Search

Different forms of flexibility can help in balancing variable generation. This work focuses on industrial demand-side flexibility applied in copper production, which is expected to grow for the build-out of green technologies. This study assesses the potential of capacity-based energy demand flexibility (over-sizing production processes) in an industry embedded in fully renewable energy systems. For this, an optimization model for multi-vector energy systems planning is extended so that it also includes the sizing and operation of a production process. A case study is presented for copper production, with greenfield results until 2050. Results show that flexibility at the concentration and refining stages belongs to the cost-optimal system design, at least over the next decade. At current costs, the potential cost savings in the energy system for the production process through capacity-based demand flexibility range from 5 % to 12 %, depending on the technology scenario. These potential savings are expected to decrease over time if cost reductions of renewable energy supply and storage technologies materialize. Technology scenarios considering seawater pumped-hydro energy storage yield lower costs over the entire projected period. • Endogenous integration of industrial process in optimal energy system planning. • Demand flexibility in copper industry beneficial in rapid energy transition. • Cost savings between 5 and 12 % for current costs of energy technologies. [ABSTRACT FROM AUTHOR]

Extreme weather events, for example, prolonged droughts, are increasingly stressing electricity systems and threatening the achievement of energy transition goals. At the same time, countries such as Chile and New Zealand are developing strategies to export renewable energy through green hydrogen. This paper economically evaluates the use of future green hydrogen exports as strategic storage under the logic of energy insurance, based on the assumption that Chile and New Zealand will adopt a hydrogen economy. Our first contribution is to compare the marginal costs of re-electrified green hydrogen, for different scenarios, to the value of lost load in New Zealand and Chile. We then determine the marginal cost of energy produced from green hydrogen based on projected production, transportation, and re-electrification costs for the year 2030. Finally, we estimate the eventual penalties that exporters would incur in the case of breaking their contracts and the overall resulting system costs of using hydrogen for system security. We found that re-electrifying hydrogen can be competitive with conventional technologies at 3 USD/kg. At 1.5 USD/kg, hydrogen is more competitive than fossil fuel-based technologies, for both New Zealand and Chile. Thus, in 2030, it could make economic sense for New Zealand and Chile to use hydrogen as a strategic reserve. The system cost of the proposed insurance scheme in 2030 ranges from 0.53 to 1.76 USD/MWh, which is small compared to total electricity costs. These values can be used for power system expansion and operation planning. •Future green hydrogen exports could be configured as strategic energy reserve. •Re-electrified green hydrogen for reserves competitive with fossil fuels at 3 USD/kg. •Green hydrogen cost in Chile and New Zealand ranges between 1.5 and 3 USD/kg by 2030. •Compensating exporters for export contract breaches is cheaper than lost load. •This hydrogen-based insurance costs ranges from 0.53 to 1.76 USD/MWh. [ABSTRACT FROM AUTHOR]

This study innovatively combines a set of methods to assess the economic potential of pumped hydro energy storage. It first provides a method based on geographic information systems to study the potential of pumped-hydro for different topologies. Second, using cost estimates for each identified site, cost-potential curves are derived. Finally, these curves are used for planning a fully renewable system to assess their impact on investment recommendations. Applications to Chile, Peru, and Bolivia show the usability of the methods. Over 450 pumped-hydro locations are identified, totaling around 20 TWh (or 1600 GW of installed capacity with 12 h of storage). These numbers exceed by 20-fold the projected daily energy demand of the corresponding countries. When taking into account investment costs, most locations are cheaper than current Li-ion batteries, but only some are expected to remain competitive in the future. When using the resulting cost-potential curves to design a future energy system, the planning tool recommends about 1.6 and 5.0 times more pumped-hydro storage compared to using average values and literature values, respectively. These differences underline the significance of the found cost curves. [ABSTRACT FROM AUTHOR]

This paper presents an overview of distributed hydrogen systems (DHS) based on a literature review of 159 scientific publications. Research has grown exponentially since 2020, but the limited application in the Global South necessitates a broader spatial investigation. Power-to-hydrogen and green hydrogen concepts are found to be prevalent in the scientific literature. Although DHS is expected to accelerate the hydrogen economy transition, further emphasis should be on its energy security benefits. Most notably, hydrogen applications in scientific publications are falling short of market expectations, which is concerning. Moreover, distributed hydrogen production costs are incomparable to centralized production of hydrogen. The diverse challenges of DHS are addressed in scientific studies by focusing on miniaturization, optimization of DHS, and future uncertainties of hydrogen. Overall, identifying the research-market gap, current technology trends, and the future role and application of DHS will allow researchers to gain a deeper understanding of DHS and support its future growth. [ABSTRACT FROM AUTHOR]

For large energy consumers transitioning to high shares of solar energy, irradiance variability causes volatility in power generation and energy expenditures. Volatility in an end user's cash flow is harmful to their financial health, especially in abnormally cloudy years. This paper explores the utility of an irradiance-based weather derivative in mitigating cloud weather risk and measures the effectiveness of the developed derivative by applying it to a case study of two Chilean copper mines. Weather derivatives are financial instruments tied to an underlying weather variable that act as an insurance for the contract holder, executing indemnity payments based on an index value. This research develops a contract with a combined index based on monthly sums of irradiance and cloudy day sequencing to mitigate a solar mine's weather risk. The design and evaluation of contracts are based on LEELO, a linear optimization model outputting optimal sizes of solar photovoltaic, battery storage, and power-to-gas systems, as well as the operation of these systems for a given mine's load, irradiance and technology costs. Results indicate contracts are effective in cloudier climates with increasing utility for mines installing solar energy systems until the year 2030. After 2030 batteries begin to become a more cost-effective risk-hedging mechanism as they become more affordable. Image 1 • Irradiance-based weather derivative is developed for risk hedging of solar systems. • Hybrid index based on monthly irradiance counts and cloudy days sequencing. • Application to Chilean mines with solar-battery systems stabilizes cash flows. • Weather derivative is very effective in cloudier regions after the year 2030. • After 2040, risk mitigation via batteries is more cost effective than derivatives. [ABSTRACT FROM AUTHOR]

• Holistic yield simulation of a bifacial PV power plant in San Felipe, Chile. • Sensitivity analysis of ground reflectivity's impact on energy yield. • Analysis of ground shadows' impact on the energy yield. • Calculation of ground-reflected irradiance (GRI) using 3D view factors. • Decomposition of absorbed irradiation into eight contributions. Bifacial photovoltaics (bifacial PV) offer higher energy yields as compared to monofacial PV. The development of appropriate models for simulating the energy yield of bifacial PV power plants is a major topic in both research and industry. In particular, the adequate calculation of the energy yield from ground-reflected irradiance (GRI) is challenging. The purpose of this work is to investigate the currently available energy yield models and suggest areas for improvement. A new model with the proposed enhancements is used to investigate the behaviour of bifacial PV power plants in more detail. The model calculates the absorbed irradiation originating from eight irradiance contributions for the front and rear of each cell string: DNI, DHI, GRI from DHI (GRI DHI) and GRI from DNI (GRI DNI). The model was tested using a defined case study power plant. The breakdown of absorbed irradiation (subscript "ab") into its contributions revealed that while in summer months GRI DNI-ab-rear is significantly larger than GRI DHI-ab-rear , both are roughly the same in winter months. Furthermore, for the calculation of GRI the common simplification of infinitely long module rows was avoided by implementing an algorithm for the view factor calculation for a three-dimensional space. This procedure allowed for the assessment of impact of the ground size on the annual energy yield. In a sensitivity analysis, it has been shown that the extension of the relevant ground area resulted in an asymptotical increase of the energy yield. Additionally, the impact of ground shadows on the power plant's performance was quantified. The presence of ground shadows reduced the annual electricity generation by almost 4%, compared to a hypothetical scenario where no ground shadows existed. Finally, five different ground surfaces and the resulting bifacial gains were analysed. The results show that while dry asphalt (12% reflectivity) gave less than 6% of bifacial gain related to generated electricity (BG el), the use of a white membrane (70%) would result in 29% of BG el. [ABSTRACT FROM AUTHOR]

Abstract Hydropower plants frequently operate at high output during peak hours and at low output (or even shutoff) during off-peak hours. This scheme, called "hydropeaking", is harmful to downstream ecosystems. Operational constraints (minimum flows, maximum ramps) are frequently used to mitigate the impacts of hydropeaking. However, they reduce the operational flexibility of hydroelectric dams and increase the operational cost of power systems. Another approach to mitigating ecological impacts from hydropeaking is using structural measures, such as re-regulation reservoirs or afterbays. The first contribution of our work is to study the cost-effectiveness of these re-regulation reservoirs in mitigating ecological impacts from subdaily hydropeaking. Our second contribution is assessing energy storage (specifically, batteries) to mitigate the financial impacts of implementing peaking restrictions on dams, which represents the first attempt in the literature. Understanding these mitigation options is relevant for new hydropower dams, as well as for existing ones undergoing relicensing processes. For this, we formulate an hourly mixed-integer linear optimization model to simulate the annual operation of a power system. We then compare the business-as-usual (unconstrained) hydropower operations with ecologically constrained operations. The constrained operation, by limiting hydropower ramping rates, showed to obtain flows close to the natural streamflow regime. As next step, we show how re-regulation reservoirs and batteries can help to achieve these ecological constraints at lower costs. While the former are cost-effective for a very broad range of investment costs, the latter will be cost-effective for hydropeaking mitigation from 2025 onwards, when their capital costs have fallen. If more stringent environmental constraints are imposed, both solutions become significantly more attractive. The same holds for scenarios of more renewable generation (in which the operational flexibility from both alternatives becomes more valuable). After 2030, batteries can match the cost-effectiveness of expensive re-regulation reservoirs. Our findings are valuable for policy and decision makers in energy and ecosystem conservation. Highlights • We compare re-regulation reservoirs with batteries for hydropeaking mitigation. • We develop profitability curves that track profitability alongside capital costs. • Re-regulation reservoirs are highly cost-effective (easily recoup capital costs). • Batteries will become economically viable for hydropeaking mitigation by 2025. • Results will inform public/private sector management of dams' environmental impacts. [ABSTRACT FROM AUTHOR]

Electrical energy storage (EES) is a promising flexibility source for prospective low-carbon energy systems. In the last couple of years, many studies for EES capacity planning have been produced. However, these resulted in a very broad range of power and energy capacity requirements for storage, making it difficult for policymakers to identify clear storage planning recommendations. Therefore, we studied 17 recent storage expansion studies pertinent to the U.S., Europe, and Germany. We then systemized the storage requirement per variable renewable energy (VRE) share and generation technology. Our synthesis reveals that with increasing VRE shares, the EES power capacity increases linearly; and the energy capacity, exponentially. Further, by analyzing the outliers, the EES energy requirements can be at least halved. It becomes clear that grids dominated by photovoltaic energy call for more EES, while large shares of wind rely more on transmission capacity. Taking into account the energy mix clarifies—to a large degree—the apparent conflict of the storage requirements between the existing studies. Finally, there might exist a negative bias towards storage because transmission costs are frequently optimistic (by neglecting execution delays and social opposition) and storage can cope with uncertainties, but these issues are rarely acknowledged in the planning process. [ABSTRACT FROM AUTHOR]

• To date the most complete model for planning South America's power sector. • South America's transition relies on solar, wind, and gas as bridging technology. • Lithium batteries and pumped hydro are the main storage technologies. • Modeling 30 nodes is a good trade-off between complexity and quality of results. • Hydrogen exports aid the integration of renewable generation. Europe and North America have numerous studies on 100% renewable power systems. South America, however, lacks research on zero-carbon energy systems, especially understanding South America as an interconnected region, despite its great renewable energy sources, increasing population, and economic productivity. This work extends the cost-optimization energy planning model LEELO and applies it to South America. This results in the to-date most complete model for planning South America's power sector, with a high temporal (8760 time steps per year) and spatial (over 40 nodes) resolution, and 30 technologies involved. Besides the base case, we study how varying spatial resolution for South America impacted investment results (43, 30, 16, 1 node). Finally, we also evaluate green hydrogen export scenarios, from 0% to 20% on top of the electricity demand. Our study reveals that South America's energy transition will rely, in decreasing order, on solar photovoltaic, wind, gas as bridging technology, and also on some concentrated solar power. Storage technologies equal to about 10% of the total installed power capacity would be required, aided by the existing hydropower fleet. Not only is the transition to renewables technically possible, but it is also the most cost-efficient solution: electricity costs are expected to reach 32 €/MWh from the year 2035 onwards without the need for further fossil fuels. Varying the spatial resolution, the most-resolved model (43 nodes) reveals 11% and 6% more costs than the one-node and one-node-per-country (16) models, respectively, with large differences in investment recommendations, especially in concentrated solar and wind power. The difference between 43 and 30 nodes is negligible in terms of total costs, energy storage, and technology mix, indicating that 30 nodes are an adequate resolution for this region. We then use the 30-node model to analyze hydrogen export scenarios. The electricity costs drop, as hydrogen is not only a load but also a flexibility provider. Most green hydrogen is produced in Chile, Argentina, and northeast Brazil. For future work, we propose to do an integrated energy plan, including transport and heat, for the region, as well as modeling local hydrogen demands. This work aims to inform policymakers of sustainable transitions, and the energy community. [ABSTRACT FROM AUTHOR]

• New method for water and energy systems planning. • First endogenous integration of coupled desalination and pumped hydro in planning models. • First design of integrated multi-vector systems for copper production. • Renewable-based desalinated water and energy supply economically attractive today. • Renewable-based is the least-cost alternative by 2030. Copper is required for the transformation of global energy systems, and its production is intensive in water and energy. Several studies have investigated the design of renewable energy systems for copper production, aiming at reducing its environmental footprint. Here, we present the first integrated design for desalinated water and energy supply that considers all forms of energy required in the copper production process. For this, we develop an optimization model for planning integrated multi-vector energy and water systems. The model includes -for the first time in an energy system planning model- a concept for integrated pumped-hydro storage using sweater and reverse osmosis desalination. Our results show that water-energy systems for copper production based exclusively on renewables can today achieve costs as low as those of conventional fossil-based systems, when integrating multi-vector planning and seawater pumped-hydro storage. For a case study in Chile and in fully renewable scenarios, the specific cost of supplying energy and desalinated water decreases from 520–670 € per ton of copper at current costs to 330–360 by 2050. By 2030, using seawater pumped-hydro storage makes a fully renewable, multi-energy scenario the least-cost alternative. Such an integrated system is an enabler for reducing the environmental footprint that copper brings into the global energy transition. [ABSTRACT FROM AUTHOR]

Wind and solar energy play a pivotal role in deep decarbonization pathways for the future. However, energy scenario studies differ substantially in the contribution of these technologies, as the technology selection in models strongly depends on the choice of techno-economic parameters. In this article, we systematically compare the cost assumptions for solar and wind technologies in global, regional and national energy scenario studies with costs observed in reality and with recent remuneration from market auctions. Specially, we compared the capital expenditure (CAPEX) and the levelized cost of electricity (LCOE) towards the year of 2050 when available with historical market prices and auction prices. Our results indicate that the trend of rapid cost declines has been structurally underestimated in virtually all future energy scenario analyses and suggest that even the most recent studies refer to obsolete or very conservative values. This leads to underestimating the future role and level of deployment of renewable technologies. We recommend an open database for costs of renewable technologies to enhance the accuracy and transparency of future energy scenarios. • Systematic review of cost assumptions for renewables in selected energy scenarios. • Cost assumptions compared with remuneration levels from market-based auctions. • Rapid cost-decline of renewables has been systematically underestimated. • An open cost-database would greatly benefit the energy scenario community. • Abstract. [ABSTRACT FROM AUTHOR]

• We calculate the optimal electricity supply for large copper mines around the world. • From 2020 onwards, all mines should have solar shares above 25%. • In 2030, the first fully solar mines should be established. • In the long-term, Chile and Peru have the lowest electricity costs. • In most locations, low-cost solar energy makes up for costs from declining ore grades. Extracting copper is energy-intensive. At the same time, copper is a key material for building the energy systems of the future. Both facts call for clean copper production. The present work addresses the greenhouse gas emissions of this industry and focuses on designing the future electricity supply of the main copper mines around the world, from 2020 to 2050, using distributed solar photovoltaic energy, storage, and a grid connection. We also consider the increasing energy demand due to ore grade decline. For the design, we use an optimization model called LEELO. Its main inputs are an hourly annual demand profile, power-contract prices for each mine, cost projections for energy technologies, and an hourly annual solar irradiation profile for each mine. Our findings show that it is attractive for the mines to have today a solar generation of 25% to 50% of the yearly electricity demand. By 2030, the least-cost solution for mines in sunny regions will be almost fully renewable, while in other regions it will take until 2040. The expected electricity costs range from 60 to100 €/MWh for 2020 and from 30 to 55 €/MWh for 2050, with the lower bound in sunny regions such as Chile and Peru. In most locations assessed, the low cost of solar energy will compensate for the increased demand due to declining ore grades. For the next steps, we recommend representing the demand with further detail, including other vectors such as heat and fuels. In addition, we recommend to include the embodied emissions of the technologies to get a more complete picture of the environmental footprint of the energy supply for copper production. [ABSTRACT FROM AUTHOR]

Renewable energy systems are now accepted to be mandatory for climate change mitigation. These systems require a higher material supply than conventional ones. Particularly, they require more copper. The production of this metal, however, is intensive in energy consumption and emissions. Therefore, renewable energy systems must be used to improve the environmental performance of copper production. We cover the current state of research and develop recommendations for the design of renewable energy systems for copper production. To complement our analysis, we also consider studies from other industries and regional energy systems. We provide six recommendations for future modeling: (a) current energy demand models for copper production are overly simplistic and need to be enhanced for planning with high levels of renewable technologies; (b) multi-vector systems (electricity, heat, and fuels) need to be explicitly modeled to capture the readily available flexibility of the system; (c) copper production is done in arid regions, where water supply is energy-intensive, then, water management should be integrated in the overall design of the energy system; (d) there is operational flexibility in existing copper plants, which needs to be better understood and assessed; (e) the design of future copper mines should adapt to the dynamics of available renewable energy sources; and (f) life cycle impacts of the components of the system need to be explicitly minimized in the optimization models. Researchers and decision-makers from the copper and energy sector will benefit from this comprehensive review and these recommendations. We hope it will accelerate the deployment of renewables, particularly in the copper industry. • Copper is required to build energy systems of the future. • Smart integration of renewables can lower the cost of cleaner copper production. • We provide six recommendations to model these systems. • Further efforts are required in the modeling of energy demand and flexibility. • Following these recommendations will enable cleaner and cheaper designs. [ABSTRACT FROM AUTHOR]

Sustainable energy transitions (SET) are complex processes spanning over decades and subject to deep uncertainty from a variety of sources, such as climate change, technology development, and social and institutional contexts. Although this is a recognized issue in SET, previous studies and reviews in this field lack a comprehensive identification of the deep uncertainty sources and the capacities of methods to cope with them. Based on the review of nearly 100 selected references that involve 19 case studies, this review systematically identifies and characterizes these sources of deep uncertainty for the first time. In doing so, it considers the techno-economic, political, and socio-technical dimensions of SET and analyses Decision Making under Deep Uncertainty (DMDU) methods to cope with the specific characteristics of SET. The analysis of the applicability of DMDU methodologies to SET reveals that no predominant methodology covers all aspects of deep uncertainty sources and that the DMDU paradigm could benefit from a multi-method perspective specifically designed for SET. Thus, through some final recommendations, this review aims to provide guidance in the process of deep uncertainty characterization in SET studies and to constitute a basis to support decision-makers in selecting the adequate DMDU method or on generating new dedicated approaches for conducting SET studies under deep uncertainty considering the specific local contexts. [Display omitted] • Characterization of deep uncertainty sources in Sustainable Energy Transitions. • Basis for selection of adequate methods for Decision Making under Deep Uncertainty. • Sustainable Energy Transitions require a specific deep uncertainty treatment method. • A multi-method approach could benefit model-based Sustainable Energy Transitions. [ABSTRACT FROM AUTHOR]

Abstract When large-scale photovoltaic power plants (PV-PPs) operate under partially-shaded conditions, their power output can be extremely fluctuating. This situation may compromise the energy balance of the electricity grid, which in turn threatens its secure operation from a frequency control viewpoint. In this context, the development of control strategies to reduce the variability of the power generated by PV-PPs is a key issue towards reaching sustainable electric systems. With this purpose, this paper proposes a novel control strategy to reduce the negative effects that PV-PPs operating under partially-shaded conditions may cause on the frequency control of electricity grids. The control operates the PV-PP in deload mode, i.e. keeping power reserves. The deload level of the PV-PP is set dynamically during the day considering a 10-min forecast of solar generation. The forecast is performed with artificial neural networks, first predicting the day-type (sunny, cloudy, overcast) and then the solar power. The controller continuously monitors the condition of the PV-PP: when the plant is under non-uniform shaded conditions, it deploys the power reserves to smooth the PV power. The proposed control was applied to a Chilean case study focused on the Atacama Desert, testing different control rules for the deload level. The obtained results show that the implementation of the proposed control considerably improves the frequency performance of the electricity grid. Although operating in deload mode implies energy losses in the PV-PP, the use of a dynamic deload level minimizes these losses when compared to a constant deload level. Altogether, the dynamic simulations show that such a control can play a relevant role for frequency control in electrical power systems with high shares of photovoltaic power. Our findings give important insights to electricity regulators about the technical requirements that they should impose to large-scale PV-PPs in electric power systems dominated by renewables energies. Highlights • Large-scale PV systems under partial shadows challenge the frequency regulation. • We operate the PV system in dynamic deload, as a function of the solar forecast. • Our dynamic PV control strategy improves the power system frequency regulation. • Our dynamic PV deload level allows operating closer to the maximum power point. • The dynamic control is critical in days with high irradiance variability. [ABSTRACT FROM AUTHOR]

Solar energy technologies are a promising option to lower the greenhouse gas emissions of energy generation. Using solar technologies in energy-intensive industries located in arid climate zones is an attractive alternative for that purpose. In this work, the environmental benefit of integrating solar energy in the Chilean copper industry is explored in respect of global warming potential (GWP). A new life cycle assessment model for copper cathodes production in Chile and the integration of three solar technologies was developed. The GWP of the production of copper cathodes was calculated considering local representative conditions for climate, energy mix, and energy demand of the industry. It was computed at 6.0 tCO 2eq /t Cu 2 for a pyrometallurgical process (P-Cu) and 4.9 tCO 2eq /t Cu for a hydrometallurgical process (H-Cu). Further contributions of this paper are the consideration of the decline in ore grade (i.e. copper content in the mineral) and the interconnection of Chile's two main power grids as sensitivities to the baseline. The interconnection of the power grids causes a GWP-reduction of 22% for P-Cu and 37% for H-Cu. In parallel, the expected lower ore grade by 2020 would increase the GWP of copper production by 10% for P-Cu and 4% for H-Cu. If the electricity that is currently taken from the grid is exclusively fed by solar technologies, the reduction on the GWP of copper production would be up to 63% and 76% for P-Cu and H-Cu processes. These numbers do not represent the upper bound for the reduction on the GWP of copper production that can be achieved with solar technologies because the substitution of on-site fossil fuel combustion with solar energy is another interesting mitigation option, which was not considered in this study. In order to achieve even less carbon-intensive production processes, an improved understanding of the copper's industry energy flows and profiles is needed. This would allow to assess the integration of further solar energy technologies and conceive the future of solar copper mining . [ABSTRACT FROM AUTHOR]

The cost-optimal pathway for moving from the current fossil-fuel based energy system to 100% renewables is still an open question. This work presents the first study that analyses the transition towards a 100% renewable energy system under different spatial resolutions (1-node, 6-nodes electrically isolated and interconnected) and various coupling configurations for the power, heat, transport and desalination sectors. With the LUT Energy System Transition Model for the case of Chile, 12 scenarios were investigated in an hourly resolution and considering more than one hundred energy-related technologies. The results show that: (1) 1-node systems deliver too simplistic results for key metrics; (2) power sector simulations can lead to a strongly distorted resources allocation compared to scenarios that include other sectors; (3) a multi-node model better reflects transmission bottlenecks and local resources, and; (4) the lowest-cost solution is reached when power transmission lines are considered. Thus, it is concluded that a cost-optimal, balanced, and realistic solution to reach a fully defossilised energy system is transitioning towards a multi-node, interconnected, and fully sector-coupled energy system. This can be called, in short, the 'Power-to-X economy', which in the case of Chile would more accurately be a 'Solar-to-X economy', given the high solar share found in the simulations. • 12 scenarios analysed with different spatial resolution and sector coupling setups. • Various coupling setups for the power, heat, transport and desalination sectors. • Electricity is the main energy carrier followed by e-hydrogen mainly for e-fuels. • A multi-node, interconnected and sector-coupled system is the most optimal solution. • First explanation of the 'Solar-to-X economy' concept. [ABSTRACT FROM AUTHOR]

• Environmental constraints in common water value tools increase calculation time. • The use of those water values is not always profitable. • The fewer the number of turbines, the greater the likelihood of that profitability. We evaluate the practical usefulness of incorporating maximum ramping rates and minimum environmental flows into a linear programming based water value calculator for hydropower plants that participate in the day-ahead electricity market. The methodology consists of three steps: first computing the water value once with and once without environmental constraints, then simulating the plant operations using each water value, and finally comparing the simulation profits. A set of nine representative hydropower plants formed by combinations of three real locations (in Colombia, Norway and Spain) and three turbine configurations (from one to three Francis units) are individually analyzed. Each plant is simulated in two synthetic 10-year long series subject to fifteen combinations of maximum ramping rates and minimum flows with the two above-mentioned water values, totaling 540 simulations. The results indicate that incorporating the analyzed environmental constraints into a linear programming based water value calculator can be significantly profitable only when the hydropower plants have only one or at most two turbines. [ABSTRACT FROM AUTHOR]