Search Results (176)

With the widespread application of combined heat and power (CHP) units, the coupling between electricity and heat systems has become increasingly close. In response to the problem of low operational efficiency of electricity–heat integrated energy systems (EH-IESs) with buildings in uncertain environments, this paper proposes a chance-constrained programming (CCP)-based decentralized optimization method for EH-IESs with buildings. First, based on the thermal storage capacity of building envelopes and considering the operational constraints of an electrical system (ES) and thermal system (TS), a mathematical model of EH-IESs, accounting for building thermal inertia, was constructed. Considering the uncertainty of sunlight intensity and outdoor temperature, a CCP-based optimal scheduling strategy for EH-IESs is proposed to achieve a moderate trade-off between the optimal objective function and constraints. To address the disadvantages of high computational complexity and poor information privacy in centralized optimization, an accelerated asynchronous decentralized alternating direction method of multipliers (A-AD-ADMM) algorithm is proposed, which decomposes the original optimization problem into sub-problems of ES and TS for distributed solving, significantly improving solution efficiency. Finally, numerical simulations prove that the proposed strategy can fully utilize the thermal storage characteristics of building envelopes, improve the operational economics of the EH-IES under uncertain environments, and ensure both user temperature comfort and the information privacy of each subject. Full article

Given the widespread use of gas-fired boilers and combined heat and power (CHP) units in existing district heating (DH) systems, this study investigates the integration of medium-scale heat pumps (HPs) into such configurations. Fifteen DH system variants were analysed, differing in installed HP capacity, operational strategies, and the synchronisation of heat and electricity production with thermal demand. A dynamic simulation model incorporating real-world equipment performance was developed to assess energy efficiency, environmental impact, and economic viability under three distinct energy price scenarios. The results demonstrate that an HP sized to 17% of the total heating capacity of the DH system achieves a 54% decrease in primary energy consumption and a 68% decrease in emissions compared to the base system. Larger HP capacities enhance environmental performance and increase the share of renewable energy but also entail higher investment. An economic analysis reveals that electricity-to-gas price ratios strongly influence the cost-effectiveness of HP integration. Under favourable electricity pricing conditions, systems with HP operational priority achieve the lowest levelized cost of heating. The most economically viable configuration consists of 600 kW HP and achieves a payback period of 4.7 years. The findings highlight the potential for HPs to decarbonize DH systems while emphasising the importance of market conditions and system design in ensuring economic feasibility. Full article

District heating systems in northern China predominantly rely on coal-fired heat sources, necessitating sustainable alternatives to reduce carbon emissions. This study investigates a biomass combined heat and power (CHP) system integrated with cascaded absorption heat pump (AHP) technology to recover waste heat from semi-dry flue gas desulfurization exhaust and turbine condenser cooling water. A multi-source operational framework is developed, coordinating biomass CHP units with coal-fired boilers for peak-load regulation. The proposed system employs a two-stage heat recovery methodology: preliminary sensible heat extraction from non-saturated flue gas (elevating primary heating loop (PHL) return water from 50 °C to 55 °C), followed by serial AHPs utilizing turbine extraction steam to upgrade waste heat from circulating cooling water (further heating PHL water to 85 °C). Parametric analyses demonstrate that the cascaded AHP system reduces turbine steam extraction by 4.4 to 8.8 t/h compared to conventional steam-driven heating, enabling 3235 MWh of annual additional power generation. Environmental benefits include an annual CO₂ reduction of 1821 tonnes, calculated using regional grid emission factors. The integration of waste heat recovery and multi-source coordination achieves synergistic improvements in energy efficiency and operational flexibility, advancing low-carbon transitions in district heating systems. Full article

The cooperative interconnection of multi-microgrid systems offers significant advantages in enhancing energy utilization efficiency and economic performance, providing innovative pathways for promoting sustainable development. To establish a fair energy trading mechanism for electricity–hydrogen sharing within multi-energy multi-microgrid (MEMG) systems, this study first analyzes the operational architecture of MEMG energy sharing and establishes a multi-energy coordinated single-microgrid model integrating electricity, heat, natural gas, and hydrogen. To achieve low-carbon operation, carbon capture systems (CCSs) and power-to-gas (P2G) units are incorporated into conventional combined heat and power (CHP) systems. Subsequently, an asymmetric Nash bargaining-based optimization framework is proposed to coordinate the MEMG network, which decomposes the problem into two subproblems: (1) minimizing the total operational cost of MEMG networks, and (2) maximizing payment benefits through fair benefit allocation. Notably, Subproblem 2 employs the energy trading volume of individual microgrids as bargaining power to ensure equitable profit distribution. The improved alternating direction multiplier method (ADMM) is adopted for distributed problem-solving. Experimental results demonstrate that the cost of each MG decreased by 5894.14, 3672.44, and 2806.64 CNY, while the total cost of the MEMG network decreased by 12,431.22 CNY. Additionally, the carbon emission reduction ratios were 2.84%, 2.77%, and 5.51% for each MG and 11.12% for the MEMG network. Full article

In this article, the planning and energy administration of energy hubs in electric, thermal and gas networks are presented, considering the resilience of the system against natural phenomena like floods and earthquakes. Each hub consists of bio-waste, wind and solar renewable units. These include non-renewable units such as boilers and combined heat and power (CHP) units. Compressed air and thermal energy storage are used in each hub. The design is formed as a bi-level optimization framework. In the upper level of the scheme, the energy management of networks bound to system resiliency is provided. This considers the minimization of annual operating and resilience costs based on optimal power flow equations in networks. In the lower-level model, the planning (placement and sizing) of hubs is considered. This minimizes the total building and operation costs of hubs based on the operation-planning equations for power supplies and storages. Scenario-based stochastic optimization models are used to determine the uncertainties of demand, the power of renewable systems, energy price and the accessibility of distribution networks’ elements against natural disasters. In this study, the Karush–Kuhn–Tucker technique is used to extract the single-level formulation. A numerical report for case studies verifies the potential of the plan to enhance the economic, operation and resilience status of networks with energy administration and the optimal planning of hubs in the mentioned networks. By determining the optimal capacity for resources and storage in the hubs located in the optimal places and the optimal energy administration of the hubs, the economic, exploitation and resilience situation of the networks are improved by about 27.1%, 97.7% and 23–50%, respectively, compared to load flow studies. Full article

In response to the challenges posed by the high proportion of photovoltaic (PV) in electrolytic aluminum (EA) industrial isolated microgrids, such as the low carbon economy problem and the dynamic dispatchability of EA and its combined heat and power (CHP) unit, a multi-timescale optimal dispatching method considering the dynamic temperature characteristics of an aluminum electrolytic cell is proposed for an EA isolated microgrid. Firstly, based on an electrothermal coupling model, the electrolyte dynamic temperature expression of aluminum electrolytic is derived, and the optimal dispatching method of an EA load considering the dynamic temperature characteristics of EA is proposed. Secondly, based on the carbon emission models of CHP units and EA loads, and with the optimization objective of maximizing the operating revenue of industrial isolated microgrids, a day-ahead-intraday multi-timescale optimal dispatching model considering the participation of EA loads in the demand response (DR) for isolated microgrids was established. Finally, numerical results for an industrial isolated microgrid have verified the effectiveness of the proposed method in improving the PV consumption rate and realizing low-carbon and economic operation of industrial islanded microgrids. Full article

Wastewater treatment plants (WWTPs) consume a considerable amount of energy. They also generate energy in combined heat and power (CHP) units, which utilise biogas from the anaerobic digestion of sewage sludge to produce renewable electricity. Different prices apply to electricity generated on site in CHP units, to the purchase of electricity from the grid, to the sale of surplus electricity to the grid and energy tariffs, which motivates the optimisation of energy costs. This paper presents a strategy for optimising electricity costs by adapting on-site electricity generation in CHP units to the demand of the WWTP. The approach is designed for a CHP system that generates electricity in multiple internal combustion gas engines. It is implemented as a two-level control system, where the lower control level dynamically adjusts the power of the individual gas engines, and the upper control level optimises the desired total power, taking into account the current energy consumption of the WWTP, biogas reserves and electricity tariffs. The proposed concept was implemented at the Domžale-Kamnik WWTP. A six-month evaluation showed that electricity purchased from the grid could be reduced from 8.7% to 3.3% of the WWTP’s electricity consumption. This reduction affects the system economically, as electricity purchased from the grid at low and high tariffs is 35% and 76% more expensive than electricity generated on site (excluding the grid fee). This approach can be extended to balance dispatchable electricity generation at the WWTP to respond to short-term grid demand. Full article

In view of the frequency regulation (FR) policy in Northeast China, a two-stage real-time rolling optimization model for power plants participating in FR ancillary services is established. The optimization object of the first stage is to maximize the overall profitability of the power plant and to obtain FR performance sub-indicators (K₁, K₂, K₃) and the electric power curve of combined heat and power (CHP) units with energy storage. The second stage of the model performs load distribution with the objective of minimizing operating cost, subject to the constraint of electric and heat power balance for CHP units and energy storage. Meanwhile, rolling optimization combined with dynamic correction is used to ensure the accuracy of the two-stage FR optimization model by updating the operating status of the CHP units and energy storage and reducing the prediction errors of the FR commands. The above models have been validated by actual case studies of a CHP plant in Northeast China. They can ensure the economic and sustainable operation of CHP units and energy storage, enabling the CHP plant to benefit in the FR ancillary services market. The models offer a useful reference for CHP enterprises in terms of FR. Full article

Hydrogen is considered a key energy carrier for which interest has grown over recent years. Chlor-alkali plants in the United States (U.S.) can potentially recover and supply the by-product hydrogen at scale. However, there is a scarcity of standard analysis for energy use and emissions associated with products from chlor-alkali plants owing to lack of data and variations in chlor-alkali plant technology and operation. A rigorous life cycle analysis (LCA) is needed to quantify the emissions of by-product hydrogen and other products from chlor-alkali plants. In this study, we performed well-to-gate (WTG) emissions analysis of chlor-alkali products based on U.S. plant operating data gathered from the U.S. Environmental Protection Agency’s (EPA’s) Chemical Data Reporting database, the U.S. Energy Information Administration survey EIA-923 form, and the EPA’s Greenhouse Gas Reporting Program. We performed process-level mass allocation to allocate energy use and emissions to the chlor-alkali products. This study shows that the by-product hydrogen has WTG CO₂ emissions of 1.3–1.9 kgCO₂/kg H₂ for plants without combined heat and power (non-CHP) and 1.5–2.4 kgCO₂/kg H₂ for plants with combined heat and power (CHP). Furthermore, we identified that electricity upstream emissions are the key driver affecting the emissions of by-product hydrogen from non-CHP plants, while CHP emissions can be reduced by electricity export to grids with higher carbon intensity (CI). Finally, the study shows that chlor-alkali plants in the U.S. can potentially meet up to 320 kilotons of hydrogen demand (approximately 3% of total demand) annually. Full article

Hydrogen-Integrated energy systems (HIESs) are pivotal in driving the transition to a low-carbon energy structure in China. This paper proposes a low-carbon economic scheduling strategy to improve the operational efficiency and reduce the carbon emissions of HIESs. The approach begins with the implementation of a stepwise carbon trading framework to limit the carbon output of the system. This is followed by the development of a joint operational model that combines hydrogen energy use and carbon capture. To improve the energy supply flexibility of HIESs, modifications to the conventional combined heat and power (CHP) unit are made by incorporating a waste heat boiler and an organic Rankine cycle. This results in a flexible CHP response model capable of adjusting both electricity and heat outputs. Furthermore, a comprehensive demand response model is designed to optimize the flexible capacities of electric and thermal loads, thereby enhancing demand-side responsiveness. The integration of electric vehicles (EVs) into the system is analyzed with respect to their energy consumption patterns and dispatch capabilities, which improves their potential for flexible scheduling and enables an optimized synergy between the demand-side flexibility and system operations. Finally, a low-carbon economic scheduling model for the HIES is developed with the objective of minimizing system costs. The results show that the proposed scheduling method effectively enhances the economy, low-carbon performance, and flexibility of HIES operation while promoting clean energy consumption, deep decarbonization of the system, and the synergistic complementarity of flexible supply–demand resources. In the broader context of expanding clean energy and growing EV adoption, this study demonstrates the potential of energy-saving, emission-reduction systems and vehicle-to-grid (V2G) strategies to contribute to the sustainable and green development of the energy sector. Full article

With the large-scale deployment of renewable energy, the issue of wind power consumption has become increasingly prominent, leading to serious wind energy abandonment. In order to promote energy sustainability, this paper proposes a low-carbon economic scheduling model of an integrated energy system (IES) that combines the flexible supply–demand response with the diversified utilization of hydrogen energy. A mixed-integer linear programming model is developed and solved using the commercial solver GUROBI to obtain the scheduling scheme that minimizes total costs. First, decoupling analysis is performed for combined heat and power (CHP) units, and the organic Rankine cycle (ORC) is introduced to enable dynamic output adjustments. On the demand side, a flexible demand response mechanism is introduced, which allows various types of loads to transfer within the scheduling cycle or substitute for each other within the same period. Additionally, combining the clean characteristics of hydrogen, this paper introduces hydrogen-doped CHP and other utilization strategies and develops a diversified utilization structure of hydrogen. A small IES is used for case analysis to verify the effectiveness of the above strategies. The results show that the proposed strategy can entirely consume wind power, reduce total cost by 21.32%, and decrease carbon emissions by 44.83%, thereby promoting low-carbon economic operation and sustainable energy development of the system. Full article

The ongoing transformation of district heating systems (DHSs) aims to reduce emissions and increase renewable energy sources. The objective of this work is to integrate solar thermal (ST) and seasonal aquifer thermal energy storage (ATES) in various scenarios applied to a large DHS. Mixed-integer linear programming (MILP) is used to develop a comprehensive model that minimizes operating costs, including heat pumps (HPs), combined heat and power (CHP) units, electric heat boilers (EHBs), heat-only boilers (HOBs), short-term thermal energy storage (TES), and ATES. Different ATES scenarios are compared to a reference without seasonal TES (potential of 15.3 GWh of ST). An ATES system with an injection well temperature of about 55 °C has an overall efficiency of 49.8% (58.6% with additional HPs) and increases the integrable amount of ST by 178% (42.5 GWh). For the scenario with an injection well temperature of 20 °C and HPs, the efficiency is 86.6% and ST is increased by 276% (57.5 GWh). The HOB heat supply is reduced by 8.9% up to 36.6%. However, the integration of an ATES is not always economically or environmentally beneficial. There is a high dependency on the configurations, prices, or emissions allocated to electricity procurement. Further research is of interest to investigate the sensitivity of the correlations and to apply a multi-objective MILP optimization. Full article

With the continuous adjustment of energy structure and the improvement of environmental protection requirements, combined heat and power microgrids (CHP-MG) have received widespread attention as an efficient and economical way of utilizing energy. The complexity of energy supply relationships and energy coupling within the microgrid system necessitates optimizing the power output of each equipment unit. In this paper, an optimization strategy for a multi-energy microgrid system is proposed based on the efficient energy supply of cogeneration microgrids: decoupling the thermoelectric connection by using the energy storage equipment on the supply side, utilizing the flexibility of the electrical loads and the diversity of the system’s heating methods, and reducing the electrical loads and changing the selection of the heating methods on the demand side. The optimization model in the paper is mainly based on mixed-integer linear programming and demand-side management theory, which simulates the system operation under different scenarios so as to find the optimal equipment output and load management strategies. Simulation results show that the optimized CHP-MG system can ensure a reliable power supply while effectively reducing operating costs, improving energy utilization and promoting sustainable operation of the energy system. The optimized microgrid system offers significant advantages in terms of economic efficiency and energy management when compared to conventional CHP systems. These findings provide actionable insights for policymakers, system operators, and researchers aimed at driving the development of efficient and sustainable energy management solutions. Full article

With the increasing application of Combined Heat and Power (CHP) units, Combined Heat and Power Economic Dispatch (CHPED) has emerged as a significant issue in power system operations. To address the complex CHPED problem, this paper proposes an effective economic dispatch method based on the Improved Artificial Hummingbird Algorithm (IAHA). Given the complex constraints of the CHPED problem and the presence of valve point effects and prohibited operating zones, it requires the algorithm to have high traversal capability in the solution space and be resistant to becoming trapped in local optima. IAHA has introduced two key improvements based on the characteristics of the CHPED problem and the shortcomings of the standard Artificial Hummingbird Algorithm (AHA). Firstly, IAHA uses chaotic mapping to initialize the initial population, enhancing the algorithm’s traversal capability. Second, the guided foraging of the standard AHA has been modified to enhance the algorithm’s ability to escape from local optima. Simulation experiments were conducted on CHP systems at three different scales: 7 units, 24 units, and 48 units. Compared to other algorithms reported in the literature, the IAHA algorithm reduces the cost in the three testing systems by up to USD 18.04, 232.7894, and 870.7461. Compared to other swarm intelligence algorithms reported in the literature, the IAHA algorithm demonstrates significant advantages in terms of convergence accuracy and convergence speed. These results confirm that the IAHA algorithm is effective in solving the CHPED problem while overcoming the limitations of the standard AHA. Full article

In the context of dual-carbon goals, it is essential to coordinate low-carbon policies and technologies. As a promising approach for clean energy integration, the combined heat–power–hydrogen virtual power plant (CHP-H VPP) effectively consolidates electricity, heat, and hydrogen to meet increasing energy demands and reduce carbon emissions. To this end, this paper proposes an optimal scheduling method for CHP-H VPPs based on a stepped carbon trading mechanism. First, at the low-carbon technology level, a CHP-H VPP architecture is constructed, incorporating thermal power units, hydrogen-doped gas turbines, hydrogen-doped gas boilers, and two-stage power-to-gas (P2G) systems. Second, at the policy level, a stepped carbon trading model is established to constrain system carbon emissions and an optimization model is formulated to minimize operating costs and emissions. Finally, a particle swarm optimization (PSO) algorithm with linearly decreasing constraints is employed to refine solution accuracy and accelerate convergence by progressively narrowing the search space and guiding the algorithm toward optimal solutions. Simulation results demonstrate that the proposed model enhances both the economic performance and carbon-reduction capabilities of the system; the simulation results also show that the proposed model effectively improves economic returns by reducing operating costs and enhancing carbon-reduction capacity, with a 7% reduction in run time. Full article