•Load signatures are formulated based on first three odd harmonic currents.•Harmonic currents’ phase angles are measured and taken into account.•Measurements in a real residential installation have ...been performed.•Three alternative load signatures formations are examined.•Results indicate high NILM performance under the consideration of the phase angles.
In the smart home context, one of the features that most users would desire is the knowledge of the operation of each electrical appliance without the need to install expensive smart plugs or measuring equipment at each outlet-appliance. The Non-Intrusive Load Monitoring (NILM) idea is an alternative method where only one meter is utilized. However, the accuracy and simplicity of NILM approaches are still under improvement and evolvement. In this paper we propose the development of load signatures by a limited number of harmonic current vectors. The rationale behind this is that simultaneously operating appliances may have opposite or displaced harmonic current vectors, which means that using only current amplitudes as load signatures will not result in reliable identification. Three alternative formations are examined aiming to highlight the contribution of the harmonic current phase angles to the robustness of the load signatures. The first formation considers only the current amplitude, the second takes into account the phase angles in the form of vector projection on the x-axis, and the third is based on harmonic current vectors. The respective disaggregation schemes are also proposed considering either amplitude summations or vector aggregations, in order to examine the correct appliance combination that matches the actual operating one. Measurements have been performed in a typical residential installation considering both stand-alone operation of appliances and scenarios with appliance combinations. The results indicate that disaggregation performance is significantly improved when relying on harmonic current vectors in respect to the case with only current amplitudes, which makes the methodology potentially suitable for the new smart meters that are expected to be widely installed.
Summary
This article deals with the problem of energy losses in distribution networks (DNs) under electric vehicle (EV) penetration. The problem of charging overlaps causing severe power losses and ...voltage drops is faced under appropriate EV charging. An optimized EV charging schedule is proposed under EV time‐of‐arrival consideration. The solution algorithm is based on a particle swarm optimization (PSO) variant, and both grid‐to‐vehicle (G2V) and vehicle‐to‐grid (V2G) schemes are included regarding the power interactions of the EVs with the grid. The goal is to optimally allocate the charging and/or discharging time periods of the EVs in order to minimize energy losses while delivering fully charges EVs to the owners. New departures after the first EVs' arrival are also handled. The results indicate that with the proposed scheduling, daily energy loss reduction could be reached up to 25% under an improved voltage profile that indicates more uniform loading for the DN.
This paper deals with the problem of energy losses in Distribution Networks under EV penetration. An optimization EV charging schedule is proposed under EV time‐of‐arrival consideration. The goal is to optimally allocate the charging and/or discharging time periods of the EVs in order to minimize energy losses. New departures after the first EVs’ arrival are also handled. The results indicate that with the proposed scheduling, daily energy loss reduction could be reached up to 25% under an improved voltage profile.
The explicit demand response (DR) is a key program for reinforcing the participation of end customers and making the most out of the potential of the smart grid. The DR is a key topic in the field of ...buildings to make use of the flexibility that they can offer. However, in order to guarantee the correct functionality of a DR system, it is fundamental to perform interoperability tests among the various components/actors. In this paper, we take into consideration the technological solutions suggested in the framework of the DRIMPAC project to enable the DR in buildings. We consider all actors/devices involved in order to reach the objective of executing a flexibility order by an asset. Following a structured interoperability testing methodology created by the Joint Research Centre, we perform interoperability tests regarding all critical links of the full chain of interacting actors to obtain the DR in buildings. The results show that the system functions properly and the benefits from the DR can be exploited. On the other hand, we provide a concrete example of how to apply the interoperability methodology in the field of testing the DR in buildings.
As microgrids have gained increasing attention over the last decade, more and more applications have emerged, ranging from islanded remote infrastructures to active building blocks of smart grids. To ...optimally manage the various microgrid assets towards maximum profit, while taking into account reliability and stability, it is essential to properly schedule the overall operation. To that end, this paper presents an optimal scheduling framework for microgrids both for day-ahead and real-time operation. In terms of real-time, this framework evaluates the real-time operation and, based on deviations, it re-optimises the schedule dynamically in order to continuously provide the best possible solution in terms of economic benefit and energy management. To assess the solution, the designed framework has been deployed to a real-life microgrid establishment consisting of residential loads, a PV array and a storage unit. Results demonstrate not only the benefits of the day-ahead optimal scheduling, but also the importance of dynamic re-optimisation when deviations occur between forecasted and real-time values. Given the intermittency of PV generation as well as the stochastic nature of consumption, real-time adaptation leads to significantly improved results.
•The siting and sizing of DG units in DNs is examined under an innovative perspective.•A Local PSO (LPSO) variant algorithm is utilized for the problem.•The algorithm provides the optimal number of ...nodes to host DG units.•Moreover, the optimal active and reactive power of each node is resulted.•The solution is not biased since all variables are optimized simultaneously.
In this paper a novel approach regarding the optimal penetration of Distributed Generation (DG) in Distribution Networks (DNs) towards loss minimization is proposed. More specific, a Local Particle Swarm Optimization (PSO) variant algorithm is developed in order to define the optimal active and reactive power generation and/or consumption requirements for the optimal number and location of nodes that yield loss minimization. Thus, the proposed approach provides the optimal number, siting and sizing of DGs altogether. In addition, based on the optimal power requirements of the resulted nodes, a combination of potential DG types to be installed is recommended. The proposed objective function in this paper is also innovative since it embeds the constraint of reverse power flow to the slack bus by the formation of a new penalty term. The proposed methodology is applied to 30 and 33 bus systems. The results indicate the optimal number, locations, and capacity of DG units, which were calculated simultaneously. Finally, the impact of the predefined amount of permissible reverse power flow to the optimal solution is also examined through two scenarios: the first considers zero reverse power flow and the second unlimited reverse power flow.
In this paper we present a new methodology for the formulation of efficient load signatures towards the implementation of a near-real time Non-Intrusive Load Monitoring (NILM) approach. The purpose ...of this work relies on defining representative current values regarding the 1st, 3rd and 5th harmonic orders to be utilized in the load signatures formulation. A measurement setup has been developed and steady-state measurements have been performed in a Low Voltage residence. A data processing methodology is proposed aiming to depict representative current values for each harmonic order in order to keep the load signature short and simple. In addition, a simple disaggregation scheme is proposed under linear equations for the disaggregation mode in order to examine the near-real time application of the methodology. The analysis indicates that the developed load signatures could be efficient for a per second application rate of the NILM algorithm. The results show that the higher harmonic currents facilitate the identification performance. Finally, the analysis concludes that for combinations that include appliances with intense harmonic content, the phase angle of the higher for harmonic currents should also be considered to the load signatures formulation.
A way to improve energy management is to perform balancing both at the Peer-to-peer (P2P) level and then at the Virtual Microgrid-to-Virtual Microgrid (VMG2VMG) level, while considering the ...intermittency of available Renewable Energy Source (RES). This paper proposes an interdisciplinary analytics-based approach for the formation of VMGs addressing energy balancing. Our approach incorporates Computer Science methods to address an Energy sector problem, utilizing data preprocessing techniques and Machine Learning concepts. It features P2P balancing, where each peer is a prosumer perceived as an individual entity, and Virtual Microgrids (VMGs) as clusters of peers. We conducted several simulations utilizing clustering and binning algorithms for preprocessing energy data. Our approach offers options for generating VMGs of prosumers, prior to using a customized Exhaustive brute-force Balancing Algorithm (EBA). EBA performs balancing at the cluster-to-cluster level, perceived as VMG2VMG balancing. To that end, the study simulates on data from 94 prosumers, and reports outcomes, biases, and prospects for scaling up and expanding this work. Finally, this paper outlines potential ideal usages for the approach, either standalone or integrated with other toolkits and technologies.
Integration of distributed generation (DG) in existing distribution networks has been studied thoroughly during the past years as a measure of reducing grid's power losses. However, the optimal DG ...placement, known as ODGP, toward loss minimisation, has not been studied in depth by considering the possible impact of the reverse power flow (RPF) caused by extended penetration of distributed energy resources. This study uses a constriction factor embedded local particle swarm optimisation algorithm along with the appropriate particle formulation that solves the ODGP problem by taking into account the impact of possible RPF. In this study, the idea of RPF modelling is introduced by providing extended versions of IEEE test systems. Modified versions of the IEEE 30-bus and IEEE 33-bus test systems are modelled and results are presented in order to highlight the impact of RPF on the ODGP problem solution. The mathematical formulation is given, results and analysis for both extended systems are presented, while the importance of RPF for different conditions is assessed.
•Energy loss reduction is solved via ODGP.•Load variations are included under the formulation of numerous snapshots.•Each snapshot describes an operating status with altered load composition.•Nodes ...are ranked based on their participation frequency to the solution.•A fixed solution is proposed regardless the load composition of the network.
The Optimal Distributed Generation Placement problem (ODGP) towards energy loss minimization depends basically on the network's layout and its load composition. Under load variations, different load compositions result, for each one of them, is highly possible to come up with a different optimal solution regarding the optimal siting and sizing of DG units. This paper examines the impact of these variations in order to verify how optimal solution should adapt to any load composition. A Local Particle Swarm Optimization Variant algorithm is proposed as the solution algorithm and numerous load composition snapshots for the IEEE-33 bus system are examined. Moreover, a methodology is proposed in order to highlight the critical nodes that prove to have an essential role to the solution. Finally, the possibility for the determination of a fixed solution with fixed installation nodes and constant power output that could yield near optimal energy loss reduction is examined.
Over the past few decades, industry and academia have made great strides to improve aspects related with optimal energy management. These include better ways for efficient energy asset management, ...generating great opportunities for optimization of energy distribution, discomfort minimization, energy production, cost reduction and more. This paper proposes a framework for a multi-objective analysis, acting as a novel tool that offers responses for optimal energy management through a decision support system. The novelty is in the structure of the methodology, since it considers two distinct optimization problems for two actors, consumers and aggregators, with solution being able to completely or partly interact with the other one is in the form of a demand response signal exchange. The overall optimization is formulated by a bi-objective optimization problem for the consumer side, aiming at cost minimization and discomfort reduction, and a single objective optimization problem for the aggregator side aiming at cost minimization. The framework consists of three architectural layers, namely, the consumer, aggregator and decision support system (DSS), forming a tri-layer optimization framework with multiple interacting objects, such as objective functions, variables, constants and constraints. The DSS layer is responsible for decision support by forecasting the day-ahead energy management requirements. The main purpose of this study is to achieve optimal management of energy resources, considering both aggregator and consumer preferences and goals, whilst abiding with real-world system constraints. This is conducted through detailed simulations using real data from a pilot, that is part of Terni Distribution System portfolio.
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