scholarly journals Control strategy for battery-supported photovoltaic systems aimed at peak load reduction

2019 ◽  
Vol 111 ◽  
pp. 05027
Author(s):  
Ruslan Zhuravchak ◽  
Natasa Nord ◽  
Helge Brattebø
Keyword(s):  
Control Strategy ◽  
Energy Demand ◽  
Moving Average ◽  
Peak Load ◽  
Consumption Rates ◽  
Wide Variability ◽  
Heated Floor ◽  
Grid Load ◽  
Grid Operators ◽  
Computational Resources

The use of photovoltaic (PV) technologies is one of the key means for achieving the balance between operational power demand and generation in net Zero Energy Buildings (nZEBs). However, direct use of PV power on-site is limited due to wide variability and uncertainty of PV output, the temporal mismatch between PV generation and load and other factors. Consequently, in addition to low self-consumption rates, the problem of peak grid load and peak PV feed into the grid persists. Batteries that are coupled to PV units may partially offer the solution to these problems, if operated under an intelligent control strategy. In this paper we proposed a forecast-based control strategy for battery-to-grid interaction aimed at enhancing selfconsumption and at reducing peak load. Python programming environment was used for data processing and algorithm development. Exemplification was made based on the reported hourly energy demand in one office building of 3000 m2 heated floor area located in Trondheim, Norway. Forecasting of electricity load profiles was based on the seasonal autoregressive integral moving average (SARIMA) model. For PV power forecasting, the algorithm communicated with external service – Solcast API. The search method for optimal scheduling of operational time and the extent of charging/discharging was proposed. The results showed that as opposed to conventional battery use, this control strategy allowed to achieve significantly more consistent grid interaction. It offered highly accurate battery scheduling on a day-ahead basis while utilising minimum historical data and computational resources. The algorithm may be beneficial for end-users and grid operators, and thus, it has a high potential for future integration into building energy supply systems.

scholarly journals Energy Demand Analysis and Design of a Hybrid Power System in Bawean Islands, Indonesia

2018 ◽  
Vol 164 ◽  
pp. 01038
Author(s):  
Ridho Hantoro ◽  
Cahyun Budiono ◽  
Ronald Kipkoech Ketter ◽  
Nyoman Ade Satwika
Keyword(s):  
Power Systems ◽  
Energy Demand ◽  
Peak Load ◽  
Electricity Consumption ◽  
Simulation Software ◽  
Diesel Generator ◽  
Time Step ◽  
Analysis And Design ◽  
Optimum System ◽  
Hybrid Power

Over 70 000 000 people in Indonesia have no access to electricity. This study was carried out in Bawean Islands which are located in the Java Sea about 150 km North of Surabaya, the headquarters of East Java. The study to determine the energy services available in the Bawean Island was done through interviewing a random sample of 72 households in two villages namely Komalasa and Lebak. Based on the average monthly electricity consumption of the sampled households connected to the grid, a hybrid renewable energy based electrical supply system was designed for Gili Timur Island, one of the satellite islands around Bawean Island. The system was designed with the aid of a time step simulation software used to design and analyze hybrid power systems. A sensitivity analysis was also carried out on the optimum system to study the effects of variation in some of the system variables. HOMER suggests that for the expected peak load of 131 kW, an optimum system will consist of 150 kW from PV array, two wind turbines each rated 10 kW, a 75 kW diesel generator and batteries for storage.

scholarly journals An R-based forecasting approach for efficient demand response strategies in autonomous micro-grids

2018 ◽  
Vol 30 (1) ◽  
pp. 63-80 ◽  
Author(s):  
Paraskevas Panagiotidis ◽  
Andrew Effraimis ◽  
George A Xydis
Keyword(s):  
Demand Response ◽  
Energy Demand ◽  
Moving Average ◽  
Electricity Consumption ◽  
End Users ◽  
Market Model ◽  
Residential Sector ◽  
Response Strategies ◽  
System Operator ◽  
Modelling Methodology

The main aim of this work is to reduce electricity consumption for consumers with an emphasis on the residential sector in periods of increased demand. Efforts are focused on creating a methodology in order to statistically analyse energy demand data and come up with forecasting methodology/pattern that will allow end-users to organize their consumption. This research presents an evaluation of potential Demand Response programmes in Greek households, in a real-time pricing market model through the use of a forecasting methodology. Long-term Demand Side Management programs or Demand Response strategies allow end-users to control their consumption based on the bidirectional communication with the system operator, improving not only the efficiency of the system but more importantly, the residential sector-associated costs from the end-users’ side. The demand load data were analysed and categorised in order to form profiles and better understand the consumption patterns. Different methods were tested in order to come up with the optimal result. The Auto Regressive Integrated Moving Average modelling methodology was selected in order to ensure forecasts production on load demand with the maximum accuracy.

scholarly journals A Fuzzy Logic-Based Control Algorithm for the Recharge/V2G of a Nine-Phase Integrated On-Board Battery Charger

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 946 ◽  
Author(s):  
Felice De Luca ◽  
Vito Calderaro ◽  
Vincenzo Galdi
Keyword(s):  
Fuzzy Logic ◽  
Control Strategy ◽  
Energy Demand ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Energy Resource ◽  
Reference Value ◽  
Active Role ◽  
Effective Control ◽  
Battery Charger

Energy demand associated with the ever-increasing penetration of electric vehicles on worldwide roads is set to rise exponentially in the coming years. The fact that more and more vehicles will be connected to the electricity network will offer greater advantages to the network operators, as the presence of an on-board battery of discrete capacity will be able to support a whole series of ancillary services or smart energy management. To allow this, the vehicle must be equipped with a bidirectional full power charger, which will allow not only recharging but also the supply of energy to the network, playing an active role as a distributed energy resource. To manage recharge and vehicle-to-grid (V2G) operations, the charger has to be more complex and has to require a fast and effective control structure. In this work, we present a control strategy for an integrated on-board battery charger with a nine-phase electric machine. The control scheme integrates a fuzzy logic controller within a voltage-oriented control strategy. The control has been implemented and simulated in Simulink. The results show how the voltage on the DC-bus is controlled to the reference value by the fuzzy controller and how the CC/CV charging mode of the battery is possible, using different charging/discharging current levels. This allows both three-phase fast charge and V2G operations with fast control response time, without causing relevant distortion grid-side (Total Harmonic Distortion is maintained around 3%), even in the presence of imbalances of the machine, and with very low ripple stress on the battery current/voltage.

scholarly journals Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

2020 ◽  
Vol 12 (14) ◽  
pp. 5561 ◽  
Author(s):  
Bhagya Nathali Silva ◽  
Murad Khan ◽  
Kijun Han
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Demand ◽  
Management Strategies ◽  
Peak Load ◽  
Critical Discussion ◽  
Future Research ◽  
Smart Environments ◽  
Challenges And Opportunities ◽  
Management Approaches

The emergence of the Internet of Things (IoT) notion pioneered the implementation of various smart environments. Smart environments intelligibly accommodate inhabitants’ requirements. With rapid resource shrinkage, energy management has recently become an essential concern for all smart environments. Energy management aims to assure ecosystem sustainability, while benefiting both consumers and utility providers. Although energy management emerged as a solution that addresses challenges that arise with increasing energy demand and resource deterioration, further evolution and expansion are hindered due to technological, economical, and social barriers. This review aggregates energy management approaches in smart environments and extensively reviews a variety of recent literature reports on peak load shaving and demand response. Significant benefits and challenges of these energy management strategies were identified through the literature survey. Finally, a critical discussion summarizing trends and opportunities is given as a thread for future research.

scholarly journals Cost implications of increased solar penetration and time-of-use rate interactions

Clean Energy ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 247-269
Author(s):  
Dominique Bain ◽  
Tom Acker
Keyword(s):  
Cost Model ◽  
Peak Load ◽  
Production Costs ◽  
Electricity Grid ◽  
Load Change ◽  
Marginal Prices ◽  
The Usa ◽  
Locational Marginal Prices ◽  
Grid Operators ◽  
Solar Generation

Abstract Electricity-grid operators are facing new challenges in matching load and generation due to increased solar generation and peak-load growth. This paper demonstrates that time-of-use (TOU) rates are an effective method to address these challenges. TOU rates use price differences to incentivize conserving electricity during peak hours and encouraging use during off-peak hours. This strategy is being used across the USA, including in Arizona, California and Hawaii. This analysis used the production-cost model PLEXOS with an hourly resolution to explore how production costs, locational marginal prices and dispatch stacks (type of generation used to meet load) change due to changes in load shapes prompted by TOU rates and with additional solar generation. The modelling focused on implementing TOU rates at three different adoption (response) levels with and without additional solar generation in the Arizona balancing areas within a PLEXOS model. In most cases analysed, implementing TOU rates in Arizona reduced reserve shortages in the Western Interconnect and, in some cases, very substantially. This result is representative of the interactions that happen interconnection-wide, demonstrating the advantage of modelling the entire interconnection. Production costs were decreased by the additional solar generation and the load change from TOU rates, and high response levels reduced the production costs the most for high-solar-generation cases. Load change from TOU rates decreased locational marginal prices for a typical summer day but had inconsistent results on a high-load day. Additional solar generation decreased the usage of combustion turbines, combined cycles and coal-fired generation.

Impact of Storage Integrated Solar Photovoltaics (PV) Power System on Utility Peak Loads

2011 ◽  
Author(s):  
K. Agyenim-Boateng ◽  
R. F. Boehm
Keyword(s):  
Large Scale ◽  
Peak Load ◽  
Average Energy ◽  
Transient Behavior ◽  
Climatic Conditions ◽  
Photovoltaic System ◽  
Solar Pv ◽  
Pv System ◽  
Grid Load ◽  
The Impact

The promise of large-scale use of renewables such as wind and solar for supplying electrical power is tempered by the sources’ transient behavior and the impact this would have on the operation of the grid. One way of addressing this is through the use of supplemental energy storage. While the technology for the latter has not been proven on a large scale or to be economical at the present time, some assessments of what magnitude is required can be made. In performing this work we have used NREL’s Solar Advisor Model (SAM 2010) with TMY3 solar data to estimate the photovoltaic system power generation. Climatic conditions close to load centers were chosen for the simulations. Then the PV output for varying sizes of arrays were examined and the impact of varying amounts of storage investigated. The storage was characterized by maximum limiting energy and power capacities based on annual hourly peak load, as well as its charging and discharging efficiencies. The simulations were performed using hourly time steps with energy withdrawn from, or input to, storage only after considering base generation and the PV system output in serving the grid load. In this work, we examined the load matching capability of solar PV generation (orientated for maximum summer output) for a sample Southwestern US utility grid load of 2008. Specifically we evaluated the daily and seasonal peak load shifting with employing varying storage capacities. The annual average energy penetration based on the usable solar PV output is also examined under these conditions and at different levels of system flexibility.

A hybrid data mining driven algorithm for long term electric peak load and energy demand forecasting

Energy ◽  
2020 ◽  
Vol 204 ◽  
pp. 117948 ◽  
Author(s):  
Mohammad-Rasool Kazemzadeh ◽  
Ali Amjadian ◽  
Turaj Amraee
Keyword(s):  
Data Mining ◽  
Energy Demand ◽  
Demand Forecasting ◽  
Peak Load ◽  
Energy Demand Forecasting ◽  
Hybrid Data

Optimal Hybrid Power Energy Systems for Residential Communities in Saudi Arabia

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Ammar H. A. Dehwah ◽  
Moncef Krarti
Keyword(s):  
Saudi Arabia ◽  
Renewable Energy ◽  
Energy Demand ◽  
Peak Load ◽  
Energy Systems ◽  
Cost Effective ◽  
Eastern Region ◽  
Residential Communities ◽  
Efficiency Measures ◽  
Cost Of Energy

To meet the increasing energy demand and to shave the peak, the Kingdom of Saudi Arabia (KSA) is currently planning to invest more on renewable energy (RE) seeking diversity of energy resources. Through the integration of demand-side management measures and renewable energy distributed generation (DG) systems, the study outlined in this paper aims at investigating the potential of hybrid renewable energy systems in supplying energy demands for residential communities in an oil-rich country. The residential community considered in this study, located in the eastern region of KSA, has an annual electrical usage of 1174 GWh and an electrical peak load of 335 MW that are met solely by the grid. The results of the analyses indicated that the implementation of cost-effective energy efficiency measures (EEMs) reduced the electricity usage by 38% and peak demand by 51% as well as CO2 emissions by 38%. Although the analysis of the hybrid systems showed that purchasing electricity from the grid is the best option with a levelized cost of energy (LCOE) of $0.1/kWh based on the current renewable energy market and economic conditions of KSA, RE systems can be cost-effective to meet the loads of the residential communities under specific electricity prices and capital cost levels.

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