Multi-objective co-optimization of power and heat in urban areas considering local air pollution

This paper suggests a novel framework to co-optimize the power and heat in smart cities considering the local air pollution from energy generation units and traffic fumes. To achieve the aim, a smart city comprised of power and heat generation units is addressed. The energy system of the smart city can be connected to the main grid or be operated as a stand-alone power system. Connecting to the main grid, the city trades power in the wholesale electricity market with price uncertainty. In order to co-optimize the operation cost of energy units and to control the pollution levels of the urban area, a Combined Economic Pollution Dispatch Problem (CEPDP) is developed. The CEPDP is optimized under air pollution constraints from both energy generation units and traffic fumes. Increasing the applicability of the suggested approach, pollution density is addressed using the Box model while the wind speed and surface roughness influence on it. To solve the CEPDP, a multi-objective Non-Dominated Sorting Genetic Algorithm (NSGA II) is proposed. The suggested approach is implemented in a virtually-designed smart city located in the center of Iran. The results show that although the use of distributed generation decreases the global emission all over the world, it transmits the air pollution from suburban areas to cities increasing the local pollution. The two conflict objectives, i.e. global and local pollutions, may change the operation of distributed generation to meet the local environment requirements of cities.