Multi-objective optimization and design of photovoltaic-wind hybrid system for community smart DC microgrid

Mohammad B. Shadmand, Robert Balog

Research output: Contribution to journalArticle

110 Citations (Scopus)

Abstract

Renewable energy sources continues to gain popularity. However, two major limitations exist that prevent widespread adoption: availability of the electricity generated and the cost of the equipment. Distributed generation, (DG) grid-tied photovoltaic-wind hybrid systems with centralized battery back-up, can help mitigate the variability of the renewable energy resource. The downside, however, is the cost of the equipment needed to create such a system. Thus, optimization of generation and storage in light of capital cost and variability mitigation is imperative to the financial feasibility of DC microgrid systems. PV and wind generation are both time dependent and variable but are highly correlated, which make them ideal for a dual-sourced hybrid system. This paper presents an optimization technique base on a Multi-Objective Genetic Algorithm (MOGA) which uses high temporal resolution insolation data taken at 10 seconds data rate instead of more commonly used hourly data rate. The proposed methodology employs a techno-economic approach to determine the system design optimized by considering multiple criteria including size, cost, and availability. The result is the baseline system cost necessary to meet the load requirements and which can also be used to monetize ancillary services that the smart DC microgrid can provide to the utility at the point of common coupling (PCC) such as voltage regulation. The hybrid smart DC microgrid community system optimized using high-temporal resolution data is compared to a system optimized using lower-rate temporal data to examine the effect of the temporal sampling of the renewable energy resource.

Original languageEnglish
Article number6880408
Pages (from-to)2635-2643
Number of pages9
JournalIEEE Transactions on Smart Grid
Volume5
Issue number5
DOIs
Publication statusPublished - 1 Sep 2014

Fingerprint

Multiobjective optimization
Hybrid systems
Renewable energy resources
Costs
Availability
Incident solar radiation
Distributed power generation
Voltage control
Electricity
Genetic algorithms
Systems analysis
Sampling
Economics

Keywords

  • Genetic algorithm
  • microgrid
  • optimization
  • photovoltaic
  • PV-storage system
  • smart grid
  • wind turbine

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Multi-objective optimization and design of photovoltaic-wind hybrid system for community smart DC microgrid. / Shadmand, Mohammad B.; Balog, Robert.

In: IEEE Transactions on Smart Grid, Vol. 5, No. 5, 6880408, 01.09.2014, p. 2635-2643.

Research output: Contribution to journalArticle

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