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The integrated energy system can realize the coupling and complementation of various energy sources such as cold, heat and electricity, and plays an important role in the consumption of renewable energy. This paper proposes a bi-level optimal design method for integrated energy system from both economic and carbon emissions aspects. The upper model aims at maximizing the system economy and optimizes the selection and capacity allocation of renewable energy power generation, storage and conversion equipment to meet the demands in the region. The lower model aims at maximizing the environment-protection performance and minimizes the system’s carbon emissions. Since the lower model contains binary variables to characterize trading states and charging and discharging states, the model cannot be transformed into a mathematical program with equilibrium constraints. To effectively handle this problem, the reformulation and decomposition method is adopted. Case studies show that this bi-level model can effectively consider the influence of the objective function in the lower model on the optimal capacity configuration in the upper model, avoid the influence of different objective weights when the multi-objective model is converted to the single-objective model, and obtain the global optimal solution.

In low latitudes, ice storage air conditioners (ISACs) have been widely used to cool while locally responding to the distribution network demand. However, due to the lack of the direct cold energy exchange between ISACs, the cooling load could only be shifted on the time scale instead of the space scale, resulting in an unsatisfactory regulation result. To address the above problem, this article proposes a novel collaborative expansion planning scheme for integrated cooling and power system. Firstly, to increase the regulation flexibility, a novel cold energy supply system is designed, where ice making stations and trucks are used to produce and deliver ices to multiple terminal ISACs. On this basis, taking the capacity of the wind turbines (WTs), large ice makers (LIMs), and trucks as configuration decisions, an optimal expansion planning model is established considering wind generation uncertainties. This model is converted into a classic mixed-integer second-order cone programming (MISOCP) problem using linear techniques, and efficiently solved by the Benders decomposition method. Finally, Shapley value method in economics is used to fairly distribute the revenues between the grid operator (GO) and ISAC owners. Simulation studies on IEEE 14-node distribution network indicate the proposed expansion model is effective and beneficial.

The development of integrated electricity and heat system (IEHS) promotes the renewable energy penetration and the complementary coupling between the electric power system (EPS) and the district heat system (DHS). The efficient energy flow calculation (EFC) in the IEHS has become a hotspot as the system scale and complexity increase. This paper firstly constructed the dynamic DHS model using Euler difference scheme. On this basis, the fast decomposed method is proposed to decompose the system with various scales and topologies, which improves the computation efficiency. Moreover, the modification mode is then developed to modify the EFC results in the decomposed systems and ensure the accuracy. Numerical simulation verifies the accuracy of the proposed method and its superiority in computation efficiency.

The problem of fossil energy shortage and pollution has become increasingly prominent. In China, government-led electric energy substitution projects are being carried out in nationwide, aiming at the end of energy consumption links, using electricity instead of coal-fired and oil-fired energy consumption, in order to optimize the energy structure and achieve the goal of energy conservation and emission reduction. Aiming at the planning and benefit sharing of electric energy substitution project, this research first designs the planning mechanism of electric energy substitution for productive users, analyses distribution network planning, transformation subsidy and so on, and puts forward three schemes. Secondly, based on the cooperative game theory, the benefit allocation model of electric energy substitution project is established. Finally, we take the flue-cured tobacco project about replacing coal with electricity in three areas of Yunnan province as an example to analyze, optimize the game strategy, and put forward three indicators to measure the benefits of the participants in the project. The pollution reduction situation that can not be converted into economic benefits is counted. The modeling results show that the density of users geographically will directly affect the cost of the distribution network transformation. The coal flue-cured tobacco heat loss and serious pollution, after optimization, power grid enterprises can quickly recover investment.

The rise of blockchain technology has injected new vitality into the energy market. At present, blockchain projects for distributed photovoltaic power generation and carbon trading are rapidly emerging, but due to the barrier of two markets and the independent operation of such projects in two chains, the two market values cannot be two-way circulation, which is not conducive to the expansion of power trading business and the scale of carbon market. This paper proposed a joint operation mechanism of cross-chain trading, combined distributed photovoltaic power generation market and the carbon market by the blockchain technology. The novelty is to construct two chains which includes the mainchain and sidechain that enables the two markets to share data and circulate value, and to design a two-way anchoring method that achieves equating between carbon trading and electricity trading by cryptocurrency. The simulation studies took the improved IEEE 33 system as an example to simulate transactions on the Ethereum platform, and technically verify the feasibility of cross-chain transactions in these two markets, and use Ether as the settlement currency.

The cross-bonding is the most common shield/sheath-bonding system now in use on single-conductor shielded power cables for long distance power transmission. But the complex bonding brings great challenges to the assessment of cable ageing conditions. This paper proposes a non-intrusive ageing assessment method using the transient disturbances originating from the system. The cable relative permittivities, instead of the traditional dielectric loss angle, were extracted from the responses of the transient disturbances to character the ageing state more sensitively. The decoupling analysis of the cross-bonded cable and the corresponding relative permittivity identification model were investigated. Since the transient disturbances appear naturally and frequently, a continuous tracking of the cable ageing conditions can be established without interferences to the power system. Moreover, only the magnitudes rather than the phase angles of the cable currents/voltages are required in this method, which effectively simplifies the functions of the signal acquisition devices. The proposed method provides a new idea to assess the ageing conditions of the cross-bonded cables, and has the potential to be applied in industry.

The microgrid is considered to have bright prospects in the future for its advantages of high economic benefits and environmentally friendly and alleviate the antinomy for energy’s supply and demand. Due to the introduction of renewable energy such as wind power into the microgrid, the intermittent, random, and unpredictability of its output makes it difficult to control the frequency when the microgrid operates in the isolated islands. In order to reduce the frequency fluctuation, this paper proposes a secondary frequency control strategy for isolated microgrid based on the linear active disturbance rejection control (LADRC) technology. Extended state observer (ESO) is used to estimate the extended state online and compensate the disturbance estimation actively so that the disturbance can be eliminated quickly and the frequency stability can be maintained. In addition, considering the demand response, the influence of different demand response coefficients on frequency control is analyzed. By a series of trial declarations, the LADRC control strategy can effectively suppress the frequency oscillation, and after adding the demand responses, the response speed can be faster than the traditional frequency modulation, reflecting its better robustness and stability. The simulation based on the frequency response model of AC microgrid results shows the effectiveness of the proposed method.