Spatial optimization of residential urban district - Energy and water perspectives

• Many cities around the world have reached a critical situation when it comes to energy and water supply, threatening the urban sustainable development. The aim of this paper is to develop a spatial optimization model for the planning of residential urban districts with special consideration of renewables and water harvesting integration. In particular, the paper analyses the optimal configuration of built environment area, PV area, wind turbines number and relative occupation area, battery and water harvester storage capacities, as a function of electricity and water prices. The optimization model is multi-objective which uses a genetic algorithm to minimize the system life cycle costs, and maximize renewables and water harvesting reliability. The developed model can be used for spatial optimization design of new urban districts. It can also be employed for analyzing the performances of existing urban districts under an energy-water-economic viewpoint. Assuming a built environment area equal to 75% of the total available area, the results show that the reliability of the renewables and water harvesting system cannot exceed the 6475 and 2500 hours/year, respectively. The life cycle costs of integrating renewables and water harvesting into residential districts are mainly sensitive to the battery system specific costs since most of the highest renewables reliabilities are guaranteed through the energy storage system.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)

Nyckelord

Genetic algorithm

Hybrid power systems

Optimization

Renewable energy

Residential urban districts

Water harvesting

Costs

Electric batteries

Electric energy storage

Genetic algorithms

Harvesting

Housing

Life cycle

Reliability

Renewable energy resources

Runoff

Site selection

Sustainable development

Water conservation

Water supply

Wind turbines

Zoning

Energy storage systems

Renewable energies

Residential districts

Spatial optimization model

Urban sustainable development

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