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The thermal inertia of a building envelope endows a building with a heat storage capability, introducing scheduling flexibility to a building energy microgrid (BEM). The flexibility is usually modelled as virtual energy storage (VES) and used to optimize the operation of BEMs to reduce electricity costs. However, the VES capacity is impacted by and varies with variations in indoor/outdoor temperature. If only the building envelope's effect on heat transfer is considered, without proper quantification of scheduling flexibility provided by the building envelope, the scheduling scheme (especially VES charging/discharging schemes) will deviate from the actual VES operating conditions, which may affect the thermal comfort of individuals in buildings or bring high electricity costs. In this paper, a time‐varying building VES model (TVES) with three time‐varying parameters (virtual electric capacity (VEC), state of charge (SOC), and charge and discharge power) is proposed to quantify the electricity storage capability of the VES at different time periods for participating in operation of the BEM. Based on the TVES, a day‐ahead optimal scheduling strategy is developed for the BEM to simultaneously reduce the electricity cost and guarantee the user's thermal comfort, where the proposed time‐varying parameters of TVES are taken as constraints in the optimization. Numerical studies verify the effectiveness of the proposed TVES and optimal scheduling strategy. [ABSTRACT FROM AUTHOR]

The energy storage system is an important part of the energy system. Lithium-ion batteries have been widely used in energy storage systems because of their high energy density and long life. However, the temperature is still the key factor hindering the further development of lithium-ion battery energy storage systems. Both low temperature and high temperature will reduce the life and safety of lithium-ion batteries. In actual operation, the core temperature and the surface temperature of the lithium-ion battery energy storage system may have a large temperature difference. However, only the surface temperature of the lithium-ion battery energy storage system can be easily measured. The estimation method of the core temperature, which can better reflect the operation condition of the lithium-ion battery energy storage system, has not been commercialized. To secure the thermal safety of the energy storage system, a multi-step ahead thermal warning network for the energy storage system based on the core temperature detection is developed in this paper. The thermal warning network utilizes the measurement difference and an integrated long and short-term memory network to process the input time series. This thermal early warning network takes the core temperature of the energy storage system as the judgment criterion of early warning and can provide a warning signal in multi-step in advance. This detection network can use real-time measurement to predict whether the core temperature of the lithium-ion battery energy storage system will reach a critical value in the following time window. And the output of the established warning network model directly determines whether or not an early emergency signal should be sent out. In the end, the accuracy and effectiveness of the model are verified by numerous testing. [ABSTRACT FROM AUTHOR]

• A T-VESS is considered in real time P2P energy trading. • A two-stage P2P energy trading method is proposed based on MPC. • Trading actions are implemented considering multiple trading preference grades. • The proposed method is effective and utilities for prosumers are much improved. With the increasing penetration of distributed energy resources (DER) in the electric power system, Peer-to-Peer (P2P) energy trading has become a promising paradigm for future electric power systems. Building thermal load, which is an important demand side resource, should be considered carefully in the design of a P2P trading method. In this paper, we investigate the application of building thermal energy storage capability in P2P energy trading. We aggregate and model building thermal loads as a virtual energy storage and derive a time-varying virtual energy storage system (T-VESS) model to quantify the flexibility of a building. Key parameters of T-VESS, including charging/discharging rate, energy capacity, and state of charge (SOC), are analyzed so that T-VESS can be embedded in the building prosumer model to participate effectively in electricity-oriented P2P energy trading. We propose a real time P2P energy trading method of prosumers based on model predictive control (MPC). This method consists of an energy supply and demand quantification stage and a transaction price optimization stage, which can effectively capture the time-varying nature of T-VESS. To preserve the trading preference for prosumers, we propose a distributed P2P energy trading actions implementation method based on the continuous double auction (CDA) considering multiple trading preference grades. Numerical results demonstrate that the proposed P2P energy trading method considering T-VESS can reduce the operational cost of prosumers by 3.7%, while also promoting the local integration of renewable energy by 3.1%. Furthermore, compared to existing P2P trading methods considering single preference grade, the proposed method greatly enhances the utilities of both individual prosumers and the overall community. [ABSTRACT FROM AUTHOR]

• A dynamic energy hub model considers varying energy conversion efficiencies. • The dependency between efficiency and load rate is included in the model. • A double-layer planning method is designed based on the model. • A case study demonstrates the effectiveness and superiority of this study. The energy hub is considered a unit where multiple energy carriers can be converted, conditioned, and stored, thereby providing the functions of input, output, conversion, and storage of multiple energy carriers using a defined coupling matrix. Thus, the energy hub is widely used in the planning and operation of integrated energy systems. However, the coupling factors (or the efficiencies of the energy conversion devices) in the energy hub coupling matrix are usually assumed to be constant for the sake of simplicity, which may result in unreasonable planning and operation schemes for the integrated energy system. For this reason, an integrated energy system planning method at the community level that considers varying coupling factors was developed in this study. First, a dynamic energy hub model was developed, where an efficiency correction model was built to determine the time-varying coupling factors with the variation in load rate. On this basis, a double-layer planning model was built to determine the optimal planning and operation schemes for the integrated community energy system. A typical integrated community energy system was employed as a test system to illustrate the effectiveness of the planning method, and the results were analysed. [ABSTRACT FROM AUTHOR]

The increasing complexities of hybrid energy Microgrid (H-Microgrid) integrated with renewable generations, dispatchable distribution generators (DGs) and low-carbon buildings require more intelligent dispatch method. The building sector occupies the main body of the energy consumption, which represents a major potential contributor for reducing the daily operating cost of the H-Microgrid. In this paper, a building based virtual energy storage system (VESS) model was developed by utilizing the heat storage capability of the building. Then, a dynamic economic dispatch (DED) model of the H-Microgrid considering the VESS was developed. Finally, the VESS was integrated into the DED model of the H-Microgrid for daily operating cost reduction. The indoor temperature of the building was adjusted within the customer temperature comfort range to manage the charging/discharging power of the VESS. Numerical studies demonstrate that the proposed DED method can make full use of the available capacity of VESS to reduce the daily operating cost, and guarantee the customer temperature comfort level at the same time. [ABSTRACT FROM AUTHOR]

In order to pursue the low-carbon development around the world, a large scale of renewable generation will be connected to the power systems. Take the Great Britain (GB) as an example, the GB power system has a large wind energy integration potential. The intermittency of wind generation will have great impact on the system frequency stability. Electric vehicles (EVs) have a crucial role in decarbonizing the transport sector. To increase the utilization of wind energy, EVs are suggested to provide frequency response service to the power system due to their quick power reaction characteristic. This paper proposes a general dynamic EV frequency control strategy considering the travelling behavior of the EV users. A droop control method is used to regulate the EV charging/discharging power according to the frequency signal. A Forced-Charge Boundary (FCB) and a Forced-Charge Area (FCA) are proposed to guarantee sufficient energy in the EV battery for user’s travel at the plug-out time. A dynamic Virtual Energy Storage System (VESS) is developed to evaluate the frequency response capacity of the EV clusters. In the case study, the model of the GB power system is used to investigate the frequency control effect of the control strategy. The simulation results show that the proposed strategy provides effective EV frequency response to the power system and thus is able to facilitate the integration of wind energy. [ABSTRACT FROM AUTHOR]

• A belt conveyor system based virtual energy storage model was developed. • An optimal scheduling model of belt conveyor integrated with virtual energy storage was developed. • The charging and discharging characteristics of the virtual energy storage were analyzed. • Influence factor like arrival time of trains and ramp rate of the belt speed were analyzed. In order to reduce the high electricity cost of the belt conveyor system in a coal mine, a virtual energy storage model of the belt conveyor system is proposed based on the coal storage ability of silo. Through coordinated control of belt speed, feed rate, silo load rate and arrival time of the train, the virtual energy storage ability of silo is utilized to realize the power balance considering distributed generations in different period in response to the time-varying electricity price. The case study indicates that the optimal scheduling method in this paper can effectively reduce the electricity cost of the belt conveyor by 61.29%, and improve the power consumption level of the distributed generations, which can help realize the green and effective operation of the belt conveyor system. [ABSTRACT FROM AUTHOR]