Abstract
A microgrid (MG) is a small-scale version of the power system which makes possible the integration of renewable resources as well as achieving maximum demand side management (DSM) utilization. The future power system will be faced with severe uncertainties owing to penetration of renewable resources. Consequently, the uncertainty assessment of system performance is essential. The conventional energy scheduling in an MG may not be suitable for active distribution networks. Hence, this study focuses on the probabilistic analysis of optimal power dispatch considering economic aspects in a multi-carrier networked microgrid. The aim is to study the impact of uncertain behavior of loads, renewable resources, and electricity market on the optimal management of a multi-carrier networked microgrid. Furthermore, a novel time-based demand side management is proposed in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. The optimization model is formulated as a mixed integer nonlinear program (MINLP) and is solved using MATLAB and GAMS software. Results show that the energy sharing capability between MCMGs and MCMGs and the main grids as well as utilization of demand side management can decrease operating costs for smart distribution grids.
Highlights
The global demand for energy has been increasing in recent years, and a rapid escalation in fossil fuel prices has been seen
Probabilistic energy scheduling problem as an mixed integer nonlinear program (MINLP) model is solved for each of the generated scenarios in a 24-h interval, using GAMS (24.1.2) software. Input data such as load and energy price of each multi-carrier microgrid (MCMG) as well as generated power by renewable units are described in the form of probability distribution function (PDF), and the results are shown in PDF or cumulative distribution function (CDF) forms in a specific interval
Since the energy prices in the input of MCMGs are specified by energy markets, the final energy prices (FEPs) of electrical and thermal controllable loads in the system output are determined based on input energy, equipment efficiency, and operation
Summary
The global demand for energy has been increasing in recent years, and a rapid escalation in fossil fuel prices has been seen. This paper solves the optimal power dispatch problem considering uncertainties in loads for electrical and thermal types, electricity price, and the probabilistic modeling of generated power by renewable sources. Probabilistic energy scheduling problem as an MINLP model is solved for each of the generated scenarios in a 24-h interval, using GAMS (24.1.2) software Input data such as load and energy price of each multi-carrier microgrid (MCMG) as well as generated power by renewable units are described in the form of PDF, and the results are shown in PDF or cumulative distribution function (CDF) forms in a specific interval. Proposing a novel time-based demand side management model which correlates the final energy price of responsive loads for multiple carriers with energy market price, energy purchase, and on-site generations.
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