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1. Comparative Analysis of Efficiencies for Renewable Energy Capacities across ISO Regions

   Ogunrinde, O. and ( January 2020 , IISE transactions)

   L. Cromarty, R. Shirwaiker (Ed.)

   This study investigates the renewable energy adoption across regions covered by Independent System Operators (ISOs) in the U.S. The study employed a deterministic model in the form of Data Envelopment Analysis (DEA) to determine the performance of ten ISO regions over a five-year period from 2013 to 2017. Inputs into the model include the Renewable Portfolio Standard (RPS) targets, fossil fuel capacity additions and the costs of capacity additions. Outputs from the model include renewable energy capacity additions and CO2 emissions per MWh of generated electricity. The results show the regions covered by CAISO, ERCOT, NE-ISO, SPP and the NON-ISO to be on the efficient frontier. For the regions not on the efficient frontier, the results identify their limitations and provide projections both for reductions in excess inputs and improvements in outputs to be on the efficient frontier. For example, we see that the regions covered by NY-ISO and PJM would require, on average, renewable energy capacity expansions of 593.65MW and 230.24MW, respectively, to be on the efficient frontier. These regions would require their average fossil capacity expansions to be limited to 234.83MW and 365.4MW respectively. These findings offer some guidance on approaches to improving the performance of these markets.
2. Air pollution disparities and equality assessments of US national decarbonization strategies

   https://doi.org/10.1038/s41467-022-35098-4  

   Goforth, Teagan ; Nock, Destenie ( December 2022 , Nature Communications)

   Energy transitions and decarbonization require rapid changes to a nation’s electricity generation mix. There are many feasible decarbonization pathways for the electricity sector, yet there is vast uncertainty about how these pathways will advance or derail the nation’s energy equality goals. We present a framework for investigating how decarbonization pathways, driven by a least-cost paradigm, will impact air pollution inequality across vulnerable groups (e.g., low-income, minorities) in the US. We find that if no decarbonization policies are implemented, Black and high-poverty communities may be burdened with 0.19–0.22 μg/m³higher PM_2.5concentrations than the national average during the energy transition. National mandates requiring more than 80% deployment of renewable or low-carbon technologies achieve equality of air pollution concentrations across all demographic groups. Thus, if least-cost optimization capacity expansion models remain the dominant decision-making paradigm, strict low-carbon or renewable energy technology mandates will have the greatest likelihood of achieving national distributional energy equality. Decarbonization is essential to achieving climate goals, but myopic decarbonization policies that ignore co-pollutants may leave Black and high-poverty communities up to 26–34% higher PM_2.5exposure than national averages over the energy transition.
3. Valuing the Capacity Contribution of Renewable Energy Systems with Storage.

   Baker, T ; Shittu, E. ; Greenwood, S. ( January 2020 , IISE transactions)

   L. Cromarty, R. Shirwaiker (Ed.)

   The growth of renewable energy technologies creates significant challenges for the stability of the system because of their intermittency. Nonetheless, we can value these technologies with storage systems. We model the supply by a renewable technology, wind, into a storage facility using the leaky bucket mechanism. The bucket is synonymous with storage while the leakage is equivalent to meeting load. Modelica is used to capture: (i) the time-dependence of the state of the bucket based on a physical model of storage; (ii) the stochastic representation of wind energy using wind speed data that is fed into a physical model of a wind technology; and (iii) the load, modeled as a resistor-inductor circuit. The strength of Modelica in using non-causal equations for basic sub-systems that are linked together is harnessed through its libraries. We find that there is a diminishing return to storage. Beyond a certain level of storage, the integration of a reliable baseload power supply is required to diminish the risk due to reduced reliability. The need for storage systems as a hedge against intermittency is dependent on the interplay between the supply volatilities and the stochastic load to guarantee an acceptable level of quality of service and reliability.
4. 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 favorablemore »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.« less
5. Combining Renewable Solar and Open Air Cooling for Greening Internet-Scale Distributed Networks

   https://doi.org/10.1145/3307772.3328307  

   Gupta, Vani ; Shenoy, Prashant ; Sitaraman, Ramesh K. ( June 2019 , Proceedings of the Tenth ACM International Conference on Future Energy Systems (e-Energy'19))

   The widespread adoption and popularity of Internet-scale Distributed Networks (IDNs) has led to an explosive growth in the infrastructure of these networks. Unfortunately, this growth has also led to a rapid increase in energy consumption with its accompanying environmental impact. Therefore, energy efficiency is a key consideration in operating and designing these power-hungry networks. In this paper, we study the greening potential of combining two contrasting sources of renewable energy, namely solar energy and Open Air Cooling (OAC). OAC involves the use of outside air to cool data centers if the weather outside is cold and dry enough. Therefore OAC is likely to be abundant in colder weather and at night-time. In contrast, solar energy is correlated with sunny weather and day-time. Given their contrasting natures, we study whether synthesizing these two renewable sources of energy can yield complementary benefits. Given the intermittent nature of renewable energy, we use batteries and load shifting to facilitate the use of green energy and study trade-offs in brown energy reduction based on key parameters like battery size, number of solar panels, and radius of load movement. We do a detailed cost analysis, including amortized cost savings as well as a break-even analysis formore »different energy prices. Our results look encouraging and we find that we can significantly reduce brown energy consumption by about 55% to 59% just by combining the two technologies. We can increase our savings further to between 60% to 65% by adding load movement within a radius of 5000kms, and to between 73% to 89% by adding batteries.« less