Net Present Cost Research Articles

Effects of dispatch algorithms and fuel variation on techno-economic performance of hybrid energy system in remote island

A stand-alone hybrid energy system is needed to mitigate the growing demand for future energy and to reduce emissions generated by conventional fuel sources. This work shows and proposes an optimum hybrid energy system configuration with less environmental pollution for a coastal region of Bangladesh with a load demand of 292.20 kWh/d and a peak load of 41.14 kW. This research presents the cost of energy (COE) and net present cost (NPC) for a PV-wind hybrid system with five alternative fuel generator technologies. For each possible configuration, the effects of three alternative dispatch algorithms, load following (LF), cycle charging (CC), and combined dispatch (CD), are examined. All three algorithms were validated using a genetic algorithm (GA), Cuckoo search algorithm (CUSA), Constrained Particle Swarm Optimization (CPSO), Harmony search algorithm (HSA), and Non-dominated Sorting Genetic Algorithm (NSGA-II). Furthermore, a sensitivity analysis is also conducted by utilizing the gasoline price, discount rate, battery cost, PV cost, and inflation rate. The results show that the PV-wind-natural gas-based system provides the minimum COE (0.196 USD/kWh) and NPC (270,483 USD) when the CD algorithm is followed. For the same optimal hybrid energy system, the COE is 0.201 USD/kWh, 0.0998 USD/kWh, 0.101 USD/kWh, 0.101 USD/kWh, and 0.0987 USD/kWh respectively for GA, CUSA, CPSO, HSA, and NSGA-II. However, COE increases by 8 % (0.212 USD/kWh) and 15 % (0.225 USD/kWh) when the CC and LF algorithms are followed. In addition, a comparison of all configurations reveals that the PV-wind-biomass configuration with the CD algorithm excludes biomass generators to lower the COE, making the system emission-free.

Economic assessment of nature-based solutions to reduce flood risk and enhance co-benefits

Flooding is expected to increase due to climate change, urbanisation, and land use change. To address this issue, Nature-Based Solutions (NBSs) are often adopted as innovative and sustainable flood risk management methods. Besides the flood risk reduction benefits, NBSs offer co-benefits for the environment and society. However, these co-benefits are rarely considered in flood risk management due to the inherent complexities of incorporating them into economic assessments. This research addresses this gap by developing a comprehensive methodology that integrates the monetary analysis of co-benefits with flood risk reduction in economic assessments. In doing so, it aspires to provide a more holistic view of the impact of NBS in flood risk management. The assessment employs a framework based on life-cycle cost-benefit analysis, offering a systematic and transparent assessment of both costs and benefits over time supported by key indicators like net present value and benefit cost ratio. The methodology has been applied to the Tamnava basin in Serbia, where significant flooding occurred in 2014 and 2020. The methodology offers valuable insights for practitioners, researchers, and planners seeking to assess the co-benefits of NBS and integrate them into economic assessments. The results show that when considering flood risk reduction alone, all considered measures have higher costs than the benefits derived from avoiding flood damage. However, when incorporating co-benefits, several NBS have a net positive economic impact, including afforestation/reforestation and retention ponds with cost-benefit ratios of 3.5 and 5.6 respectively. This suggests that incorporating co-benefits into economic assessments can significantly increase the overall economic efficiency and viability of NBS.

A Techno-Economic Comparison of a Stand-alone Hybrid System for a Household: A Case Study for the Royal Commission in Saudi Arabia

It’s exciting today to use renewable off-grid sources for driving applications in the home sector (micro-grids). The current tendency is to use renewable energy sources to increase building sector energy efficiency and protect the environment. The economic element and the expense of building these grids is the biggest barrier to these applications. How to best choose the ratings and mix of certain renewable sources based on the location of the house is one of the crucial ways to lower the cost and boost the reliability of these grids. An efficient techno-economical design for a standalone hybrid system is presented in this research. A solar energy using photovoltaic (PV), wind energy, energy storage, and diesel generator are all parts of the system. This design is carried out by a thorough analysis of the techno-economical design of a standalone system to supply the required energy load for a typical residential building for the Saudi Arabian cities of Yanbu and Jubail. Yanbu, which is at latitude 24.0097 degrees north, and Jubail, which is at latitude 27.0726 degrees north, are the two cities’ respective geographical positions. These two cities were chosen for the study of the impact of metrological influences on building performance based on total energy cost, load needs, and energy consumption of the differences in their geographic positions. To improve the performance of the suggested hybrid system, some restrictions were chosen, including Total Annual Cost (TAC) and Net Present Cost (NPC). Results show that the proposed stand-alone hybrid systems can be used to increase the economics and energy efficiency of existing buildings. For Yanbu and Jubail cities, respectively, the optimal integration of a diesel generator, PV array, wind turbine, and energy storage results in a minimum energy cost of roughly $0.483/kWh and $0.487/kWh.

Siphon-type hydroelectric plants: application for power generation in a low head dam in southern Brazil

Hydroelectric energy continues to be the most representative renewable resource in the world, accounting today for 40% of installed capacity. The availability of water, combined with the technologies for generating electricity at a reasonable cost, have sustained the success of this type of generation over the years. Continuing to leverage the hydroelectric sector is even more challenging today, because there is a growing world demand for energy, at the same time that the most attractive places from an economic point of view have already been benefited. The current context refers to approaches to water exploitation aimed at exploiting smaller-scale potentials and existing water structures that operate in a multifunctional way. Solidified in this conjecture, the purpose of this study is to contribute, in the sense of attributing alternatives, for the generation of energy in existing low head dams through the pre-dimensioning of a siphon plant. This type of plant is part of a specific and still evolving niche for decentralized power generation. The reduced structural requirements (generator, turbine, and suction tube), as well as the minimal intervention in the existing structure of the dam, the cessation of new socio-environmental and economic impacts related to the construction of a new plant are the main favorable characteristics of these facilities. The case study of an inoperative plant and the tools available in the Homer Software for data simulation were used as methodological resources. Two base configurations were considered: one with 100% renewable matrices and another one including a diesel generator. From them, different hybrid systems, to determine an optimal configuration in terms of net present cost, were simulated. Among the simulations performed, the most promising optimal solution was hybrid, considering among its components a set of siphon turbines totaling 271 kW, plus 50 kW in photovoltaic modules and 140 kW in a diesel support system. A battery bank with 32 200 Ah batteries complemented this system. The energy cost for this system is $0.164 per kWh. For a system without diesel and with 0% service failures, viable results appear only up to 2600 kWh load.

Digital twin-based design and techno-economic analysis of solar hydrail as future locomotive

A clean solar hydrail, a locomotive operated by solar and hydrogen energy, has received significant attention as an alternative to a current fossil fuel-based locomotive. Nevertheless, the feasibility test of solar hydrail is still challenging since it has not yet been practically developed. Herein, we employed digital twin technology to design and operate solar hydrail and diesel locomotive. 30 years of operation simulation starting from 2021 was conducted based on the data of Gangwon-do, South Korea. It was confirmed that replacing the single diesel locomotive with solar hydrail can provide about 59 % lower net present cost and annual harmful emission reduction of approximately 300 tons. Sensitivity analyses were also conducted to mitigate future uncertainty, and the solar hydrail was a better option than the diesel locomotive in every scenario. This study demonstrates that solar hydrail is the successful substitute for the diesel locomotive currently operated in South Korea.

Optimization of a Hybrid Off-Grid Solar PV—Hydro Power Systems for Rural Electrification in Cameroon

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

Efficient integration of photo voltaic and hydro energy technologies for sustainable power generation in rural areas: A case study

This research aims to provide an efficient and cost-effective renewable energy supply. It assesses the potential for photovoltaic (PV) and hydro energy in Pirthala, Haryana, India, using HOMER Pro® v3.14.2. A Hybrid renewable energy system (HRES) can continuously power 855 homes. The optimal HRES configuration comprises well-optimized PV modules, hydro turbines, converters, and batteries. The top four configurations were selected based on criteria such as net present cost (NPC) and cost of energy production (COE). The most effective HRES configuration involves a 3461-kW solar array, a 98.1 kW hydro turbine, 304 lithium-ion batteries of 100 kWh, and a 2785-kW converter, achieving a 100 % integration of renewable energy. This ideal HRES was thoroughly assessed regarding economic, technical, and renewable energy considerations. The results and the optimized HRES configuration can serve as a valuable reference for similar initiatives in rural areas, contributing to adopting renewable energy sources and enhancing energy access and reliability.

Turning weakness into strength - A feasibility analysis and comparison of datacenter deployment in hot and cold climates

Datacenters are major components of the Information and Communication Technologies (ICT) responsible for storing, processing and transmitting enormous amounts of data every second. The significance and importance of datacenters in the world economy can be identified from studies which report that in 2023, datacenter infrastructures consumed a total of 4 % of global electricity and contributed 3–5% of global carbon emissions, whereas between the years of 2017–2021, datacenters added $2.1 trillion to the U.S. Gross Domestic Product (GDP). A big portion of energy supplied in datacenters is consumed by the required cooling systems hence companies do not favor developments in hot climate countries. However, due to environmental and climate change concerns along with the steep increase of energy production costs in recent years made the industry look for alternatives. This work includes an in-depth feasibility and comparative study of datacenter construction and operation in hot and cold European countries and addresses the environmental impact of photovoltaics integration in the electrical supply system. The study considers cost parameters (land, operating expenses, photovoltaic system, etc.), the net present cost and levelized cost of energy which are different for each European country under investigation. Furthermore, for every country under consideration, the PV generation was simulated using the PVsyst software which includes multiple meteorological databases, whereas the feasibility analysis was simulated using the HOMER Pro software which integrates components, resources and economic calculations. An elaborate analysis of the results knocks down the common belief that datacenters have lower operational and running expenses in cold climates because of lower cooling requirements. On the contrary, this study shows that hot climates with high solar radiation levels may favor the operation of datacenters by providing 45 % higher green energy and 35 % lower CO2 emissions, whereas the cooling cost is only 5 % higher. In addition, the break-even period for the photovoltaic system in Southern European countries with hot climates is 3–4 times faster.

Feasibility Study of Using Wave-PV-Wind Hybrid System for AL Hallaniyat Island

Al Hallaniyat Island is located in the southern part of Oman. The island has a low number of population and is currently fed by a number of diesel generators with a capacity of 1568 kW. Decreasing the emission of greenhouse gases is one of the main goals for the country’s vision of 2040 as well as Oman’s commitment to net-zero emissions by 2050, in line with the Paris Agreement of limiting global warming to 1.5°C. The purpose of this paper is to study the feasibility of replacing diesel generators with 100% renewable energy sources. The proposed energy source for the Island will be a hybrid system consisting of the wave energy converter, PV, wind and battery storage system. Real load data was used in the model with measured wind speed and solar radiation. The Hybrid Optimization Model for Electric Renewables software is used in this study. Several systems were proposed but the most economical one is PV-Wind-Wave-Battery system that resulted in levelized cost of energy of US$/kWh 0.1586 and Net Present Cost (NPC) of US$ 5,010,594. Having PV-Wave-Battery will result in levelized cost of energy of US$/kWh 0.174 whereas having Wind-Wave-Battery will increase the energy cost to US$/kWh 0.42.

Improved chaos grasshopper optimizer and its application to HRES techno-economic evaluation

Current political and economic trends are moving more and more toward the use of renewable and clean energy as a result of rising energy use and diminishing fossil fuel supplies. In this paper, an improved chaos-based grasshopper optimizer used for techno-economic evaluation in integrated green power systems is investigated. The integrated system consists of a fuel cell system, a wind farm, and solar energy. The integrated solar, wind, and hydrogen fuel cell architectures increase the effectiveness and electrical output of the system while needing less energy storage in structures that are unconnected from the grid. The grasshopper optimization technique and chaos theory have been combined to create the suggested chaotic grasshopper optimizer in this study. The performance, precision, and robustness of this optimization were then assessed, using four benchmark tasks. The ICGO model is utilized to assign suitable ratings to all system devices, thereby guaranteeing the attainment of optimal performance and efficiency. The Net Present Cost (NPC) analysis revealed that the ICGO algorithm attained the lowest minimum NPC value of 274.541E4 USD and the highest maximum NPC value of 311.94E4 USD. The average NPC value of the ICGO algorithm (289.176E4 USD) was found to be comparable to the other algorithms examined in the study. These findings indicate that the ICGO algorithm outperformed other optimization algorithms in minimizing the cost of the renewable energy system. The chaotic grasshopper optimizer can handle several targets, restrictions, and variables with ease, and the results demonstrate that it is substantially more efficient and precise than standard optimization techniques. It is also quite durable, with minimal performance degradation as compared to the benchmark solutions. This study demonstrates the effectiveness of the chaos grasshopper optimizer as an HRES technique.

Driving Sustainable Energy Dispatch for Remote Communities Using Levy Flight Salp Swarm Algorithm

This study evaluates three energy dispatch algorithms to find the best way to improve hybrid energy systems in rural areas: load following (LF), cycle charging (CC), and a novel customized strategy (CS). The study examined solar and wind resources as well as projected patterns of energy consumption with a particular focus on Bambur village in Taraba State, Nigeria. The Levy Flight Salp Swarm Algorithm (LFSSA) was used in the study to assess system configurations for each method, accounting for battery storage, wind turbines, diesel generators, and photovoltaic (PV) arrays. The most cost-effective and efficient approach was determined to be the Customized Strategy (CS), which produced the lowest Net Present Cost (NPC) of 0.119/kWh. The Load Following (LF) technique had the highest costs at 0.134/kWh, while the Cycle Charging (CC) method had intermediate costs with an NPC of 0.127/kWh. With a 580-kWh battery bank, a 10 kW wind turbine, 332 kW of PV capacity, and a 78 kW diesel generator, the CS approach showed better component sizing balance. The trade-offs between energy output, storage, and backup power in real-time were optimized using this design. Sensitivity analysis revealed that increasing interest rates from 10% to 18% led to a rise in LCOE, while diesel cost fluctuations showed a non-monotonic impact on LCOE, peaking at $0.79/L before declining due to increased reliance on renewable sources and storage. CS strategy’s balance of investment and efficiency makes it ideal for remote energy management, offering key insights for rural electrification.

Towards Efficient Energy Solutions: MCDA-Driven Selection of Hybrid Renewable Energy Systems

In these days of growing awareness on Renewable Energy Sources and their benefits, there is a major issue that needs to be considered, which is selection of suitable Hybrid Renewable Energy System (HRES) among the vast multitude of choices. In this paper, multiple Multi Criteria Decision Analysis (MCDA) techniques are proposed to select the best among a choice of six HRES Systems using different criteria including but not limited to net present cost (NPC), operating cost, renewability fraction, CO2 & NOx emissions etc. The criteria weights are obtained using Analytical Hierarchy Process (AHP) based on the preference order of the criteria. The decision matrix is obtained from the statistical data of the different HRES and using different MCDA techniques such as Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), rankings are given to the HRES systems based on their closeness to the ideal solution. These rankings are helpful in the selection of suitable HRES configuration for normal household purposes. Since cost aspects are given greater preference, the obtained rankings lean more towards economically affordable solutions without compromising on the number of units generated.

Integrative analysis of diverse hybrid power systems for sustainable energy in underdeveloped regions: A case study in Indonesia

<abstract> <p>There is a goal for practical renewable electrification and renewable energy investments in underdeveloped regions. Indonesia's experience underscores the complexities and challenges in implementing such projects effectively. A study on the effects of various socio-economic factors on Carbon dioxide (CO<sub>2</sub>) emissions in Indonesia highlights the significant impact of forest area, urbanization, and industrialization on carbon emissions. A hybrid system consists of PV, a Biogas Generator, and a Wind Turbine that are successfully deployed. However, no economic analysis has been conducted to obtain the best configuration of the hybrid system. We propose to delve into the effective integration combination of hybrid power systems. In this study, we thoroughly analyzed hybrid power systems in underdeveloped areas using the HOMER software. We examined five different hybrid system configurations: Solely biogas, complete generator integration, a biogas and hydrogen combo, biogas coupled with a PV system, and biogas combined with a wind turbine. Our findings indicated varying levels of economic viability, operational performance, and environmental impact across the configurations, providing crucial insights for policymakers and stakeholders in underdeveloped regions like Indonesia. The results showed the Wind-Hydrogen and Hydrogen Only schemes as the most cost-effective, with a Total Net Present Cost (NPC) of, 969.27 and Levelized Cost of Energy (LCOE) at zhongwenzy.218. Moreover, while CO<sub>2</sub> emissions were similar across all schemes, around 27,744 kg/year, the All-Generator scheme had slightly higher emissions at 27,667 kg/year but led in electricity production with 29,101 kWh/year. These results underscore the importance of balancing cost, energy output, and environmental impact in hybrid power system schemes for underdeveloped regions.</p> </abstract>

Design optimization of a multi-source renewable energy system using a novel method based on selective ensemble learning

This study conducts a comparative assessment to optimize the design of a Hybrid Renewable Energy System (HRES) consisting of PV panels, wind turbines (WTs), and hydrogen storage (PV/WT/FC). The study focuses on Dakhla City, leveraging its favorable weather conditions to evaluate the potential of renewable energy sources. A novel approach, Selective Ensemble Marine Predators (SEMPA), is introduced. SEMPA utilizes a selective ensemble learning strategy to enhance the performance of the Marine Predators Algorithm (MPA) and determine the optimal system size with the lowest Total Net Present Cost (TNPC) and improved reliability. To benchmark SEMPA's performance, we compare it against established methods, including MPA, Particle Swarm Optimization (PSO), and Harmony Search (HS). Results demonstrate that the integrated PV/WT/FC system provides a reliable and cost-effective energy solution for the southwest region of Morocco, particularly in Dakhla. SEMPA outperforms HS, PSO, and traditional MPA, achieving stable convergence after 30 iterations. The system exhibits a superior Cost of Energy (COE) at 0.3127 $/kWh, a TNPC of 0.9689 M$, and a low Loss of Power Supply Probability (LPSP) at 0.04747.

Optimizing separate and combined grids for cost-effective hybrid renewable energy electrification in Mogadishu, Somalia

Expanding access to affordable, reliable, and sustainable electricity is an urgent priority in Somalia, which suffers from high energy costs and climate vulnerability despite negligible emissions. Therefore, this study employs MATLAB simulation software and three algorithms—particle swarm optimization (PSO), genetic algorithm, and simulated annealing—to determine optimal separate and combined grid designs for a hybrid renewable energy system in Mogadishu, Somalia. Four system configurations are assessed, namely, utilities—diesel-alone, Photovoltaic (PV)–diesel hybrid, wind–diesel hybrid, and PV–wind–diesel hybrid across the grids of three utilities—Benadir Electric Company, Mogadishu Power Supply, and Blue-Sky Energy. The algorithms evaluate technical feasibility, economic viability, and system reliability to identify the most suitable configurations. Forty-eight systems are analyzed. The combined PV/wind/diesel grid optimized with PSO is most effective, reducing the net present cost by 32%–47% and levelized cost of electricity by 41%–60% compared to diesel-only systems while maintaining reliability. Greenhouse gas emissions decrease by 38%–59% with the hybrid system.

Design and Techno-Economic Analysis of a Hydrogen-Based Micro Hydro-Solar Hybrid Energy System for Sustainable Energy Access: A Case Study in Sri Aman, Sarawak

Several rural areas in Sarawak do not have access to electricity. In Sarawak, most investigations prioritize conventional sources despite the emergence of technology such as fuel cells. Furthermore, diversified investigations on stand-alone hybrid renewable energy systems in Sarawak are lacking. This study aims to fill this gap by investigating the feasibility of a stand-alone hybrid renewable energy system for rural applications in Sarawak, with a specific focus on the potential benefits of incorporating hydrogen. Different configurations, namely A: Photovoltaic, hydrogen, micro-hydro, B: hydrogen, micro-hydro, C: micro-hydro, D: photovoltaic, and micro-hydro was explored, each with its results, and comparisons were performed between them. By analyzing the system under various load patterns and conducting a sensitivity analysis, the researchers found that scenario A was the most cost-effective and reliable option for a longhouse in Sri Aman, with a net present cost of $148,687, cost of energy of $0.19/kWh, and initial capital of $107,207. Simultaneously, scenario A has the highest annual generating capacity of up to 116521kWh annually. Sensitivity analysis revealed that the electrolyzer could impact the cost of the system. The electrolyzer is the third and second most expensive in scenarios A and B. This research demonstrates the potential of alternative energy sources to improve access to electricity in rural areas. It highlights the importance of continued exploration into emerging technologies to ensure everyone can access safe and reliable electricity.

Simulation of Photovoltaic Water Pumping System in Sam Ratulangi University

The purpose of this study is to design and simulate a PV water pumping system at Sam Ratulangi University in Indonesia. The methods employed in this study consist of a literature review, design, and simulation using HOMER (Hybrid Optimization of Multiple Energy Resources) software. The comparison between PV water pumps and dieselpowered water pumps is analysed in terms of net present cost, cost of energy (COE), and emissions to meet the water requirements in the laboratory. The simulation results are based on two design scenarios for a solar photovoltaic water pumping system at a laboratory scale. In Scenario 1, the system has a daily load of 1.5 kWh/day, 0.52 kW PV modules, 4 batteries of 80 Ah each, and a 1 kW inverter. In Scenario 2, the system has a daily pump load of 2.5 kWh/day, 0.87 kW PV modules, 4 batteries of 80 Ah each, and a 1 kW inverter. The results indicate that the utilization of solar energy to power a PV water pumping system performs well and serves as a case study showcasing the use of solar energy. Further studies on the application of PV water pump should be implemented and tested to evaluate the system’s performance.

Exploring synergistic ecological and economic energy solutions for low-urbanized areas through simulation-based analysis

<abstract> <p>In this study, we assess the feasibility of a Hybrid Renewable Energy System (HRES) for the residential area of Hengam Island, Iran. The optimal system design, based on the analysis of minimum CO<sub>2</sub> emissions, unmet electric load and capacity shortage, reveals that a hybrid system consisting of 12,779,267 kW (55.8% of production) of solar PV panels and 10,141,978 kW (44.2% of production) of wind turbines is the most suitable for this case study. This configuration ensures zero CO<sub>2</sub> emissions and high reliability over a 25-year project lifetime, with an unmet electric load of 164 kWh per year and a capacity shortage of 5245 kWh per year. However, this case has a high initial cost of equipment, with a Total Net Present Cost (TNPC) of ＄54,493,590. If the power grid is also used for energy exchange with the island, TNPC can be significantly reduced by 76.95%, and battery losses can be reduced by 96.44%. The proposed system on the grid can reduce carbon emissions to zero, making it highly environmentally compatible. The sale of excess electricity produced to the power grid creates an energy market for the island. Given the weather conditions and the intensity of the sun in the studied area, the area has very suitable conditions for the exploitation of renewable energies. Transitioning the residential sector towards renewable energies is crucial to overcome energy crises and increasing carbon emissions. Increasing renewable equipment production and improving technology can address the challenge of high prices for renewable energy production.</p> </abstract>

PLANNING AND FEASIBILITY STUDY OF A HYBRID SOLAR POWER PLANT WITH AN ADDED AUTOMATIC TRANSFER SWITCH (ATS) FOR AN OFFICE BUILDING

The Office of the Regent of Sidenreng Rappang (Sidrap), situated on Harapan Baru Street, Batu Lappa, Watang Pulu District, Sidrap Regency, South Sulawesi, consumes 200 kWh of electricity daily for lighting, resulting in substantial energy costs. Recognizing the potential for renewable energy, especially with a daily solar radiation potential of 5.8 kWh/m2, this study proposes the implementation of a hybrid solar power plant system. The system incorporates Photovoltaic (PV) as the primary energy source, with the Grid and Generator serving as backup sources through an AC Coupling configuration utilizing Automatic Transfer Switch (ATS). The research employs a simulation approach using HOMER Pro software for system modeling, SketchUp software for solar panel layout, AutoCAD software for ATS circuit modeling, and theoretical calculations for financial analysis. The results indicate a solar power plant capacity of 39.6 kW, producing 75,701 kWh/year with an impressive 83.3% renewable penetration. From an economic standpoint, the project requires an investment of IDR 642,714,960, with a net present cost of IDR 1,573,177,823, and a cost of energy value of IDR 1,401.38/kWh. In terms of feasibility, the project demonstrates a net present value exceeding zero (IDR 216,680,041), a profitability index greater than one (1.33), an internal rate of return surpassing the credit interest rate (12.488%), and a payback period of 7 years and 7 months. These findings affirm the feasibility of the hybrid solar power plant planning project for the Sidrap Regent's Office, showcasing its economic viability and potential for sustainable energy solutions.

Renewable energy incentives for project owners representing communities with heavily subsidised fossil fuel-based electricity

The significance of renewable energy (RE) as an essential component of sustainable cities is widely acknowledged. Nevertheless, the global transition towards RE faces numerous hurdles, including RE financing, particularly in regions where electricity generation from fossil fuels is heavily subsidized. This necessitates the formulation of effective incentives that can encourage project owners to invest in the transition towards RE. This manuscript proposes a comprehensive framework for incentivizing RE project owners and offers three types of incentives: capital-based, production-based, and grid support incentives. The effectiveness of the proposed set of incentives is evaluated through a detailed techno-economic analysis which aims to minimize Net Present Cost while considering power balance and grid constraints. It encompasses various aspects of RE systems, including optimal sizing of photovoltaics, batteries, inverters, and optimal power flow, at different levels of RE penetration. Additionally, the framework explores the possibility of achieving 100 % RE through off-grid systems, shedding light on potential challenges and opportunities. Further, economic indicators such as the Cost of Energy, Payback Period, Return on Investment, and Internal Rate of Return are also analyzed to evaluate the acceptability of the proposed framework. Results demonstrate that the presented incentivizing framework has the potential to facilitate RE adoption, positioning it as a valuable policy and investment opportunity for RE project owners. This yields substantial benefits including reduced financial burdens, improved return on investment, and access to diverse revenue streams.