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Buildings are typically integrated with multiple distributed energy resources (DERs), enabling them to act as building prosumers engaged in both energy production and consumption. Peer-to-peer (P2P) energy trading among building prosumers is crucial to improve their benefits. However, further exploration is required to balance the benefits between building prosumers and the system operator (e.g., the integrated community energy system (ICES) operator) since they are different entities. In this context, this paper proposes a comprehensive network charge and energy sale pricing scheme for the ICES operator on heterogeneous building prosumers with P2P multi-energy trading. The interaction between the ICES operator and building prosumers is modelled as a bi-level optimization problem that belongs to the hierarchical structure, while considering the heterogeneity of thermal insulation performance of buildings. At the upper level, the ICES operator optimizes the electricity/heat network charge prices and electricity/heat sale prices to maximize its revenue. At the lower level, building prosumers with a parallel structure optimize the schedules including P2P multi-energy trading and buildings' heating loads to minimize their costs. Furthermore, to address the bi-level optimization problem with parallel and hierarchical coupling structures, an accelerated asynchronous distributed algorithm based on alternating direction method of multipliers (ADMM) is developed, integrating a warm start strategy and a dual update accelerated iteration strategy for further improving computational efficiency. Finally, case studies demonstrate that the proposed scheme can effectively benefit both the ICES operator and building prosumers in P2P multi-energy trading at the same time. Meanwhile, the feasibility and effectiveness of the proposed algorithm are validated. • An optimal pricing scheme for ICES operator on building prosumers is proposed. • A bi-level optimization is proposed for ICES operator and prosumers with P2P. • An accelerated asynchronous distributed algorithm based on ADMM is developed. • Benefits of ICES operator and prosumers through several scenarios are analyzed. [ABSTRACT FROM AUTHOR]

Low-carbon buildings (LCBs) are normally equipped with distributed energy resources (DERs) such as photovoltaic (PV) panels and batteries, thereby creating LCB prosumers that both produce and consume energy. Peer-to-peer (P2P) energy sharing among LCB prosumers could bring higher economic benefits for themselves, and facilitate better local power balance for the power grid. To fully harness the benefits of P2P energy sharing for both LCB prosumers and the power grid, a bi-level optimization method for LCB prosumers and the power grid operator is proposed in this paper. The grid operator at the upper level imposes the optimal time-varying network charge to LCB prosumers at the lower level to maximize its profit. And LCB prosumers with the objective of minimizing their costs adjust the schedules including P2P energy sharing and their heating loads to respond to the grid operator's optimal network charge prices. Additionally, to further exploit the energy resources including heating loads in LCBs, the model predictive control (MPC) approach is integrated with the bi-level optimization in the presence of uncertainties. The bi-level optimization belongs to the NP-hard category, making it challenging to solve. To reduce the computational complexity, the bi-level optimization problem is converted to the single-level programming using Karush-Kuhn-Tucker (KKT) conditions. Numerical results illustrate that the bi-level optimization method can obtain a balanced scheduling scheme between the grid operator and LCB prosumers. In addition, incorporating the thermal inertia of building heating loads can provide more operational flexibility for both the grid operator and LCB prosumers. Furthermore, the costs of LCB prosumers based on MPC approach can be reduced with the decrease of forecast error level. • A bi-level optimization for grid operator and LCB prosumers with P2P is developed. • The time-varying pricing strategy for network charge of grid operator is proposed. • The bi-level solution method integrated with MPC approach is investigated. • The utilities of bi-level optimization through comparative scenarios are analyzed. [ABSTRACT FROM AUTHOR]

Pulsed power loads (PPLs) are commonly incorporated in medium voltage dc microgrids on naval vessels. To mitigate their detrimental effects, dedicated energy storage systems can be installed and their converters need to have excellent disturbance rejection capability. To facilitate this objective, a moving-discretized-control-set model-predictive-control (MDCS-MPC) is proposed in this letter and applied on a dual-active-bridge converter. Fixed switching frequency is maintained, enabling easy passive components design. The proposed MDCS-MPC has a small number of calculating points in each switching period, which enables the implementation in standard commercial control platforms. The operating principle of the MDCS-MPC is introduced in development of a cost function that, on one hand, provides stiff voltage regulation; on the other hand, minimizes transformer current stress online. Theoretical claims are verified on a 20 kHz 1 kW dual active bridge. [ABSTRACT FROM AUTHOR]

Abstract: With the rapid development of phase measurement unit and wide area measurement system (PMU/WAMS), power system coordinated stability control has been paid more and more attention. Since there is obvious time delay in WAMS measurement, it is important to properly evaluate the impact of time delays on power system stability analysis and controller design. In this paper, influence of time delay on power system small signal stability region is deeply investigated. Small signal stability of differential algebraic equation with time delay is first reviewed as the necessary theoretical background. Then an optimal-based algorithm is given to trace boundaries of the small signal stability region with considering the time delay. Finally, two simple systems are employed to do some verification studies. It is found that time delay has significant influence to the boundary of the small signal stability region, especially when the time lag is large. This paper is helpful to properly consider the effect of time delay in power system controller design and small signal stability studies. [Copyright &y& Elsevier]

• A multi-level overload relief method for transmission network is proposed. • The proposed method can capitalize on the capability from the ADN for overload relief in transmission network. • An interactive mechanism between the transmission network and ADN is proposed. With the fast development of technologies of renewable generations and distributed energy resources, the distribution grids become more and more active, and the coordinated transmission and distribution management (CTDM) becomes more important. Under the CTDM framework, this paper proposes a multi-level overload relief method for transmission network using the capability from an active distribution network (ADN). When an overload event occurs at the transmission network, an appropriate operational scheme for ADN is selected by the proposed multi-level method. Then, the ADN takes the decided operational scheme and adjusts its operational status (i.e., reconfiguring its network topology, transferring loads to Microgrids and shedding the controllable loads) to contribute to load curtailment from the ADN side and further alleviate overload in the transmission network. Numerical case studies show that the proposed method can alleviate the overload of transmission network and maintain the normal operation of the ADN, which demonstrates a promising application for CTDM. [ABSTRACT FROM AUTHOR]

The game relationship between the Energy Server (ES) and the Energy Consumer (EC) in the Integrated Community Energy System (ICES) can change the energy supply and consumption behaviors of both participants, and affect the economy of the ICES planning scheme. This paper proposes a bi-level model to address a joint master-slave planning-operation problem of the ICES. Firstly, the revenue models of the ES and EC in the ICES is established. Secondly, a bi-level planning model based on Stackelberg Game for the ICES is proposed. In the upper level, a joint optimal planning model of energy conversion devices and energy prices is built and used by the ES (game leader) to maximize its profit. In the lower level, an optimal energy consuming strategy is proposed for the EC (game follower) to minimize its energy bill. The Karush-Kuhn-Tucker (KKT) conditions are utilized to convert the bi-level planning problem to a single-level mathematical program with equilibrium constraints (MPEC). A typical ICES is employed as a test system to illustrate the effectiveness of the proposed bi-level planning approach, and the results show that the proposed approach can reduce the investment cost of ES while ensuring the interests of EC. • A bi-level planning method for ICES based on Stackelberg game is proposed. • Revenue models of the ES and the EC are established. • A single level MPEC is derived by using the KKT conditions transformation. • An actual ICES shows the effectiveness of the proposed bi-level planning method. [ABSTRACT FROM AUTHOR]

• A four-terminal interconnection scheme for the hybrid AC/DC microgrid is proposed. • Higher flexibility and a higher tolerance for unequal power distribution are obtained. • An improved energy control method is proposed to balance cell capacitor voltages. • The AC current component is maintained zero on the MVDC trans-mission lines. • The symmetry of the AC currents is guaranteed with this control method. With the large-scale integration of the distribution generations (DGs) and the increasing medium-voltage and low-voltage DC power demands, multi-terminal hybrid AC/DC microgrid has drawn great attention from researchers around the world. In order to reduce the number of power conversion stages and meet DC transmission demands under different DC voltage levels, this paper proposes a four-terminal interconnection scheme of the hybrid AC/DC microgrid, connecting one medium-voltage AC (MVAC) terminal, one medium-voltage DC (MVDC) terminal and two low-voltage DC (LVDC) terminals. The proposed interconnection scheme includes a modular multilevel converter (MMC) as the main interlinking converter of the MVAC grid and MVDC microgrid, and a series of dual active bridges (DAB) converters as two isolated LV DC microgrid interfaces. It has more flexibility for power supplies, especially MVDC transmission, and a more robust tolerance for unequal power distribution between the two LVDC Microgrids. To realize the DC capacitor voltage balancing control, an improved energy control method is proposed in this paper. The proposed method keeps DC capacitor voltage balance and AC current zero on the MVDC transmission lines, which contributes to the stability of the MVDC microgrid. In addition, the symmetry of the AC currents is also guaranteed with this control method. Validation results of a four-terminal hybrid AC/DC microgrid verify the effectiveness of the proposed microgrid and control scheme. [ABSTRACT FROM AUTHOR]

• An overview understanding of local flexibility markets (LFMs) is provided. • A comprehensive survey on formulations and clearing methods of LFMs are conducted. • Studies for solving operational issues of distribution systems are reviewed. • Deepen the understanding of LFMs in helping the operations of distribution systems. With high penetration of renewable generation and distributed energy resources, distribution systems are facing new operational challenges due to their intermittency and uncertainty. To cope with these challenges, distribution system operators are seeking for market tools to enable more active system management and control using flexibility. Local flexibility markets provide opportunities to trade flexibility among distribution system operators and other participants (e.g., aggregators) in an economically efficient way. Studies have been carried out to define the concepts, design the mechanisms and formulate the market clearing methods of local flexibility markets in the literature. Therefore, there is a need to classify and organize the literature on potential designs and market clearing methods of local flexibility markets. This paper reviews local flexibility markets, which are currently being discussed and designed to provide trading platforms for local participants, including distribution system operators and aggregators. Starting with a survey on the concepts and definitions of local flexibility markets, we summarize the key elements, technologies and participants of local flexibility markets. Afterwards the formulations of local flexibility markets and the solution methods for market clearing are reviewed, based on which future research directions and challenges are suggested in the last section of this paper. [ABSTRACT FROM AUTHOR]

Collaboration between transmission and distribution system operators (TSOs and DSOs) is crucial to improve power supply reliability during a massive blackout. However, these two systems usually operate separately in reality. To coordinate them, a new fully parallel decentralized TSO + DSO service restoration (D-TDSR) scheme is proposed in this paper. Based on analytical target cascading (ATC) method, the proposed D-TDSR is able to formulate the local restoration model for each TSO and DSO by decomposing shared boundary information in an iterative process. By introducing the diagonal quadratic approximation in ATC, all local restoration models are solved in a fully parallel manner with no need for a central coordinator. This parallel implementation increases the computation efficiency of decentralized restoration procedure. Furthermore, to enhance the ability of TSO and DSOs to support each other, the potential benefits of flexible regulation in DSO, including soft open points and network reconfiguration, are fully exploited, thus improving critical load restoration speed, and reducing voltage deviations. The effectiveness of the proposed D-TDSR is validated using an IEEE standard test system. • A decentralized load restoration for transmission and distribution system is proposed. • SOP flexibility is fully exploited to improve load restoration level and speed. • The fully parallel restoration procedure is proposed to reduce the computation time of each iteration. • The warm start mode is developed, which further accelerates the convergence speed of the restoration model. [ABSTRACT FROM AUTHOR]

The technology development of power electronics and battery empowers electric vehicles as practical approaches for the compensation of instantaneous power flow imbalance. To utilize the response capability of distributed vehicles and stabilize the grid frequency caused by instant power mismatch, a process model hybridizing the data-driven and conventional modes is designed for the electrical-grid-electric-vehicle system. Due to the real-time variations of power system, electric vehicles, and renewable energies, the hybrid process model directly interacts with the system feedback to remove the sophisticated model establishment, which effectively establishes the mapping relationship between system states and intelligently processing demands. Based on the hybrid process model, the smart policy network with an adversarial mechanism is then developed to enhance the model behavior. To fulfill the continuous action requirement and speed up the policy convergence, a proximal optimization strategy is further introduced to adjust hyperparameters through a stochastic ratio automatically. Bridging the huge volume of real-time dynamics and the action domain, the sufficient utilization of various operation states is achieved in the proposed process model and policy network, which notably detects the optimal operation point and reduces the power flow imbalance. The developed hybrid process model and smart policy network are validated through an electrical-grid-electric-vehicle system by comprehensive studies from four aspects of the process performance, generalization, robustness, and efficiency. Compared with the linear and naive hybrid process methods, 3.95 times superior integration performance and the improved evolution process of 64.5% improvement are both demonstrated as well as the robustness facing various circumstances. • A hybrid process model is developed to evolve the vehicle-grid process center. • A smart policy network is deployed to handle large-scale data of electric vehicles. • An adversarial neural network is introduced to assist the effective policy update. • Proximal optimization is employed for the network gradient updating. • Effectiveness, generalization, robustness, efficiency are verified facing imbalance. [ABSTRACT FROM AUTHOR]

• A P2P trading strategy is proposed for the energy balance service provider (EBSP). • The EBSP market power and market elasticity are considered in optimized pricing. • The EBSP could enhance the energy resource allocation ability of the P2P market. • The EBSP could obtain profit without harming the overall benefit of the microgrid. The peer-to-peer (P2P) energy trading technology can effectively promote the mutual exchange and complementation of energy among diversified prosumers in the community microgrid. To further improve the energy resource allocation performance of the P2P energy trading, an energy balance service provider (EBSP) can be involved in the market. EBSP is an independent commercial entity configured with high-capacity energy storage systems (ESS) or auxiliary power sources, participating in the P2P market for profit. The energy shifting ability of EBSP can further improve the overall benefit of the microgrid. However, the scale effect endows the EBSP with comparatively strong market power, which may impose influence on the equilibrium of the P2P market. From the perspective of EBSP, the P2P market can be regarded as a market with elasticity. In the existing researches on optimized pricing and trading strategies of the P2P market, such a characteristic was not fully considered, which may have negative impacts on the economic profit of the EBSP and the overall benefit of the microgrid. Therefore, a P2P energy trading strategy for EBSP considering market elasticity is proposed in this paper. A market equilibrium model for the community microgrid with EBSP is first established, which reflects the elasticity of the market. Then, an optimized pricing model and trading strategy are established and solved to maximize the EBSP's profit. Numerical results show that the proposed method can improve the profit of EBSP, meanwhile reducing the energy dispatching cost of prosumers, achieving peak load shifting and renewable energy self-consumption of the community microgrid. [ABSTRACT FROM AUTHOR]

• A transmission system resilience assessment approach is proposed for ice disasters. • Quantify resilience indices are defined from system and component perspectives. • A full-time scale resilience enhancement framework against ice disasters is proposed. A full-time scale resilience enhancement framework is proposed for power transmission system to improve its resistance against ice disasters. First, system resilience indices are developed to quantify the impacts of ice disasters on the transmission system. Next, the system resilience indices are broken down into each component, so as to locate the weak links of the system under ice disasters. On this basis, a full-time scale resilience enhancement framework is proposed involving pre-failure, during disaster and post-failure period of the ice disaster. In the pre-failure period, prevention strategies can be applied to avoid severe losses. In the during disaster period, deicing sequence can be optimal determined to delay the outage. In the post-failure period, maintenance measures of failed components can be optimized to recover the power supply as effective as possible. Case studies on the IEEE RTS-79 test system have been used to validate the effectiveness and practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

• A distributed Peer-to-Peer (P2P) energy transaction method is proposed. • A bi-level optimal transaction model is proposed for autonomous prosumers. • A real-time double auction market with continuous bidding is established. • The proposed method is effective and achieved privacy preservation and robustness. As massive integration of Distributed Energy Resources (DERs), the role of end-users in the Urban Community Microgrid System (UCMS) has transformed from traditional consumers into prosumers with capabilities of both energy production and consumption. The exchange of energy between autonomous microgrid prosumers can be achieved with the introduction of Peer-to-Peer (P2P) energy transaction, promoting the efficient allocation of energy in the UCMS. However, the existing centralized P2P energy transaction approaches require microgrid transaction brokers to obtain prosumers' private data, including energy resource configuration, operation status, and energy production/consumption schedule. With the enhancement of prosumers' awareness of privacy protection, it will be increasingly more difficult for the brokers to obtain such private data in practical application scenarios, resulting in obstacles on the implementation of such centralized approach. Thus, a novel distributed P2P energy transaction method based on the double auction market is proposed in this paper. Prosumers first generate the information of energy supply and demand autonomously utilizing distributed energy management model, then set the price targeting profit maximization, and finally initiate P2P energy transaction mutually in the double auction energy market. Compared with the existing centralized approaches, the method proposed in this paper can achieve the coordination and complementarity of energy in the UCMS, promoting economic benefit, energy self-sufficiency, and renewable energy self-consumption without sacrificing privacy preservation and robustness. [ABSTRACT FROM AUTHOR]