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The research work has progressed significantly in this first year of the project, as a result of contributions from HY4RES partners. Discover below the scientific developments carried out under the contribution and supervision of Professor Helena M. Ramos, member of the Instituto Superior Tecnico de Lisboa. This research work focused on the various aspects of developing the HY4RES model of hybrid renewable energy systems, such as comparing methods, optimising hybrid energy solutions and case studies analysis.
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This research developed smart integrated hybrid renewable systems for small energy communities and applied them to a real system to achieve energy self-sufficiency and promote sustainable decentralized energy generation. It compares stand-alone and grid-connected configurations using a developed optimized mathematical model and data-driven optimization, with economic analysis of various renewable combinations (PV, Wind, PHS*, BESS**, and Grid) to search for the optimal solution.
Four cases were developed: two stand-alone (SA1: PV + Wind + PHS*, SA2: PV + Wind + PHS* + BESS**) and two grid-connected (GC1: PV + PHS* + Grid, GC2: Wind + PHS* + Grid).
GC2 shows the most economical with stable cash flow (−€123.2 annually), low CO2 costs (€367.2), and 91.7% of grid independence, requiring 125 kW of installed power.
While GC options had lower initial investments (between €157k to €205k), the SA configurations provided lower levelized costs of energy (LCOE***) ranging from €0.039 to €0.044/kWh. The integration of pumped hydropower storage enhances energy independence, supporting peak loads for up to two days with a storage capacity of 2.17 MWh.
This proposal introduces a novel methodology that addresses the increasing irrigation demands driven by climate change and urban growth. Traditionally water-scarce areas are now facing severe water deficits, while wastewater volumes from treatment plants, often discharged into the sea, contribute to pollution.
The proposed hybrid system strategy innovatively reallocates 33 hm 3 of water annually to agricultural communities, employing a zero-discharge approach to prevent marine pollution. Evaluated from energetic, environmental, and social perspectives, this methodology shows a remarkable cost-benefit ratio exceeding 12, showing its feasibility. It features technical indicators for optimizing water distribution and regulatory components, applied effectively to 28,424 ha of farmland.
This strategy meets 24.1 % of the irrigation needs in these regions while safeguarding coastal areas from degradation. Crucially, it integrates 11.3 GWh of renewable energy annually, underscoring its sustainability and enhancing its replicability for other water-deficient regions.
This research attempts to address the gap between the theoretical fundamentals of hybrid renewable energy systems and their practical implementation at different scales through a new Conceptual Hybrid Energy Model (COHYBEM). The main objective was to develop a multi-variable model to allow a new complete and comprehensive techno-economic analysis of the performance of possible hybrid renewable power systems at different scales.
The purpose is to evaluate the influence of critical parameters by changing key parameters in the developed model and identifying their impacts. It covers big data analyses, simulation and optimization of hybrid energy solutions, combining wind, solar and hydropower energy sources with the energy storage technology of pump hydropower storage.
The research also denoted the Pareto front with the increasing power installed, for the maximum efficiency and total satisfied demand by Wind + PVSolar and by Hydro converges to a higher percentage, while a minimum waste by Wind + PVSolar is also progressing towards the increasing scales. In terms of investment costs for the 243 analyzed case studies, it varies between 45 k € present value (NPV) between 18 and 600 k scale analyzed.
This research presents a multicriteria approach for the best hybrid water supply solution of a multipurpose Pumped-Storage Hydropower (PSH) system, using the Generalized Reduced Gradient (GRG) method in Solver, with the optimization process considering key factors, such as Net Present Value (NPV), the number of energy conversion devices, renewable energy production, source availability, reservoir capacities, topographic constraints, and energy tariffs.
The methodology combines a literature review, methodological development, and machine learning applications for hybrid water-energy systems. Results indicate that solar-only solutions are insufficient in high hydropower potential scenarios while integrating wind turbines significantly enhances energy production and profitability by generating surplus energy for grid sales. The timing of energy sales and the incorporation of battery storage also impact NPV, which can exceed 180 million euros. Wind energy contributes to continuous profitability and optimized system performance, particularly in isolated regions. The PSH system can manage 130,000 cubic meters of water daily, storing 25 MWh of energy, and reducing CO 2 emissions by over 18,000 tonnes per year.
These findings highlight the importance of renewables, such as wind energy, and effective operational management. It enhances the economic viability and environmental sustainability of hybrid water-energy systems.
A thorough literature review was conducted on the effects of free surface oscillation in open channels, highlighting the risks of the occurrence of positive and negative surge waves that can lead to overtopping. Experimental analyses were developed to focus on the instability of the flow due to constrictions, gate blockages, and the start-up and shutdown of hydropower plants.
A forebay at the downstream end of a tunnel or canal provides the right conditions for the penstock inlet and regulates the temporary demand of the turbines. In tests with a flow of 60 to 100 m3/h, the effects of a gradually and rapidly varying flow in the free surface profile were analyzed. The specific energy and total momentum are used in the mathematical characterization of the boundaries along the free surface water profile. A sudden turbine stoppage or a sudden gate or valve closure can lead to hydraulic drilling and overtopping of the infrastructure wall. At the same time, a PID controller, if programmed appropriately, can reduce flooding by 20–40%. Flooding is limited to 0.8 m from an initial amplitude of 2 m, with a dissipation wave time of between 25 and 5 s, depending on the flow conditions and the parameters of the PID characteristics.
This research explores the link between hydropneumatic energy storage capacity and the efficiency and flexibility of hybrid energy systems in water-energy solutions. A new methodology is introduced, featuring mathematical models, experimental data collection, and hydraulic simulations using 1D and 2D CFD models for hydropneumatics modeling.
A promised energy storage efficiency of around 30–50 % was obtained on a small lab scale. The optimization of hybrid systems through Solver and Python algorithms with various objective functions enables optimal design choices tailored to specific needs such as drinking water supply, irrigation, or industrial processes.
Hydropneumatic vessels emerge as an effective storage solution, combining pumped storage and hydropower in one circuit. When integrated with renewable sources, such as solar (PV) and wind energy, they offer a flexible, long-lasting energy management system, applicable across different water-energy sectors to support Sustainable Development Goals. A case study with 4.8 Mm 3 /year water allocation, producing 1000 MWh of hydropower and 13500 MWh of solar energy, achieved 100 % water reliability and a 25-year cash flow of 2.5 million euros.
A new methodology, called HY4RES models, includes hybrid energy solutions (HESs) based on the availability of renewable sources, for 24 h of water allocation, using WaterGEMS 10.0 and PVGIS 5.2 as auxiliary calculations.
The optimization design was achieved using Solver, with GRG nonlinear/evolutionary programming, and Python, with the non-dominated sorting genetic algorithm (NSGA-II). The study involves the implementation of complex multi-objective and multi-variable algorithms with different renewable sources, such as PV solar energy, pumped hydropower storage (PHS) energy, wind energy, grid connection energy, or battery energy, and also sensitivity analyses and comparisons of optimization models.
Higher water allocations relied heavily on grid energy, especially at night when solar power was unavailable. For a case study of irrigation water needs of 800 and 1000 m3/ha, the grid is not needed, but for 3000 and 6000 m3/ha, grid energy rises significantly, reaching 5 and 14 GWh annually, respectively. When wind energy is also integrated, at night, it allows for reducing grid energy use by 60% for 3000 m3/ha of water allocation, yielding a positive lifetime cashflow (EUR 284,781). If the grid is replaced by batteries, it results in a lack of a robust backup and struggles to meet high water and energy needs. Economically, PV + wind + PHS (Pumped Hydropower Storage) + grid energy is the most attractive solution, reducing the dependence on auxiliary sources and benefiting from sales to the grid.
A new methodology for hybrid energy systems (HESs) was developed, namely the HY4RES model, tailored for the water sector, covering hybrid energy objective functions and grid or battery support using optimization algorithms in Solver, MATLAB, and Python, with evolutionary methods. HOMER is used for hybrid microgrids and allows for comparison with HY4RES, the newly developed model. Both models demonstrated flexibility in optimizing hybrid renewable solutions.
This study analyzed an irrigation system for 3000 m3/ha (without renewables (Base case) and the Proposed system— with PV solar and pumped-hydropower storage to maximize cash flow over 25 years).
Case 1— 3000 m3/ha presented benefits due to PV supplying ~87% of energy, reducing grid dependency to ~13%. Pumped-hydropower storage (PHS) charges with excess solar energy, ensuring 24 h irrigation. Sensitivity analyses for Case 2—1000—and Case 3—6000 m3/ha—highlighted the advantages and limitations of water-energy management and system optimization. Case 2 was the most economical due to lower water-energy needs with noteworthy energy sales (~73.4%) and no need for the grid. Case 3 led to increased operating costs relying heavily on grid energy (61%), with PV providing only 39%. PHS (Pumped Hydropower Storage) significantly lowered operating costs and enhanced system flexibility by selling excess energy to the grid.
The world’s water infrastructures suffer from inefficiencies, such as high energy consumption and water losses due to inadequate management practices and feeble pressure regulation, leading to frequent water and energy losses. This strains vital water and energy resources, especially in the face of the worsening challenges of climate change and population growth.
A novel method is presented that integrates micro-hydropower plants, with pumps as turbines (PATs), in the water network in the city of Funchal. Sensitivity analyses evaluated the microgrid’s response to variations in the cost of energy components, showing favorable outcomes with positive net present value (NPV). PV solar and micro-wind turbines installed exclusively at the selected PRV sites within the Funchal hydro grid generate a combined 153 and 55 MWh/year, respectively, supplementing the 406 MWh/year generated by PATs. It should be noted that PATs consistently have the lowest cost of electricity (LCOE***), confirming their economic viability and efficiency across different scenarios, even after accounting for reductions in alternative energy sources and grid infrastructure costs.
*PHS: Pumped Hydropower Storage
**BESS: Battery Energy Storage Systems
***LCOE: Levelized Cost Of Energy – A metric for gauging the average cost of electricity generation over the lifetime of an energy asset
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