Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties

Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods

“…Optimal DG siting is based on voltage sensitivity and apparent power load; Specific DG operational schedule is considered; Optimised DG system with lagging power factor exhibits better technical and economic performances Gampa Muttaqi et al [283] Minimum operation and power reserve costs, and emission-related environmental cost Market balance, DG generation capacity, spinning reserve limit, power flow balance, demand reserve limit, and load shedding limit Load and reserve power ratings of multiple DG technologies Uncertainty in power dispatch scheduling associated with renewable variability is incorporated into cost function; Concurrent scheduling of electric vehicle (EV) and responsive load assists in peak shaving, load shifting, reserve power supply, operating cost and emission reduction, and system reliability improvement Rabiee et al [266] Stochastic (improved) PSO Hybrid PSO -SFLA Minimum real power loss, voltage deviation, and CCT index DG power limit, voltage limit, branch power flow constraint, and power flow balance Size and capacity of (multiple) microturbine DG PSO is coupled with SFLA to overcome its premature convergence problem; CCT index is introduced to quantify power system transient stability, and serves to minimise short-circuit fault in the system design; More security-based objective functions are anticipated Nayeripour et al [275] Hybrid In addition, as inspired by multi-modelling regression approach, development of a multi-algorithm optimisation framework for energy planning context could provide an alternative solution besides model hybridisation. This method shall embed different algorithms with varying computational time, exploration and exploitation skill levels.…”

An efficient scheme for residential load scheduling integrated with demand side programs and small-scale distributed renewable energy generation and storage

“…Optimisation approaches that have been explored for this problem include binary particle swarm optimisation and greedy iterative algorithm . The optimisation objectives span minimising the end‐use energy consumption and/or maximising comfort level.…”

Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

“…In the power generation section, some models have been proposed to reduce wind and solar [29,34,35] power generation forecasting error. Stochastic formulation [28,29] has also been used to simulate power generation.…”