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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)

   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 panelsmore »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.« less
2. 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, hoursmore »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.« less
3. 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 derivedmore »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.« less
4. Design of a Laboratory Scale Solar Microgrid Cyber-Physical System for Education

   https://doi.org/10.3390/electronics10131562  

   Guo, Liping ; Kors, Jason ( July 2021 , Electronics)

   Renewable energy sources such as solar and wind provide an effective solution for reducing dependency on conventional power generation and increasing the reliability and quality of power systems. Presented in this paper are design and implementation of a laboratory scale solar microgrid cyber-physical system (CPS) with wireless data monitoring as a teaching tool in the engineering technology curriculum. In the system, the solar panel, battery, charge controller, and loads form the physical layer, while the sensors, communication networks, supervisory control and data acquisition systems (SCADA) and control systems form the cyber layer. The physical layer was seamlessly integrated with themore »cyber layer consisting of control and communication. The objective was to create a robust CPS platform and to use the system to promote interest in and knowledge of renewable energy among university students. Experimental results showed that the maximum power point tracking (MPPT) charge controller provided the loads with power from the solar panel and used additional power to charge the rechargeable battery. Through the system, students learned and mastered key concepts and knowledge of multi-disciplinary areas including data sampling and acquisition, analog to digital conversion, solar power, battery charging, control, embedded systems and software programing. It is a valuable teaching resource for students to study renewable energy in CPS.« less
5. 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)

   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 bestmore »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.« less