Integrated electrical and heating systems(IEHS) are drawing huge attention because of their cost-effective and flexible operational capabilities. Optimal dispatch of renewable units in an IEHS is challenging because of their intermittent and stochastic nature. Uncertainties in the renewable energy source (RES) forecast, electrical, and thermal loads can cause voltage and temperature violations compromising the operational security of the system. In this paper, a rule-based dynamic dispatch is proposed to handle the increasing levels of uncertain RES and ensure the system's security. A chance-constrained (CC) co-optimization algorithm considering the uncertain loads and RES is developed. In the proposed method, electric boiler power and curtailment of RES are dynamically dispatched to reduce operational costs and network losses. The developed method is tested on the IEEE 15 bus distribution system and UK Generic Distribution System (UKGDS) 95 bus test system models. The results show that the proposed method significantly reduces the voltage deviations and temperature violations compared to the deterministic case.

With the fast expansion of the power grid and increasing complexity due to modern equipment, power flow models with non-convexity and long computing time are not suitable for network calculation and optimization problems. Therefore, this paper proposes a linearized branch flow model (LBF) considering line shunts (LBFS). The strength of LBF lies in its linear mathematical structure, and hence the convex nature, which is primarily achieved by regarding the apparent power flow as the branch current magnitude. Moreover, the calculation accuracy in nodal voltage magnitude is significantly improved by appropriately modeling line shunt admittances and network equipment like transformers, shunt capacitors and distributed generators (DG). We show the application scope of LBFS by controlling the network voltages through a two-stage stochastic optimization Volt/VAr control (VVC) problem considering DG output uncertainty. Since LBFS results in a linear VVC program, the global solution is guaranteed. Simulations show that VVC framework can optimally dispatch the discrete control devices, viz. substation transformers and shunt capacitors, and also optimize the decision rules for real time reactive power control of DGs. Besides, the computing efficiency is significantly improved compared to traditional VVC methods.

This paper proposes a completely non-centralized Volt/VAr control (VVC) algorithm for active distribution networks which are faced with voltage magnitude violations due to the high penetration of solar photovoltaics (PVs). The proposed VVC algorithm employs a two-stage architecture where the settings of the classical voltage control devices (VCDs) are decided in the first stage through a distributed optimization engine powered by the alternating direction method of multipliers (ADMM). In contrast, the PV smart inverters are instructed in the second stage through linear Q(P) decision rules - which are computed in a decentralized manner by leveraging robust optimization theory. The key to this non-centralized VVC routine is a proposed network partition methodology (NPM) which uses an electrical distance metric based on node Q􀀀jV j2 sensitivitiesfor computing an intermediate reduced graph of the network, which is subsequently divided into the final partitions using the spectral clustering technique. As a result, the final network partitions are connected, stable, close in cardinality, contain at least one PV inverter for zonal reactive power support, and are sufficiently decoupled from each other. Numerical results on the UKGDS-95 bus system show that the non-centralized solutions match closely with the centralized robust VVC schemes, thereby significantly reducing the voltage violations compared to the traditional deterministic VVC routines.