Optimization Of Energy Resources Research Articles

Modeling and optimization of hybrid renewable energy with storage system using flamingo swarm intelligence algorithms

AbstractThis paper unveils the simulation and optimum design of five models based on photovoltaic (PV), diesel generator (DG), and battery energy systems for rural area farmhouse load demand (agriculture and household). The choice for designing an optimal energy system is constructed on minimum technical considerations like loss of load probability (LOLP), economic (cost of electricity [COE] with net present cost [NPC]), environmental (CO2 aspects) using a novel flamingo swarm intelligence algorithm (FSIA). The optimization results are compared by particle swarm intelligence algorithm, improved particle swarm intelligence algorithm, genetic algorithms, and hybrid optimization of multiple energy resources (HOMER‐Pro). FSIA shows PV/DG/battery energy system to be an optimal system as regards NPC (Rs. 8 056 734), COE (12.14 Rs./kWh), CO2 (13 784 kg/y), and LOLP (0.00000501 per year). The saving of the fuel cost and CO2 emission from PV/DG/battery to DG only system is 66.10% and 61.26%, respectively.

A novel approach for optimal energy resources mixing in nuclear-renewable microgrids using probabilistic energy modelling method

Zero-carbon energy infrastructure design has become one of the most consequential pivotal toward sustainable development. This article introduces a novel approach to energy infrastructure innovation that incorporates carbon-free energy generation resources- renewables and Micro Nuclear Reactors (MNRs). The integrated Nuclear-Renewable Microgrid (NRM) has minimal greenhouse gas emissions and the utmost reliability. However, the planning and modeling of NRMs may face challenges due to the variability and uncertainty of renewable resources. Therefore, the study proposes a probabilistic energy modeling approach for NRMs, which provides an outstanding estimation for energy system planning in terms of economics and resiliency. Multiple load-generation scenarios have been formulated based on the probability distribution functions. A recent nature-based optimization technique, Slime Mould Algorithm (SMA), is employed to minimize the total annual cost of the probabilistic model with reliability constraints. The statistical analyses reveal that the probabilistic energy modeling method perfectly evaluates how energy generation resources should be mixed to fulfill energy demand in an optimal manner. The key findings also demonstrate observations on finance, system resiliency, and system components before the commencement of the project. The results are validated by another recent metaheuristic optimization algorithm called Aquila Optimizer (AO).

Energy-Efficient Clustering and Routing Using ASFO and a Cross-Layer-Based Expedient Routing Protocol for Wireless Sensor Networks

Today's critical goals in sensor network research are extending the lifetime of wireless sensor networks (WSNs) and lowering power consumption. A WSN necessitates the use of energy-efficient communication networks. Clustering, storage, communication capacity, high configuration complexity, low communication speed, and limited computation are also some of the energy limitations of WSNs. Moreover, cluster head selection remains problematic for WSN energy minimization. Sensor nodes (SNs) are clustered in this work using the Adaptive Sailfish Optimization (ASFO) algorithm with K-medoids. The primary purpose of research is to optimize the selection of cluster heads through energy stabilization, distance reduction, and latency minimization between nodes. Because of these constraints, achieving optimal energy resource utilization is an essential problem in WSNs. An energy-efficient cross-layer-based expedient routing protocol (E-CERP) is used to determine the shortest route, dynamically minimizing network overhead. The proposed method is used to evaluate the packet delivery ratio (PDR), packet delay, throughput, power consumption, network lifetime, packet loss rate, and error estimation, and the results were superior to existing methods. PDR (100%), packet delay (0.05 s), throughput (0.99 Mbps), power consumption (1.97 mJ), network lifespan (5908 rounds), and PLR (0.5%) for 100 nodes are the performance results for quality-of-service parameters.

Planning and optimization of sustainable grid integrated hybrid energy system in India

The purpose of this study is to conduct the techno-economic-environmental feasibility analysis of a grid-connected hybrid energy systems, making use of locally renewable resources such as solar, wind, and biomass (pine needles). In the absence of a storage unit, five different configurations are investigated. With the use of a newly invented gaining-sharing knowledge optimization method, a mathematical model for optimum size is developed. The Gaining-sharing knowledge algorithm is based on how individuals learn and distribute information throughout their lives. The results of gaining-sharing knowledge-based model is also compared with the standard software tool, Hybrid optimization of multiple energy resources, and the commonly used optimization techniques Genetic algorithm and Biogeography-based optimization to confirm the effectiveness of the proposed approach. The Gaining-sharing knowledge (GSK) based model performance is found best among all. The grid-integrated biomass gasifier/PV amalgam system is determined to be the most economical with an energy production cost of 5.2 ₹/kWh and it saves 87.9% CO2 per annum when compared to a diesel-only system.

A Comparison of Grid-Connected Local Hospital Loads with Typical Backup Systems and Renewable Energy System Based Ad Hoc Microgrids for Enhancing the Resilience of the System

Extreme weather conditions and natural disasters (ND) are the main causes of power outages in the electric grid. It is necessary to strengthen the electrical power system’s resilience during these catastrophic occurrences, and microgrids may be seen as the best way to achieve this goal. In this paper, two different energy system scenarios were proposed for increasing the resiliency of the electric power system during random outages. In the first scenario, a diesel generator (DG) was used to deliver energy to key loads during grid disruptions, in conjunction with a utility electric grid (UEG) and local electric load (ELL). A grid-connected ad hoc microgrid (MG) with a photovoltaic (PV) system, a battery energy storage (BES) system, and local electric loads made up the second scenario. The PV system and the BES system were used to supply the key loads with electricity during the outage. The major aim of this research was to compare the two resilient-based systems from the perspectives of technology, economics, and the environment. Given that it requires greater resilience than the other loads during severe weather, a hospital load on Indonesia’s Lombok Island was chosen as the critical load. The objective function considers the system’s predefined constraints to reduce the overall net present cost (NPC) and the cost of energy in order to maximize the system resilience (COE). The Optimization of Multiple Energy Resources (HOMER) Grid simulated a 3-day outage in August 2021, and the results demonstrated that the resiliency enhancement for both scenarios was nearly identical. The first scenario resulted in fewer CO2 emissions; however, the second scenario delivered lower operating costs and COE. The simulation’s findings showed that system 1 created an annual emission of 216.902 kg/yr while system 2 only produced an emission of 63.292 kg/yr. This study shows that since RES-based MGs don’t burn fossil fuels to generate power, they are more environmentally friendly resources.

Sizing Design for a Hybrid Renewable Power System Using HOMER and iHOGA Simulators

In this study, a comparative sizing design for renewable power systems was developed based on HOMER (Hybrid Optimization of Multiple Energy Resources) and iHOGA (improved Hybrid Optimization by Genetic Algorithms) simulators. A comparative analysis of the solutions obtained with iHOGA and HOMER simulators for the same hybrid renewable power system (HRPS) is presented in detail. The system contained a new hybrid configuration that used fuel cell (FC) as a green energy source, replacing the polluting diesel generator system, as well as other renewable energy sources, namely, photovoltaic panels, wind turbine, a battery stack, power converters, and electric load. The same case study was carried out for the design of the hybrid system using HOMER and iHOGA simulators to perform a comparative analysis of the solutions obtained for potential investment. The analysis showed a higher share of renewable energy for iHOGA (92%) compared to HOMER (81%), so the first design produced 51.61 kg/year less carbon dioxide. Moreover, the operating costs (2134 RON/year for HOMER and 70.56 RON/year for iHOGA) and the cost of electricity were higher by 96% and 2.5%, respectively, for HOMER compared to iHOGA. Taking into account the need for high reliability, safe operation, and lower operation/exploitation costs, the design implemented in iHOGA is clearly more efficient and useful in practice, and this is supported by the three iHOGA case studies.

Techno-economic comparative study of grid-connected PV/reformer/FC hybrid systems with distinct solar tracking systems

The purpose of this study is to analyze and compare the techno-economic performance of grid-connected Hybrid Energy Systems (HES) consisting of Photovoltaic (PV) and Reformer Fuel-Cell (RF-FC) using different types of solar PV tracking techniques to supply electricity to a small location in the City of Chlef, Algeria. The PV tracking systems considered in this study include fixed facing south at four different angles (32°, 34°, 36°, 38°), horizontal-axis with continuous adjustment, vertical-axis with continuous adjustment and a two-axis tracking system. The software tool HOMER Pro (Hybrid Optimization of Multiple Energy Resources) is used to simulate and analyze the technical feasibility and life-cycle cost of these different configurations. The meteorological data, consisting of global solar radiation and air temperature, used in this study was collected from the geographical area of the City of Chlef during the year 2020. This study has shown that the optimal design of a grid-connected hybrid PV/RF-FC energy system with Vertical Single Axis Tracker (VSAT) leads to the best economic performance with low values of Net Present Cost (NPC), Cost of Energy (COE) with a Positive Return on Investment (ROI) and the shortest Simple Payback (SP) period. In addition, from the simulation results obtained, it can be concluded that the Horizontal and Vertical Single-Axis Trackers (HSAT and VSAT) as well as the Dual-Axis Tracker (DAT) are not always cost effective compared to the Fixed Tilt System (FTS). Therefore, it is necessary to carefully analyze the use of each tracker to assess whether the energy gain achieved outweighs the overall shortcomings of the tracker.

A Novel Stochastic Optimizer Solving Optimal Reactive Power Dispatch Problem Considering Renewable Energy Resources

Optimal Reactive Power Dispatch (ORPD is thought of as a noncontinuous, nonlinear global optimization problem. Within the system’s constraints, the ORPD manages to accomplish the reactive power flow. Due to its more intricate linkage of variables, the reactive power issue is more challenging to resolve than the optimum power flow issue. With the existence of renewable energy resources (RERs), solving the ORPD problem to attain the most stable and secure system condition has become a more challenging task. The goal of this article is to solve the objective function of ORPD combined with RERs using a metaheuristic novel optimizer named the African Vultures Optimization Algorithm abbreviated by (AVOA), where the formulation of the ORPD issue including minimization of three single objective functions as follows, voltage deviation, system operating cost, and real power loss, is introduced and also transmission power loss minimization is embraced with the simultaneous incorporation of the optimal renewable energy resources (RERs). Where the ORPD problem complexity grows exponentially with a mixture of continuous and discrete control variables, two distinct continuous and discrete types of optimization variables are considered, and the proposed single objective functions that meet different operating constraints are then transformed into a coefficient multi-objective ORPD problem and elucidated using the weighted sum approach. To validate the suggested algorithm’s effectiveness in addressing the ORPD issue, it is evaluated on three standard IEEE networks: the IEEE-30 bus small-scale network, the IEEE-57 bus medium-scale network, and the IEEE-118 bus large-scale network using different scenarios and the outcomes are compared to these other popular optimization techniques. The findings show that the suggested AVOA algorithm provides an efficient and sturdy high-quality solution for tackling ORPD situations and vastly enhances the overall system performance of power at all scales.

Integrated innovative solar lighting system for optimization of daylight utilization for public library in Alexandria, Egypt

Lighting has evolved over recent decades from an engineering perspective, in which ensuring safety and performance both indoors and outdoors has become a key discipline, engaged in a wide range of areas and having a profound impact on our daily lives. In this paper, a case study of a modern public library building will be addressed, with the main purpose of discussing energy efficiency related to light. Three parallel routes will be demonstrated to improve energy efficiency. The first is the integration of solar systems (PV) and the replacement of artificial lighting systems. The second is a change of building materials, internally and externally, to nanomaterials, and the third is through including an innovative anidolic lighting system, designed and applied in order to enhance the amount of daylight inside the library in a controlled manner. The inclusion of a vertical lighting system allows the optimization of solar energy resources, preserving the library’s style in a simple way. The system includes a collector light system, compounded by a truncated and double compound parabolic collector (PCPC) to capture natural light from outside over a wide angular range (180°) without a tracking system, preserving the building design and saving on costs and maintenance. These parallel routes, based on solar energy and lighting, can make a positive impact with minimum changes in the Alexandria library, providing environmental improvement and protecting buildings and human health in order to achieve a more sustainable example of architecture.

Analysis of grid/solar photovoltaic power generation for improved village energy supply: A case of Ikose in Oyo State Nigeria

Energy crisis is one of the major challenges confronting African countries. Nigeria is one of the countries having a high energy deficit in Africa with rural areas being at the receiving end. Hence, people in several locations of the country depend largely on fossil fuels for their energy generation due to the energy supply problem being experienced in the country. Fossil fuel-based energy generation is highly environmentally-unfriendly hence, the use of renewable energy system is adopted as a viable alternative to solve the energy crisis. This work first reviews the energy status in rural Nigeria to describe the situation and the available energy resources. Three different energy scenarios – Grid only, PV only and the PV-Grid configurations were designed and simulated using the Hybrid Optimization of Multiple Energy Resources (HOMER) tool for a village in Oyo state, Nigeria. The design of the energy systems is based on technical and economic analyses, which provide the opportunity to compare the performances of the different scenarios. The study uses the monthly grid purchase (MGP), excess electrical production (EEP), and unmet electric load (UEL), net present cost (NPC), Levelized cost of energy (LCOE), annual operating cost (OC) and the salvage value (SV) for the comparison. The simulation results demonstrated that the PV-Grid system is best option for the village with the highest MGP, EEP, and UEL of about 34, 24, and 0.7 kW, respectively. The corresponding economic implications for the PV-grid configuration are NPC, LCOE, OC, and SV values of 73388.77, 0.1904, 1957.64, and 2,173.55 USD. The sensitivity analysis result revealed that the grid only and PV-grid are not as affected by a change in temperature compared to the PV only whose energy production, and EEP values decrease with an increase in temperature and the UEL parameter increases with an increase in the surrounding temperature.

Feasibility and optimal sizing analysis of hybrid renewable energy systems: A case study of Al-Karak, Jordan

The aim of this research is to examine the techno-economic viability of both off-grid and on-grid hybrid renewable energy systems for Jordan's Al-Karak governorate. Hybrid Optimization of Multiple Energy Resources (HOMER) Pro software was used in this article to evaluate the carry feasibility to maximize the renewable energy (RE) integration in hybrid energy systems based on different configurations, grid-connected and stand-alone systems of the wind turbine, biogas plant, photovoltaic (PV) panels, flywheel, and batteries while minimizing the net present cost, the Levelized cost of energy and CO2 emissions mitigation. The results showed that the PV/Wind system, connected to the grid with batteries for storage is the optimal configuration for sustainable Al-Karak governorate electrification whilst achieving environmental benefits and guaranteeing reliable and continuous energy access with the lowest net present cost and the Levelized cost, 298,359 USD$ and 0.024 USD$/kWh respectively, and high RE share, 71.8% of electricity is generated from wind and 28.2% is purchased from the grid and emits 220 tons of CO2 per year, 53% less than a grid alone system. Such a system would provide advantages in terms of energy independence and improved environmental quality.

IoT solutions for smart farming: A comprehensive review on the current trends, challenges and future prospects for sustainable agricultureIoT solutions for smart farming: A comprehensive review on the current trends, challenges and future prospects for sustainable agriculture

Agriculture is the most resource-intensive human activity. The goal to reduce agricultural input while producing more has been a primary driver of agricultural technology advancement since its inception. With recent advancements in supporting technologies, the usage of Internet-of-things (IoT) has become a trend in farming practice for agriculture management that use information technology to ensure that soil and plants receive their requirements for optimum health and productivity. It could be significant to summarize the trends and challenges of the application of IoT-based solutions in precision agriculture, more specifically smart crop production. Thus, the current review sought to give a complete overview of the use of IoT technology in smart farming. By surveying recent high-quality publications, IoT-based solutions applied to smart farming, with four basic layers, including data collection (perception), data transmission (transport), data processing, and application layers were summarized. The use of IoT solutions allows for resolving several issues in smart farming, such as the optimization of input resources, saving irrigation water, reducing the amount of fertilizer and pesticides, and optimizing energy resources. Accordingly, we discussed some notes about sensors, microcontroller systems, communication methods, and cloud platforms. In particular, a list of low-cost sensors and several typical single-board computers was provided. The IoT communication was discussed to get insight into the essential considerations. Since then, several key points have been noted for further directions of the application of IoT-based solutions for smart farming. Taken together, our mini-review could provide solid information for further construction and development of smart models of farming.

Analyzing of hydel, wind and fuel cell hybrid system for rural electrification with reduced cost of energy

In this work, a Hybrid Renewable Energy System (HRES) is proposed to electrify remote areas. Hydroelectric and wind energy potential are exploited, and they could be converted into chemical energy and stored in hydrogen fuel cells. By this technique, carbon emissions is substantially reduced and helps to control climate change and global warming. In this proposed work, surplus amount of electrical power is diverted to the production of hydrogen through electrolysis, the stored hydrogen can be used as a energy reserve which could be utilized based on requirement. The hydrogen fuel cell acts as a backup to the grid. A simulation study was carried out using Hybrid Optimization of Multiple Energy Resources (HOMER) software. The simulation study reveals that the Cost of Energy has been significantly reduced.

Hybrid solar, wind, and energy storage system for a sustainable campus: A simulation study

The reliance on grid electricity generated from fossil fuels in many countries continues to contribute to annual CO2 emissions. Implementing renewable energy systems helps reduce the carbon footprint and enhances local grid stability, particularly in areas with high demand where power outages are frequent. This study used the Hybrid Optimization of Multiple Energy Resources (HOMER) software to determine the most cost-effective composition of a Hybrid Renewable Energy System (HRES). Simulation results indicate that a system comprising a 3007 PV array, two 1.5 MW wind turbines, and a 1927 kW converter is most suitable. Combining solar panels and wind turbines remains the most economically feasible option for on-site electricity production. The study demonstrates that installing a hybrid renewable energy system is viable on an academic campus, with an initial investment cost of US $6.58 million and yearly operational costs of US $1.38 million, which is 40.8% lower than the current system. The project payback time is estimated to be 10.11 years. These findings may be used to recommend similar systems in other regions with comparable climatic conditions. The positive monetary effects may incentivize policymakers to implement comparable systems, contributing to a carbon-neutral goal.

Future trends in organic flour milling: the role of AI

<abstract> <p>The milling of wheat flour is a process that has existed since ancient times. In the course of history, the techniques have improved, the equipment modernized. The interest of the miller in charge of the mill is still to ensure that a mill is functional and profitable, as well as to provide a consistent quality of flour. The production of organic flour means that methods of adding chemicals and unnatural agents are not possible. In organic flour production, it is necessary to work with the raw material. A grain of wheat is a living material, and its quality varies according to a multitude of factors. Challenges are therefore present at each stage of the value chain. The use of artificial intelligence techniques offers solutions and new perspectives to meet the different objectives of the miller. A literature review of artificial intelligence techniques developed at each stage of the value chain surrounding the issues of quality and yield is conducted. An analysis of a large number of variables, including process factors, process parameters and wheat grain quality from data collected on the value chain enables the development and training of artificial intelligence models. From these models, it is possible to develop decision support tools and optimize the wheat flour milling process. Several major research directions, other than constant quality, are to be studied to optimize the process and move towards a smart mill. This includes energy savings, resource optimization and mill performance.</p> </abstract>

Techno-economic assessment of hydrogen production from seawater

Population growth and the expansion of industries have increased energy demand and the use of fossil fuels as an energy source, resulting in release of greenhouse gases (GHG) and increased air pollution. Countries are therefore looking for alternatives to fossil fuels for energy generation. Using hydrogen as an energy carrier is one of the most promising alternatives to replace fossil fuels in electricity generation. It is therefore essential to know how hydrogen is produced. Hydrogen can be produced by splitting the water molecules in an electrolyser, using the abondand water resources, which are covering around ⅔ of the Earth's surface. Electrolysers, however, require high-quality water, with conductivity in the range of 0.1–1 μS/cm. In January 2018, there were 184 offshore oil and gas rigs in the North Sea which may be excellent sites for hydrogen production from seawater. The hydrogen production process reported in this paper is based on a proton exchange membrane (PEM) electrolyser with an input flow rate of 300 L/h. A financially optimal system for producing demineralized water from seawater, with conductivity in the range of 0.1–1 μS/cm as the input for electrolyser, by WAVE (Water Application Value Engine) design software was studied. The costs of producing hydrogen using the optimised system was calculated to be US$3.51/kg H2. The best option for low-cost power generation, using renewable resources such as photovoltaic (PV) devices, wind turbines, as well as electricity from the grid was assessed, considering the location of the case considered. All calculations were based on assumption of existing cable from the grid to the offshore, meaning that the cost of cables and distribution infrastructure were not considered. Models were created using HOMER Pro (Hybrid Optimisation of Multiple Energy Resources) software to optimise the microgrids and the distributed energy resources, under the assumption of a nominal discount rate, inflation rate, project lifetime, and CO2 tax in Norway. Eight different scenarios were examined using HOMER Pro, and the main findings being as follows:The cost of producing water with quality required by the electrolyser is low, compared with the cost of electricity for operation of the electrolyser, and therefore has little effect on the total cost of hydrogen production (less than 1%).The optimal solution was shown to be electricity from the grid, which has the lowest levelised cost of energy (LCOE) of the options considered. The hydrogen production cost using electricity from the grid was about US$ 5/kg H2.Grid based electricity resulted in the lowest hydrogen production cost, even when costs for CO2 emissions in Norway, that will start to apply in 2025 was considered, being approximately US$7.7/kg H2.From economical point of view, wind energy was found to be a more economical than solar.

Techno-Economic and Environmental Analysis of Renewable Mix Hybrid Energy System for Sustainable Electrification of Al-Dhafrat Rural Area in Oman

Affordable and clean energy for any rural community is crucial for the sustainable development of the community and the nation at large. The utilization of diesel-based power generation is one of the barriers to the sustainable development of these communities. Such generations require fuel that has a volatile market price and emits massive greenhouse gas emissions. This paper presents the design, modeling, and simulation of a hybrid power system for a rural area in the Sultanate of Oman that aims to reduce daily consumption of diesel fuel and greenhouse gas emissions. Hybrid Optimization of Multiple Energy Resources (HOMER) is utilized to model multiple energy mix hybrid systems and to propose the best optimal energy mix system for a selected community. In addition, Electrical Transient Analyzer Program (ETAP) software is employed to assess hybrid system operational performances, such as bus voltage profiles and active and reactive power losses. This study revealed that the PV–wind–diesel system is the optimal energy mix hybrid microgrid for the Al-Dhafrat rural area in Oman, with a net present cost of USD 14.09 million. Compared to the currently operating diesel-based system, the deployment of this microgrid can reduce the levelized cost of energy, diesel fuel consumption, and greenhouse gas emissions per year by 54.56%, 70.44%, and 70.40%, respectively. This study confirms that the Sultanate of Oman has a substantial opportunity to install a hybrid microgrid system for rural diesel-based communities to achieve sustainable development in the country.

Challenges of reaching high renewable fractions in hybrid renewable energy systems

This study evaluates the techno-economic feasibility of hybrid renewable energy systems (HRES) for providing electricity in four example localities in the United States: western New York; San Diego, California; Milwaukee, WI; and the entire state of Texas. The Hybrid Optimization of Multiple Energy Resources (HOMER) Pro Microgrid Tool was used to simulate and assess a grid model relying on solar and wind electric generation with utility-scale battery storage as back-up to serve the load on an hourly basis, when renewable resources are not available. A total of 495 HOMER trials were modeled to determine the levelized cost of electricity (LCOE) and societal cost of electricity (SCOE) for each of these locations assuming varying levels of carbon taxes, the economic value of health benefits from emissions savings, and a renewable fraction (RF) ranging from 0% to 100%. Technical and financial properties for the model, such as individual component cost, life-time, and efficiency, were obtained from the U.S. Energy Information Administration (EIA). Emission rates for various generation sources were obtained from the U.S. Environmental Protection Agency (EPA) and health benefits were analyzed using the Co-Benefit Risk Assessment (COBRA) tool. Finally, the ideal renewable fraction resulting in the lowest LCOEs were obtained for each of the four locations studied. For carbon tax values of $0/tonne and $130/tonne, this was determined to be 34% to 48% for New York; 0% to 34% for San Diego; 55% to 75% for Milwaukee; and 21% to 65% for Texas. Applying health benefits can shift the optimal RF of HRESs to higher amounts by 5.26% on average.

Economic Feasibility of a Renewable Integrated Hybrid Power Generation System for a Rural Village of Ladakh

This paper mainly dealt with the technical and economic feasibility of an off-grid hybrid power generation system for a remote rural Turtuk village of Ladakh, located in the northern part of India. The study showed that the proposed configured renewable integrated hybrid system, using Hybrid Optimization of Multiple Energy Resources (HOMER) software, efficiently met the energy demand, exhibiting optimum performance with low investment. The proposed PV(115 kW)/Wind(1 kW)/Battery(164 strings of 6 V each)/DG(50 kW) hybrid system was a highly commendable, feasible solution preferred from a total of 133,156 available solutions resulting from HOMER simulations. The net present cost and energy cost of the proposed configuration were $278,176 and $0.29/kWh, respectively. The proposed hybrid configuration fulfilled local load, with 95.97% reduced dominant harmful carbon dioxide emission, as compared to the sole us of a diesel generator power supply system. The technical performance of the hybrid system was ensured, with advantages including the highest renewable penetration and least unmet load. Furthermore, the analysis exclusively evaluated the impact of the system’s economic parameters (namely, its expected inflation rate, nominal discount rate, and project lifetime) on the net present cost and cost of energy of the system using a noble single fix duo vary approach.

Flexible Loads Scheduling Algorithms for Renewable Energy Communities

Renewable Energy Communities (RECs) are emerging as an effective concept and model to empower the active participation of citizens in the energy transition, not only as energy consumers but also as promoters of environmentally friendly energy generation solutions, particularly through the use of photovoltaic panels. This paper aims to contribute to the management and optimization of individual and community Distributed Energy Resources (DER). The solution follows a price and source-based REC management program, in which consumers’ day-ahead flexible loads (Flex Offers) are shifted according to electricity generation availability, prices, and personal preferences, to balance the grid and incentivize user participation. The heuristic approach used in the proposed algorithms allows for the optimization of energy resources in a distributed edge-and-fog approach with a low computational overhead. The simulations performed using real-world energy consumption and flexibility data of a REC with 50 dwellings show an average cost reduction, taking into consideration all the seasons of the year, of 6.5%, with a peak of 12.2% reduction in the summer, and an average increase of 32.6% in individual self-consumption. In addition, the case study demonstrates promising results regarding grid load balancing and the introduction of intra-community energy trading.