed model both in terms of reduction in HFS expected cost and risk alleviation. The results show that the transaction through bilateral contracts decreases the expected cost and CVaR respectively by 6% and 3%. The results also indicate that the participation in the balancing market decreases the expected cost and CVaR respectively by 6% and 1.6%. As per results, in scenarios in which DA market prices are lower than CWP prices, HFS operator prefers to pay a penalty fee and withdraw from CWP. The sensitivity of HFS profit to the weight factor of risk metric and the participation factor of responsive demands are assessed. [Display omitted] • A model is developed for electricity procurement of hydrogen fuel stations (HFSs). • The uncertainties in demands and market prices are considered. • HFS procures electricity by day-ahead and balancing market and bilateral contracts. • Impact of different markets and transactions on HFS profit is assessed. • Sensitivity of HFS profit to weight of risk metric is assessed. [ABSTRACT FROM AUTHOR]

This article presents a comparison of two alternative systems to supply the traction power of a tramway in Cuenca–Ecuador. Each system studies the effective combination of supercapacitors, lithium ion batteries and proton exchange membrane fuel cells (SC/LIB/PEMFC) on board. The first system uses renewable sources (PV/HKT/GB/Grid) supplying the on-board systems through the existing grid and hydrogen charging stations. While the second system uses only grid power from a single point of charge, leaving the tramway without any external connection point throughout their journey. The energy and economic analyses are based on the capacity of each system to supply the load and the resources used. The results show that the new proposed control systems, by means of the analysed configurations made up of different control states, are always capable of perfectly supplying the power required by the tramway throughout their journey. However, when using energy from renewable sources, hydrogen consumption decreases by 4.27% with respect to the grid on each round trip, with a lower net present cost. Furthermore, in the first proposed system, the depth of discharge in SC and LIB is greater. • Energy control systems based on fuel cell for a hybrid tramway in Ecuador. • Renewable components (photovoltaic, hydrokinetic and biomass). • All components are charged with the braking power of the tramway. • The study includes technical-economic analysis of two proposed systems. [ABSTRACT FROM AUTHOR]

In recent years, photovoltaic energy production has experienced significant progress, being integrated into the grid through large-scale distributed systems. The intermittent nature of solar irradiance coupled with the presence of photovoltaic failures causes fluctuations that could compromise the quality and stability of electrical grid. This paper presents a novel photovoltaic power smoothing method in a combination with moving averages and ramp rate to reduce fluctuations with hybrid storage systems (supercapacitors/batteries), the main novelty involves optimizing the number of charging/discharging cycles under PV failures. To achieve this goal, a photovoltaic failure detection method is proposed that uses machine learning to process big data by monitoring the behavior of photovoltaic. The experiments have been done under controlled conditions in the microgrid laboratory of the University of Cuenca. The results show the reduction of the supercapacitor operation with respect to other power smoothing methods. Moreover, the monitoring system is capable of detecting a failure in photovoltaic systems with a root mean squared error of 0.66 and the computational effort is reduced using the new smoothing technique. In this sense, the initial execution time is 4 times lower compared to the moving average method. [Display omitted] [ABSTRACT FROM AUTHOR]

This research presents a 100% renewable system configured based on its real potential and use of renewable energies for the Ecuadorian Amazon, considered one of the places with the greatest diversity of native plant species on the planet. The transition processes that are born from the central state seek to take a radical turn in the electricity sector but there is still no defined roadmap, this is where this research will allow it to be an important reference for its long-term transformation. The current system is based on fossil fuels and in this study an energy transition process is planned with the support of the EnergyPLAN tool that puts into practice the concept of intelligent energy, progressively and systematically achieving 100% renewable energy for 2050. Finally, after analyzing the results, it is concluded that the energy mix for 2050 can consider 36.47% hydro, 33.04% solar photovoltaic, 29.73% wind energy and other technologies to a lesser extent with 0.74%. Surpluses can be injected into the interconnection sites with Colombia and Peru, also achieving economic income to preserve and expand the infrastructure of the electricity sector. Decision makers can consider this study as a reference before committing economic resources and carrying out modern energy planning. [Display omitted] • A smart Renewable Energy approach is presented. • A convergent method is developed for greater contributions from wind and solar PV. • The proposal launched is to leave the oil underground. [ABSTRACT FROM AUTHOR]

• Using and employing vast areas of solar cells scattered around the world to collect rainwater. • Solar panels self-cleaning and cooling intelligent system. • Recycling 80% of solar panels cleaning water. • Low cost and low-maintenance solar panels cleaning system. First generation Photovoltaic (PV) systems need regular washing to avoid efficiency degradation. Dust deposition on the surface limits solar penetration into photovoltaics and consequently the PV output. Efficiency may fall by 50% after a month without cleaning the modules. This effect strongly depends on the area, being desert climates more problematic because of the proliferation of dust particles and eventual high wind speeds. This research aims to illustrate the idea of an innovative intelligent device with wide applications and advantages, which improves the efficiency of solar cells by a self-cleaning mechanism, keeping the temperature of solar cells from rising, recycling the cleaning water, and harvesting rainwater falling. In this research, an experiment was performed in the city of Salt (Jordan) to investigate the purification of solar cells at the energy production plant above the Najashi Mosque. To clean the dust periodically, an automated cleaner was installed that detects the dust on the solar panel and automatically cleans the module. Various cleaning methods were compared: manual cleaning, automatic cleaning, manual injection water, compressed air. Some outstanding features of the new proposal are identified, making it the ideal device for resolving cleaning difficulties, high temperatures, and increasing solar cell performance. It can be also utilized to gather rainwater by employing the vast areas of solar cells scattered over the world. The findings of this study may help in preserving the environment by harvesting sun and rainwater, enhancing PV efficiency, and achieving decarbonization in the energy industry. [ABSTRACT FROM AUTHOR]

The proliferation of charging stations entails multiple challenges for power systems. In this regard, the installation of photovoltaic-battery systems may help to mitigate the negative effects of charging points. However, such assets should be carefully planned, paying attention to economic aspects, principally. Most of existing works optimize the photovoltaic-battery system in charging infrastructures taking a representative-space of the involved variables (e.g. photovoltaic potential, charging demand or energy prices). However, this approach tends to ignore low-probable scenarios. Thus, the best-case scenario for charging demand (i.e. that for which the highest charging profit is accessible) may not be included in the analysis and therefore such demand could be not attended properly, thus losing this monetary opportunity. This paper focuses on this issue and questions if considering the best-case scenario into planning photovoltaic-battery systems for charging stations is worthwhile or not. To this end, a novel best-case-aware planning tool is developed, including the best-case scenario through a novel chance-constrained formulation. The overall problem is then decomposed into a master-slave structure by which the economy of the system is optimized together with the number of scenarios for which the best-case profile can be attended. A case study serves to validate the developed tool and shed light on the questions arisen in this work. In particular, it is checked that considering the best-case scenario into planning tools is questionable from a monetary point of view. Nevertheless, its inclusion unlocks some collateral advantages such as incrementing the users' satisfaction or reducing the grid-dependency. [ABSTRACT FROM AUTHOR]

Decarbonization of the energy sector calls for new energy sources and power-system operation paradigms. In this context, consumers can partake in system operation as loads and generators by leveraging own resources, such as rooftop photovoltaics (PVs). These prosumers can be gathered into energy communities (ECs) and operated in a centralized manner to exploit eventual synergies optimally. The ECs are usually connected to a distribution network and thus interact with the distribution grid operator (DSO), complicating the scheduling strategies under agent interactions. Moreover, the DSO can thus manage his own resources such as distributed generators or medium-scale storage systems. The operation becomes more complex due to multi-source uncertainties in ECs and DSO. This paper addresses this issue by developing a novel bi-level energy management framework for the robust optimal coordination of ECs and DSO against uncertainties. In this framework, the upper-level agents provide the information by solving the designed optimization problems for the EC operation, sending it to the lower-level agents to facilitate the optimal scheduling of distributed assets. In particular, a novel robust reformulation of the lower level problem is proposed, to handle with uncertainties in renewable generation, demands, and energy prices fixed by the local retailer. The resulting formulation is mixed-integer-linear programming that is efficiently manageable by common solvers. Simulation results on the standard IEEE 33-bus distribution system with six connected ECs and various distributed assets (e.g., renewable generators and storage systems) demonstrate the effectiveness and robustness of the proposed framework. The results also evidence the vital role of storage systems in maximizing the DSO's profits while reducing the ECs' operating costs. [ABSTRACT FROM AUTHOR]

Recently, biomass represents about 14% of primary energy consumption and expected to provide 50% of world total primary energy consumption by 2050. This paper clarifies an appraisal of the possibilities available in Egypt to become one of the countries of the production of bioenergy, especially from the crop remnants of agriculture production. Egypt annually produces a large amount of biomass of up to 40 million tons. Unfortunately, instead of the possibility of exploiting these wastes to contribute to the energy sector and economic growth, about 52% of these wastes are disposed of by direct burning, which may cause many environmental problems. The only widespread form of biomass use in Egypt is biogas used in rural areas. In addition, the potential theoretical energy from the most important crop residues available in Egypt is evaluated according to previous studies. It is found that energy of 189.76 PJ/year can be produced from dry crop residues of 12.5 million tons/year. For livestock residues, specifically cattle manure, it is estimated in this study that the potential biogas in Egypt of 7.2 million head of cattle is 53.2 million m 3 / day with a total potential energy of 699 TJ per year. However, the potential of bioenergy depends largely on the availability, geographical distribution and accessibility of the actual waste. The most likely areas for these potentials are Middle Delta and Upper Egypt. This could potentially develop a long-term strategy for the smart use of vital waste available for bioenergy production to be economically profitable and sustainable. [ABSTRACT FROM AUTHOR]

• A novel stochastic-robust approach is developed for energy communities. • Peer-to-peer exchanges and collective assets are considered and analysed. • The problem is solved using a novel three-stage procedure. • Operating cost is incremented 77$ when the degree of robustness grows. • Collective storage systems help to reduce unserved demand and wasted generation. Energy communities enable effective coordination among prosumers on pursuing collective targets. This paper focuses on isolated 100% renewable communities, involving individual (controllable appliances and small generators) and collective (wind generators and battery banks) assets. To effectively coordinate the agents involved in these structures, advanced energy management strategies are necessary. This work develops a three-stage day-ahead scheduling strategy for isolated 100% energy communities, involving peer-to-peer transactions among prosumers. The different uncertainties involved are incorporated through a novel stochastic-robust formulation, that results in a computationally tractable optimization framework. To validate the new model, a case study on a six-prosumer benchmark community is analysed. Results reveal the importance of collective assets and peer-to-peer exchanges among prosumers as well as the effectiveness of the developed formulation. The role of batteries is also discussed, helping to reduce the total unserved energy and operating cost by 20% and 19%, respectively, as well as enabling a more efficient use of wind energy. The impact of robustness is also studied, incrementing the expected importable energy by 28% compared to the deterministic case, while the exportable energy from prosumers is notably reduced by 40%. However, uncertainty-aware strategies have a direct impact on operational costs, incrementing the expenditures by 37% when uncertainties are considered. [ABSTRACT FROM AUTHOR]

Energy consumption from residential sector is a growing concern nowadays. It has been widely demonstrated that domestic consumption worldwide could be notably reduced implementing home energy management tools. This kind of programs allows to schedule the different controllable home assets to optimize the electricity bill and increment the penetration of onsite renewable technologies, which contributes to a further reduction in residential consumption. On the other hand, grid outages are still frequent nowadays because natural disasters or weak infrastructures. Therefore, home energy management tools do not ignore these events. To tackle this issue, this paper develops a novel three-stage solution procedure for home energy management problems considering grid outages. To this end, a novel stochastic-IGDT formulation of the home energy management problem is proposed, by which the uncertain parameters are incorporated via scenarios and grid outages are modelled using IGDT. The presented formulation is Mixed-Integer Linear programming and allows to obtain a schedule result for the home appliances immune against outages without ignoring the economy of system. A benchmark prosumer environment with Real-Time pricing is considered as a case study. The results prove the effectiveness of the developed methodology. In particular, the effectiveness of the developed formulation in modelling grid outages as well as the scheduling performance at different conflictive objectives are highlighted. In addition, the effect of primarily considering robustness or economy is discussed together the importance of onsite photovoltaic generation in incrementing the reliability of the home system. Finally, the capability of the developed procedure to jointly consider cost and outages on a whole is foregrounded. In fact, the developed methodology is able to assume up to 6.5 outage hours without increasing the electricity bill, thus evidencing its capability to obtain a result immune against outages, whereas economic concerns are also considered on a whole. [ABSTRACT FROM AUTHOR]

This paper presents an Energy Management System (EMS) for hybrid systems (HS) composed by a combination of renewable sources with the support of different storage devices (battery and hydrogen system) that allow its operation without the necessity of grid connection (i.e. a stand-alone system). The importance of the proposed EMS lies in taking into account economic issues that affect to the decision of which device of the HS must operate in each moment. Linear programming was used to meet the objective of minimizing the net present value of the operation cost of the HS for its whole lifespan. The total operation costs depend largely on the reposition costs of its components. Instead of considering predefined reposition years for each component and calculate their net present cost from them (as is commonly considered in other works), in this work it was proposed to use lifetime degradation models - based on the well-known statement that the lifetime depends on the hours of operation and the power profiles that the components are subjected to- from which the repositions are made to check how they affect to the cost calculation and, consequently, to the EMS performance. The behavior of the proposed control is checked under a long term simulation, in MATLAB-Simulink environment, whose duration is the expected lifespan of the HS (25 years). A conventional state-machine EMS is used as a case study to validate and compare the results obtained. The results demonstrate that the proposed HS and EMS combination assures reliable electricity support for stand-alone applications subject to different techno-economic criteria (generation cost and sustenance of battery SOC and hydrogen levels), achieving to minimize the operation cost of the system and extend their lifespan. [ABSTRACT FROM AUTHOR]

This paper presents an overview of the state-of-the-art of research on control strategies or energy management systems for DC networks and microgrids. For this purpose, a systematic literature review was performed, which classified the research on the topic and identified the interconnections between the different approaches described in the publications selected. The work reviewed was initially classified into two main categories, based on a set of distinguishing characteristics identified in the control strategies. These categories were the following: (1) active load sharing (which includes the subcategories of centralized control and of master–slave control; (2) droop control methods. A third ad hoc category was also established for the approaches that did not fit in the other two categories. Additionally, secondary topics affecting the control strategies were also analyzed, such as the configuration of DC networks, commonly used control methods and factors, communication system relevance, and finally, the simulation and experimental techniques used for validation. Moreover, this systematic review permitted the identification of current research gaps as well as the proposal of new research lines. The results obtained not only are useful as a guide for researchers, who are starting out in the field, but they also highlight interesting research questions that more experienced researchers can actively pursue. [ABSTRACT FROM AUTHOR]

Nowadays, photovoltaic-assisted charging stations are becoming popular worldwide because its capacity to accommodate more clean energy, reduce carbon emissions, alleviate peak charging loads and provide wider charging infrastructures worldwide. When these infrastructures are operated locally, energy management becomes a challenge due to the large number and heterogeneity of uncertainties involved. This aspect is especially noticeable in the case of charging demand, which is difficult to predict. To address this issue, this paper develops a novel stochastic-interval model for optimal scheduling of multi-mode photovoltaic-assisted charging stations. The developed model uses interval formulation to model uncertainties from photovoltaic generation and energy price, while a comprehensive stochastic model is proposed for charging demand. The developed optimal scheduling model is solved using a developed iterative model, which avoids using interval arithmetic explicitly. This methodology encompasses two Mixed-integer linear programming problems and one Quadratic-programming problem, that can be efficiently addressed by conventional solvers, and allows adopting optimistic or pessimistic strategies. A case study is presented on a benchmark mid-size charging station to validate the developed model. As a sake of example, the system profit grows by 9% and decreases by 3% adopting optimistic and pessimistic point of view, respectively. Likewise, total PV generation increases by 150 kWh/day and reduces by 50 kWh/day. Similar conclusions are extracted for other parameters like monetary balances, PV peak power or satisfied EV demand. • A novel stochastic-interval model for robust scheduling of PVaCSs is developed. • A comprehensive stochastic model for multi-mode EV charging is presented. • A multi-stage solution procedure for the developed model is described. • The new proposal allows to consider optimistic and pessimistic strategies. • A case study validates the developed formulation and modelling. [ABSTRACT FROM AUTHOR]

This paper presents a novel energy dispatching based on Model Predictive Control (MPC) for off-grid photovoltaic (PV)/wind turbine/hydrogen/battery hybrid systems. The renewable energy sources supply energy to the hybrid system and the battery and hydrogen system are used as energy storage devices. The denominated “hydrogen system” is composed of fuel cell, electrolyzer and hydrogen storage tank. The MPC generates the reference powers of the fuel cell and electrolyzer to satisfy different objectives: to track the load power demand and to keep the charge levels of the energy storage devices between their target margins. The modeling of the hybrid system was developed in MATLAB-Simulink, taking into account datasheets of commercially available components. To show the proper operation of the proposed energy dispatching, a simpler strategy based on state control was presented in order to compare and validate the results for long-term simulations of 25 years (expected lifetime of the system) with a sample time of one hour. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents two novel hourly energy supervisory controls (ESC) for improving long-term operation of off-grid hybrid systems (HS) integrating renewable energy sources (wind turbine and photovoltaic solar panels), hydrogen system (fuel cell, hydrogen tank and electrolyzer) and battery. The first ESC tries to improve the power supplied by the HS and the power stored in the battery and/or in the hydrogen tank, whereas the second one tries to minimize the number of needed elements (batteries, fuel cells and electrolyzers) throughout the expected life of the HS (25 years). Moreover, in both ESC, the battery state-of-charge (SOC) and the hydrogen tank level are controlled and maintained between optimum operating margins. Finally, a comparative study between the controls is carried out by models of the commercially available components used in the HS under study in this work. These ESC are also compared with a third ESC, already published by the authors, and based on reducing the utilization costs of the energy storage devices. The comparative study proves the right performance of the ESC and their differences. [Copyright &y& Elsevier]

Abstract: This paper presents a novel hourly energy management system (EMS) for a stand-alone hybrid renewable energy system (HRES). The HRES is composed of a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and two energy storage systems (ESS), which are a hydrogen subsystem and a battery. The WT and PV panels are made to work at maximum power point, whereas the battery and the hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as support and storage system. The EMS uses a fuzzy logic control to satisfy the energy demanded by the load and maintain the state-of-charge (SOC) of the battery and the hydrogen tank level between certain target margins, while trying to optimize the utilization cost and lifetime of the ESS. Commercial available components and an expected life of the HRES of 25 years were considered in this study. Simulation results show that the proposed control meets the objectives established for the EMS of the HRES, and achieves a total cost saving of 13% over other simpler EMS based on control states presented in this paper. [Copyright &y& Elsevier]

• Planning of electrical energy for the Galapagos Islands. • The results show that these islands can achieve 100% renewable penetration. • Study the load forecast for the Baltra-Santa Cruz Island for 2031. • Include a pumped storage hydroelectric (PH) system, more competitive than the batteries for the baltra-santa cruz electricity supply, and supplies turbine water to the desalination plant. • An optimized PV/WT/PH/DG/BAT hybrid system that supplies the electricity demand and energy consumption for drinking water supply for the Baltra-Santa Cruz islands in 2031. • The COE of the hybrid system of Baltra-Santa Cruz is reduced from 0.32 to 0.23 $/kWh. The present study focuses on the planning of electrical energy for the Galapagos islands using different renewable energy technologies for the year 2031 in order to reduce diesel consumption and achieve 100% renewable energy share. To do that, a long-term load demand forecast study on the Santa Cruz and Baltra islands (Galapagos), applying Artificial Neural Networks, is done. Then, to optimize the islands' power system, mostly based on diesel generation, different renewable energy technologies together with energy storage systems, such as batteries and hydraulic pumping, have been analyzed through the application of the HOMER Pro-software. For this purpose, two energy control models have been developed to gradually reduce the operating hours of the diesel power plant. The results show that these islands can achieve 100% renewable penetration with the following configuration: photovoltaic/wind turbines/batteries/pumping hydroelectric storage system/diesel generators (only as back-up). This implies increasing the photovoltaic capacity by 26 MWp and installing a pumped hydraulic storage of 374 MWh. In this way, the electricity generation cost would be reduced from $ 0.32/kWh to $ 0.23/kWh, and the CO 2 emissions would decrease by 16,000 tons of CO 2 into the environment. [Display omitted] [ABSTRACT FROM AUTHOR]