The DNRP problem refers to a set of actions taken by distribution network operator/planner which ensures the secure and efficient operation of the distribution network within a given planning horizon. It includes conductor replacement, installing capacitors, network reconfiguration, On Load Tap Changer settings, distributed generator connection assessment and etc. It is usually formulated as a MINLP optimization problem and it is tried to optimize the summation of investment and operating costs. The presence of uncertain parameters in electrical power systems presents an ongoing problem for system operators when it comes to making decisions. Determining the most appropriate actions relies heavily on forecasts for a number of parameters such as demand, renewable energy resources availability and more recently weather. These uncertain parameters present an even more compelling problem at the distribution level, as these networks are inherently unbalanced, and need to be represented as such for certain tasks  .
Optimization models and Solution methods
Different optimization models have been proposed to solve the DNRP problem. These models can be categorized as follows:
Single/multiple objective optimization: Single objective optimization models are the most common form of formulating the DNRP problem. These models are either naturally single objective or they combine several objectives to form a single objective function using weighted sum approach . The multi objective models try to find the Pareto optimal front of solution space .
Non-linear programming : the power flow equations contain the sin and cos functions 
Quadratic programming 
Mixed integer programming : benders decomposition 
Heuristic techniques Immune algorithm , Big Bang-Big Crunch Method , Genetic algorithm , PSO 
Uncertainty and risk consideration: robust optimization, Information gap decision theory, Stochastic methods 
Different optimization solvers and commercial software have been used for solving the DNRP problem such as CONOPT, DICOPT , OpenDSS , Digsilent , MATPOWER .
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http://sourceforge. net/apps/mediawiki/electricdss/index. php.1] Model, O. P., & Element, O. S. OpenDSS Manual. EPRI,[Online] Available at:
2] Hansen, Anca D., et al. Dynamic wind turbine models in power system simulation tool DIgSILENT. 2004.
3] Zimmerman, Ray Daniel, Carlos Edmundo Murillo-Sánchez, and Robert John Thomas. "MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education." IEEE Transactions on power systems 26.1 (2011): 12-19.
Dr Alireza Soroudi, University College Dublin