Optimal day‐ahead scheduling of multiple integrated energy systems considering integrated demand response, cooperative game and virtual energy storage

Abstract

As the physical carrier of the Energy Internet, integrated energy system (IES) is a future development trend in the energy field, and the optimal scheduling of IES for improving energy utilisation efficiency has become a hot topic. An optimal day‐ahead scheduling model of multiple IESs considering integrated demand response (IDR), cooperative game and virtual energy storage (VES) is proposed innovatively in this study to maximise the overall benefits of the cooperative alliance. IDR and VES are considered together for the first time to optimise the internal scheduling of each IES, where IDR can enhance the response potential on the demand side and VES can improve the scheduling flexibility of IES. Cooperative game theory is utilised to process the energy trading mechanism among multiple IESs and the Nash bargaining method is utilised to solve the cooperative game problem and obtain a fair and Pareto‐optimal energy trading strategy. The case study shows that the proposed model effectively improves the operating benefits and the renewable energy penetration levels of each IES.

Optimal BRA based electric demand prediction strategy considering instance‐based learning of the forecast factors

“…Architecture of neural network illustrating inputs, hidden nodes, and predicted output which guarantees that the total probability is 1. Assuming the weights and data probability distributions as Gaussian, the probability of the data given the weight w can be expressed by Equation (10) as…”

“…Long-term LF is commonly used to install new distributed generation sources, storage systems, and power system planning. 10 But, LF is a challenging task due to multiple factors affecting electrical demand, such as weather uncertainties, ACs loads in buildings, and randomness in energy usage of buildings inhabitants. 11 Regardless of the LF methodology and the prediction time horizon, some factors significantly impact the accuracy and efficiency of the LF approach adopted and should be incorporated into the model.…”

“…Both short and medium‐term LF play a vital role in the operation of generation units, facilitating the RES's integration and promoting more effective demand response (DR) actions. Long‐term LF is commonly used to install new distributed generation sources, storage systems, and power system planning 10 . But, LF is a challenging task due to multiple factors affecting electrical demand, such as weather uncertainties, ACs loads in buildings, and randomness in energy usage of buildings inhabitants 11 .…”

Optimal Dispatching of Integrated Electricity and Heating System with Multiple Functional Areas Considering Heat Network Flow Regulation

“…During hot water transmission, the exchanged heat with the outside will result in heat loss and the temperature of WM K flowing out of the pipe will decrease, as shown in Equations ( 12) and ( 13) [8].…”

“…With the application and development of combined heat and power (CHP) technology, the coupling effect of electrical energy and thermal energy has been gradually enhanced [4,5]. The interaction between the power system and the thermal system in IEHS plays an important role in facilitating the cost-effective transition to a low-carbon energy system with high penetration of renewable generation [6][7][8]. At present, it is urgent to establish a more perfect electro-thermal co-ordination dispatching mechanism, which can satisfy the requirements of heating load, reduce the operation cost of the system, and reduce the waste of wind and photovoltaic energy at the same time.…”