Multi-energy System Research Articles

Waste-to-energy (W2E) for renewable-battery-FCEV-building multi-energy systems with combined thermal/power, absorption chiller and demand-side flexibility in subtropical climates

Fuel Cell Electric Vehicle (FCEV) cogeneration powered by hydrogen can provide demand-side flexibility, and mitigate grid reliance of district buildings. Nevertheless, optimal configuration and high-efficient operation of the cogenerated FCEV-building system considering load characteristics have not been studied. In this study, a general approach with optimal system configurations and control strategies on an integrated FCEV-based cogeneration system is proposed for techno-economic performance improvement. A transient system model is developed with a state-of-the-art fuel cell degradation model on the latest automotive fuel cell techniques to characterize both power and thermal efficiency change with fuel cell decaying. Considering the dominant impact of large load changes on fuel cell degradation in FCEV's dual functions (Vehicle-to-Building (V2B) interaction and transportation), an innovative synergistic control strategy with fixed operating power is specially designed to mitigate fuel cell degradation and prolong its service lifetime. Results showed that energy flexibility can be improved by the optimal system configurations and the proposed control strategies (e.g., compared to the traditional system, the FCEV-based combined cooling, heating, and power (CCHP) systems can improve the on-site electrical energy fraction from 33.26% to 61.90%, and the off-peak grid shifted ratio from 33.71% to 53.60%, respectively), together with the decrease in operating costs between 4.49 and 6.87 CNY/m2·a. Sensitivity analysis results indicate that, the CCHP systems will be economically feasible for office buildings when the hydrogen price and the absorption chiller initial costs fall below 26.1 CNY/kg and 7900 CNY/kW. Moreover, regarding the dynamic degradation of fuel cells under large-range load change cycling, start-stop cycling, idling condition, and maximum power condition, the proposed mitigation strategy can effectively reduce the average FCEV degradation rates per unit power by 17.80%, compared to the strategy with dynamic operating power. This research provides a comprehensive methodology to evaluate the impact of system configurations and control strategies to improve energy efficiency, energy flexibility, and economic performance, and reduce FCEV degradation, together with carbon footprint analysis of hydrogen economy, accelerating carbon neutrality with advanced H2 techniques and sustainable buildings.

Intelligent day-ahead optimization scheduling for multi-energy systems

Concerning energy waste and rational use, this paper studies the optimal scheduling of day-ahead energy supply and the community’s demand with a combined cooling, heating, and power (CCHP) system in summer. From the perspective of bilateral costs and renewable energy use, this paper examines the impact of energy storage systems integrated into cogeneration systems. The Gurobi solver is used to optimize the residential community’s supply and demand sides of the traditional CCHP system (T-CCHP) and the CCHP system with energy storage (CCHP-ESS) under insufficient solar power. Subsequently, two optimal arrangements for energy consumption on the user side under these systems are suggested. In the optimization model, energy storage is added to the T-CCHP system on the energy supply side. On the user side, the energy use scheme is optimized considering the user’s comfort. The innovation point of this study is that the optimization of comprehensive energy in the park involves both supply and demand. The impact of increasing energy storage is discussed on the energy supply side, and the impact of optimization of the energy use plan on costs is discussed on the user side.

Distributed scheduling for multi-energy synergy system considering renewable energy generations and plug-in electric vehicles: A level-based coupled optimization method

Multi-energy synergy systems integrating high-penetration large-scale plug-in electric vehicles, distributed renewable energy generations, and battery energy storage systems have great potential to reduce the reliance of the grid on traditional fossil fuels. However, the random charging characteristics of plug-in electric vehicles and the uncertainty of photovoltaics may impose an additional burden on the grid and affect the supply–demand equilibrium. To address this issue, judicious scheduling optimization offers an effective solution. In this study, considering charge and discharge management of plug-in electric vehicles and intermittent photovoltaics, a novel Multi-energy synergy systems scheduling framework is developed for solving grid instability and unreliability issues. This formulates a large-scale mixed-integer problem, which calls for a powerful and effective optimizer. The new binary level-based learning optimization algorithm is proposed to address nonlinear large-scale high-coupling unit commitment problems. To investigate the feasibility of the proposed scheme, numerical experiments have been carried out considering multiple scales of unit numbers and various scenarios. Finally, the results confirm that the proposed scheduling framework is reasonable and effective in solving unit commitment problems, can achieve 3.3% cost reduction and demonstrates superior performance in handling large-scale energy optimization problems. The integration of plug-in electric vehicles, distributed renewable energy generations, and battery energy storage systems is verified to reduce the output power of 192.72 MW units during peak periods to improve grid stability. Therefore, optimizing energy utilization and distribution will become an indispensable part of future power systems.

Economy-environment-energy performance evaluation of power to hydrogen and power to methane considering renewable energy generation and carbon capture

Abstract The integration of multienergy complementary systems has become increasingly prevalent to mitigate the waste of renewable energy. As power-to-gas (P2G) technology advances, converting electricity into gas presents a viable solution for bolstering the reliability of power supplies within integrated energy frameworks. P2G plays a pivotal role in harnessing unused renewable resources, such as wind and solar energy, to produce sustainable power. While numerous studies have explored the advancement of P2G, there remains a lack of comprehensive evaluation of its various component subsystems. This research aims to design a renewable energy power system, augmented by gas-fired generation, assessing the collective advantages of both the power-to-hydrogen (P-H) and power-to-methane (P-M) conversion processes within the P2G infrastructure. It is important to note that the economic potential of P-H conversion is currently constrained by cost factors within existing P2G systems. This study takes into account the dynamics of carbon trading, as well as the hydrogen and methane markets, to compare the economic, environmental and energy-specific benefits of P-H and P-M conversions under different power demand scenarios. The goal is to formulate enhanced strategies to optimize P2G deployment in these varied contexts.

Two-stage optimization of hydrogen and storage coordination for a multi-region flexible intermodal multi-energy port system

To address the issue of imbalanced electricity and hydrogen supply and demand in the flexible multi-energy port area system, a multi-regional operational optimization and energy storage capacity allocation strategy considering the working status of flexible multi-status switches is proposed. Firstly, based on the characteristics of the port area system, models for system operating costs, generation equipment, energy storage devices, flexible multi-status switches, and others are established. Secondly, the system is subjected to a first-stage optimization, where different regions are optimized individually. The working periods of flexible multi-status switches are determined based on the results of this first-stage optimization, targeting the minimization of the overall daily operating costs while ensuring 100% integration of renewable energy in periods with electricity supply-demand imbalances. Subsequently, additional constraints are imposed based on the results of the first-stage optimization to optimize the entire system, obtaining power allocation during system operation as well as power and capacity requirements for energy storage devices and flexible multi-status switches. Finally, the proposed approach is validated through simulation examples, demonstrating its advantages in terms of economic efficiency, reduced power and capacity requirements for energy storage devices, and carbon reduction.

Multi-stage planning of integrated electricity-gas-heating system in the context of carbon emission reduction

In order to facilitate the carbon emission reduction to mitigate climate change, this paper proposes a coordinated multi-stage planning strategy for the transmission-level integrated electricity-gas-heating system. The strategy coordinates installations of gas-fired generation plants, renewable energy plants, gas wells, power-to-gas plants, transmission lines and pipelines, considering retirements of coal-fired generation plants. It can help facilitate carbon emission reduction of the electricity system as well as the integrated energy system. The objective is to minimize the total present value of the investment and the operation economic cost, with consideration of constraints from each sub-system and carbon emission restriction. In the case studies, the proposed planning strategy is verified to be able to obtain the installation plan of the related facilities. With which the system can reduce the proportion of fossil fuel energy utilization and increase renewable energy utilization. Hence, carbon emission reduction is achieved. In addition, it has demonstrated that integrating the multi-energy systems can help reduce the economic cost in the planning result.

A novel demand response-based distributed multi-energy system optimal operation framework for data centers

To address the increasing energy demands in data centers, distributed multi-energy system (DMES) can provide an efficient solution. This study proposes a DMES coupled by photovoltaics, wind turbines, ground source heat pump, internal combustion engines, electric chillers, absorption chillers, and energy storage device. The optimal scheduling of DMES with source-load interaction plays a crucial role in improving the performance of data centers. To achieve this, an integrated demand response (IDR) strategy is established, considering time-of-use pricing and renewable energy peak subsidies. Then, a clean and economical optimal operation model for DMES based on proposed IDR strategy and carbon trading mechanisms is established. Furthermore, to enhance the robustness of scheduling, this study analyzes the impacts of uncertainties in renewable energy output and demand response on DMES operation using the Monte Carlo method and interval method. Case study results demonstrate that the proposed IDR strategy increases electricity and cooling loads while reducing heat loads during the peak period of renewable energy generation, compared to the traditional IDR strategy. The proposed scheduling model, which incorporates the proposed IDR strategy and carbon trading mechanism, improves data center performance by reducing total costs by 1.85%, carbon emissions by 0.56%, electricity purchases by 2.93%, while increasing renewable energy utilization by 0.77%. The results also highlight the critical role of energy storage devices, with an optimal initial charge state is 0.5. Additionally, optimization considering multiple uncertainties, results in higher total costs and broader interval widths compared to single-factor uncertainty optimization, but reduces system operational risk.

Enhancing Residential Sustainability: Multi-objective optimization of hydrogen-based multi-energy system

To enhance residential sustainability by providing decarbonized and locally produced energy to a residential district, the relevance of a grid-connected multi-energy system, including PV panels, a battery, an electrolyzer, a hydrogen tank, and a fuel cell, is studied. A model is developed that creates high-resolution, continuous yearly profiles. The model is then utilized in a metaheuristic multi-objective optimization based on total cost and life cycle greenhouse gas emissions to highlight sizing trends. In the results, the most cost-efficient solutions rely mostly on PV power with minimal battery storage capacity, whereas hydrogen systems are necessary to achieve the best emission reductions. The analysis does not identify a promising prospect for seasonal energy storage with the current tank and battery lifetime emissions. Producing more than 65 % of the energy demand locally is not deemed beneficial.

Voltage control method for multi-energy system based on the coupling of renewable energy hydrogen production and storage

Renewable energy power generation combined with hydrogen storage, is an important way to realize the deep integration of hydrogen energy and renewable energy in multi-energy systems. In the multi-energy system of renewable energy power generation and hydrogen production in AC/DC hybrid. Due to the fluctuation of heat load and electric hydrogen production load in the system and the multi-time scale characteristics of energy flow transmission of heat storage and hydrogen storage. It will lead to the difficulty of power coordination in the whole Multi Energy System (MES). In order to solve the problem of power imbalance in MES, this paper first establishes the hybrid power flow equation of MES cluster composed of AC/DC and hydrogen energy transmission channels. The reactive voltage fluctuation characteristics of the AC/DC system under the fluctuation of energy exchange, system energy conversion, and renewable energy output of the MES cluster interconnection channel are analyzed. Secondly, a multi-energy flow model of the multi-energy system is established. The main factors affecting the voltage-reactive power of the AC system are analyzed. A reactive power model based on electro-thermal conversion, hydrogen storage, and multi-energy transmission channels is established. Then, a generation algorithm of the safe and stable boundary of pipeline pressure is proposed to maintain the pressure of hydrogen production and storage system within a safe range. The robust optimization control method is used to control the coupling of multi-energy sources. Finally, based on the actual operation data of the multi-energy power system. The simulation model of reactive power dynamic optimization control for multi-energy interconnected systems is established. The simulation results show that the control method proposed in this paper is adopted. Through the coordinated distribution of energy among multi-energy systems, the voltage stability level of the system can be effectively improved.

High fidelity modeling of pumped storage units for optimal operation of a multi-energy co-generation system

Pumped storage, as the storage technology with the largest installed capacity and mature technology, plays a key regulation role in the multi-energy co-generation system. The core of regulation accuracy is the high-fidelity modeling of pumped storage. This paper improves the insufficiency of the conventional pumped storage model (CPSM) in exaggerating the flexibility of pumped storage units by setting up non-operable operating condition regions, and incorporates the condition switching loss into the model consideration, on the basis of which a high fidelity pumped storage model (HFPSM) is established. Secondly, a multi-objective function of the operation model is set from the consideration of economy, environmental protection and stability, and a engineering application level optimal operation model of wind power-photovoltaic-thermal power-pumped storage multi-energy co-generation system based on HFPSM is proposed. Thirdly, two research indicators, the thermal power volatility indicator and the pumped storage unit utilization rate, are proposed. Fourthly, combined with examples, the effects of CPSM and HFPSM on the optimized operation of the system are investigated. It is found that adding four 50MW pumped storage units to the system can reduce the total operating cost by 10.34% and the environmental cost by 83.61%. The optimization of the high fidelity model is better under the premise of ensuring safe, stable and efficient operation of the system. Optimizing the number of unit startups and shutdowns for the high fidelity model to 25.8% of the conventional model. Finally, by exploring the optimal operation of a multi-energy co-generation system with different pumped storage installed capacities, it is found that the proposed high fidelity model makes the optimization results more in line with the actual operation. The flexibility of the pumped storage units no longer increases with the increase of installed capacity, which provides a reference for the planning of the storage capacity in the multi-energy co-generation system.

EV Charging Station Placement Considering V2G and Human Factors in Multi-Energy Systems

EV Charging Station Placement Considering V2G and Human Factors in Multi-Energy Systems

Analysis of electromechanical coupling vibration characteristics of motor-gear system based on bond graph theory

In recent years, there has been a growing demand in the field of engineering systems for research on the vibration response of motor-gear systems under non-steady state conditions. However, conventional modeling and simulation techniques are primarily restricted to systems within a single energy domain. When dealing with intricate electromechanical coupling systems, the modeling process becomes increasingly intricate. Consequently, this study adopts bond graph theory as the foundation for analyzing the vibration characteristics of motor-gear coupling systems. In addressing the vibration issue of the motor-gear transmission system, a nonlinear bond graph model is established that takes into account the time-varying mesh stiffness, static errors, and tooth surface friction, among other nonlinear factors. Then, according to the coupling relationship between motor mechanical systems and electrical systems, the electromechanical coupling dynamic model of the motor-gear system is established using the method of bond graph. In addition, the state equation of the system is derived based on the bond graph model. Finally, the system is simulated using 20-sim software, and the electromechanical coupled vibration characteristics of the simulation results are analyzed. This article lays the foundation for the design and analysis of motor-gear coupling systems and multi-energy domain complex systems.

Incorporating Multi-Energy Industrial Parks Into Power System Operations: A High-Dimensional Flexible Region Method

Incorporating Multi-Energy Industrial Parks Into Power System Operations: A High-Dimensional Flexible Region Method

Performance analysis of the comprehensive energy system based on active energy storage-discharge technology under time-sharing electricity price operation strategy

Multi-energy complementary comprehensive energy systems based on renewable energy can reliably meet the energy needs of communities and significantly mitigate carbon emissions. This is of paramount significance in the establishment of low-carbon sustainable communities. The effective operation of an integrated energy system necessitates a thorough examination of demand-side load, the dynamic performance of the energy supply system, the configuration of energy storage systems, local electricity pricing policies, and operational or control strategies for the system. It confronts substantial challenges in practical application. Considering the noteworthy performance variations of comprehensive energy systems under diverse demand-side load, fluctuating electricity prices, and various operating modes of energy storage equipment, this paper initially conducts a practical analysis of demand-side load. A comprehensive energy system with multi-energy complementary based on source-load-storage coordination (SLS-CES) model was constructed. From the perspective of system operation strategy, we identify the current electricity consumption pattern in the region, characterized by peak and valley periods. We integrate this information with the time-of-use electricity pricing policy and the equipment within the target area. An operation strategy based on local time-of-use electricity price policy was proposed. An in-depth analysis of the thermal performance, environmental performance, and economic performance of the system in the full-year dimension and typical daily dimension under this operating strategy was conducted. The results show that under this operation strategy, the system's annual net income is 415.90 thousand yuan, of which the system's energy storage battery power supply revenue during peak period reaches 254.40 thousand yuan. The initial investment is 5.03 million yuan, and the static investment payback period is 12.09 years. The annual primary energy saving rate of the system is 36.00%, and the maximum CO2 emission reduction rate is 72.23%. The maximum primary energy saving rates on typical days in winter and typical days in summer are 74.74% and 97.14% respectively. The total annual CO2 emissions were reduced by 5.47 tons and 4.54 tons respectively. Through this study, we found that a system incorporating energy storage equipment, combined with an operation strategy based on electricity price policy, can yield additional economic benefits. This approach helps alleviate peak power supply pressure on the grid and mitigates the challenges associated with the high initial investment in renewable energy systems, all while maintaining good thermal performance and environmental benefits.

Scheduling Strategy Design of Multi-energy Integrated Energy System Considering Source-Net-Load Coupling

In conventional optimal scheduling models of multi-energy integrated energy systems (IES), the energy generation and conversion efficiencies of devices are generally constants or vary with the load rates. However, it is not applicable for thermal network connected heating devices, such as heat pumps, combined heat and power generation (CHP) units. Their efficiencies are not only related to their own operating states, but also to the operational condition of thermal networks. If the interrelated nature is ignored, even without the presence of renewable energy and load forecasting error, the scheduling plan still cannot be executed accurately in the real-time operation stage. To deal with the problem, an accurate scheduling strategy considering the source-net-load coupling of a typical CHP-IES has been proposed. Comparing to conventional scheduling strategies, the actual execution results can maintain a high degree of consistency with the expected operation plan of the proposed accurate scheduling method. The supply and demand of both electrical and thermal energy can be balanced all the day.

On the Use of Optimized Models for Energy Management System in Multi Energy Hydrogen and Electric Vehicle Applications

As the world transitions towards sustainable energy solutions, integrating hydrogen and Electric Vehicles (EVs) into multi-energy systems presents challenges and opportunities. This paper explores a preliminary development of an advanced Charging/Energy Management System (C/EMS) optimization model tailored for multi-energy applications, explicitly focusing on Fuel Cell and Battery Electric Vehicles. Integrating hydrogen refueling infrastructure and EV charging stations within the depot introduces additional complexities, necessitating sophisticated EMS algorithms for effective management. The proposed EMS optimization model aims at optimizing the utilization of diverse energy sources, storage systems and demand-side resources to enhance system efficiency, reliability and environmental sustainability. The authors present the design considerations, modeling techniques and optimization methodologies employed to address these challenges and maximize the benefits. Case studies and simulation results demonstrate the effectiveness of the proposed EMS optimization model in enhancing overall system performances.

Frequency stability control method for multi-energy system considering storage characteristics and transmission inertia of hot and gas pipeline network

The grid-connected capacity of renewable energy generation in multi-energy microgrid is increasing. This leads to a decrease in the inertia level in the microgrid, which has a great impact on the frequency stabilization control. This article proposes an adaptive control method for frequency control of inertia in multi-energy microgrids. Firstly, the system frequency fluctuation problem is addressed. Analyze the response characteristics of virtual inertia and the influence of physical inertia of rotating equipment on system frequency dynamics in multi-energy microgrid. Secondly, study the energy transfer characteristics of electric, thermal and gas systems in multi-energy microgrids. The energy coupling model between the subsystems in the multi-energy microgrid is established. And according to the difference of energy transmission time inertia of electric, heat and gas subsystems, the microgrid inertia response time model of different energy systems is established. Then, according to the energy balance stability criterion of multi-energy microgrid, combined with the current operating state of the system and the state of the higher-level distribution network, the fast response adaptive over-compensation control of multi-energy microgrid cluster is carried out to realize the inertia allocation in multi-energy microgrids. Finally, the proposed advanced frequency control method of multi-energy microgrid considering inertia demand is verified by simulation.

Implementation of a Decision-Making Approach for a Hydrogen-Based Multi-Energy System Considering EVs and FCEVs Availability

Implementation of a Decision-Making Approach for a Hydrogen-Based Multi-Energy System Considering EVs and FCEVs Availability

Coordinated Cyber Security Enhancement for Grid-Transportation Systems With Social Engagement

Effective coordination of energy and transportation systems is fundamental and vital to smart city management. Yet, the deeply intertwined information and communication technologies have exposed smart city management to malicious cyberattacks vastly. This study develops a two-stage mitigation strategy for integrated transportation-energy systems (TESs) by coordinating energy and transportation systems to safeguard against false data injection attacks (FDIAs). Our strategy targets social engagements by electric vehicle (EV) users who can be incentivized to alter their regular EV usage patterns for supporting the energy system via vehicle-to-grid actions. We consider a TES that contains a multi-energy system comprised of power and gas systems as well as an urban transportation system. Integrated system operators can take emergency measures to coordinate important system assets (e.g., traditional generators, renewable generators, EV fleets) in a sensible and intelligent way, and thereby mitigate the consequences of FDIAs. Specifically, we take a two-stage distributionally robust approach to cope with uncertain FDIAs, with which a moment-based ambiguity set is employed to yield the worst-case uncertainty distribution. We leverage constraint generation-based relaxation to solve the problem iteratively. To demonstrate our strategy's value and practical utilities, we use a coupled urban TES to conduct case studies. According to the evaluation results, the optimized EV scheduling and energy dispatch scheme produced by the proposed strategy can contain cyberattacks’ impacts and enhance cyber resilience in smart city management more effectively.

Analysis of optimal configuration of energy storage in wind-solar micro-grid based on improved gray wolf optimization

To make full use of the electric power system based on energy storage in a wind-solar microgrid, it is necessary to optimize the configuration of energy storage to ensure the stability of a multi-energy system. This paper analyses the structure and function of the microgrid system, establishes the mathematical model, and analyzes the output characteristics. A double-layer optimization model of energy storage system capacity configuration and wind-solar storage micro-grid system operation is established to realize PV, wind power, and load variation configuration and regulate energy storage economic operation. The mathematical model of the improved gray wolf optimization is constructed, and the typical landscape resource data of a residential district. Comparing the difference between energy storage without an installation and energy storage with improved algorithm, it is shown that the energy storage configuration of the improved gray wolf optimization improves the economy, efficient energy use, and revenue of the whole system.