Integrated Energy Network Research Articles

Maximizing profitability in integrated energy markets: A novel framework for multi-faceted energy trading

The emergence of Integrated Energy Systems (IESs) has shifted energy management from traditional electricity paradigms to a more diverse approach involving electricity, thermal energy, and natural gas. This study introduces a framework for an Integrated Energy Network (IEN) that enables simultaneous trading across these interconnected markets. The objective is to maximize the profitability of integrated energy companies by optimizing energy trading strategies. The proposed business strategy incorporates integrated load response, addressing constraints within electric distribution systems, heating networks, and natural gas pipelines. A three-stage process is used: information sharing in the unified energy market, energy conversion in hubs, and flexible load planning in the retail market. Flexible loads are categorized as displaceable, reducible, or transformable. A Conditional Value-at-Risk (CVaR) mean-variance model addresses market price volatility. Simulations on a test system validate the model, demonstrating its effectiveness in improving profitability and operational efficiency for integrated energy companies.

Low-Carbon Oriented Collaborative Planning of Electricity-Hydrogen-Gas-Transportation Integrated System Considering Hydrogen Vehicles

Under the pressures of the energy crisis and climate change, hydrogen vehicles (HVs) have experienced significant growth in many countries recently. To promote the penetration of HVs, a low-carbon collaborative planning model based on carbon emission flow (CEF) and a modified user equilibrium theory is proposed for the electricity-hydrogen-gas-transportation integrated system. New carbon capture and storage equipment, steam methane reforming (SMR) equipment, and renewable energy equipment are planned in the model, which collaborates closely to provide green hydrogen. The proposed model considers the influence of different hydrogen production methods (electrolysis and SMR) on carbon emission reduction in the integrated energy network. Aiming to account for carbon emission from the consumption perspective, the emission caps are transferred from the energy supply side to the hydrogen production station side based on the CEF model. Additionally, the proposed modified user equilibrium model considering HV cruising range and hydrogen refueling station's location is innovatively utilized to solve the HV traffic flow assignment problem and evaluate the effectiveness of candidate roads in reducing congestion time. Overall, the total cost including equipment cost, energy consumption cost, and travel time cost is minimized to obtain the optimal integrated system planning results. Simulation results demonstrate that the proposed model is effective in reducing the carbon emissions and traffic time for the integrated network considering HV demands.

Robust Bilevel Optimal Dispatch of Park Integrated Energy System Considering Renewable Energy Uncertainty

This paper focuses on optimizing the park integrated energy system (PIES) operation, and a robust bilevel optimal dispatch is proposed. Firstly, the robust uncertainty set is constructed based on the K-means++ algorithm to solve the uncertainty of renewable energy sources output in PIES. Then, the bi-level dispatch model is proposed, with the operator as the leader and consumers as the follower. The upper model establishes an electricity-heat-gas integrated energy network, and the lower model considers the demand response of consumers. Optimizing the pricing strategies of energy sources to determine the output of each energy conversion equipment and the demand response plan. Moreover, analyzing the decision-making process of the robust bi-level model and the solution method is given. Finally, case studies show that the proposed dispatch model can increase operator profits and reduce consumers’ energy costs. The in-sample and out-of-sample simulations demonstrate that the proposed ellipsoid uncertainty set possesses high compactness, good robustness, and low conservatism.

Emerging Trends and Approaches for Designing Net-Zero Low-Carbon Integrated Energy Networks: A Review of Current Practices

Emerging Trends and Approaches for Designing Net-Zero Low-Carbon Integrated Energy Networks: A Review of Current Practices

Risk-Oriented Operational Model for Fully Renewable Cooperative Prosumers in a Modern Water-Energy Nexus Structure

The day-by-day increment in the demand for diverse types of energy together with the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -based climate concerns has intensified the need for innovative decarbonization plans leading the energy sector to produce clean, cost-effective, and reliable multi-energy. Herein, inevitable water and power interactions unlock significant benefits for the integrated energy network in the form of water-energy nexus models. In this work, a holistic water-energy nexus model is developed for the operation of cooperative prosumers equipped with 100% renewables in the modern interconnected energy structure. The model is empowered by the transactive energy technology to allow prosumers to cooperatively share multi-energy with each other for reliably serving power and water in a deregulated environment. The proposed model also benefits from hydrogen-based energy conversion units that not only improve the flexibility of prosumers in reliable energy supply but also increase their economic achievements by selling the produced gas to the gas grid. As prosumers are targeted for fully clean energy production, their contributions in the energy interactions are under the high level of risks associated with renewables' intermittences. Due to this, a risk-averse stochastic operational model is proposed that enables the decision-maker to adopt optimal strategies against the uncertain fluctuations in the system. The effectiveness of the proposed model is examined considering prosumers located in Chicago, USA. According to the obtained results, the model can affordably facilitate the realization of Chicago's plans for achieving the goal of equipping with 100% renewable energy sources for a fully clean multi-energy generation.

Distributed coordinated planning for cross-border energy system: An ADMM-based decentralized approach

Cross-border interconnection and trade (CBIT) can effectively leverage the differences in resource endowments and energy demand between regions and countries, making cross-border cooperation a potential option for addressing the high penetration of variable renewable energy. This paper presents centralized and decentralized planning approaches for the cross-border energy transmission expansion planning (TEP) problem. The proposed centralized mixed-integer second-order cone programming (MISOCP) model collaboratively optimizes the expansion of national energy networks, while considering the impact of CBIT. To protect the privacy of energy data in each country, the alternating direction method of multipliers (ADMM) algorithm is extended to decompose the centralized optimization formulation into mutually independent sub-optimization issues, and adaptively adjust the penalty parameters and Lagrangian multipliers to improve convergence. This study also quantifies the effect of cross-border cooperation in such co-expansion problems as a comparative consideration. Numerical simulations on the modified cross-border integrated energy network validates the correctness and effectiveness of the proposed model and solution methodology. The results show that cross-border cooperation can reduce a country's internal energy network congestion, thus postponing the expansion investment decisions. It also shows that the distributed coordinated planning is more efficient in terms of lower cost and renewable generation curtailment that than independent optimization method. Therefore, cross-border collaboration brings economic, environmental, and renewable integration benefits to interconnected countries.

Electric-Gas Integrated Energy Dispatch Based on Multi-ob jective Gray Wolf Algorithm

With the development of the energy Internet, the integrated energy network of electricity-gas interconnection has become an important research object of energy optimization. To improve the energy absorption capacity and energy utilization efficiency of renewable energy in a regional integrated energy network, a comprehensive energy multi-objective optimization model containing the power to gas (P2G) is proposed in this paper. The model considers the two objectives of pollutant emission and system operating cost, and the model is solved by the Multi-objective Grey Wolf Optimizer (MOGWO). The example shows that a P2G device can improve energy efficiency

Economic Dispatch of Combined Heat and Power Plant Units within Energy Network Integrated with Wind Power Plant

Cogeneration, also known as a combined heat and power (CHP) system, produces both power and heat simultaneously. It reduces the operating costs and emissions by utilising waste heat from steam turbines and contributes to incapacitating the intermittency of renewable energy. The CHP-economic dispatch (CHP-ED) is needed to overcome the load dynamics as well as renewable intermittency. In this work, a CHP system connected with a wind power plant is considered for analysing the CHPED within a typical power system area. This study examines, the CHPED with and without a wind integrated energy network. The main objective of this work is to minimise the total operating cost, while meeting the generators’ constraints and prioritising the wind power output. The feasible operating region, valve point loading impact, and prohibited working regions of the CHP plants are taken while finding a CHPED solution with an integrated wind turbine. To find a CHPED solution, an optimisation algorithm was applied and the algorithm was based on selecting the best and worst scenarios. A typical 48-unit structure was used for validating the considered technique’s success for CHPED with/without a wind power plant. In our investigation, we found that operational costs were significantly reduced with a wind energy system. The presented methodology will be useful for the CHPED process of the decentralised CHP units for promoting further integration of the wind turbines and other distributed clean energy resources.

Book Reviews [6 books reviewed

The following six books are reviewed: Gas Insulated Substations, 2nd Edition (Koch, H.J; 2022; Digital Twin Driven Service (Tao, F., et al; 2022); Space Micropropulsion for Nanosatellites—Progress, Challenges and Future (Cheah, K.H.; 2022); Bismuth-Based Materials for Environmental Remediation (Nayak, A.K.;2022); Technologies for Integrated Energy Systems and Networks (Graditi, G. and Di Somma, M.;2022); and Essentials of Semiconductor Device Physics (Martins, E.R.; 2022).

Chance-constrained optimization of distributed power and heat storage in integrated energy networks

Energy storage is widely recognized as an effective alternative to match the instantaneous imbalance between distributed renewable energy sources and loads. However, suitable installation sites and capacities are necessarily determined in integrated energy networks. This paper constructs a two-layer optimization model of integrated power and heat networks to obtain the optimal installation nodes and capacities of electric energy storage (EES) and thermal energy storage (TES) units. In the optimization model, the interchange of power to heat with storage units is collaborated to unitize distributed renewable energy sources and decrease comprehensive costs, including investment cost of storage units and operation cost. A chance-constrained optimization model is proposed to transform the uncertain variables of electric and heat loads into a deterministic optimization problem. The impacts of confidence levels involved in load probability distributions on the optimal nodes and capacities are analyzed. The results demonstrate that the optimal installation nodes are determined by the distributions of distributed power sources and load ratios in networks. The increased confidence level globally raises the optimal installation capacities of EES and TES. When the confidence level increases from 0.50 to 0.99, the utilization rate of wind power increases by 3.91 %, whereas the comprehensive cost increases by 22.34 %. The hybrid integrations of EES and TES consume more uncertain renewable power and improve the economic performances by the interchange of power to heat.

Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks

The unbalance between the renewable energy sources and user loads reduces the performance improvement of regional integrated energy systems (RIES), in which the multi-energy storage system with battery and heat tank is necessarily integrated. This paper aims to optimize the sites and capacities of multi-energy storage systems in the RIES. A RIES model including renewable wind power, power distribution network, district heating network, multi-energy storage system, and heat pump to convert electricity to heat is constructed. An optimization method combining a mixed-integer nonlinear programming optimization model is proposed to minimize the comprehensive cost of RIES. The second-order cone relaxation method performs convex relaxation of the power flow constraints, and the district heat network is operated under a constant-flow-variable-temperature strategy. The original optimization model is transformed into a mixed-integer second-order cone programming problem to solve. Three solution methods, including enumeration method, improved enumeration method and genetic algorithm, are employed to determine the optimum installation locations, and they are compared in computation time and efficiency. The results demonstrate that the distributed hybrid integration of electricity and thermal energy storages improves the RIES economy by collaborating the power and heat balances and reducing the purchased electricity from the grid. By integrating the hybrid storage system, the curtailed wind is reduced by 53.9%, and the economy is improved by 13.4%.

Dispatch optimization of electricity-gas regional integrated energy network considering carbon trading

Aiming at the scheduling optimization problem of the regional electrical integrated energy network under the background of the dual carbon target strategy, on the premise of ensuring the balance and stability of the IIES energy side supply, an optimization solution method for the regional electrical-gas integrated energy network scheduling considering carbon trading was proposed. Based on the priority model of building multi-energy equipment, and taking the minimum sum of the output cost of energy production, the cost of energy conversion, and the carbon transaction cost caused by net carbon emissions as the objective function, the daily optimal scheduling of the regional electrical integrated energy network was established. The model realized the optimal solution of the output value of different energy forms. Utilizing simulation technology, the objective function values of the unit carbon tax price of 8.32$/t, 24.79$/t, and 46.94$/t under the specific scenario of IIES were discussed. The scenario with the optimal objective function (unit carbon tax price of 24.79$/t) was further compared. In addition, the real-time output value of multi-energy equipment was analyzed when the network scheduling optimization was optimized.

Identification of critical nodes for the Integrated Energy Systems based on complex networks and unified energy flows

As the scale of the Integrated Energy System network continues to expand and the coupling and conversion of multiple energy flows deepens, the system becomes more complex and vulnerable, which poses new challenges to the stability of the system structure and the safety of its operation. Identifying the key nodes of the Integrated Energy System is the key to improve the stability and security of the system. In order to comprehensively analyze the node attributes in the integrated energy network, complex network theory and unified energy flow theory are applied to the static topology and dynamic operation state analysis of the Integrated Energy System, and the key node identification method of the Integrated Energy System is proposed from the attributes of node location information, global information and the impact on nodes during operation. Finally, simulation experiments are conducted with a typical Integrated Energy System to verify the effectiveness and superiority of the identification method proposed in this paper.

A Novel Stochastic Model for Hourly Electricity Load Profile Analysis of Rural Districts in Fujian, China

Renewable energy is important for achieving carbon neutralization. However, power generation from renewable energy sources can be uncertain and uncontrollable. Therefore, understanding the features of energy demand is pivotal for integrating renewable energy sources and storage systems within the entire energy network. Traditional load profiles are depicted by fixed typical load curves, which cannot support detailed dynamic simulations of annual hourly electricity consumption. Here, a novel stochastic model for hourly electricity load profile analysis is proposed. A clustering-based model of hourly load was constructed to depict load profiles of typical days, while a non-linear regression method determined the temperature-related factors within annual daily load consumptions, based on which a stochastic simulation model was established for hourly electricity load profiles. The model’s performance was tested with electricity data of rural districts in Fujian Province, China. The proposed model achieved a coefficient of variation of the mean absolute error of 15.7%, which was significantly lower than that of the traditional model. Further, a simplified case was employed to analyze the application of the proposed stochastic model in the design of energy storage systems. The proposed method enables the optimal design of integrated energy networks with renewable energy sources and energy storage systems.

Multi-objective synergy planning for regional integrated energy stations and networks considering energy interaction and equipment selection

Regional integrated energy system (RIES) contains multiple energy coupling equipment and differential energy demand, which demonstrates that establishing a complete source-grid-load-storage energy supply chain is conducive to renewable energy consumption, and improves RIES economy and energy utilization efficiency. This paper proposes a synergy planning approach for RIES energy stations (ESs) and pipeline networks (PNs) with energy interaction and equipment selection. First, this paper analyzes a RIES structure involving equipment selection and energy interaction, and describes the problem to be addressed in this paper. Secondly, ten equipment output models are built based on energy coupling methods, and a RIES synergy planning model is further developed to minimize the annual total costs (ATCs) and the total electricity abandonment rate (TEAR) with various constraints. Subsequently, Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) are applied to solve the Pareto solution set and best compromise solution (BCS) of this mixed-integer nonlinear model (MINLP), respectively. Finally, optimal planning combinations are selected in three scenarios so as to verify the feasibility and validity of the proposed models and method. Innovations as well as further extensions of the proposed methods, are also discussed. Optimal equipment selection and output strategy help reduce 52.42% ATCs and 19.81% TEAR. Moreover, with considerations for energy interactions, RIES synergy planning achieves higher excess electricity consumption efficiency and further 1.40 M$ savings.

Coordinated planning of multi-area multi-energy systems by a novel routing algorithm based on random scenarios

As an important Energy Internet technology, energy router (ER) can implement energy routing and information interconnection for the electrical grid within a certain geography range. However, multi-energy supply allocation between multi-energy routers (MERs) has to be resolved, which can connect isolated area networks and expand the scale of the energy Internet. In this paper, equipment capacity and network routing are planned for multi-area multi-energy system (MAMES), which integrates multiple MERs with a virtual multi-energy router (VMER). Firstly, based on the VMER, the concept of MAMES is proposed. Then, the correlation model of multi-energy networks in VMER is constructed, based on MER energy transmission conversion extension model and hybrid power flow model. And the novel routing algorithm is proposed to determine the energy candidate set of the integrated energy networks. During planning, the random scenario generation based on Latin hypercube sampling (LHS) and scenario reduction based on k-means clustering are applied. Finally, the simulation shows that the planning method based on the routing algorithm can effectively obtain the capacity of energy equipment inside MERs and the routing layout between MERs in the MAMES. Proposed routing algorithm and operation scenarios reduction greatly improve the efficiency of planning. Correlated planning helps improve energy efficiency, environment protection, and economic benefits of MAMES.

Multi-objective optimization of a combined cooling, heating, and power system with subcooled compressed air energy storage considering off-design characteristics

In this work, the performance of a combined cooling, heating, and power system is studied under dynamic operation conditions. The hybrid system consists of a wind farm and a subcooled compressed air energy storage system, providing energy for an integrated energy network including established heating, cooling, and electricity grids. For the presented system, real wind fluctuation data and the off-design performance characteristics of each component are considered. The efficiency of the integrated cooling, heating and power system and the cost of the system are taken into account as the objectives of the problem to optimize. Then, a bi-level differential evolution algorithm is proposed to handle the multi-objective optimization of the system. Different solutions are carried out and compared to investigate the trigeneration of the system under various energy demand conditions. The results show that the off-design characteristics have a significant side-effect on the trigeneration performance of the system. The storage system has more obvious advantages in the transition season, as the states of charge of the system are 82%, 84% and 92% in winter, summer and transition seasons, respectively. The application of the system can effectively avoid the negative effect of the off-design characteristics of equipment and has great potential for energy supply in combined cooling, heating, and power systems.

Cost-Based Site and Capacity Optimization of Multi-Energy Storage System in the Regional Integrated Energy Networks

Cost-Based Site and Capacity Optimization of Multi-Energy Storage System in the Regional Integrated Energy Networks

Genetic Algorithm for Energy Commitment in a Power System Supplied by Multiple Energy Carriers

In recent years, energy consumption has notably been increasing. This poses a challenge to the power grid operators due to the management and control of the energy supply and consumption. Here, energy commitment is an index criterion useful to specify the quality level and the development of human life. Henceforth, continuity of long-term access to resources and energy delivery requires an appropriate methodology that must consider energy scheduling such as an economic and strategic priority, in which primary energy carriers play an important role. The integrated energy networks such as power and gas systems lead the possibility to minimize the operating costs; this is based on the conversion of energy from one form to another and considering the starting energy in various types. Therefore, the studies toward multi-carrier energy systems are growing up taking into account the interconnection among various energy carriers and the penetration of energy storage technologies in such systems. In this paper, using dynamic programming and genetic algorithm, the energy commitment of an energy network that includes gas and electrical energy is carried out. The studied multi-carrier energy system has considered defending parties including transportation, industrial and agriculture sectors, residential, commercial, and industrial consumers. The proposed study is mathematically modeled and implemented on an energy grid with four power plants and different energy consumption sectors for a 24-h energy study period. In this simulation, an appropriate pattern of using energy carriers to supply energy demand is determined. Simulation results and analysis show that energy carriers can be used efficiently using the proposed energy commitment method.

Development Concept of Integrated Energy Network and Hydrogen Energy Industry Based on Hydrogen Production Using Surplus Hydropower

The development of hydropower industry is progressing rapidly in China, and the installed capacity and power generation are increasing year by year. However, due to factors such as transmission channels and power grid peaking capacity, hydropower consumption in some areas is facing greater pressure. As an excellent medium for energy interconnection, hydrogen energy can play an important role in promoting hydropower consumption. This paper introduces the current status and trends of hydrogen energy development in major developed countries and China, and analyzes the current status of China’s hydropower abandoned water. Based on the production of hydrogen using surplus hydropower in the Dadu River Basin in Sichuan, an integrated energy network research plan including hydropower, electrolytic hydrogen production, storage and transportation, hydrogen refueling, and hydrogen-powered vehicles is proposed. At the same time, the development concept of hydrogen energy industry including hydrogen energy source economy, hydrogen energy industry ecosphere and hydrogen energy sky road in western Sichuan is also proposed.