Hybrid Power Plant Research Articles

Dual-time scale optimal dispatch of the CSP-PV hybrid power plant considering dynamic operation

The concentrating solar power (CSP) plant, renowned for its flexibility, environmental friendliness, and energy storage capabilities, has become integral components of large-scale renewable energy projects in China. However, the grid connection methods for CSP plants, wind farms, and photovoltaic (PV) plants are independent. To enhance renewable energy consumption and improve the revenue of CSP and PV plants, this paper proposes a dual-time scale dispatch model for the dynamic operation of the CSP-PV hybrid plant. This model considers the actual startup conditions and dynamic switching models of the subsystems involved in the receiver, thermal storage subsystem, and power cycle. Based on the dynamic operation characteristics of the CSP-PV hybrid power plant, different time scales are used for prediction during day-ahead and intraday periods, improving the efficiency of the hybrid power plant and adapting to weather changes. The dispatch optimization outcomes of the CSP-PV hybrid plant serve as the reported curve for the day-ahead and intraday rolling optimal scheduling process, aiming to minimize the operating costs of the power system. A simulation is conducted to demonstrate the effectiveness of the proposed model, utilizing data from the Dunhuang area, Gansu Province, China.

Method of first-approximation calculation of take-off weight of a light aircraft with a hybrid propulsion system

The article discusses a method for calculating, as a first approximation, the take-off weight of a light aircraft with a hybrid power plant based on piston and electric engines. A brief overview of organizations dealing with hybrid power plants is given. The influence of the degree of hybridization of the power plant on the take-off weight of the aircraft is shown. The degree of hybridization of a power plant is understood as a relative value characterizing the distribution of the total power of all engines installed on the aircraft between piston and electric engines. The main parameters necessary to determine the take-off weight of an aircraft to a first approximation are presented. The take-off weight of the aircraft is determined to a first approximation from the equation of its existence. Statistical data of aircraft with different types of power plants are provided on the basis of which calculations are carried out. As a first approximation, the relative mass of the hybrid power plant is determined by analyzing the statistical data of light aircraft with piston and electric engines, from which the corresponding graphs are constructed. After the calculations, conclusions were drawn about the optimal range of characteristics of a light aircraft with a hybrid power plant.

Integrating geothermal energy and a solar chimney to maximize renewable energy production: An analytical investigation of a novel hybrid system

Hybrid renewable energy systems, which utilize multiple renewable sources, are becoming increasingly popular due to the need for sustainable energy. In this study, a new hybrid power plant that combines a solar chimney power plant with geothermal energy is investigated. The new system that can be activated when solar radiation is inadequate is called “geothermal pipe” and can produce up to 71 kW of electricity using a 1000-m-deep well. A geothermal pipe power plant was designed to be integrated with a system similar to the Manzanares solar chimney with a well depth of 200 m, generating an average of 15 kW of power. By increasing the distance between wells to 1.5 km, the output power can reach 20 kW. The study analyzed the impact of different parameters, such as well array, size, and temperature, on the output power. The results indicate that a new type of geothermal pipe with six inlets has the potential to increase the performance of the conventional geothermal pipe (with one well) by 26 %. This hybrid renewable energy system benefits from the combination of more than one renewable source, allowing for year-round energy production despite weather conditions.

Integrated procedure to design optimal hybrid renewable power plant for railways’ traction power substation

The paper suggests a 3-steps methodology, integrated in a unique-procedure, to optimally design a hybrid RPP (Renewable Power Plant) to be installed in the available areas of railway’s power plants. The procedure takes into account power profiles and time schedule of trains, traction line’s features, sizing and siting of TPSSs (Traction Power Substations) and features of renewable sources as PV (Photovoltaic) and wind turbines for optimizing the siting of the RPP, considering the investment convenience. The optimal sizing of a hybrid power plant is based on mixed-integer linear programming (MILP) taking into account the energy absorbed by TPSSs, the physical and geometric constraints and the operating and maintenance costs of RPP. The integrated procedure has been tested on a real case study regarding a new 3 kV DC railway located in the South of Italy. The main results show that a hybrid RPP with 4980 PV panels and 3 wind turbines installed in a TPSS area, adopting a capital cost of 645,000 €/MW for PV panels and 3000 €/kW for wind farms, ensures an annual revenue of 227,439 €, with a total investment of 897,400 €. Results show that the available areas in TPSS should be the target of relevant investments to support a new sustainable and green power traction supply system.

Optimal hybrid power plants for electric vehicle charging demand

Transmission constraints, increasing motivations to decarbonize, and concerns over peak electric vehicle (EV) load impacts on local grids have driven electric customers to consider behind-the-meter, hybrid power plant generation and storage at the distributed-grid level for EV charging. In this study, we develop capabilities to optimize hybrid power plant component capacities for EV charging. We then demonstrate these capabilities in a case study for Boulder, Colorado, using public EV charging data as well as wind and solar resource data.Our results show system designs that balance the cost of energy with load-meeting and peak shaving performance. Within the case study, systems designed for wind, solar photovoltaic (PV), and storage resulted in lower cost of energy than those optimized for PV and storage only. This indicates that in areas where wind resource exists, hybrid power plants that include wind, PV, and battery assets can better meet EV charging loads (including peak loads that are prone to overloading local grids) than PV and battery assets alone. Future work to address limitations in this paper include extending cost modeling to include performance losses (e.g., based on operations or weather) and charging station costs to estimate levelized cost of charging, and quantifying uncertainty and error in our aggregation methods for estimating EV charging loads at the hourly timescale.

Profit-optimal data-driven operation of a hybrid power plant participating in energy markets

An energy management system (EMS) is formulated for a hybrid power plant (HPP), consisting of a wind power plant and battery storage plant, participating in bidding stages in the German energy market. The EMS utilizes supervisory control and data acquisition (SCADA) measurements from the site to improve power forecast from the wind power plant. First, the measurement data are used together with numerical weather prediction data to accurately forecast local wind conditions. Second, the measurement data are used to adapt a baseline engineering wake model that gives the total wind power generation for a given input wind condition. The EMS also uses an online cyclic damage minimization approach to accurately balance the battery damage cost against the revenue obtained by market bidding. An HPP controller is formulated to ensure proper tracking of optimal set-points. When compared with standard formulations, the proposed approach shows an accurate estimation and balancing of revenue and costs and a significant reduction in the power deviation penalty, which leads to significantly higher overall profit.

Techno-Economic Evaluation of CSP–PV Hybrid Plants with Heat Pump in a Temperature Booster Configuration

Concentrated solar power (CSP)—photovoltaic (PV) hybrid power plants allow for the generation of cheap electrical energy with a high capacity factor (CF). A deep integration of both technologies offers synergies, using parts of the PV generated electricity for heating the thermal storage tank of the CSP unit. Such configurations have been previously studied for systems coupled by an electric resistance heater (ERH). In this work, the coupling of a CSP and a PV plant using a heat pump (HP) was analyzed due to the higher efficiency of heat pumps. The heat pump is used as a booster to lift the salt temperature in the storage system from 383 to 565 °C in order to reach higher turbine efficiency. A techno-economic analysis of the system was performed using the levelized cost of electricity (LCOE), the capacity factor and nighttime electricity fraction as variables for the representation. The CSP–PV hybrid with a booster heat pump was compared with other technologies such as a CSP–PV hybrid plant coupled by an electric heater, a standalone parabolic trough plant (PT), a photovoltaic system with battery storage (PV–BESS), and a PV thermal power plant (PVTP) consisting of a PV plant with an electric heater, thermal energy storage (TES) and a power block (PB).

Review on the development of solar geothermal complementary power generation system

Nowadays, due to the burning of fossil energy has many negative impacts on the environment, people are looking for new sustainable energy sources that can replace fossil energy, and among them, geothermal energy and solar energy are more prominent, but the two energy sources alone have certain shortcomings, and since complementary solar geothermal energy systems compensate for some of the shortcomings of the two energy sources, much research has been done in this field. This essay summarizes the conclusion from those studies and identify the shortcomings. The largest losses in the system are always in the solar power system. The component with the highest losses may be the evaporator or the trough solar collectors with over 50%. In a solar-geothermal complementary power system, the two energy sources promote each other and the system is more efficient in the summer than in the winter. In a solar-geothermal Organic Rankine Cycle power generation system, Supercritical Organic Rankine Cycle can be a better option than subcritical Organic Rankine Cycle for solar geothermal hybrid power production and cost control. And hybrid power plants benefits will increase over time

ОБОСНОВАНИЕ ПРИМЕНЕНИЯ ДИФФЕРЕНЦИРОВАННОГО СОЦИАЛЬНОГО ТАРИФА НА ЭЛЕКТРИЧЕСКУЮ ЭНЕРГИЮ ПРИ РЕАЛИЗАЦИИ ПРОЕКТА ЭЛЕКТРОСНАБЖЕНИЯ ОТ АВТОНОМНОЙ ГИБРИДНОЙ ЭНЕРГЕТИЧЕСКОЙ УСТАНОВКИ

The issue of uninterrupted power supply to remote settlements is relevant in many countries of the world, but especially in Russia. Modern autonomous hybrid power plants (AHPP), namely solar power plants (SPP), wind power plants (WPP) and other power plants using renewable energy sources (RES), combined with diesel electric power plants (DES), provide not only an increase in the amount of electricity generated, but, most importantly, they ensure uninterrupted power supply to consumers through a combination of renewable energy sources and covering the missing energy from diesel power plants. In the conditions of the northern areas of the Krasnoyarsk Region, this is especially important. ASPPs make it possible to reduce the cost of electrical energy by saving fuel consumption and budgetary subsidies for its supply to remote areas of the region. The purpose of the study was to substantiate the areas of application of autonomous hybrid power plants for the regions of the Far North with the possibility of establishing a differentiated social tariff for household consumers. To achieve the goal, load coverage graphs were constructed for Vanavara settlement; the parameters of the ASPP were studied for the conditions of Vanavara settlement; simulation of the operating modes of the ASPP was carried out; calculation of the main technical and economic indicators of the use of ASPP for power supply to Vanavara settlement was carried out; recommendations were given on rational areas of application of ASPPs with the possibility of applying special tariffs for the electricity they produce. The authors of the paper carried out a technical and economic assessment of ASUE in the Vanavara settlement with a capacity of 10 MW, including a solar power plant with a capacity of 2,5 MW. It was established that the cost of electrical energy in the first option when powered by diesel power plants is 36,75 rubles/kW.h. In the second option, the cost depends on the time of year and is 32,7 rubles/kW.h in winter, 11.6 in spring, 6.05 in summer, and 12,2 rubles/kW.h in autumn, which makes it possible to establish a differential social tariff for household consumers based on a lower cost in the summer in the amount of 7–9 rubles/kW.h.

The perspective of application and calculation of hybrid power plants in vertical take-off and landing aircraft Part 2. Calculation of the main parameters of the hybrid power plant

The perspective of application and calculation of hybrid power plants in vertical take-off and landing aircraft Part 2. Calculation of the main parameters of the hybrid power plant

Thermal analysis and dynamic attributes of a sustainable CSP-fossil hybrid power plant utilizing organic Rankine cycles for enhanced plant performance

The increasing global demand for energy, driven by population growth, highlights the need for sustainable solutions to ensure a sustainable future. This article outlines the design and optimization process of a 1 MW CSP-Fossil hybrid power plant that examines the utilization of toluene and cyclohexane as working fluids within three distinct Organic Rankine cycle (ORC) configurations (simple, recuperated, and with Open Feed Organic Heater). This study aims to propose a sustainable and effective solution for satisfying energy needs while addressing the intermittent nature of solar resources by enhancing system architecture and incorporating fossil fuel technologies. The solar field design has been based on a Concentrated Solar Power (CSP) system, which generated 44% of the total energy output from renewable solar sources. The analysis takes into consideration a selection of criteria, notably thermal efficiency, overall efficiency, power generation capacity, and cost-effectiveness. The selection of relevant performance indicators, evaluation of alternative ORC configurations and working fluids, and optimization of the solar multiple and thermal storage capacity are included among the criteria for conducting the parametric investigation. Based on the investigation, it has been determined that the ORC configuration, which includes a recuperator and utilizes cyclohexane as the working fluid, demonstrates the most favorable design. This configuration offers enhanced efficiency and improved performance. Additionally, it is determined that a solar multiple value of 1.7 and the integration of a 12-hour thermal energy storage system are optimal. This led to a 4-5 hour increase in the availability of daily power generation, thereby improving the reliability and flexibility of the CSP plant. The incorporation of fossil fuels into the hybrid CSP-Fossil plant results in a notable enhancement of the Capacity Utilization Factor (CUF). This improvement guarantees uninterrupted energy generation even when solar resources are limited. The implications of the findings are significant for the future development of CSP systems. These findings provide valuable insights into enhancing energy efficiency and tackling sustainability challenges.

Improving the calculation module for estimating pollutant emission from conventional and hybrid regional aircraft

For the aviation sector, it is extremely important to devise revolutionary solutions in the field of technology to restrain the potential impact of civil aviation on the environment to the level of the established strategic goals of ACARE (FlightPath2050). The introduction of innovative technologies (improvement of the combustion chamber, the introduction of electric hybrid power plants on airplanes, and the use of alternative aviation fuel) will ensure the sustainable growth of air transportation. To assess the effectiveness of advanced technologies, it is extremely important to have a model for calculating global/local emissions that takes into account the parameters of the flight path of conventional and hybrid aircraft, operational characteristics of the aircraft engine and hybrid powerplant, and the features of sustainable fuel. The improved module for calculating emission indices by combining the module for calculating the parameters of the flight path and the results of calculating the thermogas-dynamic calculation of the aircraft engine makes it possible to detect the influence of fuel consumption (engine thrust) on the values of the emission indices. This feature is representative for evaluating the efficiency of hybrid powerplants because the electrification of the aircraft fleet is primarily aimed at reducing fuel consumption. The analysis of simulation results reveals that the fuel consumption and EINOx are significantly reduced (for the climb stage – 25 %; for the descent stage – 30 %) for the hybrid AN26 compared to the conventional AN26. The specified operational measure, in the part of the low-pitch descend, significantly reduces EICO for the hybrid AN26 by an average of 50 % compared to the descend stage for the conventional trajectory. The results of calculations for the entire flight path demonstrate that the use of a hybrid power plant for An26 contributes to an average reduction of fuel consumption by 10 %, NOx emissions by 25 %, water vapor emissions by 10 %, and CO2 by 10 %.

Optimal sizing of hybrid PV–diesel–biomass gasification plants for electrification of off-grid communities: An efficient approach based on Benders’ decomposition

Nowadays, millions of people in remote areas do not enjoy an uninterrupted power supply due to the lack of connectivity to the main power grid. Under such circumstances, the only feasible way to access electricity is typically local power generation, often relying on diesel engine–generator sets or photovoltaic arrays. However, on many occasions, this configuration does not fully exploit all available local resources, including biomass. Indeed, most isolated areas have access to local biomass production from agricultural activities, which can be used for local electricity generation through gasification. This paper addresses this challenge by developing an innovative optimal sizing tool for hybrid power plants integrating biomass gasifiers, specifically designed for isolated areas with access to local biomass production. The novel approach models the particular features of biomass gasification technologies, including long on/off times or restrictive ramping limits. To this end, an efficient methodology based on representative weeks is proposed, which is combined with a solution strategy based on the multi-cut Benders’ decomposition, thus resulting in a tractable framework that can deal with a huge amount of data efficiently. One of the most salient features of the new proposal is the consideration of local biomass production, which is included in the methodology through an original algorithm. Accordingly, a certain amount of biomass is sourced locally, leading to more accurate and reliable results. The new methodology is applied to a benchmark off-grid community in Ghana. The results demonstrate that the use of gasifiers reduces the project cost notably (by 90%) driven by the reduced biomass cost, which can be supplemented by locally generated biomass from agricultural activities. In addition, this technology constitutes a clean source of energy, reducing the total CO2 emissions by 83% compared to a baseline case in which only diesel generators are used. Moreover, it is demonstrated that biomass gasification can effectively act as base load power generation technology to reliably cover most of the local demand, thereby enabling a clean and inexpensive dispatchable local power generation. Finally, a sensitivity analysis reveals that the economic feasibility of the plant is more sensitive to the biomass cost than the selling price of biochar, resulting in a 33% increment in the total project cost when the price of biomass increases from 0 to 0.4 $/kg. Nevertheless, gasification remains as the predominant power generation technology even under unfavorable prices.

Current Status, Sizing Methodologies, Optimization Techniques, and Energy Management and Control Strategies for Co-Located Utility-Scale Wind–Solar-Based Hybrid Power Plants: A Review

The integration of renewable energy sources, such as wind and solar, into co-located hybrid power plants (HPPs) has gained significant attention as an innovative solution to address the intermittency and variability inherent in renewable systems among plant developers because of advancements in technology, economies of scale, and government policies. However, it is essential to examine different challenges and aspects during the development of a major work on large-scale hybrid plants. This includes the need for optimization, sizing, energy management, and a control strategy. Hence, this research offers a thorough examination of the present state of co-located utility-scale wind–solar-based HPPs, with a specific emphasis on the problems related to their sizing, optimization, and energy management and control strategies. The authors developed a review approach that includes compiling a database of articles, formulating inclusion and exclusion criteria, and conducting comprehensive analyses. This review highlights the limited number of peer-reviewed studies on utility-scale HPPs, indicating the need for further research, particularly in comparative studies. The integration of machine learning, artificial intelligence, and advanced optimization algorithms for real-time decision-making is highlighted as a potential avenue for addressing complex energy management challenges. The insights provided in this manuscript will be valuable for researchers aiming to further explore HPPs, contributing to the development of a cleaner, economically viable, efficient, and reliable power system.

Stochastic optimization framework for hybridization of existing offshore wind farms with wave energy and floating photovoltaic systems

Due to the complementarity of renewable energy sources, there has been a focus on technology hybridization in recent years. In the area of hybrid offshore power plants, the current research projects mostly focus on the combinational implementation of wind, solar, and wave energy technologies. Accordingly, considering the already existing offshore wind farms, there is the potential for the implementation of hybrid power plants by adding wave energy converters and floating photovoltaics. In this work, a stochastic sizing model is developed for the hybridization of existing offshore wind farms using wave energy converters and floating photovoltaics considering the export cable capacity limitation. The problem is modeled from an investor perspective to maximize the economic profits of the hybridization, while the costs and revenues regarding the existing units and the export cable are excluded. Furthermore, to tackle the uncertainties of renewable energy generation, as well as the energy price, a scenario generation method based on copula theory is proposed to consider the dependency structure between the different random variables. Altogether, the hybridization study is modeled in a mixed integer linear programming optimization framework considering the net present value of the project as the objective function. The results showed that hybrid-sources-based energy generation provided the highest economic profit in the studied cases in the different geographical locations. Furthermore, the technical specifications of the farms have also been considerably improved providing more stable energy generation, guaranteeing a minimum level of power in a high share of the time, and with a better utilization of the capacity of the cable while the curtailment of energy is maintained within the acceptable range.

Research of an autonomous power source for elec-tric vehicles and their charging infrastructure

Research of an autonomous power source for elec-tric vehicles and their charging infrastructure

HyDesign: a tool for sizing optimization of grid-connected hybrid power plants including wind, solar photovoltaic, and lithium-ion batteries

Abstract. Hybrid renewable power plants consisting of collocated wind, solar photovoltaic (PV), and lithium-ion battery storage connected behind a single grid connection can provide additional value to the owners and society in comparison to individual technology plants, such as those that are only wind or only PV. The hybrid power plants considered in this article are connected to the grid and share electrical infrastructure costs across different generation and storing technologies. In this article, we propose a methodology for sizing hybrid power plants as a nested-optimization problem: with an outer sizing optimization and an internal operation optimization. The outer sizing optimization maximizes the net present values over capital expenditures and compares it with standard designs that minimize the levelized cost of energy. The sizing problem formulation includes turbine selection (in terms of rated power, specific power, and hub height), a wind plant wake loss surrogate, simplified wind and PV degradation models, battery degradation, and operation optimization of an internal energy management system. The problem of outer sizing optimization is solved using a new parallel “efficient global optimization” algorithm. This new algorithm is a surrogate-based optimization method that ensures a minimal number of model evaluations but ensures a global scope in the optimization. The methodology presented in this article is available in an open-source tool called HyDesign. The hybrid sizing algorithm is applied for a peak power plant use case at different locations in India where renewable energy auctions impose a monetary penalty when energy is not supplied at peak hours. We compare the hybrid power plant sizing results when using two different objective functions: the levelized cost of energy (LCoE) or the relative net present value with respect to the total capital expenditure costs (NPV/CH). Battery storage is installed only on NPV/CH-based designs, while the hybrid design, including wind, solar, and battery, only occurs on the site with good wind resources. Wind turbine selection on this site prioritizes cheaper turbines with a lower hub height and lower rated power. The number of batteries replaced changes at the different sites, ranging between two or three units over the lifetime. A significant oversizing of the generation in comparison to the grid connection occurs on all NPV/CH-based designs. As expected LCoE-based designs are a single technology with no batteries.

Modeling and optimization of hybrid geothermal-solar energy plant using coupled artificial neural network and genetic algorithm

Avoiding solar thermal energy storage reduces efficiency in hybrid solar-geothermal energy systems, making them impractical. To address this challenge, a synergistic approach involves the integration of these resources in the construction of hybrid power plants. An experiment is conducted with five independent variables: evaporator temperature, separator pressure, inlet pressure of turbine 2, effectiveness of vapor generator 1, and desalination mass ratio. Unlike most energy systems that rely on a single optimization pattern, this study utilizes response surface methodology (RSM) to design and gather data through simulation. Additionally, an artificial neural network (ANN) is employed alongside RSM to establish mappings from independent variables to response variables, including thermal efficiency and levelized cost of product. The selection of objective functions derived from ANN is predicated on their commendable performance, denoted by an R-squared value of 1. Furthermore, a cost function is formulated with the dual aims of maximizing thermal efficiency and minimizing the levelized cost of product. This function is subsequently optimized through the application of genetic algorithms (GAs). The findings elucidate that specific parameter values—namely, a desalination mass ratio of 2.43, separator pressure of 455.77 kPa, effectiveness of vapor generator 1 of 0.82, inlet pressure of turbine 2 of 12000 kPa, and evaporator temperature of −11.51 ℃—conducive to the optimal condition are identified, yielding a thermal efficiency of 30.47% and a levelized cost of product of 13.04 $/GJ. This endeavor is anticipated to furnish an algorithmic framework not only for modeling hybrid plants but also for optimizing electrical power generation processes.

Assessing the performance of hydro-solar hybrid (HSH) grid integration: A case study of Bui Generating Station, Ghana

Renewable energy sources (RES) are rapidly expanding as a result of energy security and environmental concerns. Despite their numerous benefits, they pose significant challenges to power grid operation. Ghana is dedicated to reaching a 10 % renewable energy mix target by 2030 to promote low-emission development. Ghana has the first hybrid power plant made up of 400MW hydropower plant and 50 MW solar PV plant supplying power to the national grid. The study designs a hydro-solar hybrid system configuration for Ghana's Bui generation unit, using data from the 50 MW ground-mounted solar PV and 133.33 MW hydropower units to assess the performance and challenges of the hydro-solar hybrid system at the Bui Generating Station. Methodology involves modeling and simulation in the DIgSILENT power factory software environment. Utilizing quasi-dynamic simulations, the study investigates variations in active power generation, voltage fluctuations, grid losses, and reactive power generation. Results highlight technical challenges such as voltage fluctuations and power loss, and propose mitigation measures. Comparisons between simulated and field data reveal discrepancies attributed to factors such as temperature effects, dust accumulation, and conductor resistance. Mitigation strategies are proposed, including energy storage expansion, smart grid implementation, advanced control techniques, FACTS device deployment and grid monitoring improvements. Despite limitations in data availability and simulation accuracy, the study underscores the system's reliability and provides insights for enhancing renewable energy integration in the region. Generally, the study contributes to advancing renewable energy integration efforts, with implications for sustainable development and climate action in Ghana and West Africa at large.

Hybrid power plant using synchronization controller system to save electricity cost

The application of hybrid energy power plants is one solution to save electricity cost in buildings of government agencies, industries, and universities. The problem with using hybrid power plants that use solar energy sources and paid electricity networks is that sunlight energy cannot produce energy consistently from sunrise to sunset. Maximum energy can only be obtained when the sun is vertically acceptable to the photovoltaic (PV). This results in electrical loads having to be disconnected or switched back to the grid. The application of an electrical power sharing system synchronization controller system (SCS) can automatically regulate the use of electrical energy to low PV energy. The results of research on the application of hybrid PV using the SCS system with a rooftop solar panel system at the Gorontalo State University Building can produce a total electrical power of 600,975 kWh. The need for electrical power from January to September 2022 amounted to 859,151 kWh. The SCS hybrid power plant can reduce the use of paid electrical energy and its costs by 83.60%. The investment, operational, and maintenance cost requirement is IDR 10,747,886,801. The return on investment (ROI) analysis results show that the return on investment can be achieved for up to 34 years.