Incentive-based regulations, toward higher performance networks, are the main driver for minimising losses in distribution systems. On the other hand, more renewable generation is needed to achieve environmental targe...
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Incentive-based regulations, toward higher performance networks, are the main driver for minimising losses in distribution systems. On the other hand, more renewable generation is needed to achieve environmental targets. Hence, a multiobjective model is introduced in this study seeking to minimise energy losses as well as maximise renewable generation in radial distribution systems (RDSs). Two alternative control strategies of future smart grids such as reactive power management using adaptive power factor control and coordinated voltage control are considered in the optimisation problem. The problem is subjected to the various technical constraints such as voltage limits, thermal limits and reactive capability limits of photovoltaic (PV) penetration, power factor regulations and underload tap changer adjustment. Also, the uncertainties of load and renewable generation are considered, too. Then, the obtained non-linear programming problem is relaxed and reformulated as a well-suited and computationally efficient second-order cone programming problems. To obtain more efficient and evenly distributed Pareto set to help decision-making process, a modified normal boundary intersection method is introduced for solution methodology. The implementation of the proposed framework on IEEE 33-bus RDSs shows the gains that the flexibility provided by innovative control strategies can have on energy loss reduction and PV capacity.
Decision making processes in imprecise environments are usually addressed by fuzzy multi-criteria optimization problems. It is significantly natural that complete information about non-dominated set for fuzzy multi-cr...
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Decision making processes in imprecise environments are usually addressed by fuzzy multi-criteria optimization problems. It is significantly natural that complete information about non-dominated set for fuzzy multi-criteria optimization problem not only facilitates decision making process, but also helps the process to undergo in a proper mathematical way. However, in the literature no methodology is found yet to capture entire fuzzy non-dominated set. Thus, this paper attempts to generate complete fuzzy non-dominated set of fuzzy multi-criteria optimization problem. This is the main objective of the paper. The proposed study mainly focuses to observe the problem from fuzzy geometrical framework. In the studied methodology, at first, fuzzy decision feasible region is constructed through a newly proposed fuzzy inequality relation using same points in fuzzy geometry. Then, fuzzy non-dominated set is formulated under a new definition of fuzzy Pareto set. Finally, modified normal boundary intersection method is being used to capture the fuzzy Pareto set of the problem. Proposed definitions and methodologies are supported by several numerical examples and pictorial illustrations.
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