Stand-alone Hybrid Renewable Energy System Research Articles

Optimal sizing of standalone hybrid renewable energy system based on reliability indicator: A case study

The economical electrification of rural settlements extensively utilizes renewable energy sources. In recent years, the deployment of solar photovoltaic, wind turbine, and biomass gasifier-based power generation technologies for electricity accessibility in remote regions has received greater prominence. This paper presents an optimal component design of a hybrid solar PV-wind and battery system along with a biomass gasifier to provide continuous electricity for rural communities of Uttarakhand, India. In this study, a recently developed population-based giza pyramids construction (GPC) methodology is applied to determine the optimal component sizing. The findings of the GPC method are contrasted with the particle swarm optimization (PSO) methodology to assess the effectiveness of the proposed method. The annualized system cost and levelized cost of energy of the hybrid renewable energy system have been minimized subject to technical reliability indicators such as loss of power supply probability and renewable fraction.Moreover, a systematic exploration of the system has been conducted to assess its optimal feasibility across different values of power loss probability ranging from (0% to 4%). The simulation indicates that the proposed method adeptly identifies globally optimal values, leading to a $177 decrease in annual cost and 8% reduction in average simulation time compared to PSO. The research reveals that the balanced point (relative attainment), where system reliability and cost-effectiveness intersect optimally, is achieved at a 3% power loss level, resulting in the most significant cost reduction of $199 compared to other probability levels.

An energy-economic analysis of a hybrid PV/wind/battery energy-driven hydrogen generation system in rural regions of Egypt

The production of storable green hydrogen via water electrolysis, driven by renewable energy, is an attractive alternative for paving the way for a carbon-free business and a feasible path to energy sustainability. This study investigated the technical and economic feasibility of a stand-alone hybrid renewable energy system (PV/WT-BS/WE) that relied on a photovoltaic (PV), wind turbine (WT), battery storage (BS) and water electrolyzer (WE) to generate electricity and green hydrogen in three Egyptian regions with different climate. The targeted outcomes in terms of electricity and hydrogen generation, system efficiency, and cost analysis are computed, displayed, and compared with other hydrogen production scenarios with various working policies includes (PV-BS/WE), (PV/WT-WE), and (PV-WE) utilizing MATLAB/Simulink computer simulation. According to the findings, the PV/WT-BS/WE scenario is more advantageous in Ras Ghareb as an optimal site, with a yearly generation of electricity, hydrogen of (16,984.64 kWh, 3127.65 m3), and overall system average efficiency of 14.41 %. A favorable LCOH of 2.22 $/kg found in Ras-Garb, in northeastern Egypt. This study could guide authorities in developing various national-scale hydrogen production systems since it outlines the techno-economic features of various scenarios across the country. Additionally, the effectiveness of the suggested system is evaluated against existing literature.

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

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

Sizing and energy management of standalone hybrid renewable energy systems based on economic predictive control

This paper aims to design and run a standalone hybrid renewable energy System (HRES) feeding residential building load. The suggested HRES encompasses photovoltaic panels and wind turbines as energy sources, combined with a hydrogen subsystem and a bank of batteries for energy storage. The meteorological input data includes irradiance, temperature, and wind speed for four seasonal weeks. These data sets are collected for a rural site situated in the town of Ras Munif, northern Jordan. The load profiles characterize a selected benchmark residential building. Consequently, a bi-level mixed integer nonlinear programming (BMINLP) problem is formulated to incorporate the designing problem with the energy management process. The upper level represents the sizing problem, while the lower level problem denotes the energy management strategy (EMS). Each problem has its independent objective function, constraints, and optimization variables. The EMS is an economic-based single objective optimization problem expressed as a mixed integer linear programming (MILP) problem. On the contrary, a mixed integer nonlinear programming (MINLP) approach frames the sizing problem to optimize a techno-economic-based multi-objective function. The interaction between the two problems is that the lower problem is an embedded constraint of the upper problem. Moreover, the candidate solutions from the upper problem are treated as fixed parameters in the lower problem. A multi-objective genetic algorithm is used to execute the overall problem by the MATLAB toolbox. The technical and economic performance parameters, including the investment cost, maintenance, operating costs, and others, are assessed based on the best findings. The key finding demonstrates that the summer week has the lowest total cost and energy loss factor, with around 132,000 $ and 0, respectively. Furthermore, the findings reveal that the entire system's energy loss factor for each sample period is less than 0.0009. This value is substantially less than the permitted limit of 0.01.

Evaluation of stand-alone hybrid renewable energy system with excess electricity minimizer predictive dispatch strategy

The prioritization of economic and reliability objectives in the optimization of stand-alone microgrids and off-grid hybrid renewable energy systems (HRES) has led to optimum systems with high excess electricity and low self-consumption indexes. Managing surplus power after charging the storage bank without imposing a negative impact on energy cost (COE) and environmental factors is a challenge for off-grid applications. In recent years the development of predictive dispatch strategies (PD), improves the energy efficiency in HRES compared to conventional dispatches such as load following (LF). However, the mismatch between renewable power production and demand profiles prohibits high excess electricity reduction. In this study, a novel dispatch strategy, entitled modified predictive dispatch (MPD), is developed by integrating a proactive approach to charging/discharging the battery bank and demand-side management (DSM) based on the upcoming short-term excess electricity profile. The results showed that with the participation of an average of less than 20 % deferrable components and the possibility of load shifting for less than 3 h, the excess electricity can be reduced to about 7.5 %, compared to 41 % and 18.5 % for LF and PD strategies, respectively. Furthermore, the self-utilization index of surplus power improved from less than 25 % to about 90 %. These improvements were achieved through the MPD strategy, which reduced COE by more than 10 %, reaching about 0.12 $/kWh without any significant effect on emission factors. The sensitivity analysis indicated that achieving an excess electricity self-utilization index of over 80 % requires a load-shifting possibility of more than 2 h and a deferrable load participation of about 10 % in the DSM approach. Therefore, results approved the effectiveness of the proposed dispatch strategy in high renewable penetration systems, even with low levels of participation by power consumers.

Energy management and sizing of a stand-alone hybrid renewable energy system for community electricity, fresh water, and cooking gas demands of a remote island

Research into the off-grid hybrid energy system to provide reliable electricity to a remote community has extensively been done. However, simultaneous meeting electric, freshwater, and gas demands from the off-grid hybrid energy sources are very scarce in literature. Power- to-X (PtX) is gaining attention in recent days in the energy transition scenarios to generate green hydrogen, the primary product of the process as an energy carrier, which is deemed to replace conventional fuels to reach absolute carbon neutrality. In this study, renewable–based hybrid energy is developed to simultaneously meet the electricity, freshwater, and gas (cooking gas via methanation process) demands for a remote Island in Bangladesh. In this process, an energy management strategy has been developed to use the excess energy to generate both freshwater and the hydrogen, where hydrogen is then converted to natural gas via methanation process. The PV, wind turbine, diesel generator, battery, and fuel cell have been optimized using non-dominating sorting algorithm-II (NSGA-II) to offer reliable, cost-effective solutions of electricity, freshwater, and cooking gas for the end users. Results reported that the PV/WT/DG/Batt configuration has been found the most economic configuration with the lowest COE (0.1724 $/kWh) which is 9 % lower than PV/WT/Batt configuration which has the second lowest COE. The cost of water (COW) and cost of gas (COG) of the PV/WT/DG/Batt system are also the lowest among all the four configurations and have been found 1.185 $/m3 and 3.978 $/m3, respectively.

Technical assessment of a stand-alone hybrid renewable system for energy and oxygen optimal production for fishes farming in a residential building using HOMER pro

Electricity holds both economic significance and strategic importance in many regions globally. Persistent challenges related to electricity generation, encompassing aspects like availability, quality, and cost, have impeded the progress of nations for an extended period. While conventional electrochemical storage systems have been the benchmark, they are plagued by issues such as high expenses, technical limitations in power output, and restricted storage capacity. Power generation facilities come with their own array of problems, including noise pollution, environmental impacts, and suboptimal performance, exacerbating the existing concerns of reliability and maintenance. To navigate the path of sustainable global development amidst a sharp upswing in energy consumption, it becomes imperative to foster innovative energy solutions. Independent renewable energy systems (RES) represent a promising avenue for reshaping the prevailing reliance on conventional power grids. The Hybrid Renewable Energy System (HRES) deserves careful calibration, particularly considering the considerable load fluctuations and the need for cost efficiency. The study considers a standalone HRES in a residential area on Manoka Island, where fish farming is a primary activity. This dwelling exhibits a daily electricity consumption averaging at 9.28 kWh, with peak demand hitting 0.88 kW. To evaluate the suitability of the Hybrid Optimization Model for Electric Renewable (HOMER) program, the study investigates the optimal energy generation mix for both sustaining the fish farming industry and fulfilling the energy requirements of the chosen building. The optimization process identifies four key parameters that undergo thorough assessment in this analysis. Delving into the specifics, the study attains an impressive renewable fraction (RF) of 92.5% and achieves a Deficit of Power Supply Probability (DPSP) of 0%. Furthermore, the production of 50 kg of O2 and the emission of 1.69 kg of carbon annually prove adequate for constructing a reliable and environmentally sound energy system. In a broader sense, this research serves as a compelling case study, elucidating the concept of hybrid energy systems within the framework of eco-friendly and sustainable power generation. The study not only underscores the substantial potential of RES for the country but also constitutes a significant stride for researchers active in this field.

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

The trend is now to use renewable energy sources to improve energy efficiency in the building sector and preserve the environment. The use of sources as renewable off-grid applications for driven applications in home sector (micro-grids) is very interesting nowadays. The economic factor and the cost of establishing these grids is the main obstacle to these investments. One of the key solutions to reduce the cost and increase the reliability of these grids is how to optimally determine the ratings and combination of some renewable sources based on the location of the house. This paper presents an effective techno-economical design of a stand-alone hybrid system. The system contains a photovoltaic (PV), wind turbine, battery, and diesel generator. This design is performed through an extensive examination of the techno-economical design of a standalone system to provide the desired energy load for a typical household building for both Albaha and Buraydah cities in Saudi Arabia. These two cities have different geographical locations as Albaha is located at latitude 20.0217 degrees north while Buraydah is located at 26.3592 degrees north. These two cities were selected due to the difference in their geographical locations to study the effect of the weather on the building performance in terms of cost of energy, energy penetration, and load met. To enhance the performance of the proposed hybrid system, some constraints were selected, such as Net Present Cost (NPC), and Total Annual Cost (TAC). Results demonstrate that stand-alone hybrid renewable energy systems can be applied to improve energy efficiency and economics of the existing buildings. Integration of PV system, wind turbine, battery, and diesel generator in the best configuration can provide a minimum cost of energy of about $0.596/kWh and $0.603/kWh for Albaha and Buraydah cities, respectively.

Investigating the Effects of Different Types of Battery Impacts in Energy Storage Systems on Standalone Hybrid Renewable Energy Systems

Energy plays an important role in the development of a country. Developing countries tend to lean towards the use of domestic renewable energy sources to reduce their dependency on foreign energy. However, when looking at the world as a whole, the share of fossil fuels in energy production is at high levels. Due to the rapid depletion of fossil fuels and their increasing costs, as well as the environmental damage they cause, electricity generation from cheaper and cleaner renewable energy sources is being targeted in the area where work will be done. Hybrid energy systems are used in conjunction with backup Unitss due to the variable nature of renewable energy sources such as wind and solar. In this study, a hybrid energy system with solar-wind-diesel generator-battery components was designed through HOMERPro software to meet the electricity demand of the closed prison in Burhaniye district of Balikesir. Simulations were carried out by applying 5 different battery scenarios in the hybrid energy system, and the optimum result was obtained. As a result, the effect of the batteries used on the system was examined, and the vanadium redox battery system with a high renewable energy ratio and the lowest Units energy cost was determined to be the most optimum.

Influence of environmental changes on power quality disturbances in Hybrid Renewable Energy System

Environmental changes profoundly affect PQ disturbances in Hybrid Renewal Energy Systems (HRES). The stand-alone hybrid renewable energy system is increasing its share of the energy sector. This process is now opening doors for research into this area. The power produced by these sources, especially solar and wind systems, depends on environmental conditions. Consequently, these systems behave differently under varying conditions. The research will focus on how these environmental changes can influence disturbances to power quality in the systems. The main focus will be on total harmonic distortion and other related power quality issues, including voltage sag, swell, and changes in current values. The research will be conducted by using MATLAB simulation of the system. The simulation will be tested utilising different environmental conditions, and data will be collected for analysis. The research would reveal which environmental factors will guide the hybrid system more than the other factors. To what extent do these environmental changes influence the PQ disturbances? The major contributing factor was irradiance level in the case of solar power and wind speed concerning wind power. The research will help to improve power supply in a stand-alone HRES.

Operational strategy and capacity optimization of standalone solar-wind-biomass-fuel cell energy system using hybrid LF-SSA algorithms

This paper presents a framework for the efficient design and evaluation of a standalone hybrid renewable energy system (HRES) to meet the energy requirements of a rural community in the north-eastern region of Nigeria. The proposed microgrid system incorporates solar photovoltaic, wind turbines, biomass gasifier, fuel cell, and Battery storage. The sizing of each component is determined through the utilization of real local meteorological data and the load demand over a year, employing the Levy flight-salp swarm algorithms (LF-SSA). The optimization objective is to minimize the annualized system cost (ASC) of the HRES, while also considering the reliability constraint of Loss of power supply probability (LPSP). The comparative outcomes demonstrate that the LF-SSA surpasses other examined algorithms, namely the salp swarm, genetic algorithm, and HOMER software by achieving substantial cost savings of $29033, $50796, $191771 respectively in relation to the proposed HRES. The result further shows that, the LF-SSA provides the lowest LCOE of $0.933162/kWh, in contrast to SSA at $0.947737/kWh, GA at $0.958660/kWh, and HOMER at $1.075351/kWh. Additionally, the results indicate that the implemented Energy Management System (EMS) has successfully facilitated the establishment of an environmentally friendly and cost-effective energy system.

Different Scenarios for Reducing Carbon Emissions, Optimal Sizing, and Design of a Stand-Alone Hybrid Renewable Energy System for Irrigation Purposes

Irrigation systems to supply water to agricultural land are essential in remote and isolated areas. However, these areas often face challenges and obstacles in obtaining energy for use in irrigation since many depend on diesel generators (DGs) to produce electricity. A farm located in a remote area in Al-Jafr, Jordan, uses a 100 kW DG to supply its need for electric energy for irrigation purposes. Its energy consumption is 500 kWh/day at $0.29/kWh. This paper designs a new hybrid renewable energy system (HRES) for this farm by conducting simulations using the HOMER (Hybrid Optimization of Multiple Energy Resources) software. This new system consists of solar photovoltaics (PVs), batteries, an inverter, and a 100 kW DG. The results showed a clear difference between the baseline DG-only system and the hybrid system regarding energy cost and carbon emissions. The energy price for the HRES is $0.107/kWh, and carbon dioxide emissions are reduced to 27,378 kg/yr from 184,917 kg/yr for the DG-only system. In addition, simulations and comparisons for an alternative HRES with a 60 kW DG were conducted. Based on the simulation results, the energy price was $0.091 instead of $0.19, and carbon dioxide (CO2) emissions were 15,847 kg/yr instead of 115,090 kg/yr. It was concluded that using hybrid renewable energy systems to power the irrigation of remote areas successfully reduced the energy cost, fuel consumption, emissions, and overall cost. The HOMER program makes an accurate comparison over extended periods between the four strategies (load following, cycle charging, combined dispatch, and predictive dispatch) and selects the optimal system based on the cost, emissions, fuel consumption, and percentage of renewable energy from the system.

The effect of components capacity loss on the performance of a hybrid PV/wind/battery/hydrogen stand-alone energy system

A stand-alone hybrid renewable energy system (HRES) comprising a photovoltaic (PV) array and a small wind turbine for energy production, a lead-acid battery for short-term energy storage, and a hydrogen subsystem for long-term energy storage is analyzed in this study. The hydrogen subsystem comprises a PEM electrolyzer for hydrogen production, a hydrogen compressor and a hydrogen tank for hydrogen storage, and a PEM fuel cell for power generation. Twenty-year hourly input weather data were acquired from the national meteorological service for the Mediterranean location of Split, Croatia. Two different end-user load profiles are considered, namely a year-around constant load profile and the stochastically variable load profile. Furthermore, a comparative analysis is performed for two different energy management strategies – one based on energy balance within the system, and the other based on double hysteresis loop control. The HRES performance is simulated using MATLAB. The dynamics of capacity loss of the batteries, PEM electrolyzer, and PEM fuel cell is a function of how the system operates, but at the same time, this dynamics of capacity loss affects the overall system performance. The double hysteresis control strategy results in a significantly longer battery lifetime for both load profiles considered, while the PV and battery loss of capacity causes more frequent electrolyzer and fuel cell operation for all considered cases.

Tolerable random interruption duration based reliability estimation of stand alone hybrid renewable energy system by network reduction and sequential Monte Carlo simulation

AbstractThis paper presents a novel tolerable random interruption duration (TRID) concept for estimation of reliability indices of stand‐alone hybrid renewable energy system (SAHRES) during down time. This concept utilizes the ignorance of interruption duration if it is tolerable in event of failure. It uses a framework using network reduction technique and sequential Monte Carlo simulation (SMCS) suitable for present research whereas the solution in such cases is not feasible with analytical method. Thus reliability indices such as mean up time, mean down time, failure frequency, system failure rate, interruption duration and system unavailability are estimated using SMCS. Modelling aspects are considered for load, capacity, renewable energy system and TRID due to network outage. The impact of considering random tolerable interruption duration has been demonstrated on the reliability indices and case study is presented to show the effect of change of TRID on reliability indices. A sample SAHRES has been considered for the study.

A TLBO algorithm-based optimal sizing in a standalone hybrid renewable energy system

Depletion of fossil fuels, increase in fuel prices, and global warming have motivated the utilization of renewable energy resources like solar and wind, as they are eco-friendly. Due to the stochastic nature of PV and wind, using a single energy source is not reliable and uneconomical as it results in system over-sizing. Integration of renewable sources such as PV and wind can significantly increase energy reliability compared to single-source systems. PV and wind hybrid systems are economically advantageous in isolated areas for providing continuous and quality power due to their inherent complementary characteristics and availability in most areas. Utilizing grid-tied renewable energy resources is also economical and reliable to overcome power outages in remote areas. This study proposes a TLBO algorithm for optimal design and sizing of HRES in both standalone and grid-connected modes due to its simplicity and fewer parameters to adjust. The objective of the optimization problem in standalone, as well as the grid-connected mode, is to minimize the LCE and maximize the system reliability and renewable energy integration while satisfying the system constraints and load demand. The number of PV panels, wind turbines, and batteries is taken as decision variables optimally determined by the proposed optimization algorithm. The simulations are carried out in MATLAB software. The effectiveness of TLBO in designing and sizing the hybrid system is investigated, and its performance is compared with other well-known optimization algorithms PSO; the TLBO provides the best optimal solution, better performance, and faster convergence speed compared to different algorithms

A novel cloud-based framework for optimal design of stand-alone hybrid renewable energy system considering uncertainty and battery aging

This paper performs a new optimal framework for a hybrid photovoltaic-wind system design integrated with battery storage (PV/WT/Battery), considering cloud-based uncertainty modeling and battery degradation based on real meteorological data from the Sarein-Ardabil region in Iran. The objective function is presented as minimizing the total net present cost (NPC), load loss, and battery degradation cost. The decision variables include the number of PVs, WTs, batteries, inverter power, and the angle of PVs installation, which is optimally determined via a new meta-heuristic optimization algorithm named opposition-based learning and Gradient-based optimizer (OBLGBO). In the proposed framework, the cloud theory method based on combining fuzzy theory and probability statistics has been applied for modeling the energy resources and load demand uncertainties. The simulation results indicate that considering battery degradation costs increases the overall cost of designing hybrid systems. As the cost of degradation increases, reliability indices improve due to an increase in the number of wind turbines and a decrease in the number of batteries. Also, the results demonstrated that incorporating the uncertainties based on the cloud theory increases the design cost, and the system reliability is weakened. Therefore, the proposed optimal framework has presented a real and accurate approach to the optimal design of energy systems with more accurate knowledge of electricity generation costs and the cost of improving reliability in conditions of uncertainties. Moreover, the superior capability of the OBLGBO compared with traditional GBO and the well-known particle swarm optimization (PSO) and grey wolf optimizer (GWO) is proved to achieve lower design cost and better reliability indices.

Reliability index based optimal sizing and statistical performance analysis of stand-alone hybrid renewable energy system using metaheuristic algorithms

Integration of renewable energy systems can provide reliable, environmentally sustainable, and cost-effective alternatives for meeting the demand for electricity in remote locations. In this study, recently developed meta-heuristic techniques are explored to find the optimal design for two combinations of off-grid hybrid renewable energy systems. To evaluate the performance, the Tasmanian devil Optimization (TDO) was compared to three meta-heuristic algorithms, called the COOT bird optimization algorithm (COOT), the Grey wolf algorithm (GWO), and the Beluga whale optimization (BWO), and determined the optimal design of the proposed off-grid energy system in terms of best and worst-case solutions. The system consisting of a solar-battery is more cost-effective, with the lowest total annual cost (TAC) of 36,859 $ and the lowest levelized cost of electricity (LCOE) of 0.0930 $/kWh for 0% LPSPmax level as compared to the wind turbine-battery-diesel generator with the highest TAC (102580 $) and LCOE (0.2589 $/kWh). Hence, a solar-battery hybrid system is more viable for producing clean energy with effective storage and better power system reliability enhancement. Also, the obtained simulation results reveal the supremacy of the TDO compared to the other three meta-heuristic algorithms, where it achieved the optimal solution with a quick convergence time and fewer oscillations.

Analysis of Optimal Load Management Using a Stand-Alone Hybrid AC/DC Microgrid System

Typically, diesel or other fossil fuel-based related applications meet electricity demand. Nonetheless, as the cost of fossil fuels rises, as do their harmful emissions, there is a sudden transition toward stand-alone hybrid renewable energy systems (HRESs). The proposed project proposes electrifying VIT University in Vellore, Tamil Nadu, India, using an off-grid HRES. The goal of enhancing hybrid energy system (HES) regulation, size, and component selection is to provide society with a cost-effective power supply. This article’s primary purpose is to show how to utilize HOMER Pro Software to reduce total net present cost, cost of energy, and CO2 emissions. After that, the findings were compared to four different HRES configurations. The efficient solution for transmitting power at the lowest energy cost is configuration 1 (solar + fuel cell + battery + wind + diesel generator) which is found to be the optimal solution for supplying energy with 0% unmet load at the least cost of energy, which is at 24.91 Rs/kWh. These data are used to calculate the optimal size of energy storage components based on long-term system behavior using HOMER and to forecast short-term generation and demand changes while maintaining system dependability and grid voltage. Using and incorporating model predictive control (MPC) for an interlinking converter (ILC), the proposed HRES design is validated for the study area in a novel way that sequentially applies HOMER and MATLAB simulations.

Robust metamodel-based simulation-optimization approaches for designing hybrid renewable energy systems

We propose two robust metamodel-based approaches for designing stand-alone hybrid renewable energy systems that combine conventional and renewable energy generators with battery storage. Since the cost and reliability functions of the stochastic system do not have closed-form expressions, they can only be estimated via simulation. In the response surface methodology, the simulation input/output data is used first to locally fit first-degree surrogate functions for each supply scenario to perform a stochastic gradient descent, before a second-degree function is fitted and optimized when the gradient becomes small. In contrast, the global response surface technique globally fits a convex quadratic surrogate function on the simulation input/output data, then uses its minimizer to iteratively refine the search space. To account for estimation errors, a distributional ambiguity set based on a linear ϕ-divergence function is constructed around the nominal probability distribution of supply scenarios, and the expected reliability-adjusted cost of the system is computed using the worst-case distribution in this set. The validity of the proposed approaches and the value of considering distributional ambiguity are demonstrated through a realistic case study of a remote community in Northern Ontario.

Technoeconomic Analysis of a Hybrid Energy System for an Academic Building

This work is mainly based on the optimal design of a standalone Hybrid Renewable Energy System (HRES) consisting of PV/diesel/battery systems, implemented in an academic building. Different hybrid system configurations such as PV-diesel generator-battery, diesel generator-battery, and PV-diesel generator are compared based on Net Present Cost (NPC) and Cost Of Energy (COE) to find out the best economically viable and environmentally friendly solution. Li-ion and lead-acid batteries were taken into consideration, and the optimization was done in HOMER PRO software. The PV-DG-Li-ion battery configuration emits approximately 2825387kg/year CO2 whereas the conventional DG system emits 4565074kg/year. It is concluded that the PV-DG-Li-ion battery configuration provides the cleanest and most environment-friendly and techno-economically feasible solution.