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1. A two-stage stochastic aggregate production planning model with renewable energy prosumers,” in Proceedings of the 2021 Institute of Industrial and Systems Engineers (IISE) Virtual Conference, May 22-25, 2021, pp. 223-228.

   Islam, S. ; Novoa, C. ; Jin, T. ( June 2021 , Proceedings of the 2021 Institute of Industrial and Systems Engineers (IISE) Conference)

   Ghate, A. ; Krishnaiyer, K. ; Paynabar, K. (Ed.)

   This study presents a two-stage stochastic aggregate production planning model to determine the optimal renewable generation capacity, production plan, workforce levels, and machine hours that minimize a production system’s operational cost. The model considers various uncertainties, including demand for final products, machine and labor hours available, and renewable power supply. The goal is to evaluate the feasibility of decarbonizing the manufacturing, transportation, and warehousing operations by adopting onsite wind turbines and solar photovoltaics coupled with battery systems assuming the facilities are energy prosumers. First-stage decisions are the siting and sizing of wind and solar generation, battery capacity, production quantities, hours of labor to keep, hire, or layoff, and regular, overtime, and idle machine hours to allocate over the planning horizon. Second-stage recourse actions include storing products in inventory, subcontracting or backorder, purchasing or selling energy to the main grid, and daily charging or discharging energy in the batteries in response to variable generation. Climate analytics performed in San Francisco and Phoenix permit to derive capacity factors for the renewable energy technologies and test their implementation feasibility. Numerical experiments are presented for three instances: island microgrid without batteries, island microgrid with batteries, and grid-tied microgrid for energy prosumer. Results show favorable levelized costs of energy that are equal to USD48.37/MWh, USD64.91/MWh, and USD36.40/MWh, respectively. The model is relevant to manufacturing companies because it can accelerate the transition towards eco-friendly operations through distributed generation. 

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2. An integrated approach to microgrid sizing and flow shop scheduling via climate analytics

   Subramanyam, V. ; Jin, T. ; Novoa, C. ( April 2020 , Journal of cleaner production)

   null (Ed.)

   A variety of methods have been proposed to assist the integration of microgrid in flow shop systems with the goal of attaining eco-friendly operations. There is still a lack of integrated planning models in which renewable portfolio, microgrid capacity and production plan are jointly optimized under power demand and generation uncertainty. This paper aims to develop a two-stage, mixed-integer programming model to minimize the levelized cost of energy of a flow shop powered by onsite renewables. The first stage minimizes the annual energy use subject to a job throughput requirement. The second stage aims at sizing wind turbine, solar panels and battery units to meet the hourly electricity needs during a year. Climate analytics are employed to characterize the stochastic wind and solar capacity factor on an hourly basis. The model is tested in four locations with a wide range of climate conditions. Three managerial insights are derived from the numerical experiments. First, time-of-use tariff significantly stimulates the wind penetration in locations with medium or low wind speed. Second, regardless of the climate conditions, large-scale battery storage units are preferred under time-of-use rate but it is not the case under a net metering policy. Third, wind- and solar-based microgrid is scalable and capable of meeting short-term demand variation and long-term load growth with a stable energy cost rate. 

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3. The implications of uncertain renewable resource potentials for global wind and solar electricity projections

   https://doi.org/10.1088/1748-9326/ac3c6b  

   Santos Da Silva, Silvia R ; Iyer, Gokul ; Wild, Thomas B ; Hejazi, Mohamad I ; Vernon, Chris R ; Binsted, Matthew ; Miralles-Wilhelm, Fernando ( December 2021 , Environmental Research Letters)

   Abstract Studies exploring long-term energy system transitions rely on resource cost-supply curves derived from estimates of renewable energy (RE) potentials to generate wind and solar power projections. However, estimates of RE potentials are characterized by large uncertainties stemming from methodological assumptions that vary across studies, including factors such as the suitability of land and the performance and configuration of technology. Based on a synthesis of modeling approaches and parameter values used in prior studies, we explore the implications of these uncertain assumptions for onshore wind and solar photovoltaic electricity generation projections globally using the Global Change Analysis Model. We show that variability in parametric assumptions related to land use (e.g. land suitability) are responsible for the most substantial uncertainty in both wind and solar generation projections. Additionally, assumptions about the average turbine installation density and turbine technology are responsible for substantial uncertainty in wind generation projections. Under scenarios that account for climate impacts on wind and solar energy, we find that these parametric uncertainties are far more significant than those emerging from differences in climate models and scenarios in a global assessment, but uncertainty surrounding climate impacts (across models and scenarios) have significant effects regionally, especially for wind. Our analysis suggests the need for studies focusing on long-term energy system transitions to account for this uncertainty. 

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4. Evaluating Coupling Models for Cloud Datacenters and Power Grids

   https://doi.org/10.1145/3447555.3464868  

   Lin, Liuzixuan ; Zavala, Victor M. ; Chien, Andrew A. ( June 2021 , InThe TwelfthACM International Conference on Future Energy Systems (e-Energy ’21),)

   Ardakanian, Omid ; Niesse, Astrid (Ed.)

   The rapid growth of datacenter (DC) loads can be leveraged to help meet renewable portfolio standard (RPS, renewable fraction)targets in power grids. The ability to manipulate DC loads over time(shifting) provides a mechanism to deal with temporal mismatch between non-dispatchable renewable generation (e.g. wind and solar) and overall grid loads, and this flexibility ultimately facilitates the absorption of renewables and grid decarbonization. To this end, we study DC-grid coupling models, exploring their impact on grid dispatch, renewable absorption, power prices, and carbon emissions.With a detailed model of grid dispatch, generation, topology, and loads, we consider three coupling approaches: fixed, datacenter-local optimization (online dynamic programming), and grid-wide optimization (optimal power flow). Results show that understanding the effects of dynamic DC load management requires studies that model the dynamics of both load and power grid. Dynamic DC-grid coupling can produce large improvements: (1) reduce grid dispatch cost (-3%), (2) increase grid renewable fraction (+1.58%), and (3) reduce DC power cost (-16.9%).It also has negative effects: (1) increase cost for both DCs and non-DC customers, (2) differentially increase prices for non-DC customers, and (3) create large power-level changes that may harm DC productivity. 

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5. Optimal sizing of renewable microgrid for flow shop systems under island operations

   Jin, T. ; Subramanyam, V. ; Castillo-Villar, K. ; Sun, F. ( July 2020 , Procedia manufacturing)

   null (Ed.)

   This paper addresses a critical question pertaining to manufacturing sustainability: is it economically viable to implement an island microgrid to power a flow shop system under power demand and supply uncertainty? Though many studies on microgrid sizing are available, the majority assume the microgrid is interconnected with main grid. This paper aims to size wind turbine, photovoltaic and battery storage to energize a multi-stage flow shop system in island mode. A mixed-integer, non-linear programming model is formulated to optimize the renewable portfolio and capacity with the goal of minimizing the levelized cost of energy. The island microgrid is tested in three locations with diverse climate profiles. The results show that net zero energy flow shop production is economically feasible in the areas where the average wind speed exceed 8 m/s at 80-meter tower height, or the battery cost drops below $100,000/MWh. Sensitivity analyses are further carried out with respect to installation cost, demand response program, production scalability, and weather seasonality. 

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