BibTex RIS Kaynak Göster
Yıl 2015, Cilt: 36 Sayı: 3, 1855 - 1864, 13.05.2015

Öz

Kaynakça

  • Molderink A, Bakker V, Bosman M.G.C, Hurink J.L, Smit G.J.M. A three-step methodology to improve domestic energy efficiency. Innovative Smart Grid Technologies (ISGT) 2010; p:1-8
  • Tsikalakis A. G, Dimeas A, Hatziargyriou N. D, Lopes J, Kariniotakis G. Management of microgrids in market environment. International Journal of Distributed Energy Resources 2006; 2(3):177–193.
  • Lasseter R. H. Microgrids. IEEE Power Engineering Society Winter Meeting 2002; 1: 305 –308.
  • Asanol H, Bandol S. Economic Analysis of Microgrids. Power Conversion Conf 2007; pp:654-658
  • Hernandez-Aramburo C.A, Green T.C, Mugniot N. Fuel consumption minimization of a microgrid. IEEE Trans. Ind. Application 2005; 41(3): 673-681.
  • Tsikalakis A.G, Hatziargyriou N.D. Centralized control for optimizing microgrids operation. IEEE Trans Energy Conversion 2008; 23(1): 241–248.
  • Dinghuan Zhu, Rui Yang, Hug G. Managing Microgrids with Intermittent Resources: A Two- Layer Multi-Step Optimal Control Approach. North American Power Symposium (NAPS) 2010; pp:1-8.
  • Passino K. M. Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Systems Magazine 2002 ; 22(3):52–67.
  • Farhat I.A, El-Hawary M.E. Dynamic adaptive bacterial foraging algorithm for optimum economic dispatch with valve-point effects and wind power. IET Transmission & Distribution Generation 2010;4(9):989-999.
  • Marnay C, Venkataramanan G, Stadler G, Siddiqui A, Firestone R, Chandran R. Optimal Technology Selection and Operation of Microgrids in Commercial Buildings. IEEE Trans Power Syst 2008; 23(3):975-982
  • Chakraborty S, Weiss M.D, Simoes M.G. Distributed intelligent energy management system for a single-phase high frequencyAC microgrid. IEEE Trans. Ind. Electron 2007; 54(1):97–109.
  • Dukpa A, Dugga I, Venkatesh B, Chang L. Optimal participation and risk mitigation of wind generators in an electricity market. IET Renew. Power Gener 2010; 4(2):165–175.
  • Chen C. Duan S.. CAI T Liu B. Hu G. Smart energy management system for optimal microgrid economic operation. IET Renew. Power Gener 2011; 5(3):258–267.
  • G.P. Granelli, M. Montagna, G.L. Pasini, P. Marannino, Emission constrained dynamic dispatch, Electric Power Syst 1992; 24: 56-64.
  • C.S. Chang, K.P. Wong, B. Fan, Security-constrained multiobjective generation dispatch using bicriterion global optimization, IEE Proc. Gener. Transm. Distrib1995; 142 (4):406- 414.
  • Sun J, Fang W, Wang D, Xua W. Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method. Energy Conversion Management 2009; 50(12):2967-2975
  • Bhuvaneswari R, Edrington C. S, Cartes D.A. Online Economic Environmental Optimization of a Microgrid Using an Improved Evolutionary Programming Technique. North American Power Symposium 2009; pp: 1 – 6.
  • Conti S, Rizzo S.A. Optimal Control to Minimize Operating Costs and Emissions of MV Autonomous Micro-Grids with Renewable Energy Sources. International Conference on Clean Electrical Power 2009; p: 634 – 639.
  • Lin WM, Cheng FS, Tsay MT. Nonconvex economic dispatch by integrated artificial intelligence. IEEE Trans Power Syst 2001; 16(2):307-311.
  • Wang L, Singh Ch. Environmental/economic power dispatch using fuzzified multi- objective particle swarm optimization algorithm. Electr Power Syst Res 2007; 77:1654- 1664.
  • Huanga H.Z, Gub Y.K, Duc X. An interactive fuzzy multi-objective optimization method for engineering design. Engineering Applications of Artifcial Intelligence 2006; pp: 451– 460.
  • Abido M.A. Environmental/Economic Power Dispatch using Multiobjective Evolutionary Algorithms. IEEE Transaction on Power System, 2003; 18(4): 1529-1537.
  • Sakawa M., Yano H. An interactive fuzzy satisfying method using augmented minimax problems and its application to environmental systems. IEEE Trans. SMC 1985; 17(6): 720–729.
  • Anvari-Moghaddam A, Seifi A, Niknam T, M. Multi-objective operation management of a renewable MG with back-up micro-turbine/fuel cell/battery hybrid power source. Energy 2011;36(11):6490-6507.
  • Soroudi A, Aien M, Ehsan M. A probabilistic modeling of photo voltaic modules and wind power generation impact on distribution networks. IEEE Syst J 2011;99:1e10.
  • Harr E. Probabilistic estimates for multivariate analysis. Appl Math Model 1989;13(5):313e8.
  • Hong HP. An efficient point estimate method for probabilistic analysis. Reliab Eng Syst Saf 1998;59:261e7.
  • Schellenberg A, Rosehart W, Aguado J. Cumulant-based probabilistic optimal power flow (P-OPF) with Gaussian and gamma distributions. IEEE Trans Power Syst 2005;20(2):773e81
  • Morales JM, Perez-Ruiz J. Point estimate schemes to solve the probabilistic power flow. IEEE Trans Power Syst 2007;22:1594e601.

Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria

Yıl 2015, Cilt: 36 Sayı: 3, 1855 - 1864, 13.05.2015

Öz

 

Abstract. Recently, the use of renewable energy such as wind and solar energy has rapidly increased in micro-grids. Due to the fluctuation of wind speed and solar radiation, the scheduling of  wind turbines (WTs) and photovoltaic (PV) plants are difficult in micro-grids. In this paper, a probabilistic energy management system (PEMS) is used to optimize the operation of a grid-connected micro-grid via Economic and Environmental Criteria. For optimal operation of WTs and PVs with other DERs, the fluctuations of WT and PV power generation has been considered and a multiobjective probabilistic economic/environmental load dispatch is presented. For optimal operation of the micro-grid, a complete mathematical  model for energy storage system (ESS) is introduced. Finally, an efficient improved bacterial foraging-based fuzzy satisfactory optimization algorithm is proposed to solve the multi-objective problem. The results show that the PEMS can optimize total operation cost and net emissions of the micro-grid, simultaneously.

Kaynakça

  • Molderink A, Bakker V, Bosman M.G.C, Hurink J.L, Smit G.J.M. A three-step methodology to improve domestic energy efficiency. Innovative Smart Grid Technologies (ISGT) 2010; p:1-8
  • Tsikalakis A. G, Dimeas A, Hatziargyriou N. D, Lopes J, Kariniotakis G. Management of microgrids in market environment. International Journal of Distributed Energy Resources 2006; 2(3):177–193.
  • Lasseter R. H. Microgrids. IEEE Power Engineering Society Winter Meeting 2002; 1: 305 –308.
  • Asanol H, Bandol S. Economic Analysis of Microgrids. Power Conversion Conf 2007; pp:654-658
  • Hernandez-Aramburo C.A, Green T.C, Mugniot N. Fuel consumption minimization of a microgrid. IEEE Trans. Ind. Application 2005; 41(3): 673-681.
  • Tsikalakis A.G, Hatziargyriou N.D. Centralized control for optimizing microgrids operation. IEEE Trans Energy Conversion 2008; 23(1): 241–248.
  • Dinghuan Zhu, Rui Yang, Hug G. Managing Microgrids with Intermittent Resources: A Two- Layer Multi-Step Optimal Control Approach. North American Power Symposium (NAPS) 2010; pp:1-8.
  • Passino K. M. Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Systems Magazine 2002 ; 22(3):52–67.
  • Farhat I.A, El-Hawary M.E. Dynamic adaptive bacterial foraging algorithm for optimum economic dispatch with valve-point effects and wind power. IET Transmission & Distribution Generation 2010;4(9):989-999.
  • Marnay C, Venkataramanan G, Stadler G, Siddiqui A, Firestone R, Chandran R. Optimal Technology Selection and Operation of Microgrids in Commercial Buildings. IEEE Trans Power Syst 2008; 23(3):975-982
  • Chakraborty S, Weiss M.D, Simoes M.G. Distributed intelligent energy management system for a single-phase high frequencyAC microgrid. IEEE Trans. Ind. Electron 2007; 54(1):97–109.
  • Dukpa A, Dugga I, Venkatesh B, Chang L. Optimal participation and risk mitigation of wind generators in an electricity market. IET Renew. Power Gener 2010; 4(2):165–175.
  • Chen C. Duan S.. CAI T Liu B. Hu G. Smart energy management system for optimal microgrid economic operation. IET Renew. Power Gener 2011; 5(3):258–267.
  • G.P. Granelli, M. Montagna, G.L. Pasini, P. Marannino, Emission constrained dynamic dispatch, Electric Power Syst 1992; 24: 56-64.
  • C.S. Chang, K.P. Wong, B. Fan, Security-constrained multiobjective generation dispatch using bicriterion global optimization, IEE Proc. Gener. Transm. Distrib1995; 142 (4):406- 414.
  • Sun J, Fang W, Wang D, Xua W. Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method. Energy Conversion Management 2009; 50(12):2967-2975
  • Bhuvaneswari R, Edrington C. S, Cartes D.A. Online Economic Environmental Optimization of a Microgrid Using an Improved Evolutionary Programming Technique. North American Power Symposium 2009; pp: 1 – 6.
  • Conti S, Rizzo S.A. Optimal Control to Minimize Operating Costs and Emissions of MV Autonomous Micro-Grids with Renewable Energy Sources. International Conference on Clean Electrical Power 2009; p: 634 – 639.
  • Lin WM, Cheng FS, Tsay MT. Nonconvex economic dispatch by integrated artificial intelligence. IEEE Trans Power Syst 2001; 16(2):307-311.
  • Wang L, Singh Ch. Environmental/economic power dispatch using fuzzified multi- objective particle swarm optimization algorithm. Electr Power Syst Res 2007; 77:1654- 1664.
  • Huanga H.Z, Gub Y.K, Duc X. An interactive fuzzy multi-objective optimization method for engineering design. Engineering Applications of Artifcial Intelligence 2006; pp: 451– 460.
  • Abido M.A. Environmental/Economic Power Dispatch using Multiobjective Evolutionary Algorithms. IEEE Transaction on Power System, 2003; 18(4): 1529-1537.
  • Sakawa M., Yano H. An interactive fuzzy satisfying method using augmented minimax problems and its application to environmental systems. IEEE Trans. SMC 1985; 17(6): 720–729.
  • Anvari-Moghaddam A, Seifi A, Niknam T, M. Multi-objective operation management of a renewable MG with back-up micro-turbine/fuel cell/battery hybrid power source. Energy 2011;36(11):6490-6507.
  • Soroudi A, Aien M, Ehsan M. A probabilistic modeling of photo voltaic modules and wind power generation impact on distribution networks. IEEE Syst J 2011;99:1e10.
  • Harr E. Probabilistic estimates for multivariate analysis. Appl Math Model 1989;13(5):313e8.
  • Hong HP. An efficient point estimate method for probabilistic analysis. Reliab Eng Syst Saf 1998;59:261e7.
  • Schellenberg A, Rosehart W, Aguado J. Cumulant-based probabilistic optimal power flow (P-OPF) with Gaussian and gamma distributions. IEEE Trans Power Syst 2005;20(2):773e81
  • Morales JM, Perez-Ruiz J. Point estimate schemes to solve the probabilistic power flow. IEEE Trans Power Syst 2007;22:1594e601.
Toplam 29 adet kaynakça vardır.

Ayrıntılar

Bölüm Derleme
Yazarlar

Mehdi Motevasel

Shahriar Bazyari Bu kişi benim

Yayımlanma Tarihi 13 Mayıs 2015
Yayımlandığı Sayı Yıl 2015 Cilt: 36 Sayı: 3

Kaynak Göster

APA Motevasel, M., & Bazyari, S. (2015). Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, 36(3), 1855-1864.
AMA Motevasel M, Bazyari S. Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi. Mayıs 2015;36(3):1855-1864.
Chicago Motevasel, Mehdi, ve Shahriar Bazyari. “Probabilistic Energy Manement of Micro-Grids With Respect to Economic and Environmental Criteria”. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 36, sy. 3 (Mayıs 2015): 1855-64.
EndNote Motevasel M, Bazyari S (01 Mayıs 2015) Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 36 3 1855–1864.
IEEE M. Motevasel ve S. Bazyari, “Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria”, Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, c. 36, sy. 3, ss. 1855–1864, 2015.
ISNAD Motevasel, Mehdi - Bazyari, Shahriar. “Probabilistic Energy Manement of Micro-Grids With Respect to Economic and Environmental Criteria”. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 36/3 (Mayıs 2015), 1855-1864.
JAMA Motevasel M, Bazyari S. Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi. 2015;36:1855–1864.
MLA Motevasel, Mehdi ve Shahriar Bazyari. “Probabilistic Energy Manement of Micro-Grids With Respect to Economic and Environmental Criteria”. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, c. 36, sy. 3, 2015, ss. 1855-64.
Vancouver Motevasel M, Bazyari S. Probabilistic Energy Manement of micro-grids with respect to Economic and Environmental Criteria. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi. 2015;36(3):1855-64.