Energy Demand Side Management within micro-grid networks enhanced by blockchain
Graphical abstract
Introduction
Globally over 80% of currently used energy is sourced from fossil fuels; global energy generation and use contribute to two-third of greenhouse gases (GHGs) [1]. Therefore the energy sector is sitting at the core of combating climate change. Over the next decades the projected 50% increase in global population with non-OECD economic growth is expected to bring over 30% increase in energy demand by 2050 [2], which increases the supply-demand stress. The significant roles of renewables in the energy sector transition to meet Paris Agreement climate targets and sustainable development goals (e.g. affordable and clean energy, job creation and economic growth), have been highlighted by the International Renewable Energy Agency (IRENA), which analysed the feasible targets for renewable penetration in overall energy-use (65%) and electricity generation (80%) by 2050. In particular, the advancement in renewables integration into micro-grids potentially offers reliable electrification to power diverse users in autonomous areas and provides strategic electric grid configurations for sustainability development for both on-grid and off-grid modes. Either interconnected with the main utility grids or operated in islanding mode, micro-grid infrastructures featuring multiple distributed generation units and loads operating as coordinated systems, represent emerging platforms for the increasing share of distributed energy systems over the next decades [3]. Despite the advantages of low-carbon and cost-competitiveness, the coupling of renewables with micro-grids, and particularly the interconnected micro-grids, remains untapped in many regions and is projected to be a growing market worth more than $200 billion annually [4].
The micro-grid is particularly important for the Global South (referring to the developing countries, less developed countries, and less developed regions) which is facing increasing energy supply–demand stress with rapid urbanization and an increase in quality of life [5]. As a result of this process there has been a rapid increase in the demand for electricity and a similar trend is expected to continue in future, with a 20% increase in demand forecast in next 10 years [6]. However, access to adequate, reliable and affordable energy remains a major problem. In many cases the growth in demand is much faster than the increase in energy supply due to the time required to build new generation capacity, lack of funding and socio-political reasons [7]. Consequently, many Global South countries are facing severe supply shortfalls that have resulted in massive rolling black outs, which has caused huge economic loses and devastating influences on citizens’ livelihood. Along with funding constraints, the lack of secure and stable energy infrastructure is a result of poor planning, management and maintenance of resources [8]. Distributed energy infrastructure serves as a promising solution to deal with the energy access and scarcity issues, and offers the potential to include small-scale renewable technology. However, when formed as a micro-grid to power demand through renewable resources, it faces many operational challenges e.g. resource seasonality and intermittency which make it difficult to guarantee the reliable and efficient supply, especially in standalone mode not connected to the electrical grid [9]. Demand side management (DSM) techniques offer a promising strategy to match demand with resource availability in the given context. By using DSM, demand can be manipulated to match the supply and hence the existing infrastructure can be utilized more efficiently [10]. The energy system is of heterogeneous nature consisting of multiple consumers each having their own energy usage patterns which makes the system diverse and adds greater flexibility to the system in terms of load scheduling [11]. Game theory modelling is ideally applied to address this problem as it considers the different energy scheduling strategies and payoffs of each player and provides a more holistic approach to examine the interconnection between individual players and the whole system [12]. Furthermore, solving the problem in a centralized fashion becomes increasingly challenging due to the wide scope of the problem involving numerous customers and a diverse range of electrical devices. Game theory turns the nature of the problem from centralized to distributed, thereby making it computationally tractable [13]. Moreover, ICTs and smart metering technologies have enabled the automation of DSM programs, making the process user friendly and easier to manage. At the same time, a digital system that can be accessed remotely enables data collection that can be used for effective operation, planning and development of the energy sector [14].
Section 2 in this paper first presents a comprehensive literature review of state-of-the-art research on the distributed energy systems, blockchain technologies and applications. Next, in Section 3 the methodology and model are presented, followed by a case study in Section 4 which demonstrates the model functionality and shows how blockchain can support this framework. Finally, conclusions and future work are discussed in Section 5.
Section snippets
Distributed energy management
There has been increasing research interest and publications on the optimization of renewable micro-grids and DSM, where diverse approaches have been pursued, e.g. mixed integer liner programing (MILP) [15], dynamic programming [16], evolutionary algorithms [17], hierarchical framework [18] and game theoretical agent-based approaches. Jin et al. [19] formulated a multi-objective optimization model to account for the prevailing constraints and trade-off between flexible-loads utility. Prete and
Methodology
In this section the overall methodologies for the optimization of energy supply and demand matching are presented, with a game theory based model for DSM under different supply constraints. It provides detailed mathematical formulation of the model and key assumptions adopted in scenario runs.
Micro-grid case study
The demand side energy management system evaluated in this study is outlined in Fig. 3. The case study evaluates a series of consumers belonging to different groups, modelled with multiple appliances and storage capacities owned by each individual. The energy storage component plays a key role in energy trading within the distribution network.
Conclusion
We have presented a game theoretic model for DSM that incorporates storage components and takes into account the supply constraints in the form of power outages. In the context of developing countries and the Global South, smart energy control and demand side management can be vital to bridge the continuously increasing supply and demand gaps, especially given the unreliable national electricity grids which may have multiple load shedding events. Not only is DSM in a micro-grid a meaningful
Acknowledgements
S. Noor acknowledges the financial support by the Commonwealth Scholarship Commission in the UK. X. Wang thanks the MOE AcRF Grant in Singapore for financial support to the project “Pathways to resilient Food-Energy-Water-Waste Nexus” (R-279-000-537-114). M. Guo thanks to UK EPSRC for financial support to the project 'Resilient and Sustainable Biorenewable Systems Engineering Model (EP/N034740/1). We also thank N. Shah and L. Li for the helpful discussions and support.
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Contribute equally to this paper (as co-first authors).