A Survey on Optimal Control and Operation of Integrated Energy Systems <s> Optimal Operating Constraints of IES. <s> In power systems with more and more variable renewable sources, gas generation is playing an increasingly prominent role in providing short-term flexibility to meet net-load requirements. The flexibility provided by the gas turbines in turn relies on the flexibility of the gas network. While there are several discussions on the ability of the gas network in providing this operational flexibility, this has not been clearly modeled or quantified. In addition, the gas network may also be responsible for supplying heating technologies, and low-carbon scenarios see a tighter interaction between the electricity, heating and gas sectors, which calls for a holistic multi-energy system assessment. On these premises, this paper presents an original methodology to quantify the flexibility the gas network can provide to the power system, as well as the constraints it may impose on it, with also consideration of different heating scenarios. This is achieved by a novel multi-stage integrated gas and electrical transmission network model, which uses electrical DC OPF and both steady-state and transient gas analyses. A novel metric that makes use of the concept of zonal linepack is also introduced to assess the integrated gas and electrical flexibility, which is then used to impose gas-related inter-network inter-temporal constraints on the electrical OPF. Case studies are performed for the Great Britain transmission system for different renewables and heating scenarios to demonstrate the proposed integrated flexibility assessment methodology, provide insights into the effects of changes to the heating sector on the multi-energy system’s combined flexibility requirements and capability, and assess how the electrical network can experience local generation and reserve constraints related to the gas network’s lack of flexibility. <s> BIB001 </s> A Survey on Optimal Control and Operation of Integrated Energy Systems <s> Optimal Operating Constraints of IES. <s> This paper discusses decentralized real-time energy management for multiple-source hybrid energy systems (HESs), which adapts to the sudden change in system configuration, such as due to failure of certain devices. An engine-generator/battery/ultracapacitor (UC) HES is chosen as a case study facilitating the following theoretical discussion. The energy management problem is first modeled as a noncooperative game, in which the different preferences of the energy sources (engine-generator, battery pack, and UC pack) in actual operation are quantified through their individual utility functions. The Nash equilibrium is iteratively reached at each control instant via a learning algorithm. Under the game theory based control, each source or player tends to maximize its own preference. However, its satisfaction level also depends on decisions of others. This real-time interaction in decision making provides the proposed energy management a capability to autonomously adapt to the reconfigured HES. A tuning procedure of weight coefficients in the utility functions also helps to further improve the adaptiveness of the decentralized energy management. Both the simulation and real-time implementation show that the game theory based energy management strategy has a comparable performance to the classical centralized benchmarking strategy. Meanwhile, the decentralized strategy demonstrates an obvious flexibility handling the cases when the configuration of the HES varies both statically and dynamically. <s> BIB002
In the research of optimizing constraints, besides the independent units of conventional power system, natural gas system and thermal system BIB001 , the coupling system has also been discussed in previous studies BIB002 . e speci c constraints are shown in Figure 5 .