Mixed integer linear programing based approach for optimal planning and operation of a smart urban energy network to support the hydrogen economy

Highlights

• MILP based model of energy hub network developed.

• The benefit of a distributed hydrogen production is presented.

• A case study comprising of four energy hubs are considered.

• The greenhouse emissions and urban pollution offsets are investigated.

• Optimum results are compared with four scenarios to show its performance.

Abstract

The future of urban energy systems relies on the transition to “smart energy networks” which incorporate energy storage with renewable energy sources such as wind and solar. Hydrogen provides a desirable energy vector for both energy storage and exchange of energy between energy hubs within a smart energy network. This paper aims to develop a generic mathematical model for the optimal energy management of future communities where hydrogen is used as an energy vector. An energy hub is a novel concept that systematically and holistically considers the energy requirements of both mobility and stationary loads. In order to perform optimization studies, the minimization of capital cost of hydrogen refueling stations and operation and maintenance cost of all energy hubs within the network are considered. The modeling and optimization are undertaken and carried out in the General Algebraic Modeling Software (GAMS). The case study considers four energy hubs consisting of a commercial building, school, residential complex, as well as hydrogen refueling stations. The study investigates the optimal operation of different energy conversion and storage technologies in order to meet the demand of energy. The results showed that the optimum size of electrolyser and hydrogen tank for supplying the hydrogen demand in the energy hub network is two 290-kW electrolysers and four 30-kg tanks, respectively. The average daily strike price of electricity by which the electrolyser operates is $0.036 per kWh and will not operate when the average hourly Ontario electricity price is higher than $0.13 per kWh. The levelized cost of hydrogen produced by hydrogen refueling station is estimated to be $6.74 per kg. Moreover, the optimal operation of energy conversion and energy storage technologies within each hub and the optimal interaction between energy hubs with in the network are also investigated. In addition, it is shown that distributed hydrogen generation is more preferable than H₂ delivery in environmental and economic comparison.

Introduction

The use of distributed generation is expanding with the increase in renewable energy generation and a move towards developing a ‘smart energy network’ [1]. Also, the energy demands of a community must be considered in a more holistic and comprehensive manner, thus electrical, heat and transportation demands must be taken into consideration in addition to the stationary electrical load. Mainly with the commercialization of hydrogen fuel cell vehicles starting in 2015, plug-in hybrid vehicles, and electric vehicles, transportation energy demand must be considered with an overall energy system. Communities and networks of facilities with distributed generation technologies present different energy flow problems. Serious consideration to the management of energy must be analyzed when using different energy sources such as natural gas, electricity, heat, and hydrogen. Energy vectors within a network can be exchanged and perform other key functions, such as energy arbitrage and energy storage. A distributed combined heat and power (CHP) system (i.e., a turbine operating on natural gas) can simultaneously produce electricity and heat, with an electrolyser operating within the network can satisfy the demands of both hydrogen transportation fleets and part of heat load. A key aspect to create an affordable and cleaner energy system is the development of an integrated, multi-node system with multiple energy vectors. In this system, electricity, fuel, heat, cooling, and transportation, optimally interact with one another at various levels; e.g., in a local district, city or region. This gives an opportunity to improve the technical, economic, and environmental performance of the system in comparison with traditional energy systems where different sectors are implemented independently. This improvement can take place at different stages, such as at the operational and the planning levels [2], [3]. Therefore, an integrated study of energy systems is required to properly take into account energy conversion technologies and possible energy storage of the different energy carriers to reach a more efficient level of system operation.

Traditionally, energy resources such as natural gas and electricity have been used independently. However, in the recent years there is a growing appeal to supplement the isolated use of energy for an integrated form of energy usage to improve efficiency and reduce environmental impact. Energy integration is increasingly sought after particularly in the wake of two core challenges: the rise of energy demand and environmental concerns such a climate change [4]. The necessity of smart energy networks through the integration of different energy carriers including heat, electricity, hydrogen, as well as bio energy was discussed by Orecchini et al. [5]. The integration of natural gas and electric networks for optimal power flow for the best system operation was proposed by An et al. [6]. Syed et al. [7] developed a simulation model for the operational study of a fleet of plug-in fuel cell vehicles and a commercial building based on novel energy hub concept. The input energy flow of the proposed hub is electricity. Hydrogen and electricity are the energy output for the commercial building and vehicles in fleet. However, the optimization was not carried out in this work. Sharif et al. [8] presents a simulation model for an energy hub including natural gas and renewable energy as input carriers to the model. The aim of this work is to combine different energy generation technologies, which are evaluated in terms of the production of total energy, the unit cost of produced energy, and the amount of generated emissions. Maniyali et al. [9] presents an energy hub comprising of renewable energy, hydrogen storage facilities to supply hydrogen and electricity for different sectors such as transportation and industry for long term planning in comparison with the contemporary coal-based power generating facilities. However, the optimization and energy network was not carried out in these works.

The move towards a hydrogen economy, whereby hydrogen is used for transportation and utility-scale energy applications is of great deal of interest to both industry and society at a whole. Hydrogen is favored since it can be easily generated from renewable sources of energy as well as carbon free nuclear energy, and quickly refuels vehicles providing the extended range desired by consumers [10]. Moreover, hydrogen may act as an energy vector for applications related to transport reduces environmental issue such as greenhouse gas emission and urban pollution [11], [12]. Salvi and Sabramanian reviewed the hydrogen based energy systems for the transportation sector. They discussed about the different methods of hydrogen production, its significance for the transportation systems, its safety concerns, and hydrogen vehicles [13]. Ajanovic did the economic feasibility study of usage of hydrogen based renewable energy for the transport sector in Austria [14]. Ball et al. developed a modeling approach in order to integrate hydrogen in to German energy systems [15]. In addition, hydrogen as an energy carrier is desired even from the outlook of a power grid management and competitive markets for its great energy storage potential and its cost difference between peak and low price hours, respectively [16]. To clarify, hydrogen can be produced through the low cost off-peak power and can be consumed by hydrogen vehicles or it can be stored and converted to electricity when the price of power is high [17]. However, there are still challenges to setting up the hydrogen economy in the fields of production, distribution, storage and consumption [18]. Given the many potential advantages of hydrogen as an energy carrier, there is a substantiated basis to further investigate and study hydrogen use as an enabling technology for smart energy networks. A possible future achievement of the hydrogen economy would exist in the context of integrated energy systems where all the energy carries are networked and have synergy among one another.

In urban areas where deteriorating air quality is a serious concern, hydrogen fuel offers a zero-emission option for light-duty vehicles to alleviate the impact of environmental pollutants. The implementation of hydrogen vehicles within the transport sector will help to improve the operation and efficiency of electricity grids and promote the development of renewable energy sources. Cascales et al. [19] pinpointed the environmental assessment of the displacement of conventional vehicles with fuel cell vehicles which are supplied by electrolytic hydrogen generated during the off peak power grid in Spain. Long term planning for the deployment of hydrogen refueling station in the north eastern America was carried out by Tsuda et al. [20]. Zhao et al. [21] investigated the feasibility study of hydrogen refueling stations powered by renewable energy sources using dynamic system approach. Different models of alternative fuel vehicles and their related refueling infrastructures are reviewed by Gnann et al. [22]. As part of an integrated energy system, a comprehensive and detailed study of hydrogen network comprising of converters, storage was conducted by Hajimiragha et al. [12]. The results of the study concluded that the integration of electrolysers with the hydrogen storage devices yield beneficiary results in the context of a high efficiency energy pathway, hydrogen production and storage is viable in intervals with low-cost electricity. The study conducted by Hajimiragha et al. [12] examined the impact of external hydrogen cost, size and efficiency of hydrogen production plants on integrated energy systems with regards to the operation [23]. Note that other advantages of hydrogen as an energy storage vector are that the capacity of the hydrogen generation, hydrogen storage, and energy generation are decoupled, in scale and location. For example, one could have small generation capacity that runs for a long period over low electricity demand period (i.e., when electricity is low cost), and very large hydrogen storage that could service a back-up generation capacity or a refuel capacity for the fleet, or transferred to another energy hub. The above mentioned studies have been focused on the hydrogen refueling station itself or the operation of hydrogen networks alone.

Energy hubs are implemented to simultaneously monitor integrated energy sources. An energy hub acts as an interface between different energy sources, such as electricity, natural gas, heat, and hydrogen using energy storage and conversion technologies [24], [25]. Each hub contains various energy conversion technologies, such as transformers, combined heat and power systems, electrolysers, as well as fuel cells, and energy storage technologies, such as batteries, hydrogen and potentially compressed air. Since different energy conversion technologies inside the hub have different characteristics and costs, an optimal network including energy storage and energy exchange system should be studied. The proposed energy hub networks consider the optimal contribution and exchange of each energy source and energy carrier in order to meet the required demand at minimum cost. In this work energy hub is considered as a novel concept that systematically and holistically considers the energy requirements of both mobility and stationary loads. Each hub is an energy model of one part of a given community or region, and could include facilities such as a commercial center, residential complex, a hospital, or even a fuel stations. These hubs can transfer the surplus energy flows from one node to another which may optimally employ the energy. The energy vectors can be in the form of electricity, heat, and hydrogen. The input energy flow to each energy hub can be from fossil fuel resources such as natural gas, or renewable sources like solar. The energy demand of each hub is in the forms of electricity, heat, and hydrogen. Different energy conversion technologies such as distributed energy systems more specifically, combined heat and power systems, photovoltaic, and solar collector are considered. Hydrogen can be generated from electricity via electrolyser and can be stored and fed to other hub vehicles or industrial demands, whenever required. Moreover, these hubs are also connected with the electricity grid.

Although some of aforementioned studies deal with the simulation or optimization of an individual energy hub or hydrogen refueling station alone, the optimization of energy hub networks along with the consideration of hydrogen infrastructure in urban energy systems has rarely been studied, simultaneously. Herein the modeling and optimization of a network of energy hubs, with an emphasis on developing hydrogen infrastructure in urban energy systems, is studied that is a new approach for energy management of the future urban energy systems. Due to the integrated nature of energy hubs, there is a potential to model and optimize different energy flows simultaneously. The production and use of hydrogen are considered in urban energy systems, where, grid electricity, natural gas, as well as solar energy are the main energy sources for the smart energy network, and electricity and hydrogen, and thermal energy are demands. The model of an energy hub found in this paper utilizes a framework created by Geidl [25], while focusing specifically on the hydrogen production and utilization, and distribution in the smart energy network. This work also employs an optimization based framework in order to develop the desired operation and technology configurations.

The remaining sections of this paper are organized as follows. In the 2nd section, the problem and optimization goals are described. Next, the mathematical modeling approach to optimize the network of hubs is described. For the better comprehension, in the 4th section, the model is applied to a case study of four energy hubs working together. Then the results of the optimization and the comparison results are presented. In the final section, the concluding points are drawn.