Abstract
In this study, an interval fuzzy-stochastic chance-constrained programming based energy-water nexus (IFSCP-WEN) model is developed for planning electric power system (EPS). The IFSCP-WEN model can tackle uncertainties expressed as possibility and probability distributions, as well as interval values. Different credibility (i.e., γ) levels and probability (i.e., qi) levels are set to reflect relationships among water supply, electricity generation, system cost, and constraint-violation risk. Results reveal that different γ and qi levels can lead to a changed system cost, imported electricity, electricity generation, and water supply. Results also disclose that the study EPS would tend to the transition from coal-dominated into clean energy-dominated. Gas-fired would be the main electric utility to supply electricity at the end of the planning horizon, occupying [28.47, 30.34]% (where 28.47% and 30.34% present the lower bound and the upper bound of interval value, respectively) of the total electricity generation. Correspondingly, water allocated to gas-fired would reach the highest, occupying [33.92, 34.72]% of total water supply. Surface water would be the main water source, accounting for more than [40.96, 43.44]% of the total water supply. The ratio of recycled water to total water supply would increase by about [11.37, 14.85]%. Results of the IFSCP-WEN model present its potential for sustainable EPS planning by co-optimizing energy and water resources.
Highlights
It is predicted that the electricity demand will increase about 34.51% in 2035 due to population growth, economic development, industrialization, and urbanization throughout the world [1,2].It is essential to consume more energy resources to satisfy the rising electricity demand
Where the system costs would increase with raised γ levels and decrease with raised qi levels
interval fuzzy credibility-constrained programming (IFCP) can deal with possibility distributions and interval values when this type of uncertainty exists in objective and constraints, while chance-constrained programming (CCP) has advantages in handling probability distributions
Summary
It is predicted that the electricity demand will increase about 34.51% in 2035 due to population growth, economic development, industrialization, and urbanization throughout the world [1,2]. It is essential to consume more energy resources to satisfy the rising electricity demand. Energy security is highly dependent on water availability since the processes of extracting and refining fossil fuels, electricity generation, transportation, and storage demand vast amounts of water; in turn, water extraction, conveyance, treatment, and disposal require high energy use [3,4]. The interdependence between energy and water resources is commonly defined as the energy-water nexus. For electric power systems (EPS), water is supplied to produce hydro power and cool systems (open-loop, closed-loop and dry) in thermoelectric power plants (e.g., coal, natural gas, and nuclear), representing a significant branch of the energy-water nexus [5].
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