This paper, provides the design and simulation of the control modes of three different power sources that are commonly used in hybrid systems especially when combining the sources of photovoltaic (PV), electric vehicles (EV) and Energy storage system (ESS). The control scenarios discuss the different combinations of sources and loads based on ternary logic system (0,1,2) that has many advantages over the classical binary logic system (0,1). To prove that, first, the ternary logic gates must be verified and simulated as MOSFET by Matlab / Simulink then a ternary logic control (TLCU) will be designed. TLCU can select the right direction of power flow from the energy source to the load based on the ternary truth table that shows the relationship between the inputs (ternary states of sources and loads) and each output that has only two states (ON or Off). At the end of the paper, the circuit of a ternary logic control circuit that can optimize the number of used elements of MOSFET is designed and tested. Comparing to binary, it is expected not only to optimize the number of MOSFET but also to accelerate the speed of operation.

Integrated energy systems (IESs) considering power-to-gas (PtG) technology are an encouraging approach to improve the efficiency, reliability, and elasticity of the system. As the evolution towards decarbonization is increasing, the unified coordination between IESs and PtG technology is also increasing. PtG technology is an option for long-term energy storage in the form of gas, but, compared to other technologies, it is economically expensive at the present time to optimize the technology. This article presents a comprehensive review of the state-of-the-art research and of the developments regarding integrated energy systems considering PtG technology. This presented review emphasizes planning and economic analysis, including system integration enhancements focusing on optimization, conversion technologies, and energy storage to improve the operation and stability and to enhance the facilities for consumers. The role of a PtG system in generation, transmission, distribution, and consumption is discussed. By emphasizing planning, integration, and the role, this paper aims to guide researchers, scientists, engineers, and policy makers towards effective research and broad strategies that sustain an IES-PtG.

In the context of “dual carbon”, in order to promote the consumption of renewable energy and improve energy utilization efficiency, a low-carbon economic dispatch model of an integrated energy system containing carbon capture power plants and multiple utilization of hydrogen energy is proposed. First, introduce liquid storage tanks to transform traditional carbon capture power plants, and at the same time build a multi-functional hydrogen utilization structure including two-stage power-to-gas, hydrogen fuel cells, hydrogen storage tanks, and hydrogen-doped cogeneration to fully exploit hydrogen. It can utilize the potential of collaborative operation with carbon capture power plants; on this basis, consider the transferability and substitutability characteristics of electric heating gas load, and construct an electric heating gas comprehensive demand response model; secondly, consider the mutual recognition relationship between carbon quotas and green certificates, Propose a green certificate-carbon trading mechanism; finally establish an integrated energy system with the optimization goal of minimizing the sum of energy purchase cost, demand response compensation cost, wind curtailment cost, carbon storage cost, carbon purchase cost, carbon trading cost and green certificate trading compensation. Optimize scheduling model. The results show that the proposed model can effectively reduce the total system cost and carbon emissions, improve clean energy consumption and energy utilization, and has significant economical and low-carbon properties.

The multi-timescale optimization dispatch method for integrated energy systems proposed in this paper balances sustainability and low-carbon characteristics. It first incorporates shared energy storage resources such as electric vehicles into system dispatch, fully leveraging their spatiotemporal properties to enhance dispatch flexibility and rapid response capabilities for integrating renewable energy and enabling clean power generation. Second, an incentive-penalty mechanism enables effective interaction between the system and the green certificate–carbon joint trading market. Penalties are imposed for failing to meet renewable energy consumption targets or exceeding carbon quotas, while rewards are granted for meeting or exceeding targets. This regulates the system’s renewable energy consumption level and carbon emissions, ensuring robust low-carbon performance. Third, this strategy considers the close coordination between heating, cooling, and electricity demand response measures with the integrated energy system, smoothing load fluctuations to achieve peak shaving and valley filling. Finally, through case study simulations and analysis, the advantages of the multi-timescale dispatch strategy proposed in this paper, in terms of economic feasibility, low-carbon characteristics, and sustainability, are verified.

随着大规模分散且多样化的分布式资源接入，虚拟电厂（virtual power plant，VPP）技术已成为有效管理和优化需求侧资源的重要工具。为使 VPP 更好地满足新型电力系统的发展需要，提出了一种考虑不确定性风险的 VPP 参与绿证-碳联合交易的优化调度模型。首先，构建了由风电机组、光伏机组、燃气轮机组、储能设备和用户侧柔性负荷组成的 VPP 优化运行模型，该模型以 VPP 运行成本最小为目标，并考虑了电市场、绿证-碳联合交易机制以及激励型需求响应。其次，综合考虑 VPP 中的源、荷以及需求响应等多重不确定性因素，运用条件风险价值（conditional value-at-risk ，CVaR）理论对不确定因素风险进行量化处理。最后，通过算例分析，验证了所提模型的经济性和环保性，所考虑的CVaR也为 VPP 利润与风险的平衡提供了有力的决策依据。

With the integration of large-scale， distributed， and diverse distributed resources， virtual power plant （VPP） technology has become a vital tool for effectively managing and optimizing demand-side resources. To better align VPPs with the development needs of China’s new-type power system， this paper proposes an optimal scheduling model for VPPs participating in a green certificate-carbon joint trading mechanism， taking into account uncertainty risks. First， an optimal operation model for a VPP is constructed， consisting of wind turbines， photovoltaic units， gas turbine units， energy storage systems， and flexible load resources on the user side. The objective is to minimize the VPP’s operating cost， considering electricity markets， the green certificate-carbon joint trading mechanism， and incentive-based demand response. Second， multiple uncertainty factors within the VPP， such as generation sources， loads， and demand response， are comprehensively considered， and the conditional value-at-risk （CVaR） theory is applied to quantify the risks associated with these uncertainties. Finally， a case study is introduced to verify the economic and environmental benefits of the proposed model. The inclusion of CVaR also provides a robust decision-making basis for balancing VPP profits and risks.

目的 随着需求侧响应资源的不断增长，传统的能源调度模式难以满足新能源大量接入的系统需求。为实现小区内多种能源的合理调配，提出了一种基于用户需求侧响应的能源交易策略，旨在优化智能小区内能源的调度。 方法 针对含多栋楼宇的居民小区，对其中的分布式光伏、储能设备和柔性负荷进行统一调配，并根据小区运营商和用户负荷聚合商的定价交互，采用Stackelberg博弈建立两阶段调度优化模型。 结果 算例仿真模拟结果显示，相比传统的以热定电策略，所提模型可以降低40.22%的运行成本，提高22.57%的光伏消纳水平；相比传统的最优运行成本策略，所提模型可以降低29.66%的运行成本，提高6.78%的光伏消纳水平。 结论 所设计的策略在实现公平利益分配、缓解电力波动、灵活应对调度高峰需求、加强新能源整合及确保电网运行安全方面具有良好效果。

Objectives With the continuous growth of demand-side response resources, traditional energy scheduling models struggle to meet the system requirements of high penetration levels of renewable energy. To achieve the rational allocation of multiple energy sources within a community, this study proposes an energy trading strategy based on demand-side response from users, aiming to optimize energy scheduling in smart community. Methods For a residential community with multiple buildings, this study coordinates distributed photovoltaics, energy storage systems, and flexible loads. A two-stage scheduling optimization model is established using the Stackelberg game framework based on pricing interactions between community operators and user load aggregators. Results Simulation results show that, compared to the traditional heat-determined power strategy, the proposed model reduces operational costs by 40.22% and increases photovoltaic utilization by 22.57%. Compared to the conventional cost-optimal operation strategy, the proposed model results in a 29.66% reduction in operational costs and a 6.78% increase in photovoltaic utilization. Conclusions The proposed strategy demonstrates excellent performance in achieving equitable benefit distribution, mitigating power fluctuations, flexibly meeting peak-load demands, enhancing renewable energy integration, and ensuring grid operational security.