Optimal multiple distribution generation and protective devices placement in microgrid system | |
| Author | Witoon Prommee |
| Call Number | AIT Diss. no.ET-12-02 |
| Subject(s) | Distributed generation of electric power Optimal control Microgrids (Smart power grids) |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Energy |
| Publisher | Asian Institute of Technology |
| Abstract | Microgrid (MG), a system of multiple distributed generations (DG) to serve loads, can reduce the system loss and improve system reliability. In MG planning, an improved reinitialized social structures particle swarm optimization (IRS - PSO) is proposed to minimize the total real power loss for optimal multiple DG placement , and an improved binary multi - objectives particle swarm optimization with new sigmoid function (IB - MOPSO with BSF ) method is proposed to minimize reliability indices, and total cost for optimal protective device s placement in a MG system . IRS - PSO is used for solving optimal multiple DG s placement in a MG system. The movement of each particle in IRS - PSO is pulled by an inertia term, a cognitive term (personal best) and three social learning terms including global best, local best and near neighbor best. The objective is to minimize the total real power loss within real and reactive power generation limits and voltage limits. Five DG types in a MG system are considered including MG with DG supplying real power only, MG with DG supplying reactive power only, MG with DG supplying real power and consuming reactive power, MG with DG supplying real power and reactive power, and MG with four different types of DG regulating the bus voltage. For a given number of DG units in each type, IRS - PSO can find better sizes and locations of multiple DGs than repetitive load flow, basic particle swarm optimization (BPSO), adaptive weight particle swarm optimization (APSO), and global best, local and near neighbor best particle swarm optimization (GLN - PSO) on th e 69 - bus radial MG distribution system. For MG reliability improvement , IB - MOPSO is applied for solving optimal placement of multi - protective devices in the improved MG reliability model. The multiple objectives are to minimize system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and total cost (TC) including investment and interruption cost. Binary multi - objectives PSO (B - MOPSO) is improved by adding a bell s hape function (BSF) and three particle movement strategies (MS ) including global guidance located in the least crowded areas, perturbation with different evolution method, and coverage of untouched search space in the non - dominated front. In the improved MG reliability model, IB - MOSO with BSF can find better locations and number of protective devices including reclosers, switches , and fuse s than B - MOPSO, IB - MOPSO with conventional sigmoid function ( CSF ), and B - MOPSO with BSF on the 51 sections Provincial Electricity Authority (PEA) MG test system . In summary, the proposed IRS - PSO, using re - initialization process to avoid premature convergence, can find the best location and size of three DG units in MG with DG supplying real and reactive power on the 69 bus MG test system . For multi - objectives optimal multiple protective devices placement, IB - MOPSO with BSF , using the improved reliability models, three movement strategies of particle, and BSF, can find a better compromised solution than Binary PSO on the 51 sections PEA MG test system. This will lead to substantial operation and investment cost savings, higher efficiency of distribution system, and higher reliability level |
| Year | 2012 |
| Type | Dissertation |
| School | School of Environment, Resources, and Development (SERD) |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Energy Technology (ET) |
| Chairperson(s) | Weerakorn Ongsakul |
| Examination Committee(s) | Marpaung, Charles O. P. ;Voratas Kachitvichyanukul |
| Scholarship Donor(s) | HM Queen Sirikit Scholarship ;Asian Institute of Technology Fellowship |
| Degree | Thesis (Ph. D.) - Asian Institute of Technology, 2012 |