scholarly journals Household Energy Management

2021 ◽  
Vol 11 (4) ◽  
pp. 1626
Author(s):  
Piotr Powroźnik ◽  
Robert Szulim ◽  
Wiesław Miczulski ◽  
Krzysztof Piotrowski
Keyword(s):  
Power Systems ◽  
Energy Management ◽  
Distribution System ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Photovoltaic System ◽  
Peak Demand ◽  
Work Related ◽  
Management Algorithm

Ensuring flexibility and security in power systems requires the use of appropriate management measures on the demand side. The article presents the results of work related to energy management in households in which renewable energy sources (RES) can be installed. The main part of the article is about the developed elastic energy management algorithm (EEM), consisting of two algorithms, EEM1 and EEM2. The EEM1 algorithm is activated in time periods with a higher energy price. Its purpose is to reduce the power consumed by the appliances to the level defined by the consumer. In contrast, the EEM2 algorithm is run by the Distribution System Operator (DSO) when peak demand occurs. Its purpose is to reduce the power of appliances in a specified time period to the level defined by the DSO. The optimization tasks in both algorithms are based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic algorithm. The EEM1 and EEM2 algorithms also provide energy consumer comfort. For this purpose, both algorithms take into account the smart appliance parameters proposed in the article: sections of the working devices, power reduction levels, priorities and enablingof time shifting devices. The EEM algorithm in its operation also takes into account the information about the production of power, e.g., generated by the photovoltaic systems. On this basis, it makes decisions on the control of smart appliances. The EEM algorithm also enables inverter control to limit the power transferred from the photovoltaic system to the energy system. Such action is taken on the basis of the DSO request containing the information on the power limits. Such a structure of EEM enables the balancing of energy demand and supply. The possibility of peak demand phenomenon will be reduced. The simulation and experiment results presented in the paper confirmed the rationality and effectiveness of the EEM algorithm.

scholarly journals An Efficient Technique-Based Distributed Energy Management for Hybrid MG System: A Hybrid SBLA-CGO Technique

2021 ◽  
Author(s):  
T Logeswaran ◽  
Francis H Shajin ◽  
Paulthurai Rajesh
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Energy Demand ◽  
Present Method ◽  
Perfect Match ◽  
Energy System ◽  
Photovoltaic System ◽  
Present System ◽  
Prediction Errors ◽  
Electricity Cost

Abstract This manuscript presents an optimal energy management on microgrid (MG) connected to the grid that chooses the energy scheduling based on the proposed method. The present method is the joint implementation of the Side-Blotched Lizard Algorithm (SBLA) and the Chaos Game Optimization Algorithm (CGO) and hence it is named as SBLA-CGO method. Here, the MG system contains a photovoltaic system (PV), wind turbine (WT), battery storage (BS) and fuel cell (FC). Constantly, the necessary load demand of MG system connected to the grid is measured with SBLA method. The CGO increases the perfect match of MG with the expected load requirement. Moreover, renewable energy forecasting errors are evaluated twice by MG energy management for minimizing the control. Through the operation of MG schedule of several RES to decrease the electricity cost using the first method. Balancing the energy flow and minimize the effects of prediction errors according to the rule presented as planned power reference is second method. The main aim of the present method is evaluated with connection of fuel cost, the variation of energy per hour of the electrical grid, the cost of operation and maintenance of MG system connected to the network. According to RES, the energy demand and SOC of the storage elements are the conditions. Renewable energy system units use batteries as energy sources to allow them to operate continuously on stable and sustainable power generation. The analysis of the present method is analyzed by comparing with the other systems. The results of the comparison assess the strength of the present system and confirm their potential for solving the issues.

scholarly journals Intelligent Energy Management of Electrical Power Systems

2020 ◽  
Vol 10 (8) ◽  
pp. 2951 ◽  
Author(s):  
Manuela Sechilariu
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Real Time ◽  
Energy Management ◽  
Distribution System ◽  
Power Flow ◽  
Low Voltage ◽  
Electrical Power ◽  
Building Blocks ◽  
Energy System

Smart grid implementation is facilitated by multi-source energy systems development, i.e., microgrids, which are considered the key smart grid building blocks. Whether they are alternative current (AC) or direct current (DC), high voltage or low voltage, high power or small power, integrated into the distribution system or the transmission network, multi-source systems always require an intelligent energy management that is integrated into the power system. A comprehensive intelligent energy system aims at providing overall energy efficiency with regard to the following: increased power generation flexibility, increased renewable generation systems, improved energy consumption, reduced CO2 emission, improved stability, and minimized energy cost. This Special Issue presents recent key theoretical and practical developments that concern the models, technologies, and flexible solutions to facilitate the following optimal energy and power flow strategies: the techno-economic model for optimal sources dispatching (mono and multi-objective energy optimization), real-time optimal scheduling, and real time optimization with model predictive control.

scholarly journals Advanced energy management system based on PV and load forecasting for load smoothing and optimized peak shaving of islanded power systems

2019 ◽  
Vol 113 ◽  
pp. 03001
Author(s):  
Petros Iliadis ◽  
Stefanos Domalis ◽  
Athanasios Nesiadis ◽  
Konstantinos Atsonios ◽  
Spyridon Chapaloglou ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Clean Energy ◽  
Energy System ◽  
Load Curve ◽  
Dynamic Simulations ◽  
Peak Shaving ◽  
Conventional Fuel

Photovoltaic (PV) systems constitute one of the most promising renewable energy sources, especially for warm and sunny regions like the southern-European islands. In such isolated systems, it is important to utilize clean energy in an optimal way in order to achieve high renewable penetration. In this operational strategy, a Battery Energy Storage System (BESS) is most often used to transfer an amount of the stored renewable energy to the peak hours. This study presents an integrated energy management methodology for a PV-BESS energy system targeting to make the load curve of the conventional fuel based units as smooth as possible. The presented methodology includes prediction modules for short-term load and PV production forecasting using artificial neural, and a novel, optimized peak shaving algorithm capable of performing each day’s maximum amount of peak shaving and smoothing level simultaneously. The algorithm is coupled with the overall system model in the Modelica environment, on the basis of which dynamic simulations are performed. The simulation results are compared with the previous version of the algorithm that had been developed in CERTH, and it is revealed that the system’s performance is drastically improved. The overall approach proves that in such islanding systems, a PV-BESS is a suitable option to flatten the load of the conventional fuel based units, achieve steadier operation and increase the share of renewable energy penetration to the grid.

scholarly journals A Comparison of Fuzzy-Based Energy Management Systems Adjusted by Nature-Inspired Algorithms

2021 ◽  
Vol 11 (4) ◽  
pp. 1663
Author(s):  
Diego Arcos-Aviles ◽  
Diego Pacheco ◽  
Daniela Pereira ◽  
Gabriel Garcia-Gutierrez ◽  
Enrique V. Carrera ◽  
...  
Keyword(s):  
Power Systems ◽  
Energy Management ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Cuckoo Search ◽  
Mixed Integer ◽  
Energy Sources ◽  
Power Profile ◽  
Utility Network ◽  
Nature Inspired Algorithms

The growing energy demand around the world has increased the usage of renewable energy sources (RES) such as photovoltaic and wind energies. The combination of traditional power systems and RESs has generated diverse problems due especially to the stochastic nature of RESs. Microgrids (MG) arise to address these types of problems and to increase the penetration of RES to the utility network. A microgrid includes an energy management system (EMS) to operate its components and energy sources efficiently. The objectives pursued by the EMS are usually economically related to minimizing the operating costs of the MG or maximizing its income. However, due to new regulations of the network operators, a new objective related to the minimization of power peaks and fluctuations in the power profile exchanged with the utility network has taken great interest in recent years. In this regard, EMSs based on off-line trained fuzzy logic control (FLC) have been proposed as an alternative approach to those based on on-line optimization mixed-integer linear (or nonlinear) programming to reduce computational efforts. However, the procedure to adjust the FLC parameters has been barely addressed. This parameter adjustment is an optimization problem itself that can be formulated in terms of a cost/objective function and is susceptible to being solved by metaheuristic nature-inspired algorithms. In particular, this paper evaluates a methodology for adjusting the FLC parameters of the EMS of a residential microgrid that aims to minimize the power peaks and fluctuations on the power profile exchanged with the utility network through two nature-inspired algorithms, namely particle swarm optimization and differential evolution. The methodology is based on the definition of a cost function to be optimized. Numerical simulations on a specific microgrid example are presented to compare and evaluate the performances of these algorithms, also including a comparison with other ones addressed in previous works such as the Cuckoo search approach. These simulations are further used to extract useful conclusions for the FLC parameters adjustment for off-line-trained EMS based designs.

scholarly journals Techno-Economic Analysis of a Novel Hydrogen-Based Hybrid Renewable Energy System for Both Grid-Tied and Off-Grid Power Supply in Japan: The Case of Fukushima Prefecture

2020 ◽  
Vol 10 (12) ◽  
pp. 4061 ◽  
Author(s):  
Naoto Takatsu ◽  
Hooman Farzaneh
Keyword(s):  
Renewable Energy ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Economic Assessment ◽  
Energy System ◽  
Modeling Framework ◽  
Integrated Simulation ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

After the Great East Japan Earthquake, energy security and vulnerability have become critical issues facing the Japanese energy system. The integration of renewable energy sources to meet specific regional energy demand is a promising scenario to overcome these challenges. To this aim, this paper proposes a novel hydrogen-based hybrid renewable energy system (HRES), in which hydrogen fuel can be produced using both the methods of solar electrolysis and supercritical water gasification (SCWG) of biomass feedstock. The produced hydrogen is considered to function as an energy storage medium by storing renewable energy until the fuel cell converts it to electricity. The proposed HRES is used to meet the electricity demand load requirements for a typical household in a selected residential area located in Shinchi-machi in Fukuoka prefecture, Japan. The techno-economic assessment of deploying the proposed systems was conducted, using an integrated simulation-optimization modeling framework, considering two scenarios: (1) minimization of the total cost of the system in an off-grid mode and (2) maximization of the total profit obtained from using renewable electricity and selling surplus solar electricity to the grid, considering the feed-in-tariff (FiT) scheme in a grid-tied mode. As indicated by the model results, the proposed HRES can generate about 47.3 MWh of electricity in all scenarios, which is needed to meet the external load requirement in the selected study area. The levelized cost of energy (LCOE) of the system in scenarios 1 and 2 was estimated at 55.92 JPY/kWh and 56.47 JPY/kWh, respectively.

scholarly journals The Energy System of an Ecovillage: Barriers and Enablers

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 682
Author(s):  
Zita Szabó ◽  
Viola Prohászka ◽  
Ágnes Sallay
Keyword(s):  
Renewable Energy ◽  
Spatial Structure ◽  
Energy Management ◽  
Energy Production ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Energy Sources ◽  
Energy Management System ◽  
Production And Consumption ◽  
Ecologically Sustainable

Nowadays, in the context of climate change, efficient energy management and increasing the share of renewable energy sources in the energy mix are helping to reduce greenhouse gases. In this research, we present the energy system and its management and the possibilities of its development through the example of an ecovillage. The basic goal of such a community is to be economically, socially, and ecologically sustainable, so the study of energy system of an ecovillage is especially justified. As the goal of this community is sustainability, potential technological and efficiency barriers to the use of renewable energy sources will also become visible. Our sample area is Visnyeszéplak ecovillage, where we examined the energy production and consumption habits and possibilities of the community with the help of interviews, literature, and map databases. By examining the spatial structure of the settlement, we examined the spatial structure of energy management. We formulated development proposals that can make the community’s energy management system more efficient.

scholarly journals Optimal Planning and Operation of a Residential Energy Community under Shared Electricity Incentives

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2045
Author(s):  
Pierpaolo Garavaso ◽  
Fabio Bignucolo ◽  
Jacopo Vivian ◽  
Giulia Alessio ◽  
Michele De Carli
Keyword(s):  
Renewable Energy ◽  
Power Distribution ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Distribution Networks ◽  
Building Envelope ◽  
Net Energy ◽  
Technical Equipment ◽  
Optimal Planning

Energy communities (ECs) are becoming increasingly common entities in power distribution networks. To promote local consumption of renewable energy sources, governments are supporting members of ECs with strong incentives on shared electricity. This policy encourages investments in the residential sector for building retrofit interventions and technical equipment renovations. In this paper, a general EC is modeled as an energy hub, which is deemed as a multi-energy system where different energy carriers are converted or stored to meet the building energy needs. Following the standardized matrix modeling approach, this paper introduces a novel methodology that aims at jointly identifying both optimal investments (planning) and optimal management strategies (operation) to supply the EC’s energy demand in the most convenient way under the current economic framework and policies. Optimal planning and operating results of five refurbishment cases for a real multi-family building are found and discussed, both in terms of overall cost and environmental impact. Simulation results verify that investing in building thermal efficiency leads to progressive electrification of end uses. It is demonstrated that the combination of improvements on building envelope thermal performances, photovoltaic (PV) generation, and heat pump results to be the most convenient refurbishment investment, allowing a 28% overall cost reduction compared to the benchmark scenario. Furthermore, incentives on shared electricity prove to stimulate higher renewable energy source (RES) penetration, reaching a significant reduction of emissions due to decreased net energy import.

Energy Management System for Hybrid Microgrids

2021 ◽  
Vol 69 (2) ◽  
pp. 21-30
Author(s):  
Nasreddine ATTOU ◽  
Sid-Ahmed ZIDI ◽  
Mohamed KHATIR ◽  
Samir HADJERI
Keyword(s):  
Energy Management ◽  
Electricity Market ◽  
Management System ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Energy Sources ◽  
Variable Load ◽  
Energy Management System ◽  
Price Variation

Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

scholarly journals Analysis of Energy System in Norway with Focus on Energy Consumption Prediction

2017 ◽  
Vol 9 (1) ◽  
pp. 5-14 ◽  
Author(s):  
Maryam Hamlehdar ◽  
Alireza Aslani
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Electricity Consumption ◽  
Energy System ◽  
High Energy ◽  
Regression Result ◽  
Industry Growth ◽  
The Status

Abstract Today, the fossil fuels have dominant share of energy supply in order to respond to the high energy demand in the world. Norway is one of the countries with rich sources of fossil fuels and renewable energy sources. The current work is to investigate on the status of energy demand in Norway. First, energy and electricity consumption in various sectors, including industrial, residential are calculated. Then, energy demand in Norway is forecasted by using available tools. After that, the relationship between energy consumption in Norway with Basic economics parameters such as GDP, population and industry growth rate has determined by using linear regression model. Finally, the regression result shows a low correlation between variables.

Parametric Modeling and Optimal Control of a Combined Heating and Power System With Energy Storage

2020 ◽  
Author(s):  
Claudia Lucia De Pascalis ◽  
Stephanie Stockar
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Power System ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Cost Effective ◽  
Parametric Modeling ◽  
Medium Size ◽  
Energy Management Strategy ◽  
Generation Cost

Abstract Cogeneration is a well-known and cost effective solution for generating power and heat within the same plant, leading to improved overall efficiency and reduced generation cost. Combined heating and power systems can facilitate the penetration of renewable energy sources in medium size applications through the integration of electric and thermal energy storage units. Due to the complexity of the plant as well as significantly variability in power demand and generation, the design and operation of such systems requires a systematic co-optimization of plant and controller for guaranteeing near optimal performance. In this scenario, this paper presents a physics-based parametric modeling approach for the characterization of the main components of a 1MW combined heating and power system that includes renewable sources, electric and thermal storage devices. To demonstrate the model flexibility and potential benefits achieved by an optimal sizing, the system energy management is optimized using Dynamic Programming. The operational costs for different configurations are compared showing that an optimization of the energy management strategy in conjunction with an improved system sizing lead to more than 6% of reduction in the operational cost.

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