Microgrid's Generation Expansion Planning Considering Lower Carbon Economy

Yang, Xiaohong; Tian, Wei

doi:10.1109/appeec.2012.6306895

Cited by 4 publications

(4 citation statements)

References 11 publications

(9 reference statements)

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“…In this study, sensitivity analysis and the PSO algorithm were used to carry out cost-benefit analysis and to ensure reliability criteria at different load points. The authors in [30] evaluated the generation planning in an MG, taking into account the emission constraints. In this reference, the genetic algorithm was used to determine the optimal allocations of wind and solar resources.…”

Section: T Dmentioning

confidence: 99%

“…( 28) to ( 29) and ( 30) to ( 31) are used to model the production constraints of PV panels and wind turbines respectively. Relations (28) and (30) show that the PV and wind power generation capacities in each scenario are used for internal consumption of the MG (for charging the storage device or EV) or for selling to the upstream grid. Eqs.…”

Section: = Tnpv Tpvmentioning

confidence: 99%

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Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model

Farrokhifar

Aghdam

Alahyari

et al. 2020

Electric Power Systems Research

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Energy supply through integrated renewable energy sources (RESs) and battery systems will be of higher importance for future residential sectors. Optimal energy management and sizing for the components of residential systems can enhance efficiency, self-suffiency, and meanwhile can be cost-effective by reducing investment as well as operating costs. Accordingly, this paper proposes an exhaustive optimization model for determining the capacity of RESs, namely: wind turbines and photovoltaic (PV) systems. In this study, batteries and electric vehicles (EVs) are utilized in line with other sources to capture fluctuations of RESs. To model the uncertainties of RESs, energy prices, and load demands a linearized stochastic programming framework is applied. The proposed framework involves long-term and efficient resource development alongside with short-term management and utilization of these resources for supplying the demand load. In our study, we utilize the roulette wheel mechanism (RWM) method as well as proper probability distribution functions (PDFs) to generate scenarios for all sources of uncertainties, including wind turbines, PV systems, demand, and electricity market price. The approach is verified in two different cases, including an individual home and a larger micro-grid (MG). The results of multiple numerical simulations demonstrate the effectiveness of the proposed stochastic model.

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Section: T Dmentioning

confidence: 99%

Section: = Tnpv Tpvmentioning

confidence: 99%

Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model

Farrokhifar

Aghdam

Alahyari

et al. 2020

Electric Power Systems Research

View full text Add to dashboard Cite

show abstract

“…Constraint ( 29) is to ensure that the energy saved in the units is within the upper and lower limits. Constraints (30) and (31) guarantee that only the storage units chosen to be installed make contribution to the system operation. Besides the aforementioned constraints, the problem is faced with some technical restrictions given below:…”

Section: Original Modelmentioning

confidence: 99%

“…To consider uncertainties, a genetic algorithm has been used in this study. In [29] and [30], the focus is on planning MGs with environmental objectives considering incentives and penalties for greenhouse gas emissions.…”

Section: Introductionmentioning

confidence: 99%

Enabling Demand Response Potentials for Resilient Microgrid Design

Chegenizadeh

Safdarian

2019

Scientia Iranica

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The future microgrids (MGs) hosting a multitude of uncertain and intermittent local renewable generation resources are anticipated needing fast and exible units on the generation side. However, demand response, as a load shaping tool, can alleviate this need. This paper proposes a model to consider demand response potential incorporated by timevarying prices in MG design studies. The model aims at maximizing pro t of the MG owner while technical limits and constraints are adhered to. It also ensures that the designed MG is resilient to islanding events. To handle complexity of the model, Benders decomposition was used to decompose it into a master problem and two types of sub-problems. The master problem optimized binary variables indicating installing status of generating units and batteries. The rst type of sub-problems optimized continuous variables and the second ensured the resilient operation of the MG against islanding events. In the model, the uncertainties associated with load and intermittent generation resources were captured via a scenario-based stochastic approach. Demand behavior in response to time-varying prices was modeled via price elasticity coe cients. Also, e ectiveness of the proposed model was investigated through extensive numerical studies and sensitivity analyses.

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Stochastic Capital Budgeting of Microgrid Projects Under Electricity Market Uncertainty

Khodaei,

Arabnya

2023

2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

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Microgrid's Generation Expansion Planning Considering Lower Carbon Economy

Cited by 4 publications

References 11 publications

Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model

Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model

Enabling Demand Response Potentials for Resilient Microgrid Design

Stochastic Capital Budgeting of Microgrid Projects Under Electricity Market Uncertainty

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