Load Growth Rate Research Articles

Distributed battery energy storage systems for deferring distribution network reinforcements under sustained load growth scenarios

Energy storage systems can be leveraged in electricity distribution network planning as mitigation alternatives to traditional grid reinforcements if they are strategically installed and operated to reduce congestion and voltage limit violations. This paper examines the technical and economic viability of distributed battery energy storage systems owned by the system operator as an alternative to distribution network reinforcements. The case study analyzes the installation of battery energy storage systems in a real 500-bus Spanish medium voltage grid under sustained load growth scenarios. The results show that, in general, dedicated battery energy storage systems are only a cost-efficient alternative in distribution system planning under very specific conditions, such as when low load growth rates are expected. Nevertheless, they are only required for peak shaving a few days per year. For the analyzed case study, the recoverable portion of their total cost through deferral of distribution system upgrades is higher than the fraction of cycles required for peak shaving under all sustained load growth scenarios. Therefore, it is also explored if mobile battery energy storage systems, capital grants, and revenue stacking can enable battery energy storage systems to become an efficient distribution system planning alternative.

Study of the flexural behavior of UHPC-HPC composite beams strengthened with BFRP sheet after chloride secondary erosion

To solve the issue of insufficient durability of reinforced concrete (RC) structures, a new structure of ultra-high performance concrete (UHPC)-high performance concrete (HPC) composite beam was designed, and the flexural performance of the composite beam strengthened with basalt fiber reinforced polymer (BFRP) after pre-damage was investigated. Results indicate that main cracks are formed and developed after the secondary erosion of chloride salt, leading to three forms of failure modes of the beams: BFRP sheet fracture and concrete crushing, BFRP sheet debonding and concrete crushing and BFRP sheet debonding. The test beam failure process can be classified into three stages: linear elasticity, crack development and yield. The maximum cracking and ultimate loads increased by 27.9 % and 35.8 %, respectively. The crack load growth rate of the beam decreased after 7 days (d) of secondary chloride salt erosion. The formula for calculating the peel strength of the UHPC-HPC composite beam was modified. The calculated bending capacity of the beam agrees well with the measured value. This study provides a reference for enhancing the lifespan and calculating the flexural bearing capacity of structures in corrosive environments.

Contribution of climate change and traffic load on asphalt pavement carbon emissions

The maintenance and rehabilitation of asphalt pavement contribute to carbon emissions, impacting climate change. The interaction between climate change and increasing traffic loads influences the frequency of maintenance for asphalt pavement infrastructure. This study assessed the combined impact of climate change and traffic growth on the performance and carbon emissions of Chinese freeway asphalt pavement, informing carbon reduction policies amid future climate change. Using climate prediction models (Representative Concentration Pathways 4.5 and 8.5), the research forecasted pavement performance under 2% and 4% traffic volume growth rates and estimates future carbon emissions based on maintenance strategies. Results indicated that both future climate change and increased traffic loads would have adverse effects on the asphalt pavement performance, particularly with a 4% annual traffic load growth. Freeway length with rut depths exceeding 25 mm may increase from 33,600 km in the 2020s to 94,950 km in the 2050s (an 182.6% increment). The interaction between climate change and traffic growth intensifies pavement deterioration, increasing maintenance frequency and carbon emissions. Under the conditions of RCP 8.5 and a 4% traffic load growth rate, the carbon emissions in the 2050s may increase by 71.9 million tons compared to the 2020s (an 180.7% increment). This underscores the need for strategic interventions and policy decisions to mitigate environmental impacts.

Comparison of Techno-Economic Models for Upgrading PV System without Net-Metering Option and Long Term Impact on Energy Bills

This article presents a techno-economic analysis of upgrading a Photovoltaic (PV) power system at large. A comparative study has been carried out considering various technical and economic factors like per unit cost, annual load, energy demand growth, and PV panel efficiency, annual performance degradation of system, cost of electricity, payback period, initial capital expenditure, and rate of return in the form of saving in energy bills. The PV system is proposed to be upgraded from 1 MW to 2 MW at the National University of Sciences & Technology (NUST), Islamabad. The PV system is subject to be upgraded due to the growth rate of annual load and amount saved by PV contribution, which has been forecasted using data trends of the above-mentioned technical and economic factors. While considering these factors, four economic models have been evaluated and compared, which include Self-Built via Contractor with self-financing, Self-Built with bank financing, Power purchase agreement (PPA), also known as rental agreement and Built, Own, Operate & Transfer (BOOT) model. Merits and demerits of these models have been discussed, and the most feasible model has been proposed based on the mentioned key factors and long-term sustainable development goals (SDG) for affordable clean energy to contribute to climate action, i.e., adaptation of renewable energy resources (RER) and reduction of greenhouse gases (GHG).

Low-Carbon Charging Facilities Planning for Electric Vehicles Based on a Novel Travel Route Choice Model

Promotion of charging facilities (CFs) can ameliorate range anxiety and facilitate long-distance travel by electric vehicles (EVs). In this context, a multistage low-carbon EV CFs planning model is proposed in this paper for the coupled transportation and power systems. This model not only takes into account the construction costs of newly-built CFs and their adverse impacts on the distribution system, but also considers the carbon emissions of CFs and the penalty due to the inconvenience for EVs to be recharged. In addition, a rational travel route choice model is significantly important to accurately evaluate the service capability of CFs to be constructed and thereby to obtain an optimal CF planning result. Therefore, a novel travel route choice model developed in this work allows EV drivers to take detours according to the CF locations to charge their EVs multiple times and then finish their trips. Carbon emission flow (CEF) model is innovatively employed to precisely calculate CFs’ carbon emission amount from the perspective of consumption side. Subsequently, uncertainties involved in CF planning, i.e., distribution and growth rate of traffic flow and electric load, popularity of different types of EVs, as well as location of the connected node of clean electricity, are fully considered to obtain a robust CF planning scheme that can achieve a good performance in the current stage and exhibit robustness for the uncertainties in the future stage. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model. The impacts of future carbon price and EV cruising range on the planning results are also comprehensively evaluated.

Toward a better understanding of the environmental impacts of expanding farmer-led irrigation in Sub-Saharan Africa: an exploratory assessment of irrigation-induced risk of nutrient water pollution in Ethiopia

Irrigation, and especially farmer-led irrigation, is considered to be a promising option for enhancing agricultural productivity in Sub-Saharan Africa. However, there is a lack of thorough understanding of the impacts of irrigation development on environment. Past discussions are mainly limited to the water depletion and hydrological regime change effect of irrigation. This paper presents a study to narrow the knowledge gap by assessing nutrient water pollution risk induced by the expansion of farmer-led irrigation in Ethiopia. Using household survey data collected from four woredas in Ethiopia where irrigated crop production currently concentrates, we first evaluate the impact of irrigation on cropping intensity and annual consumption level of fertilizers and then use the findings of the household survey data analysis to support conceptualization of a modeling framework for assessing agricultural nutrient water pollution risk from farmer-led irrigation development in Ethiopia at national scale. We project that overall farmer-led irrigation development in Ethiopia will lead to a gentle increase in national total of agricultural nutrient loadings. This result helps justify the endeavor of promoting farmer-led irrigation in Ethiopia. On the other hand, the projected nutrient flow and nutrient loading growth rate related to the farmer-led irrigation expansion are highly heterogeneous spatially, and risk of local water quality deterioration exists. There is still need to make investment to ensure the environmental sustainability of farmer-led irrigation development.

Time-dependent reliability assessment of a simply supported girder bridge based on the third-moment method

Concrete bridges decay over time due to environmental or operational processes, leading to a reduction in their reliability. In this paper, a new time-dependent reliability evaluation procedure is proposed taking into consideration the simultaneous non-stationarities of vehicle load effect and resistance deterioration. Using the third-moment (3M) method and the second-moment (2M) method, the time-varying reliability of a simply supported girder bridge was investigated. The 3M method is a novel approach to calculate the reliability index requiring neither iteration nor computation of derivatives. As validated by Monte-Carlo simulations, it is shown that the 3M method is more accurate than the 2M method. Based on different moment methods, the effects of parameters such as the growth rate of vehicle load and the time proportions of different operation states in the reliability of the system were investigated. By analyzing the relationship between the time-dependent reliability index and the target reliability index, the time points of maintenance and inspection were predicted.

Reliability and efficiency enhancement of a radial distribution system through value-based auto-recloser placement and network remodelling

The electric distribution system (EDS) is prone to faults leading to power interruptions. The present energy market demands that electricity utilities invest more in different measures to improve the performance of the EDS. The approach proposed here details a composite dual-phased methodology to improve the reliability and efficiency of the power delivered by the EDS. In the first phase, the optimal allocation of auto-reclosers (AR) is undertaken by employing a newly formulated algorithm. The determination of the total number and location for AR placement is based on the economic analysis of two factors, i.e., AR investment-maintenance cost and total benefit earned in terms of reliability improvement due to AR placement. The analysis also takes into account the impact of power outages on different load types, the load growth rate, and the inflation rate. Further, to enhance the efficiency of the AR-incorporated EDS, the technique of Radial Distribution System Remodelling is employed in the second phase. This method searches for a radial configuration that delivers power at minimum line losses. These phases comprising complex combinatorial operations are aided by a fresh hybrid of the Sine Cosine Algorithm, Krill Herd Algorithm, and a genetic operator of Differential Evolution. The results obtained from its application on the IEEE 69-bus distribution test system prove the credibility of the suggested formulation.

IMPLEMENTATION OF EXTENDED FINITE ELEMENT METHOD IN CRACK PROPAGATION OF CONCRETE

The Extended Finite Element Method is a numerical solution based on the Finite Element Method (FEM) XFEM has really become a very important generalization of classical finite element techniques, by establishing a mesh independent generalization of classical finite elements to reduce the mesh-dependent shortcomings of the solution. The application of XFEM in crack simulation should improve the modeling of the crack tip environment and also apply to generalized advanced global failure criteria, which is specifically designed to deal with problems in the engineering field Such as the fracture behaviour model. The purpose of this paper is to identify the application of the Extended Finite Element Method to a technical problem, namely fracture behaviour model. The media used is pure boneless concrete modelled with COMSOL Multiphysics 5.6 software by combining stress ratio, lateral strain due to axial loading, concrete density, and crack growth rate. The crack growth process provides initial prolonged growth along with the increase in crack size. In the end, the growth is faster. The reason for this accelerated growth is the stress intensity factor at the crack tip. As the crack grows, the stress intensity factor increases, leading to faster growth. The crack grows until it reaches a critical value, and fracture occurs. The test results obtained the cause of failure: the critical stress intensity is exceeded. See a comparison of crack size and stress cycle as the crack size increases. This accelerated growth is because the growth rate depends on the stress intensity factor at the crack tip, and the stress intensity factor depends on the crack size. As the crack grows, the stress intensity factor increases, leading to faster growth. The crack grows to a critical size, and failure occurs. The results show a relatively strong relationship between increasing crack size and increasing crack growth rate.

Incidence of Cytomegalovirus disease and viral replication kinetics in seropositive liver transplant recipients managed under preemptive therapy in a tertiary-care center in Mexico City: a retrospective cohort study

BackgroundIn the absence of an adequate prevention strategy, up to 20% of CMV IgG+ liver transplant recipients (LTR) will develop CMV disease. Despite improved reporting in CMV-DNAemia, there is no consensus as to what the ideal CMV-DNAemia cutoff for a successful preemptive strategy is. Each transplant centre establishes their own threshold. We aimed to determine the effectiveness of our preventive strategy in CMV IgG+ LTR, and evaluate CMV replication kinetics.MethodsIn this retrospective study we determined the incidence of CMV disease in the first 6 months following transplantation in CMV seropositive LTR in a tertiary-care centre in Mexico. Secondary outcomes were determining the number of patients who required preemptive therapy (treatment cutoff ≥ 4000 UI/ml), adherence to the centre’s prevention protocol and calculation of viral replication kinetics.ResultsOne-hundred and twenty-four patients met inclusion criteria. Four patients (3.2%) developed CMV disease. Ninety-six (85%) had detectable DNAemia and 25 (22%) asymptomatic patients received preemptive therapy, none of them developed CMV disease. The highest viral loads were observed on the second posttransplant month. The number of viral load measurements decreased over time. Patients with DNAemia ≥ 4000 UI/ml had a faster viral load growth rate, shorter viral load duplication time, and higher basic reproductive number. Viral load growth rate and autoimmune hepatitis were associated with development of DNAemia ≥ 4000 UI/ml.ConclusionCytomegalovirus disease occurred in 3.2% of the study subjects. Preemptive therapy using a threshold of CMV ≥ 4000 UI/ml was effective in reducing the incidence of end-organ disease. The viral replication parameters described in this population highlight the importance of frequent monitoring, a challenging feat for transplant programs in low- and middle-income countries.

Развитие распределительных электрических сетей напряжением 11 и 33 кВ Республики Союз Мьянма

A drastic (by about a factor of three) increase of electricity demand is predicted for the next decade in the Republic of the Union of Myanmar. It is planned to connect all households to the country’s national power grid. These electrical load growth rates will require, first of all, a significant development of the 11 kV and 33 kV electrical distribution networks. The load curves of 33 kV substations are given. The results of the first load measurements in 11 kV electrical distribution networks are presented. Based on the load curves and load measurement results, the loading patterns of 11 kV and 33 kV power lines and 33/11 kV and 11/0.4 kV transformers were analyzed for the studied electrical networks of the Republic of Myanmar Mandalay district. In most cases, the existing load of 33/11 kV and 11/0.4 kV transformers does not exceed 65%, which allows their loading to be doubled without exceeding the permissible systematic overload capacity. The 33 kV lines also have at least a 100% transmission capacity margin. Most of 11 kV lines have no more than 40% capacity margin. The load of some 11 kV lines has reached the maximum level. Based on the obtained analysis results, the development lines of distribution networks in the Republic of the Union of Myanmar have been determined.

Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets

Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols.

Optimal Scheduling Model of Virtual Power Plant and Thermal Power Units Participating in Peak Regulation Ancillary Service in Northeast China

In recent years, the rapid development of wind power generation and the low load growth rate have brought challenges to the peak regulation of power grid in Northeast China. In order to solve the peak regulation problem, virtual power plant (VPP) is proposed to participate in the peak regulation auxiliary service market in Northeast china, especially for deep peak regulation. Firstly, two modes of peak regulation in Northeast China are introduced in this paper, which are thermal power unit and VPP. With the definition of the peak regulation capacity for VPP, the Optimal Scheduling Model of VPP participating in peak regulation ancillary service is established. The simulations are carried out in MATLAB. The results show that the economy of peak regulation is significantly improved in peak regulation auxiliary service based on VPP.

Optimal clean heating mode of the integrated electricity and heat energy system considering the comprehensive energy-carbon price

Clean heating is a powerful solution for satisfying the building heat demand by synergizing energy efficiency and carbon emission. For satisfying the newly increased heat load, this paper constructs an alternative integrated electricity and heat energy system (IEHES) to consider different clean heating supply modes, namely electrical-heating mode (EH, electric boiler or electric heat pump), CHP unit with high back-pressure turbine heating mode (HBP–CHP), and auxiliary heat source heating mode (AHS, coal-fired boiler or gas-fired boiler). An optimal configuration planning and dispatch model is proposed for comparing the performance of the three heating modes. Wherein, a new comprehensive energy-carbon price is proposed as the optimization objective to minimize this system's total production costs and carbon emission costs. The results show that the HBP-CHP mode is the optimal solution when the heat load growth rate λ is lower than 14%, followed by the electric heat pump heating way under the EH mode. However, the HBP-CHP mode will limit the flexibility of the IEHES when λ is larger than 8%. Therefore, we propose a combined heating mode by introducing the electric heat pump into the HBP-CHP heating mode that facilitates the flexibility of the IEHES and brings the optimal system coal-saving effect.

Techno‐economic optimization of a grid‐connected hybrid energy system considering electric and thermal load prediction

AbstractOptimal planning of hybrid energy systems has always been a considerable task. While several studies have conducted techno‐economic analysis on hybrid energy systems, most of them have neglected to consider appropriate electric and thermal load growth rates. This paper proposes an efficient strategy for optimizing a grid‐connected hybrid energy system considering electric and thermal load growth rates. HOMER software is used for optimizing hybrid energy systems. It uses a nonderivative optimization to recognize the system with the minimum net present cost (NPC) among hundreds of configurations. The exponential smoothing method is also used for predicting upcoming load peak values based on historical data. The proposed hybrid system includes solar photovoltaic (SPV) system, wind turbine (WT) system, converter, battery storage system (BSS), gas generator (GasGen), fuel cell (FC), fuel‐fired boiler, and resistive boiler. Unlike previous studies, electricity price growth and SPV degradation rates are considered in this study. The grid‐connected system has also been compared to the stand‐alone system to understand grid connection impacts on the optimization results. Environmental analysis has been performed to analyze the greenhouse gas emissions of each system. The effects of growth rates in thermal and electric loads and electricity price are comprehensively investigated. Neglecting load growth rates affected the financial results severely. In this condition, the NPC and COE are achieved −11 383.4 US$ and −0.02376 US$/kWh. Results indicate that the combination of WT system (15 kW), converter (10 kW), resistive, and fuel‐fired (10 kW) boilers is the most economical configuration in grid‐connected mode. The WT system plays an essential role in the electric power provision and revenues of the hybrid system. The net present cost (NPC) and the cost of energy (COE) for grid‐connected operating mode are achieved −0.0162272 US$/kWh and −5243.956 US$, respectively. For off‐grid operating mode, the NPC and COE are obtained 47 024.19 US$ and 0.1983879 US$/kWh, respectively. Thanks to the feed‐in‐tariff (FiT) policy, the proposed grid‐connected system is more economical and environmentally friendly than the stand‐alone system. In off‐grid operating mode, 63 575.45285 kg CO2 is produced, which is higher than CO2 production in the grid‐connected mode (more than 8262 kg).

Algorithm to select the voltage class for the gas field electricity supply system

The current algorithms and mathematical models to select the voltage class based on the theory of experimental planning are developed for industrial enterprises (overhead lines with a length of up to 10 km, a power of up to 20 MV, a radial arrangement with a transformation at the end of the line). They do not consider the features of gas fields (overhead lines with a length of up to 20 km and a capacity of 1 MV with a projected growth of up to 10 MV, a transmission network with one pass-through trunk line with distributed transformation along the line). Currently, to develop a mathematical model, the following factors are considered: the average length of the power line and the total load of an enterprise. The proposed models do not allow us to quantify the dynamics of the gas fields power supply system considering the multiple growth of the electrical load in each period of the life cycle. The purpose of this study is to develop a model to solve this problem. An extreme experiment has been carried out during the research. The following input data are set: the average length of the power line; the number of gas clusters; the growth rate of the electric load. The response function is the voltage class that is optimal for the minimum discounted cost. The authors suggest the regression model. In this model the “total load” factor is split into two components, they are gas clusters and growth rate of electric loads. The algorithm to select the optimal voltage class of a distribution grid is proposed. The dynamic experiment is carried out and the growth rate of electric loads in the regressive model is being changed while other factors are being unchanged. As a result, the optimal minimum of the discounted costs of the voltage class for each period of the field life cycle is obtained. The algorithm is implemented in “PRON” software. With the help of “PRON” software, the distribution grids of several operating gas fields in Western Siberia have been investigated. The optimal voltage class of a distribution grid of gas fields is 20 kV. The reliability of the results is verified by reference models of calculating discounted costs.

Optimal Design of an On-Grid MicroGrid Considering Long-Term Load Demand Forecasting: A Case Study

In this article, an optimal on-grid MicroGrid (MG) is designed consideringlong-term load demand prediction. Multilayer Perceptron (MLP) ArtificialNeural Network (ANN) is used for time-series load prediction. Yearlydemand growth has also been considered in the optimization process based onthe forecasted load profile. Two different case studies are performed with theforecasted and historical load profiles, respectively. According to the results,by considering the predicted load profile, realistic results of net present cost(NPC), cost of energy (COE), and MG configuration would be achieved. TheNPC and COE are obtained as 566,008$ and 0.0240 $/kWh, respectively.It is also demonstrated that utilizing battery storage systems (BSSs) is not economic in the proposed approach. The introduced MG also produces loweremissions compared to the system with the historical load profile. In thisregard, 563,909 kg of CO2 is produced over the optimization year, whichis 35,623 kg lower than the case with no load growth rate. According to thesensitivity analysis results, when the inflation rate increases from 18.16 % to32.36 %, the COE’s value rises to 0.021 USD/kWh accordingly. In contrast,the NPC of the system decreases significantly from above 400 × 103 USD toabout 200 × 103 USD as the inflation rate increases from 18.16 to 32.36.

Techno-economic Analysis of Renewable-based Stand-alone Hybrid Energy Systems Considering Load Growth and Photovoltaic Depreciation Rates

The increasing trend in power consumption, mainly due to the rapid population growth, has resulted in grid outages and low-reliability grid connections. Renewable-based hybrid energy systems are one of the emerging alternatives for traditional and low-reliability grid connections. In this paper, a stand-alone hybrid energy system is proposed for a remote residential house. HOMER software is used for the optimisation of the proposed energy system. The main contribution of the paper is focused on considering two influential parameters, such as annual load growth and photovoltaic (PV) degradation rates in the optimal planning of the hybrid energy system. Simulation results indicate that considering influential parameters more realistic results, including system configuration, total net present cost (NPC) and optimal operation of the energy sources are achievable. Total NPC of the system obtained as 70,072 US$, which shows 52,029 US$ growth in comparison to the case neglected annual load growth and PV degradation rates. The optimum configuration benefits from higher penetration of renewable energy sources (RESs). Moreover, according to the comparison made with only-grid system, the proposed hybrid renewable-based energy system saves a large number of emissions. Based on the results, around 292,049.4202 kg emissions have been saved over 25 years of the project.

A hybrid stochastic/robust-based multi-period investment planning model for island microgrid

Microgrid is becoming an effective way to solve the power supply problem in off-grid islands. The investment economy is one of the key factors affecting its development and application, which is very challenging due to various uncertain information involved in the investment decision process. In this paper, a multi-period investment planning model is proposed to support decision-making for the stakeholders in determining the optimal sizing as well as investment timing of distributed energy resources of an island microgrid. The applicability of the model in dealing with various uncertainties is enhanced via a hybrid optimization framework, in which the long-term uncertainty of energy price fluctuation is captured by a stochastic programming approach and the short-term variations of renewable energy generation and load are addressed through robust optimization method. The dynamic information of load growth, unit cost variation and device degradation are considered to make the decision more practical and economically attractive. The multi-period investment planning model is formulated as a mixed integer linear programming problem, and the conservatism of the decision can be flexibly adjusted by regulating the robustness of the model. Simulation results based on actual data illustrate that the proposed model shows better economic and synergetic performances than the traditional multi-year optimization model, with the total planning cost dropped by nearly 3.6%, the initial investment cost reduced by nearly 36.6%, and the utilization rate of renewable energy increased by nearly 5.4%. In addition, the sensitivity analyses for load growth rate, loan ratio, unit cost, and uncertain budgets further verify the applicability of the proposed model under various conditions.

A fuzzy decision-making model for optimal design of solar, wind, diesel-based RO desalination integrating flow-battery and pumped-hydro storage: Case study in Baltim, Egypt

This paper aims to propose a conceptual design model for sustainable hybrid renewable stand-alone energy system (HRSES) to meet the electricity demand of a large-scale reverse osmosis desalination plant in Baltim, Egypt. The model investigates the feasibility of different HRSES alternatives and develop a fuzzy-based multicriteria decision-making model for meticulously selecting the optimal energy solution. Both zinc-bromine flow battery and turbine-pumped hydro energy storage technologies are integrated independently with wind, solar, and diesel power sources. Firstly, the proposed model uses HOMER software to execute an energy-economic-ecological optimization analysis for studying the practicability and components sizing of nine HRSES alternatives. Second, an integration between Fuzzy-AHP and Fuzzy-VIKOR decision-making methods is executed to choose the best design considering ten performance criteria. In the second stage, the fuzzy environment is engaged to expedite decision-makers to express their ratings in linguistic terms and to achieve more sensible and accurate results. Among ten feasible alternatives, the results reveal that the optimal system consists of 5 × 20-kW wind turbines, 328-kW photovoltaic array, 100-kW diesel generator, 112 batteries and 235-kW converter. This system has the best economic performance among all alternatives with least NPC, COE, and payback-period of $1,048,046, 0.101$/kWh and 1.1 yr, respectively. Besides, it has a treasured share of renewable of 95.55%; hence, it produces a realistic CO2 of 25,426.46 kg/year. Lastly, the sensitivity analysis illuminates that the future load growth and low-interest rate hurt upcoming investments while the projected reduction in the cost of energy storages has an encouraging influence on financing decisions.