This study presents a reliability-constrained optimization approach to determine the number and size of combined heat and power (CHP) system components, including CHP units, auxiliary boilers, and heat-storage tanks. To this end, the loss-of-load expectation and the expected energy not supplied are considered since the reliability indices ensure the security of operation. The load forecasting inaccuracy and the random outages of CHP system components as well as the loss of mains are modeled as a scenario tree using the Monte Carlo sampling approach. The problem is formulated as two-stage stochastic mixed integer linear programming. A scenario reduction technique is also introduced to reduce the computational burden of the scenario-based planning problem. Finally, the proposed model is applied to a large residential complex in Tehran as a case study.

This paper presents a comprehensive data-driven distributed combined primary/secondary controller design method for microgrids. This method provides transient and steady-state performance including power-sharing and voltage and frequency restoration while guaranteeing stability for fixed communication delay. The measured data is directly used for controller design with no need for knowledge about the order or structure of the system and grid physical parameters. Moreover, no assumption is made on X/R-ratio of feeders. All the control specifications are formulated as frequency-domain constraints on the 2-norm of weighted sensitivity functions. Then, using a recently developed frequency-domain robust control design method, a distributed fixed-structure controller is synthesized in one step. The performance of the obtained controller is validated using Hardware-In-the-Loop (HIL) experiments. The results show considerable improvement in transient performance, while providing power-sharing and voltage and frequency restoration using distributed implementation. Index Terms-Data-driven controller design, frequency control, voltage control, power-sharing, microgrid control, distributed control.

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