The electricity generation-transmission-utilization system was one of the first examples of a modern integrated energy system. The subsequent rapid growth of such systems is well-known. This approach was overly simplistic in that it promoted the conversion of almost all primary sources of energy into electricity and resulted in the spread of transmission lines and the use of electrical end-use appliances and equipment to meet energy needs. It is now recognized that such an approach suffers serious limitations. The principles of integrated systems based on a combination of energy sources which provide a variety of types of energy appropriate to different tasks are discussed. Mainly renewable, decentralized and locally-available sources are involved in such systems.

Integrated energy systems

With economic development in the world and growing energy demand, the concept of sustainable energy has received more attention from energy planners in different energy sectors. To achieve sustainable energy development (SED), appropriate utilization of all types of sustainable energy resources is vital. One further requirement for this is the integration of various energy systems in the framework of a multi-energy system where all energy system elements have the possibility of synergy with others for minimizing losses and maximizing the utilization of any availabilities. Further requirements for such a highly yet wisely integrated energy system (IES) have recently been specified in the context of smart energy systems (SESs). Smart energy hub (SEH) is introduced as a novel concept that provides a distinguished framework to model SESs. The main challenge for the modeling of SEH is finding the optimal design/sizing and operation strategy of the system components based on the uncertainty of renewable sources, demands, energy market spot prices, etc. Uncertainty modeling assists in reaching a realistic optimal approach in the decision-making process and thus is a promising line of future research in the modeling of SEH. The main aim of this work is to classify and evaluate the existing methods to employ uncertainty in the design, operation, and planning of SEH to reach a better understanding of future challenges in this way. 

A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors

A microgrid scenario that consists of electric vehicle (EV) station, combined heat and power (CHP) co-generation, main power grid, and external natural gas station, as well as thermal energy storage water tank is considered in this paper. By jointly considering the uncertainty of real-time electricity price, electricity and heat demands and EVs’ behaviours, the EVs’ batteries are used as energy storage adjusters to reduce the time-averaged operation cost, which includes energy acquiring cost from main power grid, the natural gas cost for CHP generation and heat only generation. We propose a real-time energy management algorithm for EV based microgrid by adopting Lyapunov stochastic optimization technique which optimizes the microgrid average cost without knowing future price, demands and other system information. Furthermore, our approach can accommodate a wide spectrum of characteristics of EVs, including the independent charging/discharging action, dynamic charging energy limits, and lifetime-guaranteed battery. Lastly, extensive simulations are provided to demonstrate that our proposed algorithm can outperform the other three alternatives.

Real-Time Energy Management for Microgrid With EV Station and CHP Generation

The demographic growth and the irreversible decline of fossil fuel deposits argue for alternative resources to meet energy demand. The main challenge is to make renewable energy sources (RES) and hydrogen carriers work synergistically to minimise waste and increase sustainability. Hybrid renewable energy systems (HRES) tackle this task by integrating RES and other resources to provide energy. Recently, Power-to-X (P2X) has been gaining attention for its versatility in converting hydrogen into different energy carriers. This review provides a comprehensive overview of the HRES literature and the current state of the art, highlighting key features, analysis, and methods. Future research trends are discussed, emphasising the need to integrate other energy carriers, including hydrogen. A survey of the Power-to-X possible uses in HRESs is carried out, describing which Power-to-X technologies belong to HRES state-of-the-art. Power-to-X paths not yet explored are discussed, remarking the benefit and potential uses as a means to increase the reliability of the energy system of each HRES Power-to-X technology integration, highlighting the unexplored paths. In addition, future developments and gaps in the current state of the art according to HRES with Power-to-X are highlighted. Finally, recommendations on hybrid renewable energy systems, including Power-to-X, are highlighted by outlining future research areas. • HRESs scientific literature and current state-of-the-art. • HRES future research trends. • HRES with P2X state-of-the-art. • Current gaps and trends on P2X in HRES integration. 

The role of power-to-X in hybrid renewable energy systems: A comprehensive review

Optimal Dispatching Model of CCHP Type Regional Multi-microgridsConsidering Interactive Power Exchange Among Microgrids andOutput Coordination Among Micro-sources

The energy crisis and increasing concerns about the environment in modern society have fostered the development of the integrated energy system (IES) in smart grid. The energy hub (EH) is a minimum construction of the IES. The chief purpose of this paper is to propose a Lyapunov optimization-based energy management strategy for the energy hub with an energy router. First, this paper describes a configuration of the EH with an energy router and sets the basic operating principles of the energy router. Second, a method is proposed to analyze the energy balance equations of the EH. Furthermore, the problem of energy management is formulated considering the constraints of energy balance equations, energy storage, flexible loads, and other constraints of operation. Finally, energy storage and flexible electric loads are modeled as stochastic processes, and three virtual queues are constructed to relax these constraints. The Lyapunov drift-plus-penalty function is applied to formulate a relaxed form of the energy management problem. Case studies of a single EH and two-connected EHs are performed to test the effectiveness of the proposed strategy, and the results are compared with a greedy algorithm.

Zhen Li

Papers

A Lyapunov Optimization-Based Energy Management Strategy for Energy Hub With Energy Router