Proposed Operation Model Research Articles

A Low-Carbon Optimal Operation Method for an Industrial Park Multi-Energy Coupling System Utilizing By-Product Hydrogen

To enhance the utilization efficiency of by-product hydrogen and decrease the power supply expenses of industrial parks, local utilization of by-product hydrogen plays a crucial role. However, the methods of utilizing by-product hydrogen in industrial parks are relatively limited. In response to this issue, an optimization method for a multi-energy system with by-product hydrogen considering the production process of chlor-alkali plants was proposed in this paper. Firstly, on the source side, models were established for hydrogen production using the ion exchange membrane electrolyzer and for the energy consumption during the caustic soda solution evaporation process. Secondly, on the load side, this paper explored the potential for local utilization of by-product hydrogen, including its participation in the production of downstream chemical products, combustion when mixed with natural gas, and utilization in hydrogen fuel cells. Next, this paper considered the influence of correlations among various loads within the factory and wind power generation, proposing a method for generating scenarios that takes into account the spatiotemporal correlation of source-load variables. Then, aiming to minimize the system operation cost and carbon trading cost, an operation strategy for a multi-energy system in a low-carbon industrial park, considering local utilization of by-product hydrogen, was proposed. Finally, the effectiveness of the scenario generation method proposed in this paper, considering spatiotemporal correlation, and the economic and environmental benefits of the proposed operation model utilizing the by-product hydrogen are verified through arithmetic simulation, based on the operation data of a chlor-alkali chemical park.

Analysis of multi-cascade CCHP system with gas turbine bypass extraction air energy storage

The operational load of gas turbine can be regulated by using compressor bypass extraction. In this paper, a combined cooling, heating and power (CCHP) system integrating gas turbine cycle (GTC), compressed air energy storage (CAES), supercritical CO2 Brayton recompression cycle (SCRC), organic Rankine cycle (ORC) and absorption refrigeration cycle (ARC) is proposed. The use of CAES not only enables flexible recovery of waste heat and load demand regulation, but also enables effective storage and secondary use of bypass extracted air from the compressor. The temperature of the graded expanded air is reduced and returned to the gas turbine unit, improving its thermal performance. The exergy and economic analyses show that the GTC has the largest percentage of both exergy destruction and investment cost rates, over 60%. Under the proposed operation model, the payback period of a single gas turbine is 4.12 years, and the payback period of the proposed CCHP system is 2.44 years. Thermodynamic, economic and environmental evaluation models are established to analyze the system performance at different loads. At the lowest load operation, the energy efficiency of the CCHP system can reach 75.99%, the exergy efficiency is 45.89%, the unit energy cost is 0.032 $/kWh, and the greenhouse gas equivalent emission is 0.313 kgCO2e/kWh. Compared with the other four cascade waste heat recovery systems, the proposed CCHP system greatly improves the thermodynamic performance and reduces the unit energy cost rate and greenhouse gas equivalent emissions, especially under low load operation conditions.

Collaborative Operation Between Power Network and Hydrogen Fueling Stations With Peer-to-Peer Energy Trading

In recent years, hydrogen fueling electric vehicles (H2EVs) have developed rapidly and drawn much attention. Indeed, the prevalence of H2EVs may introduce a notable interaction between the power network (PN) and the transportation network (TN) via the hydrogen fueling station (HFS). Therefore, it is worth investigating the efficient interaction of PN and HFSs under the constraints of coupled power flow in the PN and traffic flow in the TN. To this end, this article establishes the operation model of HFSs coupled power-traffic system, in order to investigate their impact relationship. Then, a collaborative operation framework with peer-to-peer (P2P) energy trading is proposed to promote the interactive efficiency between the PN and the HFS, considering both energy and reserve. On this basis, the P2P energy trading strategy with dynamic pricing and arbitrage prevention mechanism is developed to further reduce the total operation cost and ensure the fairness of the transaction. Case studies on the HFS-coupled power-traffic system verify the effectiveness of our proposed operation model and the collaborative framework considering P2P energy trading, which results in a lower operation cost, compared with the independent operation and collaborative operation without P2P energy trading, respectively.

Operation of a commercial district integrated energy system considering dynamic integrated demand response: A Stackelberg game approach

To facilitate energy coupling and coordinate distributed resources economically, this paper proposes an operation model of a district integrated energy system (IES) with a Stackelberg game approach. In the proposed model, a dynamic integrated demand response (IDR) mechanism is designed. The scenario theory is utilized to model uncertainties and the conditional value at risk (CVaR) method is employed to capture the risks of uncertainties. The district energy operator (DEO) is a common leader, while the building prosumers (BPs) and the electric vehicle aggregator (EVA) are followers. Each participant pursues the maximization of their personal benefits. Regarding the business mode, two aspects are innovative in the paper. Firstly, the relation between risk sources and risk bearers is defined. Secondly, the economic benefits of participants are guaranteed by diverse business channels. The paper demonstrates the existence and uniqueness of the Stackelberg equilibrium (SE), which is achieved by employing a bisection-based distributed algorithm. Finally, the case study of a commercial district verifies the effectiveness of the algorithm, and shows the merits of the proposed operation model, including the good benefits of all participants, as well as the significant effects of IDR programs.

A Probabilistic Model for Minimization of Solar Energy Operation Costs as Well as CO2 Emissions in a Multi-Carrier Microgrid (MCMG)

This paper proposes a probabilistic model with the aim to reduce the solar energy operation cost and CO2 emissions of a multi-carrier microgrid. The MCMG in this study includes various elements such as combined heat and power (CHP), electrical heat pump (EHP), absorption chiller, solar panels, and thermal and electrical storages. A MILP model is proposed to manage the commitment of energy producers, energy storage equipment, the amount of selling/buying of energy with the upstream network, and the energy consumption of the responsible electrical loads for the day-ahead optimal operation of this microgrid. The proposed operation model is formulated as a multi-objective optimization model based on two environmental and economic objectives, using a weighted sum technique and a fuzzy satisfying approach. In this paper, the 2 m + 1-point estimate strategy has been used to model the uncertainties caused by the output power of solar panels and the upstream power supply price. In order to evaluate the performance of the proposed model, and also for minimizing cost and CO2 emissions, the simulation was conducted on two typical cold and hot days. Numerical results show the proposed model’s performance and the effect of electrifying the heating and cooling of the microgrid through the EHP unit on greenhouse gas emissions in the scenarios considered.

Projection method for blockchain-enabled non-iterative decentralized management in integrated natural gas-electric systems and its application in digital twin modelling

Integrating natural gas and electricity systems increases system flexibility for the accommodation of the large penetration level of renewable energy and thus achieves decarbonization in the energy system. This paper aims at providing non-iterative and scalable decentralized energy management for multi-integrated natural gas-electricity systems with uncertain wind power. An operation space projection transformation method is proposed to reformulate the electricity and natural gas system operation problems for constructing equivalent feasible operation space with the optimality information contained. Accordingly, the proposed decentralized management is privacy-preserving, low-complex, and globally optimal. Moreover, the mathematical proof of the optimality of the reformulated problem is provided. In addition to privacy protection, trust issues are taken into account. Blockchain is applied to safeguard the proposed decentralized management against potential malicious behaviours. We introduce how the proposed decentralized management is embedded in the consensus process of the blockchain. The potential of the projection transformation method in the digital twin application is analyzed. Numerical results are presented to validate the effectiveness of the proposed decentralized energy management method. The synergistic effect and robustness of the proposed operation model are embodied, while the computational accuracy and performance of the non-iterative solution technique are validated.

Changing the regulations for regulating the changes: From distribution system operator (DSO) to electricity distribution stakeholders’ organization (EDSO)

Followed by the extensive activation of demand side entities, the anti-competitive and monopolistic aspects of distribution system operator (DSO) is becoming more apparent. The business model of the DSO and its regulations are not capable enough to fully leverage the capacity of emerging technologies and responsive prosumers. This paper criticized the challenges/deficits revolving around the conventional DSO model and proposes an interactive platform based on the sharing economy business model at the network level. The electricity distribution stakeholders’ organization (EDSO) as the substitute of DSO in active distribution networks is developed based on the collaborative governance decision-making model. The EDSO has the privilege to legislate on the platform operation and its main policy is to preserve the public interest as well as the integrity of electric distribution system. The superiority of proposed operation model is its non-monopolistic and non-profit nature which materializes the perfect competition of active customers and guaranties their maximum utilization.

Stochastic Economic Dispatching Strategy of the Active Distribution Network Based on Comprehensive Typical Scenario Set

The increasing penetration of renewable energy resources in the distribution network has posed great uncertainties and challenges for the system security operation. To model various uncertain factors like the wholesale market price and renewable energy generation in the active distribution network (ADN), a similarity measurement method considering the amplitude, volatility and variation trend is proposed. The Latin hypercube sampling method and Graph Pyramid clustering algorithm are adopted to obtain the comprehensive typical scenario set. Furthermore, this study proposes a scenario-based stochastic day-ahead optimal economic dispatch approach based on typical scenario set. The energy trading between the distribution system and the wholesale energy market, various distributed generators, network topology and power flow model are jointly formulated in the proposed operation model. The effectiveness and scalability of the proposed approach are verified using the IEEE 33-bus system. Numerical simulation results under different implementation scenarios indicate that the proposed approach offers a high computational efficiency and promotes the security and economy of the distribution system operation, which has a promising industrial application value.

Optimization of hydrogen yield of a high-temperature electrolysis system with coordinated temperature and feed factors at various loading conditions: A model-based study

High-temperature electrolysis (HTE) is a promising technology for achieving high-efficiency power-to-gas, which mitigates the renewable curtailment while promoting decarbonization by transforming wind or solar energy into fuels. Different from low -temperature electrolysis, a considerable amount of the input energy is consumed by auxiliary equipment in an HTE system for maintaining the temperature, so the studies on systematic energy description and parameter optimization of HTE are essentially required. A few published studies investigated HTE’s systematic optimization based on simulation, yet there is not a commonly used analytical optimization model which is more suitable for integration with power grid. To fill in this blank, a concise analytical operation model is proposed in this paper to coordinate the necessary power consumptions of auxiliaries under various loading conditions of an HTE system. First, this paper develops a comprehensive energy flow model for an HTE system based on the fundamentals extracted from the existing work, providing a quantitative description of the impacts of condition parameters, including the temperature and the feedstock flow rates. A concise operation model is then analytically proposed to search for the optimal operating states that maximize the hydrogen yield while meeting the desired system loading power by coordinating the temperature, the feedstock flows and the electrolysis current. The evaluation of system performance and the consideration of constraints caused by energy balances and necessary stack requirements are both included. In addition, analytical optimality conditions are obtained to locate the optimal operating states without performing nonlinear programming by further investigating the optimization method. In the case study, a numerical case of an HTE system is employed to validate the proposed operation model and optimization method, which proves that the proposed operation strategies not only improve the overall conversion efficiency but also significantly enlarge the load range of the HTE system. A 24-h case with fluctuant power input is also simulated to validate the beneficial effects of the proposed operation strategies on producing more hydrogen from a specific profile of surplus electricity. At last, some results comparisons with existed papers and possible research extensions are discussed briefly.