Integrated cost-benefit assessment of customer-driven distributed generation

被引：0
作者：
机构：
[1] Faculty of Electrical Engineering, University of Banja Luka, Banja Luka
[2] School of Electrical Engineering, University of Belgrade, Belgrade
来源：
| 1600年 / University of Banja Luka, Faculty of Electrical Engineering卷 / 18期
关键词：
Customerperspective approach; Distributed generation (DG); Integrated cost-benefit assessment; Long-term planning; Monte Carlo simulation; Uncertainty analysis;
D O I：
10.7251/ELS1418054Z
中图分类号：
学科分类号：
摘要：
Distributed generation (DG) has the potential to bring respectable benefits to electricity customers, distribution utilities and community in general. Among the customer benefits, the most important are the electricity bill reduction, reliability improvement, use of recovered heat, and qualifying for financial incentives. In this paper, an integrated cost-benefit methodology for assessment of customer-driven DG is presented. Target customers are the industrial and commercial end-users that are critically dependent on electricity supply, due to high consumption, high power peak demand or high electricity supply reliability requirements. Stochastic inputs are represented by the appropriate probability models and then the Monte Carlo simulation is employed for each investment alternative. The obtained probability distributions for the prospective profit are used to assess the risk, compare the alternatives and make decisions.
引用
收藏
页码：54 / 61
页数：7
相关论文
共 31 条
  • [1] Pepermans G., Driesen J., Haeseldonckx D., Belmans R., D'haeseleer W., Distributed generation: definition, benefits and issues, Energy Policy, 33, pp. 787-798, (2005)
  • [2] Chowdhury A.A., Agarwal S.K., Koval D.O., Reliability modeling of distributed generation in conventional distribution systems planning and analysis, IEEE Transactions on Industry Applications, 39, pp. 1493-1498, (2003)
  • [3] Moreno-Munoz A., de-la-Rosa G.J.J., Lopez-Rodriguez M.A., Flores-Arias J.M., Bellido-Outerino F.J., Ruiz-de-Adana M., Improvement of power quality using distributed generation, International Journal of Electrical Power Energy Systems, 32, pp. 1069-1076, (2010)
  • [4] Gil H.A., Joos G., On the quantification of the network capacity deferral value of distributed generation, IEEE Transactions on Power Systems, 21, pp. 1592-1599, (2006)
  • [5] Gil H.A., Joos G., Models for quantifying the economic benefits of distributed generation, IEEE Transactions on Power Systems, 23, pp. 327-335, (2008)
  • [6] Bae I.-S., Kim J.O., Kim J.-C., Singh C., Optimal operating strategy for distributed generation considering hourly reliability worth, IEEE Transactions on Power Systems, 19, pp. 287-292, (2004)
  • [7] Barina A., Pozzatti L.F., Canha L.N., Machado R.Q., Abaide A.R., Arend G., Multi-objective analysis of impacts of distributed generation placement on the operational characteristics of networks for distribution system planning, International Journal of Electrical Power Energy Systems, 32, pp. 1157-1164, (2010)
  • [8] Zangiabadi M., Feuillet R., Lesani H., Hadj-Said N., Kvaloy J.T., Assessing the performance and benefits of customer distributed generation developers under uncertainties, Energy, 36, (2011)
  • [9] Marnay C., Chard J., Hamachi K., Lipman T., Moezzi M., Ouaglal B., Siddiqui A., Modeling of customer adoption of distributed energy resources, Lawrence Berkeley National Laboratory Report LBNL- 49582, (2001)
  • [10] Siddiqui A.S., Marnay C., Firestone R.M., Zhou N., Distributed generation with heat recovery and storage, Journal of Energy Engineering, 133, pp. 181-210, (2007)
1234