Distributed Energy Technologies Research Articles

Evaluation of Technological Configurations of Residential Energy Systems Considering Bidirectional Power Supply by Vehicles in Japan

To reduce CO2 emissions in the residential and transportation sectors, distributed energy technologies, such as photovoltaic power generation (PV), stationary storage batteries (SBs), battery electric vehicles (BEVs), and vehicle-to-home (V2H) systems, are expected to be introduced. The objective of this study was to analyze the impact of the installed capacity of PV and SB, the type of vehicle, and their combination on the economic and environmental performance of the total energy consumption of residences and vehicles. Thus, this study developed a model to optimize the technological configuration of residential energy systems, including various vehicle types and driving patterns. The simulation results showed that it is more economically and environmentally efficient to install a BEV and a V2H system in households with longer parking times at the residence and to install an SB in addition to these technologies in households with shorter parking times at the residence. Furthermore, comparing a gasoline vehicle and an SB, the most economical combination, with a BEV and a V2H system and with a BEV, a V2H system, and an SB, estimated the carbon tax rate necessary for cost equivalence. The result indicated that the carbon tax rate needs to be increased from its current level.

Distributed energy technologies, decentralizing systems and the future of African cities

Within global debates, decentralization with respect to renewable electricity is positioned as pivotal in overlapping calls for decarbonization, energy access and just transitions. The promise is that technologies that are smaller and distributed will deliver a range of benefits, including enabling infrastructural innovations and expanding sustainable access, notably by empowering local authorities. While shifting to low-carbon systems is imperative, in this paper we call for attention to the complexity, opportunities and risks of commonly celebrated experiments in distributed electricity technologies when applied to African contexts. We draw on the case of Uganda, unpacking a series of four innovative electricity projects currently under way. For each case, we look at the actors involved and the imagined relationship between the projects and the incumbent grid. From these cases, we argue that, in this African context characterized by contested urban governance and fragmented networks, careful attention to supporting urban scale institutional and infrastructural development is necessary, although in many cases bypassed.

CO-OPTIMIZATION OF DISTRIBUTED ENERGY RESOURCES UNDER TIME-OF-USE PRICING FRAME

Abstract Distributed energy systems (DES) have been considered as a promising solution due to the benefits on efficiency and environment sides. However, despite the rapid development of distributed energy resources and technologies, the share of the distributed energy generation is still small in comparison to that of traditional generation. Time-of-use (TOU) pricing can be an important incentive strategy to encourage the penetration of distributed energy systems. In this paper, a multi-objective optimization considering the time-of-use pricing impacts is proposed to determine the optimal configuration and capacity of distributed energy system involving different technologies including solar photovoltaic (PV), solar thermal collector (STC), combined heating and power system (CHP), and integrated energy storage (ES). The distributed energy system is designed to satisfy the electric and thermal load of commercial buildings (large hotel and medium office) partially or entirely. The proposed multi-objective optimization is utilized to configurate the optimal combination of distributed energy technologies as well as the system capacity to reduce both the cost and environment impact of the system in different locations. Results show that the proposed optimization method can achieve a trade-off between system cost and environment impact based on the existing time-of-use pricing structure.

Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs.

Neural-assisted HVACs optimal scheduling for renewable energy communities

Renewable energy communities (RECs) show a high potential for the efficient use of distributed energy technologies at local levels according to the Clean Energy Package of the European Union. Nevertheless, many problems are encountered during the planning phase of a REC because a large number of decision variables should be considered depending on the types of community participants and their load profiles. Moreover, the load schedule is fundamental with the aim of maximizing the energy shared within the community and the economic revenue of the REC. This is the main objective of this work that deals with the problem of optimal scheduling for electrical heating and cooling systems in a university lecture building included in a renewable energy community. The conditioning systems are significant electrical loads that can be scheduled both to reduce the energy requirements of the buildings and to synchronize energy injection and withdrawal from the grid, achieving energy self-consumption. The energy demand for the building is estimated using a specific simulation environment (EnergyPlus) which is experimentally validated with a campaign of measurements. From this software, a training dataset is created and used to implement a computationally lean neural network to represent through a black-box model the thermal-electrical behavior of the lecture building. Through the use of this neural model, the building thermal set points are processed by an optimization algorithm to maximize the economic revenue of the REC, while retaining the comfort boundaries of the building. The innovative proposed strategy is applied on a yearly simulation of the REC resulting in reduced energy required for thermal conditioning, higher cash-flows associated with the energy market and a smaller carbon footprint of the community.

Redefining business models for the energy transition: Social innovation and sustainable value creation in the European energy system

Business as usual in the energy sector has become more challenging in the EU as distributed energy technologies and supportive policy included in the EU Energy Package have meant that new types of stakeholders, including citizens, citizen collectives, and municipalities, can participate in the energy system in innovative ways. Their “new” relationships, behaviors, and actions in the context of the energy transition, vis à vis the existing system, are often referred to as social innovation in energy systems. Socially innovative activities may deliver products and services similar to those of incumbent energy business models e.g., sustainable energy generation, but also create social value that traditional energy business models may not. This paper views these socially innovative activities using elements of a sustainability-oriented business model – the business model for sustainability (BMfS) – analyzing them in terms of their goals, involved stakeholders, and value creation processes. Analysis is conducted in case studies that span Western and Eastern Europe, using a mix of primary data (semi-structured stakeholder interviews) and secondary data (online materials). In addition to showcasing how socially innovative activities may contribute to value creation processes in the context of an energy business model, the case studies also depict differences in the extent and types of social innovation that can occur in the European context, with some reflection on how infrastructure and historical dynamics may play a role in these differences. I conclude with some reflections on definitions of business models and the applicability of the BMfS for a decentralizing energy system.

PROTECTING THE FUTURE OF CLEAN AND DISTRIBUTED ENERGY TECHNOLOGIES THROUGH COLLABORATIVE CYBER THREAT ANALYSIS AND INFORMATION SHARING

A changing climate, aging infrastructure, technological innovation, and cyber risks (or threats) are driving changes to our energy infrastructure at an unprecedented pace. These changes often involve significant digitization and continuously rely on external data to make smart, rapid adjustments. These changes also mean new and increased connections to partners, and ultimately increased cyber risk. Cyber threat information sharing helps reduce risk through early warning of shared threats. Unfortunately, modern information sharing is not living up to its promise. This article reviews current and historical approaches to cyber threat information sharing, identifies gaps and areas where current approaches fall short, and proposes a path forward leveraging a collaborative approach to secure our energy infrastructure of the future.

How do macroeconomic dynamics affect small and medium-sized enterprises (SMEs) in the power sector in developing economies: Evidence from Turkey

Developing economies are currently projected to hold a major share of the global energy demand in the upcoming decades, giving them a key role in addressing climate change. However, new renewable energy investments in these countries have so far been relatively slow. A specific set of challenges dominate the investment environment in developing countries, including higher exposure to macroeconomic and political risks, uncertainties due to climate change, limited domestic manufacturing capabilities, and heavy reliance on foreign debt in capital investments. These factors tend to disproportionately affect small and medium-sized enterprises (SMEs) which currently hold a sizeable share of renewable and distributed energy technology investments. Not only does this impact the viability of energy transition, but also has important energy justice and local economic development implications – an overlooked subject in the literature. Using a rich, novel dataset and panel data methods, this paper estimates the effect of a set of key macroeconomic variables on the capital structure and investment outcomes of SMEs within the Turkish power sector. Our results indicate that unfavorable macroeconomic conditions, which lead to a significant growth in liabilities and increased risk of bankruptcy, can cause a slowdown in power sector SME investments despite the prevalence of subsidies.

Resilient Buildings and Distributed Energy: A Grassroots Community Response to the Climate Emergency

The severity and incidence of extreme weather events are increasing with climate change. In particular, wildfires are becoming more frequent, more intense, and longer lasting than before. Fuelled by long periods of dryness and high temperatures, the Australian wildfires of 2019/2020 were record breaking in terms of destruction and chaos. Rural communities were severely affected by power cuts disabling access to essential services. Following the wildfires, a concept for energy resilient public buildings (“Emergency Distributed Energy System”) emerged as a grassroots community idea from the wildfire-affected area of Gippsland, southeast Australia. A combination of desktop and empirical research explored international examples of energy resilience and climate mitigation, the local services and technologies that are needed in Gippsland, and the legal and regulatory challenges and enablers in Australia. The findings were informed by case studies of responses to natural disasters that included California and Greece (wildfires), New Zealand (earthquake), and India (cyclone). The results determined that community resilience can be increased by offering a more reliable electricity supply that would support greater social, political, and economic structures. The deployment of resilient energy systems should be driven by political will, economic incentives and working with communities to support a concerted shift towards low-emissions and distributed energy technologies.

Development of street lighting systems based on projects in the field of energy conservation and the use of alternative energy sources

The article presents the results of the analysis of the current electricity consumption in different countries. Various directions and approaches to reducing the carbon footprint have been analyzed, which have shown the high importance of implementing projects in the field of energy conservation and alternative energy. It has been established that the implementation of these projects will allow not only to reduce the harm caused to the environment, but also to obtain a significant economic effect due to energy conservation and the use of distributed energy technologies. An example of the implementation of projects for the modernization of street lighting systems in the Smolensk region, based on the use of energy – saving technologies and solar panels, is considered. The results of the analysis showed that the main difficulty in the implementation of projects in the field of development of street lighting systems on the basis of this approach is associated with the lack of sufficient financial resources, which is due to their high science intensity. Various mechanisms and practices of attracting investments in these projects in the USA, Germany and Russia were considered.

A blueprint for capturing grid value in a decentralized electricity sector

This study addresses the question of how the electricity grid can best be priced, in the context of disruptive technologies, increasing decentralisation of the power sector and new business models. The emergence of business models can affect the design of tariffs, but at the same time, tariff design can trigger new business models as they can nudge adoption towards certain technologies. Network tariffs have traditionally been established using a cost accounting method. Due to its cost structure, network tariffs are second best constructs, as marginal cost pricing does not lead to cost recovery. Second best solutions, in all probability, will overcompensate some inputs which in turn will be overused (the Averch-Johnson effect). New distributed energy technologies that perform better in these overcompensated inputs will therefore see a higher penetration in the market. Penetration of some technologies over others in a previously monolithic vertically integrated power sector will open up new customer needs and therefore business opportunities. Each resulting business opportunity would make use of the grid differently from which it was originally conceived, and at one extreme, they can bypass it altogether. We provide a framework of analysis that leads to the pricing of the services provided by the electricity grid for each new business opportunity.

Distributed Generation and Renewable Energy Integration into the Grid: Prerequisites, Push Factors, Practical Options, Issues and Merits

Power system operators are in search of proven solutions to improve the penetration levels of distributed generators (DGs) in the grid while minimizing cost. This transition is driven, among others, by global climate concerns, the growing power demand, the need for greater flexibility, the ageing grid infrastructure and the need to diversify sources of energy production. Distributed renewables would not easily substitute the conventional electric grid system, perhaps because the latter is a well-established technology and it would not be prudent to abandon it, while the new distributed renewable energy technologies are generally not adequately developed to support the total load. Thus, it is becoming increasingly necessary to consider sustainable options such as integrating renewable energy sources into the existing power grid. This study is a review that is mainly hinged on distributed generation (DG) classification, the challenges of DG to grid integration, practical options used in DG integration, lessons learned from some countries with successful DG to grid integration, push factors in the growth of DGs and the merits of DG to grid integration. These standpoints of DG to grid interconnection are critical in conducting grid planning and operational studies, which should be conducted in strict observance of aspects such as optimal technology selection, optimal capacity and a suitable connection point of DGs in the network. Therefore, the perspectives highlighted regarding DG can assist power system engineers, developers of DG plants and policymakers in developing a power network that is stable, efficient and reliable.

Operational performance and grid-support assessment of distributed flexibility practices among residential prosumers under high PV penetration

This study explores the impacts of increased photovoltaic (PV) penetration on a real-world power grid. Detailed operational scenarios of existing distributed energy technologies, including grid-tied PV, heat pump, micro-cogeneration, and battery systems among smart residential prosumers are examined using smart meter data. Then, to quantify the grid-support interactions of the decentralized electricity generation and consumption under high grid PV penetration, we introduce grid-support indicators to recognize their induced month-to-month variations based on the dynamic grid spot trading price and carbon emission density profiles. The results show that increased electricity consumption is attractive when the flexible consumption is shifted to a low grid spot trading price and carbon emission intensity period. The grid-support benefits of distributed generators are improved when their output enables a reduction in imported electricity during the grid residual load peak period. The direct simple integration of distributed PV generation makes it difficult to achieve grid-support operation at high solar penetration levels. The analysis results provide insight into the favorable scheduling of the heat pump consumption for time periods corresponding to a large quantity of available on-site PV generation to improve the grid-support performance. The results would help policymakers govern grid-support assets more equitably from a system-level perspective.

Mixed-integer linear programming based optimization strategies for renewable energy communities

Local and renewable energy communities show a high potential for the efficient use of distributed energy technologies at regional levels according to the Clean Energy Package of the European Union. However, until now there are only limited possibilities to bring such energy communities into reality because of several limitation factors. Challenges are already encountered during the planning phase since a large number of decision variables have to be considered depending on the number and type of community participants and distributed technologies. This paper overcomes these challenges by establishing a mixed-integer linear programming based optimal planning approach for renewable energy communities. A real case study is analyzed by creating an energy community testbed with a leading energy service provider in Austria. The case study considers nine energy community members of a municipality in Austria, distributed photovoltaic systems, energy storage systems, different electricity tariff scenarios and market signals including feed-in tariffs. The key results indicate that renewable energy communities can significantly reduce the total energy costs by 15% and total carbon dioxide emissions by 34% through an optimal selection and operation of the energy technologies. In all the optimization scenarios considered, each community participant can benefit both economically and ecologically.

A distributed energy equipment with highly efficient heat dissipation

Distributed energy technology is an important development direction of the world energy technology in the future [1]. It has the characteristics of high energy utilization efficiency, small negative impact on the environment, improving the reliability of energy supply and good economic benefits. At present, China’s distributed energy technology is not mature enough. Aiming at the heat dissipation problem of distributed energy technology, we propose a method of using natural rainwater air cooling to realize the efficient heat dissipation of distributed energy equipment. It provides a reference for the development of distributed energy technology.

The Week the Lights Went Out in Texas

In previous issues this journal has reported on the need for modernization of the electricity grid and investments in innovation and cleaner distributed energy technologies as critical components of a resilient grid, particularly as states and cities across the country are setting aggressive climate mitigation and decarbonization goals. With increasing frequency society is living through catastrophic weather events, including more frequent and damaging hurricanes and tornadoes, polar vortexes and widespread blizzards with subzero temperatures, forest fires followed by torrential rains and flooding, and record‐setting heat indexes and drought. Natural gas and electric utilities work across the country to monitor weather closely and work hand‐in‐hand with weather forecasters, local Emergency Response Offices, be they state and/or municipal, preparing in advance for severe weather events. Utilities are adept and efficient at entering “storm response mode” – to prepare the electricity grid and ensure utility crews are on hand and at the ready to restore power as quickly as possible to its customers. State and federal regulators require this, and if utilities fail in preparation or response, they can face significant penalties and fines and in some instances potentially lose their franchise operating license. While it is rare to lose a franchise, threats are often made by political leaders when frustrations boil over and constituents are completely frustrated with a utility's response.

Identifying and Regulating the Environmental Risks in the Development and Utilization of Natural Gas as a Low-Carbon Energy Source

In response to climate change and energy transition, natural gas has been rapidly developed as a relatively low-carbon energy source by many countries. However, there remain environmental risks at different stages in the entire process from exploitation to utilization. Firstly, this article identifies various environmental risks and benefits of natural gas along the entire industry chain from upstream exploitation and midstream transportation to downstream utilization. It is found that, during upstream exploitation, hydraulic fracturing has the worst environmental impact. During the midstream storage and transportation stage, methane leakage is the biggest environmental risk. In the downstream combustion and utilization stage, the risk to environment is less than other energy sources, although there are some greenhouse gas effects and water pollution issues. Thus, this article puts forward some policy recommendations for different stages from exploitation to utilization. In the upstream stage, especially hydraulic fracturing activity, we suggest strengthening environmental assessment management, improving policy standards, creating a water quality monitoring plan, and promoting the innovation of key technologies. In terms of the midstream, besides pipeline laying and site selection, we focus on monitoring the system, including leak detection, quality management of engineering materials, and risk identification and management. When it comes to the downstream, we encourage the application of advanced technologies to improve thermal efficiency and reduce emissions, such as gas-fired related technologies, natural gas recycling technologies, distributed energy technologies, and green and low-carbon service technologies.

Solar panels and smart thermostats: The power duo of the residential sector?

Rising peak demand is a major cause for high emissions from the electricity sector. In this study, we investigate how different combinations of distributed energy technologies affect peak grid load, energy consumption from the grid, and emissions in the residential sector under time-varying prices. To do so, we develop an optimization framework in which households with varied amalgamations of distributed energy technologies minimize electricity costs, amortized capital, and operational costs over a year, with marginally increasing penalties for deviating from room temperature set-points. The four technologies we consider are: solar panels, lithium-ion batteries, ice cold thermal energy storage, and smart thermostats. The study also incorporates a one-parameter thermal model of the home, so that the discomfort penalties can apply to the room temperature rather than the total appliance load. Based on empirical energy consumption profiles and solar generation data from 25 homes in Austin, we find that residential customers would keep overall annual expenditure and environmental footprint low by investing in solar panels and smart thermostats. The capital costs of both storage systems are still too high to make them economically profitable investments for typical residential customers. Additionally, the Value of Solar policy disincentivizes solar customer investment in storage systems. The study also shows that, while the energetic effect of the two storage systems can be favorable or detrimental depending upon the pricing structure and the household load profile, lithium-ion batteries are the main instruments to avoid high demand charges. Thus, we recommend that, as an effective peak load control mechanism, electric utilities should offer significant rebates to encourage residential customer investment in storage systems in addition to subjecting them to demand charges.

Coordinated Optimal Power Flow for Integrated Active Distribution Network and Virtual Power Plants Using Decentralized Algorithm

With the wide application of distributed energy technology in active distribution networks (ADNs), virtual power plants (VPPs) are introduced as a promising integration and management technology. To coordinate their operation schedule and ensure confidentiality, we establish a coordinated optimal power flow (OPF) model and propose an efficient decentralized algorithm based on multi-parametric quadratic programming and Benders decomposition. In feasible sub-problems, the quadratic exchanging functions are built, which greatly accelerates the convergence process. In infeasible sub-problems, feasible cut sets can be calculated based on benders decomposition. Besides, an effective relaxation method is developed to address the degeneracy problem. To eliminate redundant feasible cut sets, a predetermined feasible region is constructed according to the characteristics of each VPP. The effectiveness of the proposed method is demonstrated via numerical tests using two cases of different scales. The results show that the proposed method converges much faster than some prevailing methods. Furthermore, the coordinated OPF has a better fuel economy than the conventional OPF scheme.

Research on Interactive Scenarios and Mechanisms of Energy Supply and Use Modules of Park-level Integrated Energy System

The integrated energy system can realize the complementary advantages of multiple energy sources and effectively solve the problem of low integrated energy efficiency of traditional energy systems. Carrying out research on the interactive scenarios and mechanisms of the energy supply and use modules of the integrated energy system is conducive to promoting the development of clean energy and promoting the indepth integration of energy Internet and distributed energy technology, smart grid technology, and energy storage technology. First, it summarizes the scenarios of the energy supply and use modules of the integrated energy system, and analyzes the interaction mechanism and paths of the energy supply and use modules of the integrated energy system on this basis.