The objective of this thesis is to provide a foundation for evaluating the water costs associated with electricity production to calculate the avoided water cost of energy for solar PV and wind technologies relative to coal, natural gas, nuclear, geothermal, concentrated solar thermal, and biomass. Water consumption is estimated for energy production (fuel extraction and preparation) and electricity generation (power plant operation) using the best available information from published articles. The quantity of water consumed for electricity production is monetized for a Southern California case study based on the water rates of Metropolitan Water District of Southern California (MET), which is the largest wholesale supplier of surface water in the United States. Water withdrawals are addressed but not included in the monetization of water consumption. Case studies of specific power plant’s water costs are used for comparison and demonstrate variation in water costs due to variations in water consumption. Water costs are estimated in terms of water cost ($) per unit energy generated (MWh). Since solar PV and wind energy are shown to have negligible water consumption relative to the other technologies, the water costs for each of the other electrical generation methods are equivalent to the water savings potential of solar PV and wind generated electricity. Compared to other evaluated electricity sources that could provide electricity to Southern California, solar PV and wind energy can save water worth $0.76/MWh for natural gas combined-cycle plants, $0.94/MWh for geothermal power plants, $1.01/MWh for biomass power plants, between $1.14 and $1.82 per MWh for concentrated solar thermal plants, $1.43/MWh for nuclear power plants, and $1.49/MWh for coal power plants. Results indicate that there are three processes that use substantial amounts of water: fuel extraction (for coal, natural gas, and nuclear), thermoelectric cooling of power plants and emissions controls such as carbon capture and sequestration. Carbon capture and sequestration are estimated to almost double the water consumption costs of coal and natural gas power plants. Of the evaluated technologies, only solar PV and wind do not require any of those three steps. Solar PV and wind energy can thus save the greatest value of water when displacing power plants that utilize (or may someday be required to utilize) all three of the major culprits of water consumption. Even the use of one of these processes (particularly thermoelectric cooling) results in substantial water consumption. Total water costs for each technology were normalized to the total expected electrical output of a typical capacity natural gas combined-cycle power plant to demonstrate the economies of scale of power production. Over a forty year lifespan of a typical natural gas power plant, total water consumption would result in $67 million worth of water (southern CA wholesale prices). To generate the same amount of electricity the total value of water consumption is estimated to be $83 million for geothermal plants, $89 million for biomass plants, $100 million to $160 million for concentrated solar thermal plants, $126 million for nuclear plants, and $131 million for coal power plants. The use of carbon capture and sequestration is expected to nearly double these total water costs. Compliance with environmental regulations can cause expenses much greater than water consumption. For example, mitigation costs for impingement and entrainment (a consequence of cooling water withdrawals) as well as the cost to convert to closed-loop cooling for environmental compliance can be considered costs associated with water usage. This is demonstrated by a case study about the Los Angeles Department of Water and Power regarding the elimination of once through cooling. The conversion to closed-loop cooling for the Haynes natural gas power plant is expected to cost $782 million, resulting in an estimated unit cost of $10.66/MWh. Finally, the economic benefits of the California Renewables Portfolio Standard are calculated with respect to water consumption. By holding hydroelectricity, geothermal, biomass and CST production constant and utilizing solar PV and wind to meet the 33% renewables target by 2020, a water value of $28.5 million/year can be conserved relative to meeting rising electricity demand with only natural gas combined-cycle generation. MET water rates increased 70% from 2008 to 2014. If water rates increase at the same rate over the next six years, the water savings of the Renewable Portfolio Standard would be 70% higher in 2020 dollars, equating to water savings of $48.4 million per year.

Yes / In this research, the effect of operating parameters on the fresh water production cost of hybrid Multi Effect Distillation (MED) and Reverse Osmosis (RO) system is investigated. To achieve this, an earlier comprehensive model developed by the authors for MED + RO system is combined with two full-scale cost models of MED and RO processes collected from the literature. Using the economic model, the variation of the overall fresh water cost with respect to some operating conditions, namely steam temperature and steam flow rate for the MED process and inlet pressure and flow rate for the RO process, is accurately investigated. Then, the hybrid process model is incorporated into a single-objective non-linear optimisation framework to minimise the fresh water cost by finding the optimal values of the above operating conditions. The optimisation results confirm the economic feasibility of the proposed hybrid seawater desalination plant.

Sistemas de irrigação localizada são conhecidos pela economia no consumo de água. No entanto, por ser um sistema de rede fixa, os custos de instalação e de operação tendem a ser elevados e sua utilização inibida. O presente trabalho teve como objetivo principal otimizar redes de distribuição de água para irrigação localizada, frente a diferentes configurações de declividade do terreno (0% a 5%) e tarifação de energia elétrica (0,0884 R$/kW a 0,2652 R$/kW) e água (0,01 R$/\'M POT.3\' a 0,10 R$/\'M POT.3\'. As variáveis de decisão para otimização, com auxílio de algoritmos genéticos, foram os diâmetros de cada trecho da rede, pré-definidos por: dois para linhas laterais, quatro para linhas de derivação, quatro para linhas secundárias e um para linha principal. Foi desenvolvido um código em MatLab, considerando todas as perdas de energia distribuídas e localizadas entre o início da rede e o conjunto motobomba para uma rede de irrigação localizada padrão. A vazão em marcha ao longo das linhas laterais foi representada pela vazão de serviço de cada emissor. No final executou-se uma análise de sensibilidade. Os resultados mostram que o custo da rede varia entre 1816,42 a 2312,13 R$/ha.ano. Observa-se que o aumento da declividade do terreno e da tarifa de energia elétrica diminui o custo proporcional com equipamentos e aumenta o custo total anualizado da rede de irrigação e o custo proporcional com energia elétrica. / Low-pressure irrigation systems are known for the economical advantage in water consumption. However, the installation and operation costs tend to be high and its use inhibited. The present work has the objective to optimize distribution water networks in low-pressure irrigation systems with respect to different configurations of land declivity (between 0% and 5%), electric energy cost (between 0.0884 R$/kW and 0.2652 R$/kW) and water cost (between 0.01 R$/\'M POT.3\' and 0.10 R$/\'M POT.3\'. The decision variable for optimization, with genetic algorithms, was the diameter of each stretch of the network, predefined as: two options for drip lines, four for derivation lines, four for secondary lines and one for main line. An optimization code was developed in MatLab, considering all the distributed and punctual energy losses between the network beginning and the pumping device for a low-pressure irrigation standard network. The outflow rate throughout the drip lines was represented by the service outflow of each emitter. Finally a sensitivity analysis was executed. The results show that the network cost varies between 1816.42 and 2312.13 R$/ha.year. The increase of the slope land and the tariff of electric energy diminishes the proportional cost with equipment and increases the total cost of irrigation network and the proportional cost with electric energy.

Sistemas de irrigação localizada são conhecidos pela economia no consumo de água. No entanto, por ser um sistema de rede fixa, os custos de instalação e de operação tendem a ser elevados e sua utilização inibida. O presente trabalho teve como objetivo principal otimizar redes de distribuição de água para irrigação localizada, frente a diferentes configurações de declividade do terreno (0% a 5%) e tarifação de energia elétrica (0,0884 R$/kW a 0,2652 R$/kW) e água (0,01 R$/\'M POT.3\' a 0,10 R$/\'M POT.3\'. As variáveis de decisão para otimização, com auxílio de algoritmos genéticos, foram os diâmetros de cada trecho da rede, pré-definidos por: dois para linhas laterais, quatro para linhas de derivação, quatro para linhas secundárias e um para linha principal. Foi desenvolvido um código em MatLab, considerando todas as perdas de energia distribuídas e localizadas entre o início da rede e o conjunto motobomba para uma rede de irrigação localizada padrão. A vazão em marcha ao longo das linhas laterais foi representada pela vazão de serviço de cada emissor. No final executou-se uma análise de sensibilidade. Os resultados mostram que o custo da rede varia entre 1816,42 a 2312,13 R$/ha.ano. Observa-se que o aumento da declividade do terreno e da tarifa de energia elétrica diminui o custo proporcional com equipamentos e aumenta o custo total anualizado da rede de irrigação e o custo proporcional com energia elétrica. / Low-pressure irrigation systems are known for the economical advantage in water consumption. However, the installation and operation costs tend to be high and its use inhibited. The present work has the objective to optimize distribution water networks in low-pressure irrigation systems with respect to different configurations of land declivity (between 0% and 5%), electric energy cost (between 0.0884 R$/kW and 0.2652 R$/kW) and water cost (between 0.01 R$/\'M POT.3\' and 0.10 R$/\'M POT.3\'. The decision variable for optimization, with genetic algorithms, was the diameter of each stretch of the network, predefined as: two options for drip lines, four for derivation lines, four for secondary lines and one for main line. An optimization code was developed in MatLab, considering all the distributed and punctual energy losses between the network beginning and the pumping device for a low-pressure irrigation standard network. The outflow rate throughout the drip lines was represented by the service outflow of each emitter. Finally a sensitivity analysis was executed. The results show that the network cost varies between 1816.42 and 2312.13 R$/ha.year. The increase of the slope land and the tariff of electric energy diminishes the proportional cost with equipment and increases the total cost of irrigation network and the proportional cost with electric energy.