Premium
Dynamic environmental‐economic load dispatch in grid‐connected microgrids with demand response programs considering the uncertainties of demand, renewable generation and market price
Author(s) -
Rezaee Jordehi Ahmad
Publication year - 2020
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.2798
Subject(s) - microgrid , demand response , renewable energy , grid , particle swarm optimization , computer science , dynamic demand , smart grid , upstream (networking) , distributed generation , schedule , mathematical optimization , economic dispatch , dynamic pricing , electric power system , power (physics) , electricity , economics , engineering , microeconomics , electrical engineering , physics , geometry , mathematics , quantum mechanics , computer network , machine learning , operating system
Microgrids (MGs) as a key building block of smart grids have been emerged to address the proliferation of distributed energy resources. In grid‐connected MGs, dynamic economic load dispatch (DELD) module determines optimal schedule of distributed energy resources and adjustable loads and power to be exchanged with upstream grid, while all operational constraints of the MG are respected. DELD in MGs represents a constrained optimization problem with uncertain input data, as the forecasts of demand, renewable generation and market price are uncertain. In this research, particle swarm optimization (PSO) as a bio‐inspired optimization algorithm is used to solve DELD in grid‐connected MGs, while demand response program is integrated into MG and the uncertainties of demand, renewable power generation and market price are dealt with two‐point estimate method (TPEM). Load curtailment as a demand response program is used for reducing operation cost of microgrids. The performance of PSO is compared with two optimization algorithms including grey wolf optimization and backtracking search algorithm. As per the results, at times with low grid power price, microgrid imports power from upstream grid and at times with high power price it exports power to the upstream grid. The results show that the integration of demand response has significantly reduced the operation cost of the microgrid. The effect of change in maximum curtailable power on the operation cost of the MG has been investigated.