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Optimal power management of dependent microgrid considering distribution market and unused power capacity

Abstract This study presents an optimal power management for a microgrid (MG) in distribution market environment. The MG operator is able to have interactions with the distribution market operator (DMO) and adjacent MG (AMG) operator to supply its local loads. The DMO regulates the electricity market, and assigns the electricity price and power profile for the MG. The motivation behind the use of The DMO is that it works as an entity between MG and independent system operator (ISO) in order to guarantee a flexible operation by reducing power fluctuation and reduce the unintentional peak loads in low market price hours. The unused power capacity in AMG is used during the islanded hours through an additional interconnection point connected to the MG. Using this method reduces the need for installing new generation resources, which will be a practical and economical solution for MG developer. This MG which is able to provide power from distribution market and the AMG with two interconnection points is named dependent MG (DMG). A market-based stochastic model containing distribution market constraints and AC power flow formulations employs conditional value at risk (CVaR) methodology to capture the loads and wind uncertainties. The effectiveness of the presented model is evaluated on a 20 kV test system using different case studies. In this test system, the operator is the owner of all generation units. The numerical analysis explicate that presented model reduces the operation cost of DMG with the aim of responsive loads, unused power capacity, energy storage system (ESS) and power generation units. The market-based scheduling also provides operational flexibility for distribution system by adjusting flexibility limit of market constraints. It is also shown that changing risk preferences level changes the power generation pattern in ESS and causes a costly operation of resources in risk-averse strategy. The competence of this model is significant when the preventive maintenance (PM) program is carried out, and the DMG should rely on its flexible resources and AMG’s available power capacity, which could reduce the load shedding.
- University of Tehran Iran (Islamic Republic of)
- Babol Noshirvani University of Technology Iran (Islamic Republic of)
- University of Vassa Finland
- University of Tehran Iran (Islamic Republic of)
- University of Porto Portugal
electricity consumption, ta222, capacity, costs, fi=Sähkötekniikka|en=Electrical Engineering|, production of electricity, electrical power networks, energy production (process industry), renewable energy sources, prices, distribution of electricity, industrial management
electricity consumption, ta222, capacity, costs, fi=Sähkötekniikka|en=Electrical Engineering|, production of electricity, electrical power networks, energy production (process industry), renewable energy sources, prices, distribution of electricity, industrial management
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).20 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
