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Integrated electricity and heat systems facilitate efficient interactions between individual energy sectors for higher renewable energy accommodation. However, the feasibility of operational strategies is difficult to guarantee due to the presence of substantial uncertainties pertinent to renewable energy and multi-energy loads. This paper proposes a novel efficient robust scheduling model of integrated electricity and heat systems based on extensions of disturbance invariant sets. The approach has high computational efficiency and provides flexible and robust strategies with an adjustable level of conservativeness. In particular, the proposed robust scheduling method obtains scheduling strategies by solving a nominal uncertainty-free scheduling problem, whose complexity is identical to a deterministic problem. The robustness against uncertainties is enhanced by endowing the nominal scheduling model with properly tightened constraints considering time-variant uncertainty sets. Towards this end, a novel direct constraint tightening algorithm is developed based on the dual norm to calculate multi-period tightened constraints efficiently without linear programming iterations. Furthermore, the budget uncertainty set is newly combined with constraint tightening to flexibly adjust the conservativeness level of robust solutions. The effectiveness of the proposed robust method is demonstrated in simulation studies of two test systems in terms of computational efficiency, decision robustness and cost reduction. [ABSTRACT FROM AUTHOR]

Combined heat, and power dispatch promotes interactions, and synergies between electric power systems, and district heating systems. However, nonlinear, and nonconvex heating flow imposes significant challenges on finding qualified solutions efficiently. Most existing methods rely on constant flow assumptions to derive a linear heating flow model, sacrificing optimality for computational simplicity. This paper proposes a novel convex combined heat, and power dispatch model based on model simplification, and constraint relaxations, which improves solution quality, and avoids assumptions on operating regimes of district heating systems. To alleviate mathematical complexity introduced by the commonly used node method, a simplified thermal dynamic model is proposed to capture temperature changes in networked pipelines. Quadratic, and polyhedral relaxations are then applied to convexify the original problem with quadratic equality, and bilinear constraints. Furthermore, an adaptive solution algorithm is developed to successively reduce the relaxation area based on sequential bound tightening, which improves solution optimality with desirable computational efficiency. The proposed method is verified on a distribution-level, and a transmission-level integrated electricity, and heat systems, compared to constant-flow-based solutions, and iterative algorithms. [ABSTRACT FROM AUTHOR]

Combined heat and power dispatch (CHPD) is utilized for energy-efficient coordination of integrated electricity and heat systems. By incorporating district heating networks (DHNs) into CHPD, the thermal storage capability of network pipelines can be exploited to increase the operational flexibility for high penetration of renewable energy. This article proposes a flexibility evaluation method based on a generalized thermal storage model to systematically characterize and quantify the flexibility of DHNs in CHPD. In particular, systematic flexibility metrics are introduced to define the parameters of the proposed thermal storage model, including heat ramping capability, heat input limits, and heat storage capacities. A direct quantification method is proposed to explicitly derive these metrics without extensive simulations required in traditional methods. Besides, four different control modes of district heating systems are identified and modeled according to the controllability of mass flow rates and supply temperature at heat sources. A simplified CHPD model is developed based on sequential linear programming and a lumped heat loss model to enhance the computational efficiency. Comprehensive case studies validate the effectiveness of the proposed method in evaluating the flexibility of DHNs in CHPD. It is demonstrated that the flexibility of DHNs in CHPD can be exploited as far as possible in the control mode with adjustable mass flow and supply temperature. [ABSTRACT FROM AUTHOR]

Increasing deployment of distributed energy resources intensifies interactions among electric, gas, heating, and cooling systems. Inherent uncertainties ranging from internal parameters to external inputs also impose significant challenges on system operation. A coordinated scheduling method is, therefore, desired for facilitating efficient operation of multi-energy microgrids under multiple uncertainties. In this paper, a deterministic coordinated scheduling model is developed first with detailed modeling of system dynamics and device parameters to fully characterize complex interactions among multi-energy carriers. Then, a hybrid stochastic-interval method is proposed to account for heterogeneous uncertainties in decisions of operational strategies. Specifically, performance and efficiency uncertainties of distributed energy resources, and injection uncertainty of renewable sources and multi-energy demands are characterized by interval-based uncertain operation regions and probability distributions, respectively. A scenario-based two-stage algorithm is developed to solve the problem so that multiple uncertainties are preserved in the entire decision-making process. Moreover, adjustable operational strategies are determined to hedge uncertainty by considering operators’ risk preferences. The validity of the proposed method is verified by comprehensive case studies on a test system. [ABSTRACT FROM AUTHOR]