A Survey on Optimal Control and Operation of Integrated Energy Systems <s> Natural Gas Network. <s> This paper proposes an integrated model for assessing the impact of interdependency of electricity and natural gas networks on power system security. The integrated model incorporates the natural gas network constraints into the optimal solution of security-constrained unit commitment. The natural gas network is modeled by daily and hourly limits on pipelines, sub-areas, plants, and generating units. The application of fuel diversity (e.g., generating units with fuel switching capability) is presented as an effective peak shaving strategy for natural gas demand which could hedge price volatilities of natural gas and electric power. The proposed model can be used by a vertically integrated utility for the commitment and dispatch of generating units and the allocation of natural gas for the next day utilization. The proposed model can also be used for measuring the security of social services by modeling the interdependency of natural gas and electric power system infrastructures. If the proposed model is used by GENCOs, gas constraints will be submitted to electricity markets as energy constraints. Illustrative examples show the impact of natural gas supply infrastructure on the economic operation of a vertically integrated utility. The examples also discuss the impact of generating units with fuel switching capability on the power system security when the supply of natural gas is limited. <s> BIB001 </s> A Survey on Optimal Control and Operation of Integrated Energy Systems <s> Natural Gas Network. <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> BIB002
e air ow through the pipeline depends on the pressure at both ends of the pipeline and is expressed as follows: where is the ow value of natural gas pipeline from node m to node n; Δ is the pressure di erence between node and ; sgn Δ is the ow direction in pipeline; "1" means from node to node ; "−1" means from node to node ; is the constant of pipeline, and generally calculated by , Li et al. BIB001 uses cooperative game theory to optimize multiple IES systems by adjusting the existing IES control algorithm, and proves that the cooperative game has a balanced distribution point of economic bene t. Clegg and Mancarella BIB002 proposes an optimal operating framework for intelligent areas with multienergy devices and integrated energy networks. e framework is based on two-stage iterative modeling, involving linear approximation of MILP and nonlinear network equations. Practical cases in England prove that the proposed model can eliminate uncertainty to a certain level and has important reference value for evaluation of system exibility.