Socially-and-Environmentally-Aware Power Management in a Residential Neighborhood under Heat Wave Events.

Extreme ambient temperatures can place significant stress on various power grid components by pushing them towards their operational limits. From an electric utility perspective, it is desired to reduce the power consumption and alleviate the stress on assets. This can be achieved by implementing demand response targeting air conditioning units, which typically account for the largest portion of residential demand during a heat wave. However, this is a delicate matter since excess indoor temperatures can affect the health of the residents, especially children and the elderly. This places a limitation on how frequently and to what extent A/C demand response should be used. In addition to reducing demand, efficient asset utilization necessitates that impacts of temperature on capacity and lifetime of assets be considered in order to avoid overloading them. Hence, the energy dispatch problem poses multiple objectives that need to be optimized simultaneously. To make matters more complicated, the problem is subject to uncertainties associated with parameters and input data, e.g. building occupancy levels, electric demand, and temperature-related correction factors for capacity of generation resources, to name a few. To address these uncertainties, the energy dispatch model needs to be able to guarantee feasibility even under worst-case conditions. In this paper, a robust optimization solution is introduced that tries to solve the above multi-objective optimization problem subject to uncertainties in model parameters and input data. It is shown through a case study that considering the uncertainties makes the dispatch more conservative. However, this is necessary since failing to include them can lead to mismatches between demand and generation, which could jeopardize the security of the grid.