Journal
IET RENEWABLE POWER GENERATION
Volume 13, Issue 14, Pages 2623-2633Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-rpg.2019.0036
Keywords
renewable energy sources; investment; optimisation; power distribution economics; power grids; power generation reliability; power generation economics; distributed power generation; wind turbines; investment year; project net present value; investment costs; operation costs; two-stage coordinated stochastic optimisation model; long-term DG investment; test MEMG system; conventional DG placement approaches; RES uncertainties; heterogeneous energies; optimal placement; heterogeneous distributed generators; grid-connected multienergy microgrid; wind turbines; diesel generators; power plants; proper placement; system energy efficiency; network reliability performance; two-stage coordinated method; heterogeneous DGs; MEMG project; renewable energy sources
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Funding
- Ministry of Education (MOE), Republic of Singapore, under grant AcRF TIER 1 [2017-T1-001-228 (RG92/17)]
- National Research Foundation (NRF) of Singapore [NRF-2018SR2001-018]
- Nanyang Assistant Professorship from Nanyang Technological University, Singapore
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The multi-energy microgrid (MEMG) comprises heterogeneous distributed generators (DGs) such as wind turbines, diesel generators, combined cooling, heat and power plants etc. Proper placement of these DGs is critical for the system energy efficiency and network reliability performance. This study proposes a two-stage coordinated method for optimally placing heterogeneous DGs in an MEMG project considering the uncertainties from renewable energy sources (RESs). Apart from optimising the traditional DG size and location, this method considers the optimal DG type and investment year simultaneously by maximising the project net present value (NPV), which consists of investment costs and operation costs. The whole problem is modelled as a two-stage coordinated stochastic optimisation model, where the long-term DG investment is determined at the first stage and operation decisions are determined at the second stage. The proposed method is verified on a test MEMG system. The simulation results show that its NPV is positive, which means the method is effective and should be implemented. Compared with the conventional DG placement approaches, the proposed method is more robust against the RES uncertainties and can better coordinate the heterogeneous energies with higher dispatch flexibility and economic profits.
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