Energy Mix Research Articles

Assessing the Potential of Biomass Power Generation for Renewable Energy Transition in South Papua Province, Indonesia

This study aims to explore the potential for biomass-based power plant to accelerate the development of renewable energy to replace the role of fossil energy in Merauke district, South Papua Province. The method used in this study is, first, to collect data and analyze the load on the grid system and the portion of the energy mix as well as the availability of woody biomass from forest areas by making a simulation of the development of a 2 x 12 MW Biomass Power Plant. Second, by conducting experiments to obtain woodchip conversion, as the fuel of the Biomass Power Plant, from the wood log and conversion from Biomass Power Plant capacity to the required biomass plantation area. The results provide an overview of the big potency for developing biomass-based power generation by utilizing biomass from the local industrial plantation forest and show the energy transition towards energy independence. This study can be useful for policy makers and opportunities for entrepreneurs or suppliers of wood biomass, as well. For the future, in terms of fuel efficiency, it is necessary to reduce the plantation area as a source of biomass for power plants by reducing the moisture content of the woodchip to increase the calorific value and utilizing the forest residue. Furthermore, the comparison cost study between fossil power plant and biomass power plant, as well as the strategy for preserving the plantation to ensure a steady biomass supply is conducted.

Towards Integrating Pressure-Sound Piezo Energy Generator in Sports Facility Energy Mix

The paper examines the evolving landscape of energy sources within sports facilities. Traditionally reliant on electrical power and other forms of power from non-renewable resources such as coal, petroleum, and natural gas, these facilities face the inevitability of resource depletion and environmental repercussions. In response, this paper advocates for the adoption of new avenues, including energy conservation, emission reduction, energy recovery, and embracing renewable energy sources. A pioneering focus is on the implementation of a piezoelectric power generation system, tapping into typically wasted sources such as sound and human locomotion. An experimental approach explored the feasibility of such a system in order to ascertain its reliability, efficiency, and sustainability. With applications ranging from powering low-power electronic devices to environmental monitoring sensors, the successful integration of this technology promises a substantial advancement in the use of other renewable energy sources, diminishing reliance on non-renewable sources albeit on a small scale. The paper endeavours to shed light on the potential application of piezoelectric power generation in the electricity production field, aligning with the overarching objective of harvesting energy from unconventional sources and converting it into usable electrical energy. Moreover, it aims to shed light on the potential integration of piezoelectric and audio-electric generators in the energy or renewable energy mix of sports facilities, and address emerging technologies, societal impacts, and strategies to overcome barriers to adoption.

Thermochemical valorisation of cattle manure into gaseous fuel and furfural-rich bio-oil

Surplus carbon, in the form of carbon dioxide (CO2), has aggravated global warming over several past decades. To divert the current energy mix that relies heavily on fossil fuels, researchers have realised waste materials as alternative energy. Such attempts could reduce CO2 emissions and potentially contribute to establishing a circular economy. This study investigated the transformation of cattle manure (CM) into value-added products (syngas and furfural) via a thermochemical pathway. The CM was treated with FeCl3 prior to pyrolysis to enhance the conversion selectivity toward syngas and furfural. Slow-pyrolysis was conducted to determine the mechanisms of syngas production, and fast-pyrolysis was undertaken to optimize bio-oil production. Thermogravimetric analysis revealed that Fe impregnation facilitated the thermal degradation of CM, resulting in enhanced syngas formation. The oil product obtained from the Fe-impregnated CM exhibited notable enrichment in furfural and a much simpler chemical composition than that of the untreated CM. Furthermore, the produced biochar catalytically expedited the kinetics of the transesterification reaction of canola oil. The overall results of this study offer a practical means of converting livestock manure into useful resources, thereby contributing to the realisation of a circular economy.

Thermodynamic Study on Biomimetic Legionella gormanii Bacterial Membranes.

The presented studies were aimed at determining the interactions in model membranes (Langmuir monolayers) created of phospholipids (PL) isolated from Legionella gormanii bacteria cultured with (PL + choline) or without (PL - choline) choline and to describe the impact of an antimicrobial peptide, human cathelicidin LL-37, on PL's monolayer behavior. The addition of choline to the growth medium influenced the mutual proportions of phospholipids extracted from L. gormanii. Four classes of phospholipids-phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylglycerol (PG), cardiolipin (CL), and their mixtures-were used to register compression isotherms with or without the LL-37 peptide in the subphase. Based on them the excess area (Ae), excess (ΔGe), and total (ΔGm) Gibbs energy of mixing were determined. The thermodynamic analyses revealed that the PL - choline monolayer showed greater repulsive forces between molecules in comparison to the ideal system, while the PL + choline monolayer was characterized by greater attraction. The LL-37 peptide affected the strength of interactions between phospholipids' molecules and reduced the monolayers stability. Accordingly, the changes in interactions in the model membranes allowed us to determine the difference in their susceptibility to the LL-37 peptide depending on the choline supplementation of bacterial culture.

Experimental and computational assessment of an energy-saving innovation in a customised testing cabin

The aim of this paper is to assess the performance of an energy-saving device, called ‘Thermocill’ in a customised test cabin, located in a controlled environment. With the UK domestic energy sector responsible for nearly 27 % of the total energy mix in 2022, and massive increases in the cost of energy on homeowners and tenants, simple and low-cost retrofit measures could potentially be of great value, if they prove to be effective at saving energy. The paper describes the experimental and computational methods in detail with the goal of setting an important example/standard for the assessment of similar energy-saving innovations under the UK Standard Assessment Procedure (SAP). This, in turn, would enable the performance of such innovations to be captured in the Energy Performance Certificates (EPCs) for Building Regulation compliance. On that basis, a test cabin was constructed at Salford Energy house 2.0 to investigate Thermocill’s impacts on energy consumption and loss within the cabin. The experimental procedure is subsequently compared against a series of Computational Fluid Dynamics (CFD) simulations conducted for a larger number of scenarios. The performance of Thermocill was explored at different room temperature setpoints (16, 21, and 24 °C), window types (air and argon-filled double-glazed), and with/without blinds. The results were presented for four main scenarios including ‘cabin without Thermocill/blind’, ‘cabin with blind’, ‘cabin with Thermocill’, and ‘cabin with blind/Thermocill’. The results were presented in the form of U-values and heat losses for the windows, while additional results were provided from CFD simulations. A good correlation between the experiments and the CFD was found, showing confidence in both methods. Findings demonstrated that, when Thermocill is in operation, it reduces the average U-value by around 3–4 %, which is considered a significant payback for a passive and economical measure. The methodology presented in this paper is expected to set an important example/standard for the assessment of similar energy-saving innovations under UK SAP. This, in turn, would enable the performance of such innovations to be captured in the EPCs for Building Regulation compliance.

Technological Paradigm Between the Production of Photovoltaic and Thermal Solar Energy in Sahelo-Sahelian Countries

The energy sector in Sahelian countries such as Burkina Faso, Mali and Niger is facing enormous challenges. Indeed, electricity shortages, characterized by recurrent breakdowns of means of production and import dependency due to an unfavorable energy mix, are numerous in these countries. Concerns about the high costs of facilities and operations, as well as environmental pollution, not forgetting to mention the matter of the countries' energy sovereignty, have led to the desire to use reliable, profitable and adapted means of production. The aim of this study is to review the literature on electric power generation systems in the world, in Africa and in Sahelian countries, with an emphasis focus on photovoltaic and thermal solar energy. In addition, it highlights, in views of the problems raised, works that have suggested solutions. To achieve this, scientific articles, theses and other scientific documents dealing with electric power generation systems from 2014 to 2024 have been consulted. This enabled us to get knowledge on the various electric power generation systems, to know their advantages and limitations, and above all the perspectives in terms of electric power generation. Additionally, they provided a source of inspiration for setting up an electric power generation system in line with the realities of the countries of the Alliance of Sahel States (ASS).

The role of utilizing artificial intelligence and renewable energy in reaching sustainable development goals

Many nations want to use only renewable energy by 2050. Given the recent rapid expansion in RE use in the global energy mix and its progressive impact on the global energy sector, the evaluation and analysis of Renewable Energy's impact on achieving sustainable development goals is insufficient. Wind energy could be renewable. For smart grid supply-and-demand issues, wind power forecasting is critical. One of the biggest challenges of wind energy is its significant fluctuation and intermittent nature, which makes forecasting difficult. This study's goal is to develop data-driven models to predict wind speed and power. This paper uses Machine Learning (ML) and Deep Learning (DL) to improve a wind speed prediction and recommendation system for wind turbine power production using site climatological data. This system optimizes turbine use by selecting the right number of turbines to operate solely based on the required energy, which is related to wind power and speed, and recommends the best power station location to determine the best turbine run time. The Proposed Enhanced Recommendation System (PERS) includes the Wind Speed Prediction Module (WSPM), Wind Speed vs. Power Consumption Calculation (WSPC), and Recommendation Module (RM). Test results showed the suggested method works in run time. The XGBoost or Random Forest regressor predicted 15-day power output with 94 % accuracy and 6 % mean average percentage error.

Equilibrium modelling of steam gasification of PKS system and CO2 sorption using CaO: A digitalized parametric and techno-economic analysis

The conversion of palm oil waste into energy can complement the energy mix with renewable energy and bring economic benefits to the palm oil industry. A process simulation model for palm kernel shell (PKS) steam gasification for H2-enriched syngas with the integration of CO2 capturing using CaO has been investigated using Aspen Plus V10®. Techno-economic and energy analyses have also been conducted to identify energy-saving opportunities for commercialization. The effect of process variables, including reactor temperature (600–800 °C), Steam/PKS ratio (0.5–2 wt/wt), and CaO/PKS ratio (0–1.5 wt/wt), have been determined, with the predicted results compared to the reported experimental data. H2 concentration has been increased with 76–78 vol% with the temperature elevation from 650 to 750 °C. Additionally, a substantial increase in H2 content from 68 to 72vol% was observed when the steam flow rate was increased from 0.5 to 1.5. Conversely, the CO2 concentration decreased from 25 to 8vol% as the adsorbent ratio was raised from 0.5 to 1.5. The techno-economic analysis showed that the capital investment is $4.11 million, and the operating cost is $3.89 million per year, which is also very high due to the high raw material costs. In the case of energy, saving that 3.03 and 1.513 Gcal/hr can be saved in terms of utilities and gas cooling that economized the process which shows that utilization of these in heat exchange networks can significantly reduce costs, with up to 78 % savings in heat exchanger capital and 35 % in total energy consumption. The energy potential could be harnessed through the digitalization of the process.

Glimpse on Spot and Derivative Market of Electricity and Nepal’s Hydropower

Energy plays a vital role in a country’s economic development. Nepal abundantly blessed with various renewable resources like hydropower, solar energy, biogas, and biomass can achieve prosperity both economically and socially. Further, with a significant opportunities for the regional electricity market as the country has been surrounded by big powerhouses like China and India. It has huge possibilities for regional trading of renewable energy. The present total Installed capacity of power is 3157 MW in Nepal. With 95% hydropower generation, the energy mix in the Integrated Nepal Power System makes the country a surplus of electricity during the wet season when the water in the river is very high and a shortage during the dry season when the discharge in the river is minimal. Hence, to address the surplus generation during the wet season and shortage of power during the dry season, trading in the region plays a very vital role in balancing the demand and supply of the country. Nepal has been importing power during the dry season power deficit in the market during the dry season when the demand is high leaving NEA at risk of interrupting the supply to its customers. Likewise, uncertainty about clearing a bid during the wet season when the power production is high and Nepal is in the position to export the power in the regional market, as the Hydropower plant has to compete with the cheap coal power plant resulting in financial loss and uncertainty of return on investment. Hence, to tackle the mentioned financial risks, the Electricity Derivative market can be one of the best options as derivatives markets can be used to hedge against price fluctuations in electricity spot markets. Similarly, the uncertainty of power sale can be avoided by selling or buying the electricity through a derivative market for the future time period that secures the price and the amount that can be sold in the market in the future. In a nutshell, the Electricity Derivative market can be a useful mechanism for the development of hydropower in Nepal in the future.

Model based study of temperature dependent thermodynamic and surface properties of Al-Ti-Ni-Cr system in liquid state

Thermodynamic and surface properties of Al-Ti-Ni liquid alloy with adding Cr, Al-Ti-Ni-Cr, were studied at 2000 K, 2100 K, 2200 K, 2300 K, and 2400 K using different theoretical models. The self-consistent energy interaction parameters of constituent binary subsystems were taken from the literature for the purpose. The thermodynamic properties like excess Gibbs free energy of mixing and the activities of the components in the alloy were investigated using the General Solution Model (GSM). Surface tension of the liquid alloy and surface concentrations of components in it were calculated using Butler's model with the aid of determined thermodynamic functions. The mixing tendency of the Al-Ti-Ni-Cr liquid alloy was found to decrease with the addition of Cr atoms for all compositions at its melting temperature, 2000 K. The activity of Cr decreased while those of the remaining components increased with the temperature rise. The surface tension of both Al-Ti-Ni and Al-Ti-Ni-Cr liquid alloys decreased linearly at elevated temperatures.

Urban low-carbon governance and ecological efficiency: new evidence from prefecture-level cities in China

IntroductionIn the search for sustainable development, urban eco-development is becoming a core agenda for all countries. China’s low-carbon city pilot (LCCP) policy is an important initiative to promote urban low-carbon governance. And exploring the direction of LCCP policy is an important step towards sustainable urban development.MethodsSuper-SBM is employed to calculate urban ecological efficiency using panel data from 254 prefecture-level cities between 2007 and 2020. The methods of kernel density estimation and spatial Markov chains are applied to the spatial analysis of urban ecological efficiency. The spatial analyses examine the spatiotemporal patterns and dynamic evolving trends of urban ecological efficiency. Additionally, the multiperiod difference-in-differences method is used to assess the impact of the LCCP policy on urban ecological efficiency. On this basis, we apply the method of mechanism analysis to discuss the influence mechanism.ResultsThe results indicate that urban ecological efficiency gradually forms a continuous spatial clustering pattern, although there is a widening tendency in the absolute differences. In the subsequent transfer process, the spatial factor plays a highly significant role. Benchmark regressions and auxiliary robustness tests demonstrate that the LCCP policy is effective in improving urban ecological efficiency. Further analysis shows that the effect of LCCP policies on ecological efficiency can be transmitted by promoting green technology innovation as well as facilitating a low-carbon transition in the energy mix. The above findings indicate the presence of the "Green Innovation Effect" and the "Decoupling Effect".DiscussionThese discoveries enhance the theoretical framework of urban ecology and offer valuable insights for other regions seeking to implement low-carbon urban governance.

An agent-based cooperative co-evolutionary framework for optimizing the production planning of energy supply chains under uncertainty scenarios

Nowadays, energy and power companies compete to get the raw materials and equipment they need on time, as project times lengthen, costs spiral, stock-out continues to plague plans to a decarbonized energy future. The risks reflect the impact of uncertainty and volatility on the resilience of the supply chains. Therefore, there is a need for the enhancement of the production planning in Energy Supply Chains (ESCs), as it enables affordable energy supplies and supports the companies transition to a clean, secure and sustainable energy mix. This study aims to understand the interactive behavior among individuals and optimize their production planning under uncertainty scenarios. In particular, we propose a novel framework to couple an Agent-based Modelling (ABM) and a Co-evolutionary Algorithm (CEA), to realize its capacity to solve a Many-objective Optimization Problem (MaOP) where the profits of multiple agents are concurrently maximized in their interactive transaction processes under normal conditions and uncertain disruption events.For demonstration, we illustrate the proposed approach by considering a five-layer oil and gas ESC model, where uncertainties from multiple sources and the structural dynamics challenge the balance between supply and demand. The results obtained by an integration of a Cooperative Co-evolutionary Particle Swarm Optimizer (CCPSO) algorithm into ABM show the pricing and orders of the target agents are optimized while the loss of ESC resilience is minimized under uncertainty scenarios, proving its capacity of improving the diversity and the convergence, compared to the classic evolutionary algorithms.

Development of green manufacturing implementation framework based on life-cycle assessment

Climate change stabilization at 1.5 to 2 °C requires a shift in paradigm of industries to transition to low carbon industries. The way forward to decarbonize industries is green manufacturing, as the environmental facet of manufacturing has often been compromised for the sake of economic gains. In order to implicate green manufacturing, it is incumbent upon manufacturing facilities to introduce such measures which ensure that carbon footprint and environmentally detrimental emissions are minimized. In this context, Life-cycle Assessment (LCA) is an excellent tool to record, analyze and critically review the environmental impact of a process. In order to investigate the environmental hotspots, the authors have performed LCA of an auto-parts manufacturing industry in Pakistan by using a unique gate-to-gate approach. ReCiPe Midpoint impact assessment method was utilized to investigate the effects of manufacturing and transportation related emissions of the monthly produce on climate change, fossil depletion, ionizing radiation and human toxicity. Furthermore, the authors discuss three scenarios, which include current state, optimized future state and an energy mix involving hydropower and photovoltaic generation. The results helped in developing a comprehensive framework for green manufacturing which suggests that the prerequisite of a green manufacturing process is an optimized process flow, which significantly reduces the environmental emissions up to 24%. Moreover, the use of photovoltaic cells results in 54% reduction, thus indicating that conventional hydropower systems in developing countries should be mixed with solar power to reduce the environmental burden. A detailed green manufacturing framework based on LCA is proposed by the authors to enhance the functionality and to improvise the carbon burden of the manufacturing sector of Pakistan.

ENERGY CONSUMPTION IN KARNATAKA: INSIGHTS INTO CURRENT TRENDS AND FUTURE DIRECTIONS

This study examines Karnataka's energy consumption patterns and projections to provide a comprehensive understanding of its current and future energy landscape. Karnataka, a rapidly developing state in India, has experienced significant changes in energy demand driven by factors such as population growth, urbanization, and industrialization. The analysis reveals a complex energy mix for 2023-24, with coal remaining the dominant source of power, while substantial investments are being made in renewable energy sources like solar and wind. The study also highlights fluctuations in per capita power availability and overall power availability, reflecting challenges in sustaining long-term growth in power supply. Projections for energy consumption and peak demand up to 2031-32 indicate a steady increase, necessitating strategic planning and industrialization. development to accommodate rising demands. The review of literature underscores the importance of energy efficiency, renewable energy adoption, and policy frameworks in shaping Karnataka's energy future. This study aims to provide insights into both current trends and future directions, emphasizing the need for balanced energy strategies to support the state's ongoing growth and development. KEYWORDS: consumption, demand, industrialization., industrialization., growth and development.

Probabilistic Analysis of Green Hydrogen Production from a Mix of Solar and Wind Energy

This article describes an example of using the measurement data from photovoltaic systems and wind turbines to perform practical probabilistic calculations around green hydrogen generation. First, the power generated in one month by a ground-mounted photovoltaic system with a peak power of 3 MWp is described. Using the Metalog family of probability distributions, the probability of generating selected power levels corresponding to the amount of green hydrogen produced is calculated. Identical calculations are performed for the simulation data, allowing us to determine the power produced by a wind turbine with a maximum power of 3.45 MW. After interpolating both time series of the power generated by the renewable energy sources to a common sampling time, they are summed. For the sum of the power produced by the photovoltaic system and the wind turbine, the probability of generating selected power levels corresponding to the amount of green hydrogen produced is again calculated. The presented calculations allow us to determine, with probability distribution accuracy, the amount of hydrogen generated from the energy sources constituting a mix of photovoltaics and wind. The green hydrogen production model includes the hardware and the geographic context. It can be used to determine the preliminary assumptions related to the production of large amounts of green hydrogen in selected locations. The calculations presented in this article are a practical example of Business Intelligence.

Promoting green taxation and sustainable energy transition for low-carbon development

Since there is a scientific consensus that the energy sector has brought the planet to the tipping point of climate change, transitioning to sustainable energy sources is inevitable to halt foreseeable climatic adversities. This study looks at how promoting green taxation and sustainable energy transition affected the G7 nations’ goal of low-carbon development between 1994 and 2020. This study used Generalized Least Squares Random Effects Regression and Driscoll-Kraay Standard Errors-based Least Sqaures approaches for empirical analysis. The latter approach accounts for cross-sectional dependence, heteroscedasticity, and autocorrelation to provide robust empirical outcomes. The empirical results are as follows: Firstly, through lowering CO2 intensity and greenhouse gas emissions, the environmental tax revenues have enhanced the condition of the environment. The total tax revenues linked to the environment had a greater overall impact than the tax revenues related to the energy industry. Furthermore, compared to CO2 intensity, both of the environmental tax revenue factors contributed considerably more to greenhouse gas emissions. Second, the sustainable energy transition helped to lower greenhouse gas and CO2 intensity. Among covariates, international trade was supportive of low-carbon development, but industrialization and GDP per capita did the opposite. The panel bootstrap causality revealed a unidirectional causal connection from all independent variables, except foreign direct investment, to CO2 intensity and greenhouse gas emissions. These results demonstrated that the G7 nations’ environmental policies supported their commitment to achieving low-carbon development goals. In this respect, the G7 nations’ environmental emission reduction efforts benefited more from the overall environmental tax revenues. To secure the industrial emissions reduction for a future with net-zero carbon emissions, it is thus advised to continue using policies that price environmental emissions, such as the carbon taxation regulations. Additionally, plans for the sustainable energy transition that includes a quick rise in renewable energy sources in the overall energy mix are successful in lowering environmental emissions. For environmental sustainability and low-carbon development, it is thus advised to divert the taxation burden from renewable energy technologies to the fossil fuel industry to enhance the sustainable energy transition phenomenon for achieving Sustainable Development Goals (especially SDG-7 and SDG-13).

Carbon Emission Prediction Algorithm for Community Electricity Consumption Based on Improved PSO Algorithm with Optimized Autoregressive Moving Average Models

Abstract The anticipation of carbon emissions stemming from community electricity usage stands as a pivotal field of study. Such analysis holds the potential to furnish communities with informed pathways towards crafting viable carbon reduction strategies, thereby contributing significantly to the overarching goals of carbon peaking and eventual neutrality. The intricacies of carbon emissions from community electricity consumption are manifold, entangled with variables like energy consumption patterns, energy mix, and carbon emission coefficients. Hence, the imperative lies in crafting a predictive framework adept at holistically integrating these variables to enhance prognostic precision and reliability. Within this research, we propose a dynamic carbon emission factor regression model. This model is uniquely poised to capture real-time shifts influenced by changes in energy structure and policy landscapes, thereby amplifying predictive sensitivity. Leveraging the Particle Swarm Optimization (PSO) algorithm, we synchronously optimize the autoregressive terms (p) of the Autoregressive Integrated Moving Average (ARIMA) model and the moving average terms (q) of the MA model to attain a globally optimal solution. Crucially, this approach obviates the need for manual intervention and arbitrary parameter selection. In contrast to conventional optimization methodologies, our paper advances the PSO’s weight calculation mechanism. By assigning greater weight values during the initial iterations, the algorithm maintains robust global search capabilities. Subsequently, the inertia weight diminishes progressively throughout the iteration process, fostering precise local exploration.

Potential Utilization of Tamblang Dam for Micro Hydro Power Plant to Increase Renewable Energy Mix for Indonesia

Abstract Bali, a prominent tourist destination in Indonesia, faces an increasing demand for electricity, primarily supplied by non-renewable sources. With a target to increase renewable energy mix, Bali focuses on leveraging its water resources, notably Tamblang Dam, for hydroelectric power generation. This research aims to determine the potential utilization of Tamblang Dam as a micro hydro power plant, highlighting its capacity to significantly contribute to renewable energy mix in Indonesia generally and Bali particularly. Analysis reveals a potential electricity generation of 0.52 MW, with an annual hydro power production estimate of 4.57 GWh. Considering discharge availability, height of falling water and efficiency of hydro power system. The research also underscores the project’s economic viability and profitability, emphasizing its role in fostering sustainable energy practices in the region.

Used Cooking Oil Methyl Esther (UCOME) Production on a Pilot Scale in Bali Island, Indonesia, and Its Utilization as a Component Blending for Bio-Marine Fuel Oil

Abstract Indonesia aims to achieve a New & Renewable Energy mix of 23% by 2025, so it is necessary to have policies related to the use of complementary feedstocks in the biofuel development program in Indonesia. Used Cooking Oil (UCO) is a domestic waste with the potential to be utilized as a complementary feedstock due to its abundant availability and almost zero carbon emission. However, to assess the sustainability of UCO utilization, especially as a component blending for Bio-Marine Fuel Oil, it is necessary to identify UCO characteristics and quality of its product, called as UCOME, also the production cost impact. The 10,000 liters of UCO used as feed in the pilot-scale UCOME production came from the household sector and HoReCa (Hotels, Restaurants, and Cafes). It was found that UCO had water content and %FFA ranging from 1421.03 - 1666.74 ppm and 1.7 - 15.9%. Furthermore, the UCOME produced has characteristics that comply with the standard of Marine Fuel Oil (MFO) ISO 8217 and SNI 7182 and has a price in the range of Rp.17,000 - 18,000. The results revealed that the UCO has the potential to be a feedstock for producing UCOME as a blending component for Bio-Marine Fuel Oil.

Simulation of Rooftop Solar Photovoltaic for Tourist Accommodation Villa as a Mean to Promote Green Tourism in Bali – Indonesia

Abstract Indonesian government renewable energy mix can be accelerated if tourism industry also contributes to the generation of green electricity such as rooftop solar PV, especially for Bali Province as the world tourist destination with thousands of accommodations spread across the Bali island. In this research, the feasibility analysis to implement rooftop solar PV in Sanctoo Suite and Villa located in Gianyar Regency, Bali Province was carried out using Helioscope software simulation. The design was aimed to maximizing the benefit of free rooftop space with financial investment cost of installation. It was determined to reduce electricity bill of 345 kVA load capacity of the villa operation. Based on the simulation, the rooftop solar capacity of 69.3 kWp was available. Furthermore, the energy output generated by the rooftop solar PV annually was around 106.4 MWh. From financial analysis, the monthly electricity bill saving achieved was on average around 12 %. Further calculation on NPV and IRR shows positive value for feasible investment. It was estimated that the payback period for the investment will be around 18 years. These results showed that installation of rooftop solar PV for tourist accommodation is feasible and will promote green tourism for the industry in Bali.