New green energy policies are encouraging district heating (DH) companies to exploit heat production by power-to-heat (P2H) assets e.g. heat pumps (HPs) and electric boilers (EBs). Therefore, they are shifting to exploit these assets in their distribution network besides the traditional central combined heat and power (CHP) units in their production chain. It will lead to an increasingly complex interaction between DH networks and electricity markets. This paper proposes an economic model predictive control (EMPC) framework to investigate how DH companies can manage this extra complexity and if they can contribute in an efficient way towards balancing the production and consumption of electric power in smart grids through playing in the reserve capacity markets. The framework is applied to a real world case study and the results are discussed. The results show the new paradigm increases operation costs. However, reserving a part of the capacity for playing in reserve capacity market will not only make up for the extra costs to some extent, but also improve the capability of providing regulating power.

Due to the new green energy policies, district heating companies are being increasingly encouraged to exploit power-to-heat assets, e.g., heat pumps and electric boilers, in their distribution networks besides the traditional central combined heat and power units. The increased utilization of these assets will generate a more complex interaction between power distribution grids and district heating networks including markets for provision of ancillary services. Enabling the participation of power-to-heat units in the ancillary service markets, e.g., frequency reserves, may increase the revenue streams for assets’ owners. However, some technical challenges must first be addressed, including optimization of portfolios of assets that accounts for ancillary service markets, new coordination and operational schemes for portfolio of assets, increase data exchange and interactions with transmission system operators, and new local control schemes for units. This paper proposes a systematic model based design approach for assessment of provision of frequency regulation by power-to-heat assets using the smart grid architecture model. The proposed approach is demonstrated in a Real-Time Control Hardware-in-the-Loop laboratory environment.

In the context of increasing energy demands and the integration of renewable energy sources, this review focuses on recent advancements in energy storage control strategies from 2016 to the present, evaluating both experimental and simulation studies at component, system, building, and district scales. Out of 426 papers screened, 147 were assessed for eligibility, with 56 included in the final review. As a first outcome, this work proposes a novel classification and taxonomy update for advanced storage control systems, aiming to bridge the gap between theoretical research and practical implementation. Furthermore, the study emphasizes experimental case studies, moving beyond numerical analyses to provide practical insights. It investigates how the literature on energy storage is enhancing building flexibility and resilience, highlighting the application of advanced algorithms and artificial intelligence methods and their impact on energy and financial savings. By exploring the correlation between control algorithms and the resulting benefits, this review provides a comprehensive analysis of the current state and future perspectives of energy storage control in smart grids and buildings.

This paper presents a unified passive–active fault-tolerant control strategy to compensate the loss of actuators’ effectiveness. The proposed approach is capable of handling the system in pre- and post-fault diagnosis intervals by passive and active approaches, respectively. The stability of the designed system is independent of the accuracy of information provided by the fault detection and diagnosis unit, however, a precise estimation could improve the conservation. Actuator saturation and L_∞ disturbances effects are considered in the design stage. The trade-off between maximising the domain of attraction and minimising the effects of L_∞ disturbances is tackled by developing a non-constant state feedback strategy. The feedback gains are determined by solving an optimisation problem. The proposed method is implemented on a model of Boeing 747 and results are discussed.