A.10. Power Management
F. Sabahi
Abstract
This paper develops an energy management approach for a multi-microgrid (MMG) taking into account multiple objectives involving plug-in electric vehicle (PEV), photovoltaic (PV) power, and a distribution static compensator (DSTATCOM) to improve power provision sharing. In the proposed approach, there ...
Read More
This paper develops an energy management approach for a multi-microgrid (MMG) taking into account multiple objectives involving plug-in electric vehicle (PEV), photovoltaic (PV) power, and a distribution static compensator (DSTATCOM) to improve power provision sharing. In the proposed approach, there is a pool of fuzzy microgrids granules that they compete with each other to prolong their lives while monitored and evaluated by the specific fuzzy sets. In addition, based on the hourly reconfiguration of microgrids (MGs), granules learn to dispatch cost-effective resources. To promote interactive service, a well-defined, multi-objective approach is derived from fuzzy granulation analysis to improve power quality in MMGs. A combination of the meta-heuristic approach of genetic algorithm (GA) and particle swarm optimization (PSO) eliminates the computational difficulty of the nonlinearity and uncertainty analysis of the system and improves the precision of the results. The proposed approach is successfully applied to a 69-bus MMG test with results reported in terms of stored energy improvement, daily voltage profile improvement, MMG operations, and cost reduction.
A.10. Power Management
Kh. Valipour; A. Ghasemi
Abstract
The optimal reactive power dispatch (ORPD) is a very important problem aspect of power system planning and is a highly nonlinear, non-convex optimization problem because consist of both continuous and discrete control variables. Since the power system has inherent uncertainty, hereby, this paper presents ...
Read More
The optimal reactive power dispatch (ORPD) is a very important problem aspect of power system planning and is a highly nonlinear, non-convex optimization problem because consist of both continuous and discrete control variables. Since the power system has inherent uncertainty, hereby, this paper presents both of the deterministic and stochastic models for ORPD problem in multi objective and single objective formulation, respectively. The deterministic model consider three main issues in ORPD problem as real power loss, voltage deviation and voltage stability index, but, in the stochastic model the uncertainty on the demand and the equivalent availability of shunt reactive power compensators have been investigated. To solve them, propose a new modified harmony search algorithm (HSA) which implemented in single and multi objective forms. Since, like many other general purpose optimization methods, the original HSA often traps into local optima, to aim with this cope, an efficient local search method called chaotic local search (CLS) and global search operator are proposed in the internal architecture of the original HSA algorithm to improve its ability in finding of best solution because ORPD problem is very complex problem with different types of continuous and discrete constrains i.e. excitation settings of generators, sizes of fixed capacitors, tap positions of tap changing transformers and the amount of reactive compensation devices. Moreover, fuzzy decision-making method is employed to select the best solution from the set of Pareto solutions.
