Integrated Energy Network Research Articles

A Graph Theory-Based Method for Regional Integrated Energy Network Planning: A Case Study of a China–U.S. Low-Carbon Demonstration City

With the significant attention on global climate change, regional integrated energy systems (RIES) in low-carbon city planning has become one of the most important ways for global cities to achieve the goal of energy conservation and emission reduction. However, the planning strategy used in the primary stage of RIES establishment will greatly affect the system economy and environment. In view of the lack of planning guidance mechanisms for the large-scale RIES in China, a method for RIES preliminary overall planning, focused on energy types and use, is proposed in this paper. A graph theory-based mathematical optimal model was established with the lifetime costs of the whole system as the economic goal, and an improved Prim algorithm was put forward to solve the costs of the transmission and distribution network with the dynamic weight set of pipeline flow. The model was solved by an algorithm based on the idea of a dynamic minimum spanning tree and optimal path planning. The model and method were applied in a China–U.S. low-carbon demonstration city to verify feasibility and validity. The results could help us to comprehensively integrate regional energy and accurately plan future cities.

NG tank contribution in the integrated energy networks

The energy saving and optimal operation of energy networks are essential issues in today's system management studies. A kind of natural gas (NG) storages called NG tank is presented in this Letter. The NG tank is modelled and formulated in the integrated energy network in a way that it can improve the optimal operation of an energy network as well.

Development and optimization of an integrated energy network with centralized and decentralized energy systems using mathematical modelling approach

Decentralized energy generation (DEG) system which characterizes local power generation and utilization are recently getting more attention in energy system planning and implementation because it produces cleaner energy from renewable resources and is capable to avoid significant energy losses during the power transfer from the centralized power plants. These DEGs are however scattered in locations and have intermittent power supply, making it difficult to self-sustain. In this study, a novel integrated energy system consisting of multiple DEGs connected to the existing CEG is proposed. New aspects that are included in the model include the distribution and transmission losses as well as impact of operating load on the heat rate of power plants. Energy storage system were also modelled to operate within the DEG and CEG network. Through a case study demonstration, the capacities of the integrated system were optimized using superstructure-based mixed integer non-linear programming (MINLP) mathematical modelling. The system was also optimized based on economic and energy efficiency to study the effects and trade-off between the two parameters. The results revealed that the optimal system can be obtained with levelized cost of electricity of MYR 0.44/kWh. The result also revealed that biomass and wind energy favours industrial users.

Bi-level Planning Model for Integrated Energy Network in Solid Waste Treatment Park

In this paper, a bi-level planning model was proposed for the integrated energy network in solid waste treatment park to achieve optimal energy planning in the park. Firstly, the factors affecting planning were analyzed from the aspects of energy and environment. Then, the physical architecture of the integrated energy network planning of the solid waste treatment park was proposed, and the typical energy component models of the solid waste treatment park were proposed. This paper took the annual total cost as the first-level target and the annual operating cost as the second-level target, then proposed the bi-level planning model of the integrated energy network. Finally, the advantages of the model were verified by example. The example shows that under the action of the bi-level planning model, the energy, environment and economic benefits of the solid waste treatment park can be significantly improved.

Energy Systems Integration in Smart Districts: Robust Optimisation of Multi-Energy Flows in Integrated Electricity, Heat and Gas Networks

Smart districts can provide flexibility from emerging distributed multi-energy technologies, thus bringing benefits to the district and the wider energy system. However, due to nonlinearity and modeling complexity, constraints associated with the internal energy network (e.g., electricity, heat, and gas) and operational uncertainties (for example, in energy demand) are often overlooked. For this purpose, a robust operational optimization framework for smart districts with multi-energy devices and integrated energy networks is proposed. The framework is based on two-stage iterative modeling that involves mixed integer linear programming (MILP) and linear approximations of the nonlinear network equations. In the MILP optimization stage, the time-ahead set points of all controllable devices (e.g., electrical and thermal storage) are optimized considering uncertainty and a linear approximation of the integrated electricity, heat, and gas networks. The accuracy of the linear model is then improved at a second stage by using a detailed nonlinear integrated network model, and through iterations between the models in the two stages. To efficiently model uncertainty and improve computational efficiency, multi-dimensional linked lists are also used. The proposed approach is illustrated with a real U.K. district; the results demonstrate the model’s ability to capture network limits and uncertainty, which is critical to assess flexibility under stressed conditions.

Operation Optimization of Natural Gas Transmission Pipelines Based on Stochastic Optimization Algorithms: A Review

Operation optimization of natural gas pipelines has received increasing attentions, due to such advantages as maximizing the operating economic benefit and the gas delivery amount. This paper provides a review on the most relevant research progress related to the steady-state operation optimization models of natural gas pipelines as well as corresponding solution methods based on stochastic optimization algorithms. The existing operation optimization model of the natural gas pipeline is a mixed-integer nonlinear programming (MINLP) model involving a nonconvex feasible region and mixing of continuous, discrete, and integer optimization variables, which represents an extremely difficult problem to be solved by use of optimization algorithms. A survey on the state of the art demonstrates that many stochastic algorithms show better performance of solving such optimization models due to their advantages of handling discrete variables and of high computation efficiency over classical deterministic optimization algorithms. The essential progress mainly with regard to the applications of the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Simulated Annealing (SA) algorithms, and their extensions is summarized. The performances of these algorithms are compared in terms of the quality of optimization results and the computation efficiency. Furthermore, the research challenges of improving the optimization model, enhancing the stochastic algorithms, developing an online optimization technology, researching the transient optimization, and studying operation optimization of the integrated energy network are discussed.

A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies

A multi-objective optimisation model, based on mixed integer linear programming, is presented that can simultaneously determine the design and operation of any integrated multi-vector energy networks. It can answer variants of the following questions:What is the most effective way, in terms of cost, value/profit and/or emissions, of designing and operating the integrated multi-vector energy networks that utilise a variety of primary energy sources to deliver different energy services, such as heat, electricity and mobility, given the availability of primary resources and the levels of demands and their distribution across space and time? When to invest in technologies, where to locate them; what resources should be used, where, when and how to convert them to the energy services required; how to transport the resources and manage inventory?Scenarios for Great Britain were examined involving different primary energy sources, such as natural gas, biomass and wind power, in order to satisfy demands for heat, electricity and mobility via various energy vectors such as electricity, natural gas, hydrogen and syngas. Different objectives were considered, such as minimising cost, maximising profit, minimising emissions and maximising renewable energy production, subject to the availability of suitable land for biomass and wind turbines as well as the maximum local production and import rates for natural gas.Results suggest that if significant mobility demands are met by hydrogen-powered fuel cell vehicles, then hydrogen is the preferred energy vector, over natural gas, for satisfying heat demands. If natural gas is not used and energy can only be generated from wind power and biomass, electricity and syngas are the preferred energy carriers for satisfying electricity and heat demands.

Constructing post-carbon institutions: Assessing EU carbon reduction efforts through an institutional risk governance approach

This paper examines three different governance approaches the European Union (EU) and Member States (MS) are relying on to reach a low carbon economy by 2050. Current governance literature explains the operational methods of the EU's new governance approach to reduce carbon emissions. However, the literature neglects to account for the perceived risks that inhibit the roll-out of new low carbon technology. This article, through a novel approach, uses a grounded theoretical framework to reframe traditional risk literature and provides a connection to governance literature in order to assess the ability of EU governance mechanisms to reduce carbon emissions. The empirical research is based on responses from European energy stakeholders who participated in a Delphi method discussion and in semi-structured interviews; these identified three essential requirements for carbon emissions to be reduced to near zero by 2050: (1) an integrated European energy network, (2) carbon pricing and (3) demand reduction. These features correspond to institutionalized responses by the EU and MS: the Agency for the Cooperation of Energy Regulators (ACER); European Union Emission Trading Scheme (EU ETS) and energy efficiency directives and policies integrated into existing MS institutions. The theoretical and empirical findings suggest that governance by facilitation (energy efficiency) fails to induce significant investment and new policy approaches and cannot be relied on to achieve requisite reductions in demand. Governance by negotiation (ACER) and governance by hierarchy (EU ETS) do reduce risks and may encourage the necessary technological uptake. The term ‘risk governance’ is used to explain the important role governance plays in reducing risks and advancing new technology and thereby lowering carbon emissions in the energy sector.

Oil, Carrots, and Sticks: Russia's Energy Resources as a Foreign Policy Tool

This paper will explore the growth of Russia's energy leverage in recent years, a source of power which Russia has used both to reward its friends and punish its enemies. It will briefly trace the origins of this power in the integrated energy networks of the former USSR and Warsaw Pact. It will then examine recent cases of the use of ‘oil power.’ Both positive and negative linkage will be considered. Some states-such as Armenia, Belarus and the Ukraine under President Kuchma-have been favored with heavily subsidized energy. Others-such as Georgia, Moldova, the Baltic States and the Ukraine under President Yushchenko-have been targeted by supply disruptions and punitive price increases. Russia's new ‘petro-power’ is of great importance today, and not just for its immediate neighbors: like other ‘petro-states,’ Russia is likely to gain ever more power as oil and gas become scarcer in the future.