In this paper, a framework is proposed for integration of peer-to-peer (P2P) trading-based local energy market (LEM) with the blockchain technology. The proposed LEM model allows prosumers and consumers to trade electricity among each other ensuring the presence of the retailer and network utility – who are also essential parts of a P2P network. The P2P contracts settled between various prosumers and consumers are governed by mutually agreed upon smart contracts – which are then written in an Ethereum blockchain to record and store bidding history, P2P transactions, and settlements. An effective formulation is also presented to capture P2P trading quantities and prices among participating prosumers and consumers in a decentralised fashion with an appropriate analysis of financial viability. Finally, a case study is conducted in a real Australian context; in which the engagement of both prosumers and consumers are taken into account, and the performance of the proposed blockchain-enabled LEM is compared with business-as-usual (BAU) to demonstrate the model's superiority.
Cloud computing is already a part of the daily lives of both people and companies and as such, there is a concern about how it impacts the environment. The union of these two realities provides an opportunity for the emergence of Green Cloud Computing with new proposals, approaches, and metrics to make data centers more efficient, mainly in terms of energy, as well as to reduce CO2 emissions and its environmental impact. Knowing the metrics that can be used to measure the energy cost and environmental impact of data centers are fundamental in Green Computing, this article studies the relationship between energy consumption and execution times, architecture, and costs of a cloud environment. Using simulators it was possible to see an improvement in energy efficiency above 44%, as well as to get a cost reduction of at least 17%, and a reduction of of 55% in the environmental impact from the emission of CO2. It is important to note that there was no impact on processing times, by using the adoption of algorithms for complex problems, in the scheduling of Virtual Machines.
Halted business from grid outages leads to financial damage suffered by the business. Photovoltaic and battery energy storage system paired microgrids are presenting an attractive opportunity for investors, by enabling them to generate and store their own energy and reducing their electricity cost for operations. A microgrid can, during grid outage, operate in islanded mode in which the loads at the microgrid remain energized by the BESS locally. In this paper models for the energy and financial transactions between microgrid and grid are formulated. A simulation is programmed from these models in which multiple grid reliability and microgrid configurations are simulated. The capability to island along with battery arbitrage, outages, and cost of electricity transactions are captured in a case study. It is shown that as grid reliability decreases, through increase in SAIFI, the optimal BESS size also increases. Finally, the lowest cost for electricity is found with small-storage + large-capacity PV systems because systems in this range show higher resilience against grid outages and benefit from lower component costs.
The adoption of blockchain in various industries is gaining more popularity, especially in the energy industry. With the increase of distributed energy resources (DER), energy users can generate, store, and trade their resources with others. Utility companies or energy users are influenced by blockchain-based peer-to-peer (P2P) energy trading markets. Blockchain adds transparency and immutability to the involved transactions. Smart contracts in blockchain automatically execute when the conditions are met without any third-party intervention. Motivated by these benefits, in this paper an energy trading framework is developed using Ethereum smart contracts. Energy users can trade their excess energy or buy energy using the smart contract functions. Smart contract written in solidity is compiled and deployed using remix with injected metamask provider. Ganache is used to create accounts and these accounts are imported to metamask for signing transactions. We also discuss alternative methods for smart contract deployment. Computational cost analysis is performed by evaluating the gas consumption analysis for the smart contract functions.
Switch mode power supplies present light weight power conversion solutions, but degradation affecting sub-components have been known to transition the converter to move to unstable dynamic operations. This paper presents a method to build interpretive prognostics for switch mode power supplies with electromagnetic input filters by modeling sub-component degradation trajectories and using discrete event simulation to generate lifecycle data associated with the system impedances to use as inputs into machine learning based prognostics to make interpretable remaining useful life predictions. As a usage case, a buck-boost switch mode power supply with parasitic elements for all components and time-dependent degradation concerning the input and output filtering capacitor is analyzed.
Recognizing and visualizing customers’ electricity consumption behaviors plays a vital role in enhancing the reliability and efficiency of distribution networks. This paper presents a clustering and visualization platform in real-time and shows the level of consumption using simple visualization means. Based on the level of consumption at each feeder, the tool changes the color to indicate Low, Medium, or High consumption. The platform was applied to a clustering algorithm that was applied to the IEEE 33 Bus test feeder considering Golden, CO, USA. Such a platform will help network operator to improve distribution planning, demand response, market segmentation and management, and energy efficiency.
This article presents a reinforcement learning (RL) algorithm for state-of-charge (SoC) balancing of battery cells in a modular multilevel converter (MMC) system. As converter topology, the Battery Modular Multilevel Management (BM3) topology is used. A Q-Learning algorithm is implemented and evaluated as a reinforcement learning algorithm. The SoC balancing of batteries in MMCs could be shown as an application area of RL. Up to seven BM3 modules can be balanced based on the proposed model. The scalability of the model represents a limited applicability. However, the findings serve as a basis for further research in RL in the environment of MCCs.
Using Wave Energy Converters as Distributed energy resources gained significant interest nowadays. A recent article from the US National Renewable Energy Laboratory introduced a concept called Distributed Embedded Energy Conversion Technology (DEEC-Tec). In this work a wave energy converter, with compressed air energy storage system and Oscillating Water Column principle, is proposed to be used as a DEEC-Tec. The proposed device addresses power quality issues associated with OWC devices. A Laboratory scale device was developed and tested. The device worked properly, however the produced output was low and recommendations to improve the device are given.
In the transition to clean, cheap, and sustainable energy, microgrid-based renewable energy resources (RES) are widely utilized in islanded or grid-connected modes. However, due to the intermittent nature of RES such as photovoltaic (PV) or wind energy systems, energy storage systems (ESSs) such as batteries are mandated to satisfy load demands and stabilize system operation. For instance, stabilizing the dc bus voltage in islanded microgrids is crucial to keeping the system reliable, dependable, and stable. This paper proposes an adaptive dc bus voltage control technique based on a fuzzy-PI controller. Moreover, a performance comparison between fuzzy-PI and conventional proportional-integrator (PI) controllers is performed based on a MATLAB/Simulink model. The results show that the fuzzy-PI controller has a faster response to any reference voltage variation and less overshoot compared to conventional PI controllers. Additionally, the proposed controller can efficiently stabilize the dc bus voltage during load variation portions.
Formulating a wind turbine power system (WTPS) as an optimal control problem is very natural and with great appeal – given the optimized objectives WTPSs always aim at achieving, such as but not limited to maximizing power generation and reducing fluctuations in the generated power; these objectives are better to be achieved especially when the WTPS is experiencing sudden changes or even faults. However, the literature does not provide much contributions in this domain given the nonlinearity of the problem and the lack of highly accurate time domain models. In this paper, we provide a novel nonlinear optimal control formulation for WTPSs taking advantage of very recent developments in accurate nonlinear time-domain modeling of WTPSs. This novel formulation enable, for the first time in the literature of WTPSs, the use of powerful optimal control solvers which traditionally work with systems of differential equations. We use in this paper the software optimal control solver GPOPS2, which is compatible with available software such as MATLAB ® ; this powerful solver has been proven promising in other fields such as unmanned aerial systems and robotics. we provide some simulation cases which show that optimal control solutions outperform PID controllers traditionally used by industry. We follow that with discussion on this novel approach and intended future directions.
Over the last two decades more than 75 international supercapacitor manufacturers have introduced several different supercapacitor families. Some have now reached the energy density of lead-acid batteries and while all families exhibit power density that are several orders higher than lithium based rechargeable battery chemistries. IoT devices for various sensing and monitoring applications, particularly systems deployed to monitor pollution, or ecosystem parameters have a need for self-sustaining energy sources. While batteries have been the common choice, these are not self-sustainable fit-and forget energy storage devices. In these cases modern supercapacitor families can be used to replace batteries, which can rely on lower levels of energy harvesting to become self-sustaining fit-and-forget devices. This paper presents a summary of modern supercapacitor families, used to design a minimum component count supercapacitor based power management systems for sensor networks. Some preliminary investigation results are presented, while more work is underway to develop a robust, sustainable supercapacitor energy storage solution for remote IoT devices.
Smart grid technologies have evolved into advanced Technology that can provide an infrastructure for efficient electric power transfer and a road map to solve the shortcoming of the current power system. It is a sophisticated classical power system with a high degree of interface among energy, control, and communication subsystems. The growing amount of electric energy from Renewable Energy Sources (RES) requires pertinent grid integration. Wind and solar are the fastest sectors among all renewable energy sources. With an excellent wind resource, New Mexico is home to a lot of wind power development. There are challenges and opportunities for integrating wind energy into smart grids. One promising approach is via Wireless Power Transfer (WPT). WPT is a technology for transmitting power through an air gap to electrical devices for energy replenishment. The two main application methods are Inductive Power Transfer (IPT) and Capacitive Power Transfer (CPT) of WPT. IPT is the most common method and applies to many power levels and gaps. The fundamental principle of IPT is that two separate coils with the same resonance frequency can form a resonant system based on high-frequency magnetic Coupling and exchange energy with a high-efficiency level. The recent advancement in WPT technology has provided a promising alternative way to address energy issues of battery-powered devices. One primary application of IPT is in charging Electric Vehicles (EVs). EVs are flooding the market and are considered the future of world transportation. Adequate stand-alone or smart grid-connected wireless charging stations along major roads encourage the public to purchase EVs for long-distance travel. In addition, Stand-alone charging stations can be powered via isolated RES wirelessly along major highways. One promising application of WPT in charging EVs.
The operation and planning of electric power systems are supported by continuous studies based on models. However, the fast evolution of the system topology with the integration of green technologies has brought challenges to the classical representation of each component. In this paper, a model to characterize the operation of battery energy storage systems for frequency support is proposed. This representation considers a positive sequence model of the voltage source converter which permits to regulate the exchange of real and reactive powers. Thus, it is possible to interact with a classical electromechanical representation of synchronous generators, and also with turbine-governor, and power support based on battery energy storage systems for large-scale power systems. To verify the scope of the proposed model, the equivalent New England power grid is evaluated. Simulation results with the proposed strategy are compared with the classical dynamic representation of synchronous generators for frequency stability studies. Severe changes of load and generation are analyzed to demonstrate the proposed model applicability.
This paper investigates the potential of using brushless excitation (BLE) for not only riding through the fault but also to damp inter-area power oscillation with the help of a synchronous generator (SG) used in Type 5 Wind Power Plant (WPP). In BLE, an auxiliary synchronous generator (ASG) behaving like an exciter is coupled and driven by the rotor of the main SG. The BLE's field current's ASG is fed by two separate loops of the automatic voltage regulator (AVR) and power system stabilizer (PSS). The AVR system implements a control loop to regulate the generator terminal voltage, V T . For the PSS, the kinetic energy of the wind turbine is utilized according to the estimated rotational speed of the synchronous generator shaft of the SG. It may mitigate the necessity of any curtailment of active power for damping. The effectiveness of the proposed control scheme is verified with a three-phase short circuit fault in a two-area power system.
Natural disasters cause large-scale and long-duration power outages that can have devastating societal repercussions. These outages can suspend emergency response services and critical systems such as water, transportation, and communications. Power outages do not affect individuals equally, and certain socioeconomic or built-environment factors have been shown to increase an individual's vulnerability. This paper presents a three-dimensional metric of social vulnerability to quantify the degree to which a person's life or livelihood is put at risk by a long-duration power outage. Dimensions of vulnerability include health, preparedness, and evacuation intention and means. Principal component analysis and an L2 norm model are applied to produce a single metric for each dimension of vulnerability. The three scores are then aggregated using Pareto ranking to determine the overall vulnerability. Results are presented for a case study of the United States at the census-tract level and are mapped in ArcGIS Pro to visualize the comparative vulnerability across the nation. These results can be integrated into power grid resilience models to account for the social impacts of power outages.
Access to modern energy technologies is necessary for socioeconomic development of communities worldwide. Electricity is essential for providing education, improving health and hygiene, enhancing safety, creating job opportunities, and development of local industries. Although access to energy has not yet been established as a basic human right, it is considered as a derived human right. Rural communities are often the ones being impacted by energy injustice in the form of lack of access to reliable power. These communities are typically scattered over large geographical areas and are far away from the nearby cities, which makes electrification projects challenging due to the high capital costs and low rate of return. However, with the latest advances in distributed and renewable energy resources, off-grid systems are being considered as an emerging solution for rural electrification. In addition, mobile energy storage systems are gaining attention to overcome energy injustice in rural areas. In this paper, the concept of energy justice and the corresponding challenges are discussed along with existing and potential solutions to overcome injustice in access to electricity.
Lightly-loaded induction motors are normally working far from their best efficiency condition, moreover if they are supplied directly from the power network. The direct-on-line starting of induction motors may also cause undesirable high inrush current. The high spike of current can bring about troublesome tripping of protective equipment, an improper start of the motor, as well as voltage dips in the power line. The high torque related to high current may cause undesired abrupt acceleration of the motor which could damage the connected mechanical loads. Reduced voltage has been long proposed to improve efficiency under light load conditions. It has also been adopted to reduce the severity of current surge during motor starting, by increasing the supply voltage gradually. However, under low voltage conditions, the torque generated may not be sufficient to drive the load. An alternative method can be applied by maintaining the flux in the air gap through a reduction of the supply frequency in proportion to the input voltage to avoid machine saturation. This paper is intended for instructional purposes and describes the application of the variable-voltage variable-frequency method during an induction motor starting under loaded conditions. The results show the benefit of applying the supply frequency reduction along with the voltage reduction to improve the low-torque value at low-voltage conditions, which also means energy usage improvement.
Application of Blockchain Technology (BCT) in the energy industry in Blockchain Enabled Interconnected Smart Microgrids (BSMGs) is on the rise as it can automate local energy markets; execute energy trading; and implement market operations and management. However, they are limited by their scalability and low transactions rate. Also, with the increase in adoption of BSMGs, different types of BCT platforms will emerge, creating heterogeneity in the system. This shortcoming may lead to a monopoly of certain platforms over the rest. These drawbacks can be overcome by establishing interoperability between heterogeneous blockchains. Interoperability can also enable inter-microgrid transactions which will be hindered if there is no inter-chain communication and transaction. Cosmos is a network of blockchains which allows blockchains, applications and services to be interconnected through Inter Blockchain Communication (IBC) protocol. Ignite CLI is an open-source, command line interface which easily creates modular and customizable blockchains which are inherently connected to Cosmos through IBC. In this paper, Ignite CLI is used to create blockchains for BSMGs which exchange data and calls for inter-microgrid transactions via IBC. The procedure to establish inter-chain communication is defined. Interoperability between BSMGs is explored and demonstrated through different examples, for the first time in the energy domain. The execution times for different cases and varying numbers of information packets have been observed.
Natural disasters can devastate the critical infrastructure of the affected regions, including the power and energy systems. Power grid resilience can be achieved during operation, by adopting risk-based dispatch strategies, or through proactive grid reinforcement and hardening strategies. A solution is proposed in this paper for optimal line reinforcement in order to enable microgrid formation during the course of a natural disaster event. The problem is formulated as a mixed-integer nonlinear multi-objective optimization model to minimize the reinforcement cost and maximize the amount of load served. The problem is solved subject to power flow and network topology constraints. A case study is presented to illustrate that through a selective and targeted line reinforcement, multiple microgrids can be formed in order to continue the local supply of the loads until damaged components are repaired or replaced, and service is restored to the main grid.
Microbial Fuel Cells (MFCs) are a promising renewable and sustainable energy solution for low-power field electronic devices, but still remain in the research phase due to low power output efficiency. This research systematically studied three tubular MFC systems including standalone soil microbial fuel cells (S-MFCs), plant microbial fuel cells (P-MFCs), and a proposed hybrid MFC (H-MFC) system. All tubular MFC systems were carefully constructed using three types of soils (potting soil, yard soil, and river soil), four plants (Bonnie Curly Spider, Peace Lily, Lemongrass, and Tomato Plant), and two types of electrodes (zinc mesh as the cathode and copper spiral as the anode). Power density from each system was calculated as a function of the days during growth and was based on the experimental measurement of the open voltage of every setup. The results showed that a standalone S-MFC system had easy implementation and a higher power density initially than some P-MFCs but was not as sustainable as P-MFCs, whereas both P-MFC and hybrid systems could produce power densities for sustained periods of time. However, the difference in power density between P-MFC and hybrid systems was observed after 18 days for potting soil and 11 days for yard soil, and after 30 days, the power density of all hybrid systems was roughly 2 times that of all P-MFC setups. Furthermore, the hybrid systems displayed significant advantages over their S-MFC and P-MFC counterparts, especially in the sustained power output and ease of replaceability, meaning that future implementation of this technology in a scaled-up setting is more feasible. Therefore, it is suggested that hybrid MFC systems will be the future direction of S-MFC and P-MFC technology.
