Active distribution networks planning with integration of demand response. (December 2015)

• Record Type: Journal Article
• Authors: Mokryani, Geev
• Is Part Of: Solar energy. Volume 122(2015)
• Page Start: 1362
• Page End: 1370
• Publication Date: 2015-12
• Subjects: Photovoltaic cells -- Uncertainties -- Loss minimization -- Demand response -- Distribution network operators -- Monte Carlo simulation; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2015.10.052
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: A probabilistic method for active distribution networks planning with integration of demand response (DR). Modeling uncertainties related to solar irradiance, load demand and future load growth are modeled by probability density functions (PDFs). Simultaneously minimizing the total operational cost and total energy losses of the lines from the point of view of distribution network operators (DNOs) with integration of DR over the planning horizon considering active management schemes such as coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated PDFs and the weighting factor method is used to solve the multi-objective optimization problem. Abstract: This paper proposes a probabilistic method for active distribution networks planning with integration of demand response. Uncertainties related to solar irradiance, load demand and future load growth are modeled by probability density functions. The method simultaneously minimizes the total operational cost and total energy losses of the lines from the point of view of distribution network operators with integration of demand response over the planning horizon considering active management schemes including coordinated voltage control and adaptive power factor control. Monte Carlo simulation method is employed to use the generated probability density functions and the weighting factor method is used to solve the multi-objective optimization problem. The effectiveness of the proposed method is demonstrated with 16-bus UK generic distribution system.