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1. 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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2. Stochastic Multi-objective Low-Carbon Generation Dispatch Considering Carbon Capture Plants

   https://doi.org/10.1109/IAS44978.2020.9334846  

   Akbari-Dibavar, Alireza; Mohammadi-Ivatloo, Behnam; Zare, Kazem; Khalili, Tohid; Bidram, Ali (October 2020, IEEE Industry Applications Society Annual Meeting)

   null (Ed.)

   This paper presents a multi-objective (MO) optimization for economic/emission dispatch (EED) problem incorporating hydrothermal plants, wind power generation, energy storage systems (ESSs) and responsive loads. The uncertain behavior of wind turbines and electric loads is modeled by scenarios. Stochastic programming is proposed to achieve the expected cost and emission production. Moreover, the carbon capture systems are considered to lower the level of carbon emission produced by conventional thermal units. The proposed optimization problem is tested on the IEEE 24-bus case study using DC power flow calculation. The optimal Pareto frontier is obtained, and a fuzzy decision-making tool determined the best solution among obtained Pareto points. The problem is modeled as mixed-integer non-linear programming in the General Algebraic Modelling System (GAMS) and solved using DICOPT solver. 

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3. Investigating the impact of wind speed variability on optimal sizing of hybrid wind-hydrogen microgrids for reliable power supply

   https://doi.org/10.1016/j.ijhydene.2025.01.444  

   Eniola, Victor; Cimorelli, Jack; Niezrecki, Christopher; Willis, David; Jin, Xinfang (March 2025, International Journal of Hydrogen Energy)

   Addressing resource intermittency is crucial for designing effective and economical renewable energy systems for many applications. Hydrogen as long-term energy storage medium shows promise for increasing renewables penetration into the grid. Cost-effective hybrid wind-hydrogen microgrids (HWHMs) require system-level sizing of each subcomponent. This study employs low-order HWHM component models in a system-level framework to predict HWHM performance. It introduces a novel approach to investigate the optimal sizing of HWHMs. The study uniquely addresses the impact of wind speed fluctuation amplitudes and frequency variations on system design – an area not previously explored. The model is run for 7 days using several different wind speed profiles and real load demand data from an off-grid Naval facility on an island in California. In our test cases, the findings indicate that fewer wind turbines and more hydrogen tanks are required to successfully meet demand when wind speed fluctuations increase. For example, when the wind speed fluctuation increases from 0.68 to 2.04 m/s, and the wind turbine is expected to maintain an average power equivalent to 90% of the peak load, the turbine capacity drops by 17%, requiring a 304% rise in the number of tanks. However, the frequency of wind speed variation has a negligible effect on the optimal HWHM configuration. Through a rule-based optimization algorithm, this research offers important insights for designing reliable microgrids capable of meeting critical loads despite highly variable wind conditions. 

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4. The quest for carbon-neutral industrial operations: renewable power purchase versus distributed generation

   https://doi.org/10.1080/00207543.2017.1394593  

   Jin, T.; Shi, K.; Park, T. (January 2018, International journal of production research)

   Integrating renewable energy into the manufacturing facility is the ultimate key to realising carbon-neutral operations. Although many firms have taken various initiatives to reduce the carbon footprint of their facilities, there are few quantitative studies focused on cost analysis and supply reliability of integrating intermittent wind and solar power. This paper aims to fill this gap by addressing the following question: shall we adopt power purchase agreement (PPA) or onsite renewable generation to realise the eco-economic benefits? We tackle this complex decision-making problem by considering two regulatory options: government carbon incentives and utility pricing policy. A stochastic programming model is formulated to search for the optimal mix of onsite and offsite renewable power supply. The model is tested extensively in different regions under various climatic conditions. Three findings are obtained. First, in a long term onsite generation and PPA can avoid the price volatility in the spot or wholesale electricity market. Second, at locations where the wind speed is below 6 m/s, PPA at $70/MWh is preferred over onsite wind generation. Third, compared to PPA and wind generation, solar generation is not economically competitive unless the capacity cost is down below USD1.5 M per MW. 

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5. Joint sizing and placement of battery energy storage systems and wind turbines considering reactive power support of the system

   Khaki, Bahman (January 2021, Journal of energy storage)

   Uwe Sauer, Dirk (Ed.)

   A B S T R A C T The probabilistic and intermittent output power of Wind Turbines (WT) is one major inconsistency of these Renewable Energy Sources (RES). Battery Energy Storage Systems (BESS) are a suitable solution to mitigate this intermittency by smoothening WT’s output power. Although the main benefit of BESSs mentions as peak shaving and load-shifting, but in this research, it will verify that optimal placement and sizing them jointly with WTs can lead to more benefits like compensating the required system’s reactive power support from WTs. The reactive power size of WTs and BESSs will be derived from the result of the joint sizing and placement in this study, as well as their active power output to meet the load demand. This can facilitate WTs and BESSs contribution to cover the system’s required reactive power and their participation in the reactive power market and ancillary services. This paper also proposes new cost functions for both WTs and BESSs and minimizes their cost while ensuring minimal total loss (active and reactive) in the power distribution system. This can benefit both WTs’ and BESSs’ owners as well as system operators. Suitable placement and sizing of the WTs and BESSs can also improve the load bus voltage profiles, which can benefit the end-users, and will verify using the proposed optimization by different case studies on the 33 bus distribution system. The results of case studies ascertain the consistency of the proposed formulation for placement and sizing BESSs and WTs jointly, as well as other benefits to the power system, the power plant owners, and system operators. 

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