Online benefit optimization in a liberalized/free microgrid market model

In this paper, an efficient online energy management problem for a liberalized microgrid market model is formulated. Online optimal power dispatch problem solved by particle swarm optimization with time varying acceleration co-efficient (PSO-TVAC) and backward-forward sweep power flow is used to manage the microgrid sources and loads, considering fuel and emission costs of distributed energy resources (DERs), hourly profits, load curtailment and buying/selling of power from/to the main grid. Instantaneous measured data of demand and renewable energy are used to optimally dispatch the conventional DERs, trade the grid power and curtail the selected loads to satisfy the power balance in the online mode. The effectiveness of the formulated problem and the proposed method is investigated on the residential feeder of the LV benchmark radial microgrid in terms of fuel cost, emission, voltage deviation, curtailed load, upstream grid power traded and overall execution time. Two different objectives of the microgrid central controller (MGCC) based on different levels of participation in the open market are compared viz. ;overall profit maximization ; and operational cost minimization.