Multi-facility aggregate production planning with prosumer microgrid: A two-stage stochastic program.

The U.S. industries accounted for 37% of the wind turbine capacity installed in 2020 and corporate solar purchases have totaled $22 billion over the last 10 years. However, affordability and intermittency of renewable generation are still the main obstacles for firms to power their operations using wind and solar energy. Aggregate production planning models that incorporate onsite renewable energy (APPMs-RE) are the state-of-the-art to facilitate renewable adoption. A large number of APPMs are available in the literature, but renewables-based APPMs are still inadequately investigated. This paper proposes a novel APPM-RE because it optimizes wide-ranging RE decisions such as microgrid capacity, energy storage, prosumer energy transactions, and demand response along with production, machine usage, and workforce levels to minimize cost. The model is a two-stage stochastic program considering uncertainties in product demand, labor and machine capacity, and power generation. The research goals are to (1) investigate the feasibility of decarbonizing the production, transportation, and warehousing operations, (2) examine the system affordability under practical hourly load requirements, (3) assess the cost-benefit of a prosumer energy transaction mechanism (PETM), (4) identify the effect in cost and microgrid capacity of time-of-use tariff, and (5) demonstrate the suitability of a two-stage stochastic programming model. The numerical experiments relying on climate analytics of six U.S. cities represent a broad scope of climate conditions. The managerial insights derived from this study are: (1) renewable microgrids with PETM may attain net-zero carbon operations with an affordable levelized cost of energy, and (2) time-of-use stimulates more adoption of solar generation than the flat rate. The Aggregate Production Planning Problem with Renewable and Prosumer Microgrids in a Multi-Site Manufacturing Supply Chain System. [Display omitted] • Jointly optimizes aggregate production planning and microgrid sizing decisions. • Considers uncertainties in products' demand, labor capacity, machine capacity and microgrids generation. • Incorporates time-of-use, prosumer energy transactions, and variable hourly load. • Includes probability distributions for hourly capacity factors of the renewables. • A holistic approach to assess the viability of onsite renewables in supply chains. [ABSTRACT FROM AUTHOR]