Probabilistic optimal power allocation of dispatchable DGs and energy storage units in a reconfigurable grid-connected CCHP microgrid considering demand response

This paper proposes a hierarchical two-stage coordinated stochastic energy management strategy (SEMS) for a multi-energy carrier grid-tied AC microgrid in presence of combined cooling-heat-power (CCHP) based dispatchable distributed generators, renewable generators, distribution static synchronous compensator, energy storage units, auxiliary boiler, chiller and loads. The first-stage of the optimization strategy deals with a mixedinteger non-linear programming framework aiming at maximizing estimated day-ahead operation profit. In this stage, a mixed demand response program as part of demand side management measures is implemented for responsive electric loads to achieve both supply-side and demand-side benefits. The second stage of the power management strategy is driven by the objective of reducing expected hour-ahead operation cost including pollutant emission conversion cost and the associated optimization problem is solved using a meta-heuristic optimizer called hybrid particle swarm and grey wolf optimizer. Several operational constraints are considered while solving the problem. In this stage, Hong's 2m+1 point estimate method coupled with Nataf transformation is employed to model the correlated uncertainties associated with random variables. Power outputs of dispatchable units, electricity market price, incentive rate, charging/discharging power schedule of energy storage units, and the power exchange between the main grid and microgrid are considered as the control parameters of optimization. Furthermore, a group of measures like remote-bus voltage-constrained power flow with different types of microgrid structures and network reconfiguration is incorporated within the energy management scheme to enhance the steady-state performance and reliability of the microgrid. The efficacy of the proposed framework is validated on a 33-node grid-tied AC microgrid test system.