Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

Microgrids are a type of restricted power distribution systems in which electricity is generated,transmitted,and distributed within a small geographic region.They are used to ensure that renewable energy sources are used to their full potential.Microgrids provide further benefits,such as lowering transmission losses and the expenses associated with them.This research compares and contrasts the aims of economic dispatch,emission dispatch,fractional programing based combined economic emission dispatch,and environmental restricted economic dispatch(ECED).A low-voltage microgrid system is investigated for three different scenarios.As a study optimization tool,an innovative,resilient,and strong hybrid swarm-intelligence optimization algorithm is utilised,which is based on combining the properties of the traditional grey-wolf optimiser,sine-cosine algorithm,and crow search algorithm.The employment of a time-of-use energy mar-ket pricing approach instead of a fixed pricing plan resulted in a 15%decrease in gen-eration costs throughout the course of the research.When ECED was assessed with a 15%-20%demand side management based restructured load demand model for the microgrid system,the generation costs were reduced even further.

Modified branch-and-bound algorithm for unravelling optimal PMU placement problem for power grid observability: A comparative analysis

Safe operation of the power grid requires a complete and robust control network to ensure full observability;However,redundancy measurements can create problems in expense,management,and control.The optimal phasor measurement unit(PMU)positioning problem(OPPP)is proposed to limit the number of PMUs deployed in the power grid and ensure the whole grid's observability in the meantime.A modified branch-and-bound algorithm(MBBA)to unravel the OPPP is presented.Original BBA,which uses a single search order to create a binary tree,gives only one solution to the OPPR although more than one optimal solution exists.The proposed MBBA method consists of two different stages:the vertexes in the search tree are investigated by depth-first search(DFS)in stage 1,and the search route continues as the breadth-first search.In stage 1,the LP relaxing problems are solved by dual simplex,and in stage 2,the basic viable solution from stage 1 is used to configure the primary simplex until the optimum solution is found.OPPP is formulated as a binary decision variable MBBA model,minimizing linear objective function subject to linear matrix observability constraints.The MBBA model is unravelled using a linear integer-based external approximation scheme.IEEE test systems are used to check the feasibility of the proposed approach.Matlab software performs simulation based on a number of graph theory-based methods such as DFS,graph-theoretical method,simulated annealing,and recursive N-algorithms.These algorithms are compared to the algorithmic perspective of the proposed MBBA method.IEEE test network results confirm the validity of the proposed methodology.

Hybrid intelligence approach for multi-load level reactive power planning using VAR compensator in power transmission network

This paper formulates and solves a techno-economic planning problem of reactive power (VAR) in power transmission systems under loadings. The objective of the proposed research work is to minimize the combination of installation cost of reactive power sources, power losses and operational cost while satisfying technical constraints. Initially, the positions for the placement of reactive power sources are determined technically. Different cost components such as VAR generation cost, line charging cost etc. are then added in the total operating cost in a most economical way. Finally, the optimal parameter setting subjected to reactive power planning (RPP) is obtained by taking advantages of hybrid soft computing techniques. For the justification of the efficiency and efficacy of the proposed approach the entire work is simulated on two inter-regional transmission networks. To validate the robustness and ease of the soft computing techniques in RPP the responses of benchmark functions and statistical proof are provided simultaneously.

Weak bus-constrained PMU placement for complete observability of a connected power network considering voltage stability indices

Phasor measurement units(PMUs)are preferred for installation at weak buses in a power network.Therefore,the weak buses need to be located and the strategic locations of PMUs identified to ensure network observability.Thus,the primary aim of this work is to identify the placements of the maximum number of PMUs installed at the weak buses in the electrical network.The voltage collapse proximity indicator,line stability index,fast voltage stability index,and a new voltage stability indicator utilizing load flow measurement are used to determine the weak buses.A novel deterministic methodology based on a binary-integer linear programming model is then proposed to determine the optimal locations of PMUs.The effect of a single PMU outage considering the weak buses is also demonstrated.The effectiveness of the developed approach is tested and validated on the standard IEEE 14-,118-,300-,and New England 39-bus systems.The obtained results are also compared to those using different weak bus methodologies.