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• A joint energy-frequency regulation power market is proposed for energy transition. • Environmental cost of fossil-fueled generation is incorporated into electricity trading. • Renewable energy generation is motivated to actively manage uncertainty and intermittency of outputs. • Extensive numerical simulations are conducted to validate the proposed system. Striving to develop renewable energy generation (REG) has become a global trend. Due to high carbon emissions, fossil-fueled generation units (FFGUs) in an electrical energy market such as the day-ahead and real-time electricity markets are facing unprecedented constraints. From the perspective of FFGUs, an effective way is to change their market roles from energy suppliers with high environmental costs to secure and reliable frequency regulation service providers. To help FFGUs successfully complete the transition, a bi-level optimization model for the joint energy and regulation service market is proposed in this paper. Different from existing joint markets, both the environmental cost of FFGUs and the frequency regulation service (FRS) cost of REG units are considered in this research for market operators to determine the scheduling priorities of submitted bids from generation units. In the frequency regulation service market model, a dynamic approach to determining the FRS demand is applied, which not only incentivizes REG units to initiatively manage their outputs, but also derives the price signals through the equilibrium of the FRS demand and supply to ensure the revenue of FFGUs in the FRS market. Meanwhile, the decision-making model of the FFGUs under the proposed market mechanism is also presented. Finally, extensive numerical experiments demonstrate the feasibility and efficiency of the mechanism. Simulation results show that the proposed mechanism can stimulate a smooth transition of FFGUs by adapting to actual situations and policy changes. [ABSTRACT FROM AUTHOR]

• A fully decentralized P2P power market with AC modelled network constraints is proposed. • Network operational security is guaranteed under proposed P2P market mechanism. • User privacy is protected as nodal voltage variables are the only public variables shared among participants. • Extensive numerical simulations are conducted to validate proposed models and solving algorithm. The rapid growth of Distributed Energy Resources (DERs) and demand response in modern power grids calls for decentralized electricity trading mechanisms to effectively induce and coordinate responses from massive DERs and load entities. This paper proposes a fully decentralized peer-to-peer (P2P) distribution electricity trading mechanism backboned by a modified version of Alternating Direction Method of Multipliers (ADMM). Comparing with the state-of-the-art P2P electricity markets, the proposed electricity trading mechanism comprehensively incorporates power network constraints formulated by an alternating current power flow model. In the proposed method, nodal voltages are designed as the only public variables shared among participants. Privacy of each participant is thus sufficiently preserved without exposing the bid data to the others. Meanwhile, the proposed P2P method can also ensure the global optimality of social welfare in electricity transactions. Comprehensive case studies are carried out using the IEEE 33-node distribution system to demonstrate the feasibility and efficiency of proposed P2P electricity trading mechanism. The results indicate that the proposed model can efficiently integrates network constraints in the market clearing process while maintaining computational performance, ensuring stable convergence regardless of distribution system congestion. The proposed P2P electricity market can achieve global maximization of social welfare, with a relative difference of no more than 5.0% compared to the conventional centralized market. Even in worst-case scenarios, the relative difference remains within 7.32%. Meanwhile, the method accurately accounts for network losses, guaranteeing the feasibility of trading plans within the physical network. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

• A novel generator start-up sequence optimization strategy is proposed in this work, taking the integration time of wind-solar hybrid systems into account. • The proposed model requires fewer variables compared with other models, therefore the computational efficiency can be greatly improved. • The confidence gap decision theory based generator start-up sequence strategy is proposed to address the generation uncertainty of wind-solar hybrid systems. • Better generator start-up sequence solutions with higher computational efficiency and less conservatism can be attained by employing the proposed strategy. A reasonable start-up sequence of generators considering renewable energy generation integration can effectively improve the restoration efficiency of the power system concerned. The restoration strategy of generators is time-sensitive, however, the computation procedure of existing methods is not fast enough to meet the requirements of practical applications. In this paper, the generator start-up sequence optimization (GSSO) problem is addressed with the integration of wind-solar hybrid systems (WSSs) considered in bulk power systems. Specifically, a deterministic model for GSSO is formulated to maximize the total generation capability during the restoration procedure, in which fewer auxiliary variables are required to promote the computational efficiency. On this basis, in order to deal with the inherent and significant uncertainties of WSSs, a confidence gap decision theory (CGDT) based approach is proposed combining the advantages of stochastic optimization and the information gap decision theory based method while considering the worst-case realization of unknown probability distributions, so that a chance-constrained robust generator start-up solution is thereby attained. Moreover, the formulated CGDT based model is transformed into a mixed integer linear programming problem. Finally, the IEEE 39-bus power system and a modified version of an actual power system in China are employed to demonstrate the feasibility and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

• A load restoration scheme is proposed to coordinate the transmission, distribution, and gas systems. • The coordinated load restoration is achieved in a distributed manner to respect the information privacies. • The line-packs caused by slow gas slow dynamics is exploited to assist in load restoration. • An efficient algorithm is proposed to solve the distributed load restoration scheme with excellent calculation performance. Recent electricity systems have witnessed many power outage events, and the interrupted loads must be restored as soon as possible to reduce the enormous outage losses. However, the ever-increasing interdependencies of the transmission, distribution, and gas systems cause the restoration behaviors of a system to inevitably influence the others, which brings about new impacts on the load restoration decisions. Moreover, the different velocities of power and gas flows cause additional complexities in making load restoration decisions for the whole system. To address these problems, this paper proposes a new load restoration scheme coordinating transmission, distribution, and gas systems. Firstly, to respect the information privacy of individual energy subsystems, a distributed load restoration coordination structure is proposed with the interactions of different energy systems and corresponding load restoration models considering pipeline gas storage capacity caused by slow gas flow dynamics. Based on the distributed restoration coordination structure and considering that discrete variables in load restoration models hinder the efficient calculation, a projection function-based adaptive alternating direction method of multipliers is then proposed with iterative relaxation and projection of discrete variables. Finally, simulation results in the T118-D33-N56 test system and a real-world system in China demonstrate that coordination of transmission, distribution, and gas systems and considering pipeline gas storage capacity can shorten the load restoration time. The proposed solution method also shows good computational performance. [ABSTRACT FROM AUTHOR]