Harvesting maximal PV energy with fine grained energy distribution: An alternative to traditional PV systems in buildings

Khalid, Qasim; Ikram, Muhammad Jahangir; Arshad, Naveed

doi:10.1016/j.enbuild.2017.04.033

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…The data used in this study are taken under profile form for wind farm 1 and 2 and PV 1 and 2, for one day or 24 hours. The profile was generated based data used for wind farm and PV in the literature [33][34][35][36][37]. Wind farm, PV, BESS and SG powers can be write as following:…”

Section: Wind Farm and Pv Arraymentioning

confidence: 99%

Predictive Active Power Control of Two Interconnected Microgrids

Tungadio

Bansal

Siti

et al. 2018

Technol Econ Smart Grids Sustain Energy

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When dealing with interconnected power systems, any sudden load changes leads to the deviation of active power and frequency in the tie-line. The daily management of the power system is also conditioned by the control of the active power and the frequency. It is a very important task in the conduct of the any electrical network to supply sufficiently and with high reliability the active power to be transmitted to the customers. Maintaining the frequency of each area and tie-line active power flow variation within prescribed value by adjusting the generator active outputs remain one of the main tasks of the network operators. This paper presents a model predictive regulator in controlling the power flow in tie-lines and frequency deviations in the microgrid, which will lead to power balance between the total active power generated and active power demand of the system. The system being studied consists of two microgrids, each made up of a wind farm, conventional thermal and hydro plants generator, photovoltaic (PV) system, storage system and active power demand. Predictive control algorithm is applied to control the power flow between two microgrids.

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