Value Of Energy Cost Research Articles

Modified Harris Hawks optimization for the 3E feasibility assessment of a hybrid renewable energy system

The off-grid Hybrid Renewable Energy Systems (HRES) demonstrate great potential to be sustainable and economically feasible options to meet the growing energy needs and counter the depletion of conventional energy sources. Therefore, it is crucial to optimize the size of HRES components to assess system cost and dependability. This paper presents the optimal sizing of HRES to provide a very cost-effective and efficient solution for supplying power to a rural region. This study develops a PV-Wind-Battery-DG system with an objective of 3E analysis which includes Energy, Economic, and Environmental CO2 emissions. Indispensable parameters like technical parameters (Loss of Power Supply Probability, Renewable factor, PV fraction, and Wind fraction) and social factor (Human Developing Index) are evaluated to show the proposed modified Harris Hawks Optimization (mHHO) algorithm’s merits over the existing algorithms. To achieve the objectives, the proposed mHHO algorithm uses nine distinct operators to obtain simultaneous optimization. Furthermore, the performance of mHHO is evaluated by using the CEC 2019 test suite and the most optimal mHHO is chosen for sizing and 3E analysis of HRES. The findings demonstrate that the mHHO has achieved optimized values for Cost of Energy (COE), Net Present Cost (NPC), and Annualized System Cost (ASC) with the lowest values being 0.14130 $/kWh, 1,649,900$, and 1,16,090$/year respectively. The reduction in COE value using the proposed mHHO approach is 0.49% in comparison with most of the other MH-algorithms. Additionally, the system primarily relies on renewable sources, with diesel usage accounting for only 0.03% of power generation. Overall, this study effectively addresses the challenge of performing a 3E analysis with mHHO algorithm which exhibits excellent convergence and is capable of producing high-quality outcomes in the design of HRES. The mHHO algorithm attains optimal economic efficiency while simultaneously minimizing the impact on the environment and maintaining a high human development index.

Investment analysis of solar power plant installation on the roof of the central business district office building with the best investment value

The Central Business District (CBD) office building is making efforts to reduce building electricity costs, and one alternative is solar power plant installation. PT. Rancang Prima Sejahtera, engaged in the solar energy industry, conducts consulting services with Central Business District office buildings, so PT. Rancang Prima Sejahtera made an indicative proposal with several solar power plant installation scenarios to be installed on the roof of the Central Business District office building. Four scenarios are created from the combination of 2 PV modules and two inverters. Each scenario created will be assessed for the level of opt, and the investment value will be calculated. In combining components using the principles of the Vereun Deutsche Ingineuer (VDI) 2222 method and assessed each scenario using six aspects of assessment.Meanwhile, the investment analysis assessment uses the parameters of Cost of Energy (CoE), Net Present Value (NPV), Internal Rate of Return (IRR), Benefit-Cost Ratio (B-CR), and discounted payback period. The results of the analysis conducted found that the third scenario was the best scenario with a percentage of the design value of 82.5%, CoE value of Rp398.31/kWh, NPV value of Rp2,451,719,005, IRR percentage of 23.75%, B-CR value of 7.8, and DPP value for 6.8 years with a project life of 30 years. The findings of the investment research indicate that the implementation of solar power plant installations in office buildings located in Central Business Districts yields long-term cost reductions in electricity expenses over a 30-year period, as opposed to relying solely on the services provided by the State Electricity Enterprise.

An effective aeration system for high performance pond aeration at low energy cost

With the effective use of aerators with low energy cost and high aeration performance, aquaculture areas can be developed and supported. The main objective of this study is to determine the optimal physical parameters of high aeration capacity high head conduits and to ensure low energy costs, thus to present a comprehensive review of its usability for pond aeration. In this study, a high-head gated conduit was used as the aeration unit. After obtaining the design that will maximize the aeration performance of the high-head gated conduit, a prototype model was developed to ensure its effective use in pond aeration. The parameters affecting the performance of this developed aeration system and the corresponding energy cost values were determined. According to the results, the most important parameters affecting the aeration performance are, respectively, flow rate, the opening of the gate, hydrostatic level, and jet plunge angle. In the optimal design, more than three times the unit volume of water circulating in the system is added to the system. The cost value of this operation in terms of energy was measured as 0.10 kWh/m3 air. The developed system was found to have significantly higher energy efficiency values compared to alternatives, based on specific energy consumption data.

Application of hybrid renewable energy systems for supplying electricity demand of a water pump station of agricultural plants: a case-based research

Abstract Employing clean energy production in agricultural purposes has attracted the attention of many researchers. One of the challenges is the flexible nature of irrigation of the plants that need to have a changeable power source of pump stations to supply the load demands. Renewable energies are among the best solutions to supply environmentally-friendly power, especially in remote areas where there is no access to the electricity. This study considers the needed water of five different plants, and according to the calculated hydromodule, the capacity of the pump station as well as its monthly and yearly load demands are determined. Based on the calculated load demand, different configurations of hybrid renewable energy systems (HRES) are considered, and the optimum sizes of equipment are determined. The needed load demand is 1463 kWh/day and peak load is 266.16 kW. Based on the suppositions and inputs of this study, results show that the best economic configuration would be PV/wind turbine/diesel generator/battery the way that cost of energy (COE) and net present cost (NPC are 0.28 ($/kWh) and $2.48 million. Also, the best environmentally friendly system (PV/wind turbine/battery) where CO2 emission is zero and RF is 100%, can be obtained with 647 kW PV panels and 106 wind turbines, the way that COE and NPC values are 0.5 ($/kWh) and 4.41 $ million. To reach the best technical system (PV/generator/battery), 514 kW PV, 100 kW diesel generator, and 1816 batteries would have the least unmeted load and excess electricity where COE and NPC values are 0.34 ($/kWh) and 2.98$ million.

Quantitative techno-economic comparison of a photovoltaic/wind hybrid power system with different energy storage technologies for electrification of three remote areas in Cameroon using Cuckoo search algorithm

This research work presents a techno-economic comparisons and optimal design of a photovoltaic/wind hybrid systems with different energy storage technologies for rural electrification of three different locations in Cameroon. The determination of the optimal, cost-effective, and reliable configuration is performed for the locations of Fotokol, Figuil and Idabato which describe the weather conditions diversity in Cameroon with different solar and wind energy potentials. The sizing-optimisation problem is founded on real data of wind speed and solar radiation, with the principal goal of minimizing the hybrid system net present cost (NPC) while taking into consideration the load deficit probability (LDP) as the reliability constraint. The cuckoo search algorithm with a high convergence rate is utilised to find the optimal combination of the hybrid system with the lowest cost of energy (COE) and NPC which satisfies the LDP of the considered locations. At each location, six different configurations namely photovoltaic/wind/battery, photovoltaic/battery, wind/battery, photovoltaic/wind/fuel-cell, photovoltaic/fuel-cell and wind/fuel-cell are optimised and compared in view of satisfying the heavy, medium and small activities electrical loads demand of non-domestic subscribers. The optimal configuration is obtained for each activity and location in connection with the minimum cost and best reliability. The results revealed that the optimal, cost-effective, and reliable configuration for all activities and locations is a battery-based photovoltaic/wind hybrid system. The results showed that integration of 20 photovoltaic arrays, 1 wind turbine and 27 batteries with LDP value of 0.0486 is the most appropriate configuration which leads to the lowest NPC and COE of 23,024$ and 0.1570 $/kWh, respectively for satisfying the heavy activity load demand at Fotokol. The best hybrid system configuration needed for covering loads demand for medium and small activities at Fotokol were found to be 8 photovoltaic arrays, 1 wind turbine and 19 batteries with LDP, NPC and COE values of 0.0497, 16,640$ and 0.1942 $/kWh, respectively for medium activity; and 5 photovoltaic arrays, 1 wind turbine and 10 batteries with NPC, COE and LDP values of 12,860$, 0.2120 $/kWh and 0.0494, respectively for small activity. The optimisations studies performed at the site of Figuil considering the heavy activity load demand revealed that the cost-effective configuration which leads to the minimum NPC and COE of 28,400$ and 0.1937 $/kWh, respectively consists of 26 photovoltaic panels, 1 wind turbine and 38 batteries with the LDP equal to 0.0499. The obtained results also indicated that substituting the battery banks with a chemical storage which consist of a combination of an electrolyser, hydrogen reservoir and fuel cell is possible, though the cost increases because of the important investment cost of the system constituents. Integrating photovoltaic/wind/fuel-cell at the site of Idabato gives the lowest NPC and COE values of 48,864$ and 0.8056 $/kWh, respectively with a LDP of 0.0491. The optimum sizing of this configuration has 9 photovoltaic arrays, 1 wind turbine and 15 hydrogen tanks.

Analysis of Power Generation and Distribution of Hybrid Energy for Electricity Loads in Batakan Village

The need for electrical energy continues to increase over time. However, in Indonesia power plants are still dominated by fossil fuel power plants, and there are still many areas without access to electricity. The use of renewable energy is needed to replace fossil fuels considering that fossil fuels can run out one day. The coastal area of Batakan Village in Tanah Laut Regency, South Kalimantan Province, was chosen as the focus location for conducting hybrid power plant simulations because this village is located in a coastal area where wind and solar energy sources are abundant. Batakan Village is approximately 40 km from Pelaihari City. Medium-voltage network transmission system (JTM) is supplied from Pelaihari City, and it is almost certain that this village experiences large power losses over long distance. This power loss will be detrimental if an effort is not made to reduce it. The purpose of this research is first to determine the optimal hybrid power plant configuration design to reduce power loss in the electricity system in Batakan Village. Second, it will analyze the power loss of the hybrid power plant system in Batakan Village, and finally, this research is going to analyze the investment feasibility of the hybrid power plant system in Batakan Village. In this study, the design of renewable energy plants, such as solar power plants (PLTS) with a total capacity of 406.1 kW and wind power plants (PLTB) with a total capacity of 125 kW, and the electricity network (grid system) are used together in a hybrid power generation system. The ETAP software was used to analyze the power losses of the hybrid power generation system, while the HOMER software was used to determine the net present value (NPV) and cost of energy (COE) of the hybrid power generation system. The results show that the configuration of the solar, wind, and grid systems is the most optimal. It is obtained from the results of ETAP simulations that have been carried out during average load and peak load conditions that by including the Solar Power Plant and Wind Power Plant power losses in the electricity system in Batakan Village can be reduced from the previous one using the system configuration only connected to the PLN power grid (grid system only). The total power losses incurred was 269.1 kW of active power and 1613.5 kvar of reactive power at average load reduced to 266.9 kW of active power and 1568.9 kvar of reactive power. At peak load the total power losses were 423.4 kW of active power and 2573.0 kvar of reactive power and they deceased to 41.,5 kW of active power and 2510.5 kvar of reactive power. In terms of investment, the COE value decreased by IDR 111, and the NPC decreased by IDR 6,600,000,000 at the average load. At the peak load COE decreased by IDR 88, while NPC by IDR 7,000,000,000. The return of investment (ROI) value is 13.2%, which indicates that the investment is still in the profitable stage.

Techno‐economic analysis of PV–wind–diesel–battery hybrid power systems for industrial towns under different climates in Spain

AbstractThis study aimed to provide a techno‐economic analysis of hybrid energy systems, including wind turbines, photovoltaic systems (PV) panels, diesel generators, and batteries, for selected cities in five different climate zones in Spain to meet the load requirements of industrial towns. Homer software was used to determine the most efficient configuration for supplying the average load of the industrial sector, with a value of 1500 kWh/day and a peak load of 114.58 kW, and the residential sector, with a value of 150 kWh/day and a peak load of 27.85 kW. Optimization is carried out to minimize the evaluation parameters of net present cost (NPC) and cost of energy (COE). According to the software outputs, it appears that the system utilizes a variety of renewable energies. The priority is to use all hybrid system components, and the wind–PV–diesel–battery configuration has performed best in all cities. The cities of A Coruña, Bilbao, Ponferrada, Almería, Barcelona, Salamanca, Seville, Zaragoza, and Madrid, respectively, with NPC values of 1.39, 1.67, 1.76, 1.92, 2.23, 2.29, 2.39, 2.55, 2.61 M$ and COE values of 0.199, 0.24, 0.252, 0.276, 0.32, 0.329, 0.343, 0.366, 0.374 $/kWh have economic efficiency from the highest to the lowest. Reducing pollution production is one of the key reasons for approaching hybrid technologies. In this regard, A Coruña has the lowest carbon emissions among the selected cities, with 25,190, and 95.5% of its energy production is renewable. On the other hand, Madrid, which uses 89% renewable energy, has the highest carbon dioxide production with a value of 59,242. The system analysis in different cities of Spain provides insight into the conditions necessary for establishing such systems in different climate zones, which can serve as a road map for other places in the country.

Energy cost differences between marathon runners and soccer players: Constant versus shuttle running.

Purpose: In the last decades, the energy cost assessment provided new insight on shuttle or constant running as training modalities. No study, though, quantified the benefit of constant/shuttle running in soccer-players and runners. Therefore, the aim of this study was to clarify if marathon runners and soccer players present specific energy cost values related to their training experience performing constant and shuttle running. Methods: To this aim, eight runners (age 34 ± 7.30y; training experience 5.70 ± 0.84y) and eight soccer-players (age 18.38 ± 0.52y; training experience 5.75 ± 1.84y) were assessed randomly for 6' on shuttle-running or constant-running with 3days of recovery in-between. For each condition, the blood lactate (BL) and the energy cost of constant (Cr) and shuttle running (CSh) was determined. To assess differences for metabolic demand in terms of Cr, CSh and BL over the two running conditions on the two groups a MANOVA was used. Results: O2max were 67.9 ± 4.5 and 56.8 ± 4.3ml·min-1kg-1 (p = 0.0002) for marathon runners and soccer players, respectively. On constant running, the runners had a lower Cr compared to soccer players (3.86 ± 0.16Jkg-1m-1 vs. 4.19 ± 0.26Jkg-1m-1; F = 9.759, respectively; p = 0.007). On shuttle running, runners had a higher CSh compared to soccer players (8.66 ± 0.60Jkg-1m-1 vs. 7.86 ± 0.51Jkg-1m-1; F = 8.282, respectively; with p = 0.012). BL on constant running was lower in runners compared to soccer players (1.06 ± 0.07mmolL-1 vs. 1.56 ± 0.42mmolL-1, respectively; with p = 0.005). Conversely, BL on shuttle running was higher in runners compared to soccer players 7.99 ± 1.49mmolL-1 vs. 6.04 ± 1.69mmolL-1, respectively; with p = 0.028). Conclusion: The energy cost optimization on constant or shuttle running is strictly related to the sport practiced.

Renewable based techno-economic analysis for telecommunication system: A case study of western Himalaya

This research article presents a technoeconomic analysis of an RET-based model for powering a hilly remote area telecom tower in Chamba district of Himachal Pradesh, India. Using the HOMER software tool with various evolutionary algorithms, the study found that the most feasible configuration was 30 kW of SP panels, 10 kW of DG units, 20 batteries, and 10 units of converter with a minimum energy cost value of 0.256 $/kWh. The energy cost values from various evolutionary techniques such as HHO, WOA, PSO, and GA were also observed to be competitive. After policy intervention and government subsidies, the cost of energy reduced to 0.167 $/kWh, which is significantly less compared to the diesel-powered system. Furthermore, sensitivity analysis was carried out for changes in solar radiations, ambient temperature, and diesel fuel prices to determine the best optimal configuration for the study.

Techno-Economic and Environmental Study of Optimum Hybrid Renewable Systems, including PV/Wind/Gen/Battery, with Various Components to Find the Best Renewable Combination for Ponorogo Regency, East Java, Indonesia

Nowadays, hybrid renewable systems can be the best solution for meeting electricity demand, especially where grid extension and environmental issues are important. This study aimed to find the best combination of the typical components used in East Java, Indonesia. In this regard, four types of photovoltaic (PV) panels, four types of wind turbines, and two types of batteries were selected, and the HOMER software simulated all possible combinations of the systems, including 32 scenarios (Sen). Then, considering the most important 15 parameters, such as pollutant emissions and economic values, the results were analyzed and sorted by the multicriteria decision-making (MCDM) method to find the best scenario for the case-study region. The results showed that SunPower E20-327 as PV, Eocycle EO10 10 kW as wind turbine, and Generic 1 kWh Li-Ion as the battery could be the best selection to design a hybrid renewable system for the case-study region since it can fulfill both economic and environmental needs. The cost of energy (COE) of the best-designed system and net present cost (NPC) are 0.24 ($/kWh) and 1.64 million $, respectively, where the renewable fraction (RF) is 55.1% and the scaled annual average load is 1126 kWh/day. The results of the sensitivity analysis on the best scenario’s parameters (where the capital cost of PV, battery, and wind turbine changes from 0.6 to 1.2, from 0.7 to 1.2, and from 0.7 to 1.4 of the current price, and diesel price from 0.5 to 1.1 ($/L)) showed that the RF, COE, and NPC values ranged between 51% to 93%, 0.2 to 0.3 ($/kWh), and 1.4 to 2.1 (million $), respectively.

Analisis Performa PLTS Off Grid Untuk Sistem Desalinasi Metode Osmosis Terbalik

Bondan Hamlet is a hamlet in Kampung Laut District, Cilacap. One of the community's problems is the lack of clean water and the PLN electricity network. In 2020, a desalination facility named Sidesi Mas will be built in Bondan Hamlet with a capacity of 240 liters/hour and using the reverse osmosis principle. The energy source for desalination uses a solar power plant (PLTS). Desalination management requires economic analysis, especially in determining the selling price of desalinated water. The cost of producing desalinated water can be calculated using the Cost of energy (CoE) value of the PLTS or the costs incurred to produce electrical energy per 1 kWh. To get the PLTS CoE, this article discusses a simulation to analyze the performance of PLTS desalination systems with Homer software. Homer performs analytical calculations based on a location input, solar energy potential, capacity, and costs of PLTS components as well as electrical load data. The simulation results show that PLTS energy production is 535 kWh/year, the CoE value is IDR 21,975/kWh and the production cost for producing clean water is IDR 183.13/liter.

Study of Wind Power Plant for Alternative Energy in Vannamei Litopeneaus Shrimp Cultivation

The focus of this research is to utilize wind energy for power generation as an electric power service for shrimp farming in the Kulon Progo district of Yogyakarta. This is done in order to minimize the use of diesel fuel in daily operations to drive the aerator pump that produces air bubbles and needs lighting. The method used is to calculate the need for electrical power in 24 hours, plan the windmill according to the local average wind speed. Parameters for measuring the final result are net present cost (NPC), cost of energy (CoE), and payback period. The scenario is used by installing a wind power generator compared to a generator from a diesel engine. The results of the study with a wind power generation system capable of producing 41755,07kW/year of power with the NPC value having a more efficient economic value of Rp. 158,254,000.00, a more efficient CoE value of Rp. 477.41, and for a diesel power plant of Rp. 1,569,015,240.00 and CoE worth Rp5,867,45. The payback period for the scenario with wind power is 3 years and 9 months and and 15 years 7 months for the scenario with diesel power plants.

Design of IoT-oriented demand side management model in microgrid via improved metaheuristic framework

The amplified use of power applications by customers is a rising concern in the energy field every day, which leads to an imbalanced ratio of supply and demand. The integration of renewable energy sources and increasing greenhouse gas emission leads to power demand and affects the climate. Shortage of power supply is the major issue in remote areas, to rectify this issue microgrids have become the best solution. Demand side management (DSM) is a very important means for avoiding major deficits from the supply side and improving energy efficiency (EE). The development in the management of energy mainly focuses on minimizing the entire cost of electricity with no limitation in the utilization part and instead, it chooses to lessen the power utilization at peak hours. This paper intends to introduce a sophisticated DSM and controlling scheme for an Efficient Energy Management system (EMS) in Smart Microgrids (SMG). Initially, an optimal cost-efficient EMS operation is established depending on Modified Cat Swarm Algorithm (M-CSA) model and is augmented via time-of-use pricing (ToU) theory. Subsequently, the SMG frequency and voltage are optimally controlled via an improved PID-based Mixed Sensitivity H-infinity (PID-MSH∞) model while functioning in islanded mode. Thus, the developed approach exploits the massive IoT (Internet of Things) aptitudes for ensuring a secure and economic operation of SMG. The energy cost value of the proposed method is 8138.9 which is 33.67%, 37.94%, 35.42%, and 32.27% superior than the traditional approaches such as CSA, IDE, GA and JA. Thus, several analyses are used to demonstrate the created approach's superiority.

Thermal design and analysis of an organic rankine cycle system utilizing the main engine and cargo oil pump turbine based waste heats in a large tanker ship

The utilization of main engine-based waste heat sources using organic Rankine cycle (ORC) systems is only available during the navigation phases of marine vessels, which leads to reductions in the system uptake time and economic viability of the investment during cargo loading/discharging operations and waiting periods in ports. The novel perspective of this study is to propose the cargo oil pump turbine (COPT) based waste heat as a utilizable source, which has not been introduced in the literature yet, and show the economic viability of ORC systems for tanker ships. In this regard, a new waste heat recovery system specifically designed for a reference crude oil tanker ship was introduced that can utilize both main engine-based waste heat during navigation and COPT-based waste heat during cargo discharge operations. The optimal heat exchanger network of the main engine and COPT-based waste heats was designed using pinch point analysis method for achieving optimum waste heat recovery. Energy and exergy analyses were conducted for the proposed ORC integrated waste heat recovery system for both navigation and discharge operation modes of the ship. The economic performance of the ORC system was further assessed by calculating payback periods and levelized energy costs for eleven design points. The highest energy conversion efficiency (16.2%) was achieved when the ORC condenser outlet temperature was taken as 15 °C for R1233zd(E). COPT based waste heat reduced the levelized energy cost of the system by at least 8.9% and the minimum levelized energy cost value was obtained as 0.1307. The best economic performance was yielded with COPT utilization at design point 9 with a payback period of 6.2 years, which was reduced by at least 0.7 years with the utilization of COPT based waste heat.

Economic evaluation of hybrid electrical systems for rural electrification: A case study of a rural community in Nigeria

ABSTRACT Diesel generators have long been in use in rural communities in Nigeria despite the impact of emissions caused by these generators on the environment. Due to the high cost and fluctuation in the diesel price and the need for a greener environment, such electric generating systems seem not to be economical and environmentally friendly and need to be addressed. The potential of utilizing the major renewable energy sources prevailing in the Umuejim Amorka community was investigated based on related site surveys and data collected from each household. This paper also investigates the feasibility and economic viability of employing a hybrid-electric system in rural communities. The HOMER software that analyzes system configuration was used to study the application and functional limitations of each hybridized arrangement. The results showed that the renewable energy (RE) based system, photovoltaic (PV)//battery(B), has the lowest cost of energy (COE) and net profit cost (NPC) compared to the PV/Diesel Generator (DG)/B and standalone DG systems. Although the diesel generator (DG) hybrid-electric system (HES) has lower NPC and COE values compared to PV/DG/B, the DG system has the highest significant pollution emission. Furthermore, the result revealed that the PV/B system has the lowest capital and total costs compared to the other two HESs. Moreso, the PV/B system, has the highest return on investment (ROI), making the system the most economically viable and adjudged to be a better candidate for rural community electrification demands.

Development of a Hybrid Renewable Energy System with Co-Firing Option

ABSTRACT In this study, a hybrid renewable energy systems (HRES) composed of solar photovoltaic and biogas co-firing is designed for a hazelnut cracking plant in Ordu province of Turkey. Technical and economic analysis are carried out based on the change in government incentives on renewable sources before (Option A) and after 2021 (Option B) based on net present cost (NPC) and cost of energy (COE). In addition, four different HRES configurations namely Scenarios 1, 2, 3, and 4 are analyzed to compare energy generation with/without co-firing of hazelnut shell and natural gas alongside with/without solar photovoltaic (PV). Sensitivity analysis is also made by considering grid sale capacity, inflation rate, discount rate, biomass price, and sellback rate. It is found that Option A has the lowest NPC and COE values, which are estimated as $3.000 M and $0.098/kW, respectively. In the sensitivity analysis of HRES configuration, total NPC and COE values between nominal discount rate and biomass price generally increase, while the values between expected inflation rate and sellback rate are on a downward trend. Consequently, Scenario-4 has the lowest NPC and COE values, and the highest renewable fraction at around 73.6%, whereas CO2 and NOx emissions are lowest in Scenario-2.

Cost/comfort-oriented clustering-based extended time of use pricing

Real-time pricing (RTP), as the most effective electricity pricing method, has recently attracted significant attention in tackling the challenges of the evolving power grid such as peak shaving and shifting, as well as the emergence of energy prosumers. However, the realization of RTP schemes require an advanced metering infrastructure (AMI). Therefore, time-of-use (ToU) pricing is still in use in residential sectors. This paper presents a novel clustering-based extended time of use pricing (ETOU) algorithm as an intermediate solution, which combines the advantages of both RTP and ToU pricing methods, without a need for AMI, while considering consumers’ desired comfort level. The proposed ETOU is designed based on analyzing the consumption patterns and the real cost of energy generation. The proposed rates are defined considering the dominant consumption and energy cost values extracted by clustering. The effectiveness of the proposed ETOU is verified through numerical analysis of a residential building with an electrical thermal system modeled as a controllable load and an electrical vehicle modeled as a delay-tolerant demand. Results show that the proposed tariffs, in comparison with RTP and ToU rates, noticeably increase the load factor and energy flexibility and decrease the maximum power ramp and electricity costs, while providing the desired comfort level. Additionally, implementation of the proposed ETOU does not require AMI despite the RTP method.

Accessibility and Sustainability of Hybrid Energy Systems for a Cement Factory in Oman

Diesel generators are being used as a source of electricity in different parts of the world. Because of the significant expense in diesels cost and the requirement for a greener domain, such electric generating systems appear not to be efficient and environmentally friendly and should be tended to. This paper explores the attainability of utilizing a sustainable power source based on a cross-breed electric system in the cement factory in Salalah, Oman. The HOMER software that breaks down the system setup was utilized to examine the application and functional limitations of each hybridized plan. The result showed that a renewable-energy (RE)-based system has a lower cost of energy (COE) and net present cost (NPC) compared to diesel generator-based hybrid electric and standalone systems. Although the two pure renewable hybrid energy systems considered in this study displayed evidence of no emissions, lower NPC and COE values are observed in the photovoltaic/battery (PV/B) hybrid energy system compared with photovoltaic/wind turbine/battery (PV/WT/B). The PV/WT/B and PV/B systems have higher electricity production and low NPC and COE values. Moreover, the PV/B has the highest return on investment (ROI) and internal rate of return (IRR), making the system the most economically viable and adjudged to be a better candidate for rural community electrification demands.

Comparative evaluation of hybrid photovoltaic, wind, tidal and fuel cell clean system design for different regions with remote application considering cost

In this paper, a comparative evaluation to optimal, cost-effective, and reliable designing of hybrid renewable and clean energy systems consisting of photovoltaic (PV), wind turbine (WT), tidal, and fuel cell (FC) energy (PV/WT/tidal/FC) with hydrogen storage (HS) is proposed. The determination of optimal system configuration is provided for three regions of Iran: Gorgan, Urmia, and Yazd with suitable weather conditions because of assessing the potential of renewable energy in these regions. The evaluation is based on real data regarding radiation, wind speed and water speed, with the objective of minimising the hybrid system net present cost (HSNPC) and satisfying the reliability constraint, i.e. the load deficit probability (LDP). A whale optimisation algorithm (WOA) with high convergence and accuracy speed is considered to determine the optimal configuration of the hybrid system with the minimum HSNPC and cost of energy (COE) that satisfies the LDP for different regions. In this study, seven different design combinations of hybrid systems are implemented. The optimal combination is determined for any region in view of the lowest cost and best reliability, as well as the contributions from renewable energy sources and storage systems. It has been also confirmed that the WOA is superior to particle swarm optimisation (PSO) for hybrid system optimisation. The results showed that optimal combination for all regions comprises a hybrid PV/WT/tidal/FC based HS. The COE values for Gorgan, Urmia, and Yazd are found to be $0.7789, $1.0864, and $0.4477, and the LDPs for these regions are 0.0090, 0.0093, and 0.0090. Moreover, the results clarified the additional contribution of tidal energy for the Gorgan and Yazd regions, the additional PV contribution to the Urmia region, and the reduced contributions related to WT sources.

Exergo-Economic Optimization of Organic Rankine Cycle for Saving of Thermal Energy in a Sample Power Plant by Using of Strength Pareto Evolutionary Algorithm II

Waste heat recovery plays an important role in energy source management. Organic Rankine Cycle (ORC) can be used to recover low-temperature waste heat. In the present work a sample power plant waste heat was used to operate an ORC. First, two pure working fluids were selected based on their merits. Four possible thermodynamic models were considered in the analysis. They were defined based on where the condenser and evaporator temperatures are located. Four main thermal parameters, evaporator temperature, condenser temperature, degree of superheat and pinch point temperature difference were taken as key parameters. Levelized energy cost values and exergy efficiency were calculated as the optimization criteria. To optimize exergy and economic aspects of the system, Strength Pareto evolutionary algorithm II (SPEA II) was implemented. The Pareto frontier solutions were ordered and chose by TOPSIS. Model 3 outperformed all other models. After evaluating exergy efficiency by mixture mass fraction, R245fa [0.6]/Pentane [0.4] selected as the most efficient working fluid. Finally, every component’s role in determining the levelized energy cost and the exergy efficiency and were discussed. The turbine, condenser and evaporator were found as the costliest components.