Cost Of Electrical Energy Research Articles

Photocatalytic removal of AR14 from aqueous solutions under visible light irradiation by synthesising sugarcane bagasse magnetic graphene oxide

ABSTRACT At this present investigation, sugarcane bagasse magnetic graphene oxide (SCBMGO) was synthesised in several stages and used to remove Acid Red 14 dye under LED visible light. XRD, FT-IR, SEM, EDX, VSM and pHPZC analyses demonstrated the structural characteristics. The effect of variables like the pH, catalyst dose, dye concentration, hydrogen peroxide, purging gases, organic compounds, ionic strength, and comparison of different processes, radical scavengers, and reusability on AR14 removal efficiency were investigated. The most removal efficiency occurred under ideal situation: [AR14]0 = 10 mgL−1, SCBMGO dosage = 0.5 gL−1, pH = 3, hydrogen peroxide = 5 mM, and contact time equal to 120 minutes. Except for the dose, the efficiency of photocatalytic removal of AR14 decreased with the addition of other variables. AR14 photocatalytic removal obeyed the pseudo-second-order reaction kinetic. The EEO value for LED/SCBMGO (59.62 kWh/m3) process, as a function of removal proficiency, illustrated that this process was elevated productivity and diminished the cost of electrical energy consumed by the system. The highest removal efficiency of AR14 occurred in the LED/SCBMGO process (89.85%). In addition, recycling test efficiency was the same at the beginning, and the 6th stage. The removal efficiency of AR14 in drinking water was (71.45%). SCBMGO, as an effective and environmentally friendly catalyst, can be used in removing AR14 dye and organic pollutants of aqueous environments under the LED visible light.

Возможный вариант повышения представительности тарифа на продукцию естественных монополистов

В статье рассмотрен вариант повышения представительности тарифов, через выделение части, связанной с обеспечением готовности объекта к эксплуатации и части, обусловленной затратами на производство требуемого объема продукции (услуги). Также показано, что использование приведенной величины потерь на единицу поверхности или на единицу протяженности больше соответствует процессу потерь продукции при доставке до потребителя. Рассмотрен вариант определения стоимости тепловой и электрической энергии при их совместном производстве (когенерация), улучшающий их достоверность.

Does the cost of energy matter for innovation? The effects of energy prices on SME innovation in Sub-Saharan Africa

PurposeEnergy and environment has gained traction within the field of entrepreneurship literature, but a comprehensive empirical study that examines the relationship between the cost of energy and small- and medium-sized enterprise (SME) innovation is an omission. Therefore, this novel study aims to examine the relationship between the cost of energy and SMEs innovation in Sub-Saharan Africa (SSA) by first examining the differential impact of the various generation sources on the price of electric energy. This research has enabled us to investigate and understand the transmission mechanism of increasing/decreasing electricity price on innovation decisions and activities of SMEs in SSA.Design/methodology/approachUsing quantitative approach, with the data from the World Bank Enterprise and Innovation Follow-up Surveys, the study utilises a Tobit model to test whether the generation mix (renewable and non-renewable generation sources) increases or decreases electricity prices and examine the impact of the cost of electric energy on SMEs innovation in SSA.FindingsThe findings of this study shows that the cost of electricity affects negatively on SMEs innovation decision and activities of SMEs in SSA. The impact of renewables on the price of electricity has a larger magnitude relative to that of non-renewables. This finding has implications for policy makers promoting renewable energy without a policy design to tackle the unintended price effect of promoting renewable energy.Originality/valueThis is the first study to introduce cost of energy into an innovation model and to empirically examine the role of cost of energy for innovation activities of SMEs in SSA. Further, it examines the sources of generation on electricity price in SSA. The study contributes towards the empirical literature, and the findings also have implication for policy makers regarding the unintended consequences of promoting the transition to low-carbon electricity generation sources on SMEs via the cost of doing business implication.

Electric Energy Management for Plug-in Electric Vehicles Charging in the Distribution System by a dual cascade scheduling algorithm

This paper presents an algorithm for plug-in electric vehicles (PEVs) charging in the three-phase distribution system for residential houses. It aims to prevent violent voltage level deviation and increasing losses on the three-phase distribution system due to uncontrolled charging and allocate power to each plug-in electric vehicle. The algorithm is comprised of two processes. The first process is power limitation and limited power of load imbalance by if-else rules, while the second process is power allocation to each PEV by the dual cascade scheduling algorithm which is the integration of tasking scheduling algorithms. A 100 kVA distribution transformer and 30 houses are defined in the simulation situation. Also, the available PEVs in single-phase, two-phase, and three-phase systems are assigned for verification of the proposed algorithm. Root-mean-square deviation (RMSD) referred to the satisfaction of PEV owners, total PEVs charged energy, and the average percentage of achieved charging time, as the result indicators. The results show the proposed algorithm can provide good results without rejected PEVs charging. Furthermore, this paper also displays the analysis of voltage level, percentage of voltage unbalance factor, and loss in the distribution system. In the future, coordination with home appliances to gain a high load margin or electric energy cost control will be improved in the proposed algorithm

On the use of thermal energy storage in solar-aided power generation systems

The solar-aided power generation (SAPG) technology has been proven to be one of the most efficient ways to integrate solar thermal energy into coal-fired power plants. An open question is whether to integrate the SAPG plant with a thermal energy storage system (TES). Conventionally, most SAPG plants are not designed to include TESs due to high costs and challenges related to the intermittent nature of solar energy. To address this question, a realistic case study utilizing a 330MWe SAPG plant is investigated in this paper. The simulation shows that when the SAPG plant uses a TES with a proper regulation strategy, the energy efficiency of the SAPG can be increased by 2.5% and the levelized cost of electric energy (LCOE) can be reduced by 0.27 cents/kWh. A well-regulated TES does not deteriorate the economic performance of the SAPG plant here and has a positive impact on its operational safety (especially under sudden irradiance change). To the best of authors’ knowledge, this is the first time to study the operational strategies of TES (based on the operating characteristics of the SAPG systems) and to combine them with the TES’s size optimization to maximize the techno-economic performance of the SAPG plant.

Home Energy Management Strategy-Based Meta-Heuristic Optimization for Electrical Energy Cost Minimization Considering TOU Tariffs

It is well documented that both solar photovoltaic (PV) systems and electric vehicles (EVs) positively impact the global environment. However, the integration of high PV resources into distribution networks creates new challenges because of the uncertainty of PV power generation. Additionally, high power consumption during many EV charging operations at a certain time of the day can be stressful for the distribution network. Stresses on the distribution network influence higher electricity tariffs, which negatively impact consumers. Therefore, a home energy management system is one of the solutions to control electricity consumption to reduce electrical energy costs. In this paper, a meta-heuristic-based optimization of a home energy management strategy is presented with the goal of electrical energy cost minimization for the consumer under the time-of-use (TOU) tariffs. The proposed strategy manages the operations of the plug-in electric vehicle (PEV) and the energy storage system (ESS) charging and discharging in a home. The meta-heuristic optimization, namely a genetic algorithm (GA), was applied to the home energy management strategy for minimizing the daily electrical energy cost for the consumer through optimal scheduling of ESS and PEV operations. To confirm the effectiveness of the proposed methodology, the load profile of a household in Udonthani, Thailand, and the TOU tariffs of the provincial electricity authority (PEA) of Thailand were applied in the simulation. The simulation results show that the proposed strategy with GA optimization provides the minimum daily or net electrical energy cost for the consumer. The daily electrical energy cost for the consumer is equal to 0.3847 USD when the methodology without GA optimization is used, whereas the electrical energy cost is equal to 0.3577 USD when the proposed methodology with GA optimization is used. Therefore, the proposed optimal home energy management strategy with GA optimization can decrease the daily electrical energy cost for the consumer up to 7.0185% compared to the electrical energy cost obtained from the methodology without GA optimization.

Dynamic simulation and parametric analysis of green roofing in buildings

Enhancing energy efficiency and performance of the buildings and improving the air quality are acquisition during the cooling and heating seasons. According to the 2010 report by General Electricity Company of Libya, electrical energy consumption by residential sector account for approximately 39% of total demand in Libya. The green roof technologies in buildings are one of the main methods for using energy economically and reducing CO2 emission. The economic parameters such as the vegetation thickness and its thermal conductivity for the green roof, the electrical energy cost, coefficient of performance and EER all affect CO2 emission and total cost of the buildings. This study focuses on the impact of these parameters on the application of green roofs as well as degerming the optimum vegetation thickness and thermal conductivity of vegetation layer. Tripoli's degree days were used as one of methods to achieve these calculations or the results. The green roof and mathematical models were performed to find energy savings, and payback, and CO2 reductions. This study focuses on investigating these parameters that affect the green roof for external building based on life-cycle cost analysis (an economic model). As a result, the total cost increased from 6.7 to 23.05 $/m2; while CO2 emission decreased from 2.5 to 1.52 kg/m2/years with increasing the electricity costs which includes the effects of Interest rate on CO2 emission and total cost. Total cost decreased from 16.7 to 14.9 $/m2; while CO2 emission increased from 1.85 to 1.94 kg/m2/years with increasing the Interest. An increase in COP (Coefficient of Performance) and EER (Energy Efficiency Ratio) causes the CO2 emission to decrease from 2.2 to 1.51 kg/m2/years and from 2.08 to 1.37 kg/m2/year and total cost to decrease from 18.3 to 12.9 $/m2 and from 17.4 to 11.76 $/m2. The total cost and CO2 emission are increased from 13.7 to 16.5 $/m2 and from 0.34 to 1.74 kg/m2/years with increasing the thermal conductivity of vegetation. And the effects of degree day on CO2 emission and total cost, the total cost and CO2 emission are decreased from 18.6 to 14.67 $/m2 and from 2.45 to 1.55 kg/m2/years with increasing the degree day.

HEAT BALANCE OF COMBINED HEAT EXCHANGER AERODYNAMIC HEATING DRYERS

Today, the use of aerodynamic dryers for drying various types of fruit crops is very current. In them, the electric energy spent on the drive of the centrifugal fan is transformed into thermal energy due to the mutual friction of the air flows circulating in the closed chamber. In order to increase the energy efficiency of the drying process, the heat of the waste drying agent was used in the research. The presented dryer was equipped with a combined heat exchanger. In order to predict the thermal performance of the combined heat exchanger depending on external factor variables, the dependence of the temperature of the fresh drying agent at the outlet of the combined heat exchanger on the dryer operation time is theoretically determined on the basis of the heat balance equation. The air solar collector in the combined heat exchanger made it possible to increase the temperature of the drying agent at the outlet by another 10oC without extra costs of electrical energy. A comparative analysis of the results of experimental and theoretical studies showed their high convergence.

Сравнение энергетической эффективности грузовых электровозов переменного тока с коллекторным и асинхронным тяговым приводом

Electric locomotives with asynchronous traction drive are operated on the Russian road network in passenger and freight traffic. The advantage of such a drive is a large specific power. At first glance, electricity consumption of an electric locomotive with asynchronous traction drive should be less than that of an electric locomotive with a collector traction drive. The same is declared by manufacturers of traction rolling stock [1, 2]. But the answer to the question which electric locomotive is more economical in freight traffic: with a collector or asynchronous traction drive? - is far from being unambiguous [3, 4, 5]. In order to determine which electric locomotives have the best energy efficiency regarding the traction drive, a comparison of electric energy costs for traction of freight trains by electric locomotives of the VL80S series with collector traction drive, operated in two- and three-section versions, and a promising two-section electric locomotive of the 2ES7 series with asynchronous traction drive was performed. The energy efficiency assessment was carried out using methods based on elements of mathematical statistics and probability theory, including estimation of the distribution parameters of the studied quantities, statistical hypothesis testing and variance analysis. This article presents the main results of the research carried out at the testing area of the Gorky Railway during the pilot operation of the 2ES7 series electric locomotive on the Druzhinino - Vekovka section.

Performance modelling and optimization of three vacuum-enhanced membrane distillation modules for upscaled solar seawater desalination

Membrane distillation using multi-envelope modules in vacuum enhanced air gap (V-AGMD) operation has been demonstrated as the best alternative to the current thermal desalination technologies. This work presents for the first time the use of response surface methodology (RSM) to model and validate the performance of V–AGMD operation for seawater desalination in three multi-envelope modules with different internal designs. Permeate productivity (PFlux) and condenser outlet temperature (TCO) were modelled and validated from results obtained in steady-state experiments, considering the evaporator inlet temperature, the condenser inlet temperature, and the feed flow rate as inputs. To gain accuracy in the estimations of thermal efficiency regarding previous works, a novel strategy was applied, consisting in calculating the specific thermal energy consumption (STEC) using the models of PFlux and TCO, developed from direct measurements. The models of the three modules were used to search the optimal operating conditions that minimize the levelized cost of water (LCOW) in a large-scale MD plant under different scenarios. Different costs of thermal and electrical energy were considered and their influence on the number of modules required in the facility was also discussed.

Power Monitoring and Passenger Classification on Logistics Elevator

The elevator has an important role in assisting transportation and logistics activities in a building. However, if the elevator is not used wisely, then the power consumption will be inefficient. A policy of elevator usage is necessary to ensure the effectiveness of elevator power consumption. Therefore, in this study, elevator power consumption monitoring is proposed. The power consumption behavior can be learned so a suitable policy can be made accordingly. Two elevators in Telkom Campus Surabaya are monitored to understand the daily electrical energy usage. Internet of Things (IoT) based real-time power monitoring system is used to monitor the electrical energy usage of the elevator. A raspberry pi is used to collect the data of electrical usage via a current and power sensor. The data is sent to the cloud, which later is displayed through a dashboard website. The result shows that the elevator usage on weekdays and weekends is different. The peak power on weekdays is obtained from 15.00 to 16.00, meanwhile, on weekends, the peak occurs from 9:00 to 10:00. On weekdays, the total power consumed by the elevator is 51.74kW, while on weekends, it is 11.94kW. Restrictions on the use of lifts are applied to periods when the lift has few passengers and has a short distance. From the results obtained, the total power consumed can decrease by an average of 37%. It is expected that the suggested policies can reduce elevator power consumption and the monthly cost of electrical energy.

Re-Allocation of Distributed Generations Using Available Renewable Potential Based Multi-Criterion-Multi-Objective Hybrid Technique

Integration of Distributed generations (DGs) and capacitor banks (CBs) in distribution systems (DS) have the potential to enhance the system’s overall capabilities. This work demonstrates the application of a hybrid optimization technique the applies an available renewable energy potential (AREP)-based, hybrid-enhanced grey wolf optimizer–particle swarm optimization (AREP-EGWO-PSO) algorithm for the optimum location and sizing of DGs and CBs. EGWO is a metaheuristic optimization technique stimulated by grey wolves, and PSO is a swarm-based metaheuristic optimization algorithm. Hybridization of both algorithms finds the optimal solution to a problem through the movement of the particles. Using this hybrid method, multi-criterion solutions are obtained, such as technical, economic, and environmental, and these are enriched using multi-objective functions (MOF), namely minimizing active power losses, voltage deviation, the total cost of electrical energy, total emissions from generation sources and enhancing the voltage stability index (VSI). Five different operational cases were adapted to validate the efficacy of the proposed scheme and were performed on two standard distribution systems, namely, IEEE 33- and 69-bus radial distribution systems (RDSs). Notably, the proposed AREP-EGWO-PSO algorithm compared the AREP at the candidate locations and re-allocated the DGs with optimal re-sizing when the EGWO-PSO algorithm failed to meet the AREP constraints. Further, the simulated results were compared with existing optimization algorithms considered in recent studies. The obtained results and analysis show that the proposed AREP-EGWO-PSO re-allocates the DGs effectively and optimally, and that these objective functions offer better results, almost similar to EGWO-PSO results, but more significant than other existing optimization techniques.

Optimal switching control of an air to air heat pump operating under variable time-based electricity pricing

The electrical energy related expenditure in residential buildings may become substantial when it comes to peak pricing with regards to the Time-of-Use (TOU) tariff structure. Effective energy management strategies should be implemented at the large residential buildings scale to conserve energy, which in turn, can assist in relieving the burden on the national energy grid. This paper presents an optimal switching control strategy for an air to air heat pump used to provide space heating to a typical two-bedroom residential building in which two occupants are residing, is presented. Accurate and reliable data, which is obtained from a local weather station, is applied to the established model. The main purpose of this paper is to develop an optimal control algorithm, which minimizes the running energy cost of the air to air heat pump under time-based pricing and the level of discomfort with regards to the desired building temperature. Additionally, various exogenous disturbances, such as the ambient temperature, amount of occupants present and the amount of lights switched on during each moment in time, are taken into account. The thermostat-based control of an air to air heat pump which is adopted as the first baseline, illustrates a daily electrical energy cost of USD 4.8. The timer with thermostat-based control method which is adopted as the second baseline illustrates a daily electrical energy cost of USD 4.78. The optimal switching control of an air to air heat pump illustrates a daily electrical energy cost of USD 4.48. Therefore, the optimal switching control model achieved a 6.67% cost savings in electricity compared to the first baseline and a 6.28% cost savings in electricity to the second baseline.

Optimization of electrical energy waste in house using smart appliances management System-A case study

A substantial quantity of energy is consumed by residential buildings. The appliance runs on a set schedule in most of the houses. As a result, the appliance remains switched ON whether user need it or not. This results in significant energy waste and high electricity bill. To address this problem a smart energy management system (SEMS) has been proposed that generates switch ON/OFF control actions for appliances depending on physical characteristics. The SEMS optimize the energy waste and energy cost by reducing the operative time of the appliances without affecting the user comfort. The SEMS further reduces the electricity bill, if public utility offer the time varying electricity price for the residential consumers. A residential building microgrid system with smart appliances, rooftop mounted photovoltaic system, energy storage (electric car, and battery) linked to the public utility is regarded to assess the performance of the SEMS. The performance of the SEMS is tested for both flat and real time electricity price system. The potentiality and functioning of SEMS are verified by measuring energy and environmental performance, as well as user comfort and acceptance of the control system, throughout the course of a normal day. The findings show a potential for energy savings of 31% and a electricity energy cost reduction by 35%. The appliance smart scheduling and management of appliances according to the renewable power generation or the grid electricity cost are reflecting the novality and originality of the proposed SEMS system.

Determinants of Electrical and Thermal Energy Consumption in Hospitals According to Climate Zones in Poland

Energy use in hospitals is higher than in other public buildings, so improving energy efficiency in healthcare buildings is a significant challenge in this sector of engineering. For this, it is necessary to know the various determinants of energy consumption. Until now, the main factor affecting energy consumption in healthcare facilities studied in the literature was hospital capacity. However, the commonly used variables connected with hospital size and the number of beds do not take into account the medical activities carried out in these buildings. Assuming that energy consumption in hospitals is multiple and shaped by many factors that overlap, not only on an individual level but also on a higher scale level, this study devises a more integrated approach to its determinants. This study aims to investigate the determinants of electrical energy costs (EEC) and thermal energy costs (TEC) in Polish hospitals with regard to factors related to their size, work intensity and climate zones. The analysis was carried out using financial and resource data from all Polish hospitals for the years 2010–2019. The study used a multivariate backward stepwise regression analysis. In order to use climate as a moderating variable, a sample of Polish hospitals from 16 Polish NUTS 2 was divided into four climate zones. This article provides new empirical evidence on the determinants of electricity consumption in Polish hospitals related to their size and medical activity, taking into account climate zone as a moderating variable. The results of the analysis show that both electricity and heat consumption in hospitals are positively related to the number of doctors, beds and the number of medical operations performed. As expected, larger hospitals seem to use more energy. Moreover, there is regional heterogeneity in energy consumption in hospitals related to the climatic zone in which they operate. The conducted analysis shows that Polish hospitals located in the warmest climatic zone are characterized by higher energy consumption than hospitals in the coldest zone. It especially regards EEC in surgery hospitals. The warmer the climate zones, the higher intensity in terms of the number of surgeries, the higher EEC. In terms of nonsurgical hospitals, the influence of climate zone on EEC was not observed. Knowing the factors influencing energy consumption in hospitals can facilitate the correct adoption of an energy-saving strategy in the health sector, which is a reasonable response to climate change and supports a healthy and sustainable future.

Nonlinear observer for electromagnetic position estimation using active current control

This paper proposes a novel electromagnetic position estimation system suitable for piston-cylinder actuators using active current control. The inexpensive non-contacting position measurement system is composed of an electromagnet on the stationary cylinder and a magnetic sensor on the piston rod. The measured amplitude of an alternating magnetic field is used to estimate piston position. The current supply to the electromagnet needs to be actively controlled so as to increase monotonically with piston position, allowing for sufficient magnetic sensitivity along the whole stroke length. Since the position itself is unknown, this poses a challenging coupled estimation-control problem. A nonlinear state observer is designed based on Lyapunov theory to ensure both asymptotically stable position estimation and current modulation. The desired current profile is optimized using a direct trapezoidal collocation method to achieve accurate position estimation even for regions with low magnetic sensitivity. The active position system is experimentally validated using a piston-cylinder setup with 20 cm stroke length. Experimental results show that the active position estimation system can achieve 1% measurement accuracy all through the stroke length while a system with constant current consuming the same average power shows nearly twice the estimation error. Through active control of the current supply, the electromagnetic position estimation system offers the potential to either improve measurement accuracy at locations with weak sensitivity, extend the overall position sensing range, or to save electrical energy cost.

Comparison of cost indicators of Ukrainian wind farms with cost indicators of wind energy global producers

Efficiency improvement in wind conversion field is the most critical scientific-and-technical problem, which is chiefly settled by increasing the power of wind turbines. A new technique was pioneered for determining the efficiency of wind turbines operation in the wind conditions of the Northern Black Sea region of Ukraine. It is found out that the main parameters that have an impact on the cost of electricity are as follows: the cost of a wind turbine itself and annual electric energy production. The cost indicators of wind turbines of the Ukrainian wind farms were defined in the wind conditions of the Northern Black Sea region in 2018, according to which it was ascertained that the cost of electric energy generated in Ukraine was by 17 % cheaper as compared to the world cost value. In illustration of application of the first ever developed technique, we have made the assessment of effective operation of the Ukrainian wind farms in the years of 2019 – 2020. The results obtained bear compelling evidence as to the correlations between the cost of produced electric energy and the size of wind turbines. In view of the above, application of wind turbines of super-large sizes in the conditions of the Northern Black Sea area of Ukraine (as well as in other regions of the world) is hardly expedient due to increase in the cost of electric power generated by them.

Electrochemical comparative study of Ti/Ta2O5/Pt‐RuO2‐IrO2 and Ti/Ta2O5/Pt anodes: Stability, service lifetime, and electrooxidation performance

AbstractThis work aimed to compare the stability, service lifetime, and electrooxidation performance of Ti/Ta2O5/Pt‐RuO2‐IrO2 (PRI) and Ti/Ta2O5/Pt (Pt) electrodes thermally prepared. The service lifetime study performed under 410 mA/cm2 in a 9N H2SO4 showed that PRI electrode had six (06) times longer lifetime than the Pt electrode. Bulk electrolysis experiments were carried out on Pt and PRI under 20 mA/cm2. COD removal, current efficiency (CE), specific energy consumption (SEC), electrical energy cost, and anode efficiency ( ) were estimated. Both electrodes lead to the conversion of the parent compounds. However, the Pt electrode was best suited for amoxicillin (AMX) electrooxidation with 36.89% by COD removal in KClO4 0.1 M. Besides, the PRI electrode provided the best performances for the AMX electrooxidation (8.15%) and telebrix (TLX) (29.28%) in HClO4 0.1 M and KClO4 0.1 M, respectively. The presence of NaCl enhanced significantly the organic compound electrooxidation in terms of COD removal, CE, SEC, electrical energy cost, and on the both electrodes. This is probably because of the co‐action of direct and indirect (by active chlorine) oxidations. But the PRI electrode presented the best performance in the presence of chloride ions. In summary, the experimental conditions can determine the performance of an anode.

Design of Power Monitoring and Electrical Control Systems to Support Energy Conservation

The increasing demand for electrical energy and the decreasing supply of fossil fuels in recent years have increased the cost of electrical energy. So that the culture of saving electrical energy is a habit that must be cultivated in the community. On the other hand, energy-saving behavior cannot be realized massively without a support system that can control energy use. With these concerns, it is necessary to develop a method that encourages a culture of saving electrical energy. This paper proposes a system that supports active energy efficiency methods that can support an energy-efficient culture. This system is an electric power monitoring system that is integrated with a smart electrical panel that continuously monitors the use of electrical energy and can control electrical loads automatically, record electricity usage, provide comprehensive reports and analyze energy usage. The method used to carry out this research is research and development. This research has produced a prototype of electrical power control and monitoring system that has a smart panel based on a raspberry PI 3 and PZEM-004t power energy meter. The monitoring system performs and executes automatic control of electrical loads. The system can also provide reports in the form of data monitoring in daily, weekly, monthly or annual period. From the test results, it can be concluded that the system can work well. This research is expected to contribute to providing a system that can support government efforts in saving energy.

Planning for clean energy utilization in the provision of clean water on Barrang Caddi Island

Barrang Caddi Island has a Diesel Power Plant (Genset) of 340 kVA which is operated by self-management by the local community and cannot meet the electricity needs of the community because the Genset only operates for 8 hours at night. The discontinuity of the Genset operation on Barrang Caddi Island makes the Ready to Drink Water Machine or Arsinum on the island to provide its own electrical energy which is supplied by a 15 kVA Genset machine that operates 24 hours/day. The drinking water produced by Arsinum is clean water but has the potential to produce environmental pollution because the power plant used is diesel fuel. In addition, the cost of electrical energy will also increase due to the increasing price of oil. Therefore, planning is carried out to optimize the operation of Arsinum by making several models of power plants that can supply the machine. From the planning results, it was found that the optimal Hybrid Power Plant (Genset – Solar Power Plant) model to be applied so that it could supply electrical energy of 128092 kWh/year. The advantage of this model is that the operating costs are small and can contribute to renewable energy by 33%.