scholarly journals Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3666 ◽  
Author(s):  
Mahmoud M. Gamil ◽  
Makoto Sugimura ◽  
Akito Nakadomari ◽  
Tomonobu Senjyu ◽  
Harun Or Rashid Howlader ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Sea Water ◽  
Peak Load ◽  
Mixed Integer ◽  
Japanese Island ◽  
Total System ◽  
System Cost ◽  
Optimal Sizing ◽  
Demand Response Programs

Optimal sizing of power systems has a tremendous effective role in reducing the total system cost by preventing unneeded investment in installing unnecessary generating units. This paper presents an optimal sizing and planning strategy for a completely hybrid renewable energy power system in a remote Japanese island, which is composed of photovoltaic (PV), wind generators (WG), battery energy storage system (BESS), fuel cell (FC), seawater electrolysis plant, and hydrogen tank. Demand response programs are applied to overcome the performance variance of renewable energy systems (RESs) as they offer an efficient solution for many problems such as generation cost, high demand peak to average ratios, and assist grid reliability during peak load periods. Real-Time Pricing (RTP), which is deployed in this work, is one of the main price-based demand response groups used to regulate electricity consumption of consumers. Four case studies are considered to confirm the robustness and effectiveness of the proposed schemes. Mixed-Integer Linear Programming (MILP) is utilized to optimize the size of the system’s components to decrease the total system cost and maximize the profits at the same time.

Optimum sizing and simulation of hybrid renewable energy system for remote area

2021 ◽  
pp. 0958305X2110301
Author(s):  
Animesh Masih ◽  
HK Verma
Keyword(s):  
Renewable Energy ◽  
Reliability Index ◽  
Energy System ◽  
Energy Resources ◽  
Total System ◽  
Renewable Energy Resources ◽  
Optimal Sizing ◽  
Remote Areas ◽  
Grasshopper Optimization Algorithm ◽  
Hybrid Renewable Energy

In current scenario, people tend to move towards outskirts and like to settle in places that are close to nature. But, due to urban lifestyle and to fulfill the basic needs, demand of electricity remains the same as in urban areas. This demand of electricity can be only fulfilled by using hybrid renewable energy resources, which is easily available in outskirts. Renewable energy resources are unreliable and more expensive. Researchers are working to make, it more reliable and economic in terms of utilization. This article proposes a metaheuristic grasshopper optimization algorithm (GOA) for the optimal sizing of hybrid PV/wind/battery energy system located in remote areas. The proposed algorithm finds the optimal sizing and configuration of remote village load demand that includes house electricity and agriculture. The optimization problem is solved by minimization of total system cost at a desirable level of loss of power supply’s reliability index (LPSRI). The results of GOA are compared with particle swarm optimization (PSO), genetic algorithm (GA) and hybrid optimization of multiple energy resources (HOMER) software. In addition, results are also validated by modeling and simulation of the hybrid energy system and its configurations at different weather conditions-based results. Hybrid PV/wind/battery is found as an optimal system at remote areas and sizing are[Formula: see text] with cost of energy (COE) (0.3473$/kWh) and loss of power supplies reliability index (LPSRI) (0%). It is clear from the results that GOA based methods are more efficient for selection of optimal energy system configuration as compared to others algorithms.

scholarly journals Strategies for Datacenters Participating in Demand Response by Two-Stage Decisions

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuling Li ◽  
Xiaoying Wang ◽  
Peicong Luo
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Smart Grids ◽  
Peak Load ◽  
Two Stage ◽  
The Sustainable Development ◽  
Second Stage ◽  
Potential Demand ◽  
Electricity Costs ◽  
Demand Response Programs

Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.

scholarly journals Research on Economic Operation Strategy of CHP Microgrid Considering Renewable Energy Sources and Integrated Energy Demand Response

2019 ◽  
Vol 11 (18) ◽  
pp. 4825 ◽  
Author(s):  
Jun Dong ◽  
Shilin Nie ◽  
Hui Huang ◽  
Peiwen Yang ◽  
Anyuan Fu ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Rapid Development ◽  
Utilization Efficiency ◽  
Energy Output ◽  
Mixed Integer ◽  
Energy Structure ◽  
Economic Operation

Renewable energy resources (RESs) play an important role in the upgrading and transformation of the global energy structure. However, the question of how to improve the utilization efficiency of RESs and reduce greenhouse gas emissions is still a challenge. Combined heating and power (CHP) is one effective solution and has experienced rapid development. Nevertheless, with the large scale of RESs penetrating into the power system, CHP microgrid economic operation faces great challenges. This paper proposes a CHP microgrid system that contains renewable energy with considering economy, the environment, and system flexibility, and the ultimate goal is to minimize system operation cost and carbon dioxide emissions (CO2) cost. Due to the volatility of renewable energy output, the fuzzy C-means (FCM) and clustering comprehensive quality (CCQ) models were first introduced to generate clustering scenarios of the renewable energy output and evaluate the clustering results. In addition, for the sake of improving the flexibility and reliability of the CHP microgrid, this paper considers the battery and integrated energy demand response (IEDR). Moreover, the strategy choices of microgrid operators under the condition of grid-connected and islanded based on environment and interest aspects are also developed, which have rarely been involved in previous studies. Finally, this stochastic optimization problem is transformed into a mixed integer linear programming (MILP), which simplifies the calculation process, and the results show that the operation mode under different conditions will have a great impact on microgrid economic and environmental benefits.

scholarly journals Key Factors Which Contribute to the Participation of Consumers in Demand Response Programs and Enable the Proliferation of Renewable Energy Sources

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8273
Author(s):  
Adrian Tantau ◽  
András Puskás-Tompos ◽  
Costel Stanciu ◽  
Laurentiu Fratila ◽  
Catalin Curmei
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Online Survey ◽  
Consumer Behaviour ◽  
Renewable Energy Sources ◽  
Energy System ◽  
Energy Sources ◽  
Main Role ◽  
Key Factors ◽  
Demand Response Programs

Consumer behaviour in the energy field is playing a more important role in the new approach dominated by the proliferation of renewable energy sources. In this new context, the grid has to balance the intermittent and uncertain renewable energy generated, and find solutions, also, on the consumer side for increasing the stability and reliability of the energy system. The main de-mand response solutions are price and incentive based, but there is a need to identify the main factors which can influence their efficiency due to the fact that there is a lack of knowledge about the preferences of consumers. The main goal of this article is to identify the main demand response solutions and the related key factors which influence the participation of consumers in demand response programs and may contribute to the spread of renewable energy sources. For this research, semi-structured interviews were organised with experts in energy from Romania, Hungary and Serbia, as well as workshops with experts in energy, and an online survey with customers for electricity. This article reduces the gap between the results of technical studies, related in demand response programs, and their practical implementations, where the consumer behaviour and its social dimensions are neglected even though, in reality, they are playing the main role. The results suggest that the consumer’s participation in demand response programs is highly influenced by different aspects related to the promotion of the renewable energy and the reduction of CO2 emissions and the global warming impact.

scholarly journals Intelligent Dynamic Pricing Scheme for Demand Response in Brazil Considering the Integration of Renewable Energy Sources

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4839
Author(s):  
Diego B. Vilar ◽  
Carolina M. Affonso
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Dynamic Pricing ◽  
Renewable Energy Sources ◽  
Rebound Effect ◽  
Peak Load ◽  
Energy Sources ◽  
Load Factor ◽  
Pricing Scheme ◽  
Improve Algorithm

This paper proposes a novel dynamic pricing scheme for demand response with individualized tariffs by consumption profile, aiming to benefit both customers and utility. The proposed method is based on the genetic algorithm, and a novel operator called mutagenic agent is proposed to improve algorithm performance. The demand response model is set by using price elasticity theory, and simulations are conducted based on elasticity, demand, and photovoltaic generation data from Brazil. Results are evaluated considering the integration effects of renewable energy sources and compared with other two pricing strategies currently adopted by Brazilian utilities: flat tariff and time-of-use tariff. Simulation results show the proposed dynamic tariff brings benefits to both utilities and consumers. It reduces the peak load and average cost of electricity and increases utility profit and load factor without the undesirable rebound effect.

Optimal sizing and operation for microgrid with renewable energy considering two types demand response

2020 ◽  
Vol 12 (6) ◽  
pp. 065901
Author(s):  
Makoto Sugimura ◽  
Mahmoud M. Gamil ◽  
Homeyra Akter ◽  
Narayanan Krishna ◽  
Mamdouh Abdel-Akher ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Optimal Sizing

scholarly journals An Economic Analysis of Demand Side Management Considering Interruptible Load and Renewable Energy Integration: A Case Study of Freetown Sierra Leone

2019 ◽  
Vol 11 (10) ◽  
pp. 2828 ◽  
Author(s):  
Abdul Conteh ◽  
Mohammed Elsayed Lotfy ◽  
Kiptoo Mark Kipngetich ◽  
Tomonobu Senjyu ◽  
Paras Mandal ◽  
...  
Keyword(s):  
Developing Countries ◽  
Renewable Energy ◽  
Economic Analysis ◽  
Sierra Leone ◽  
Demand Response ◽  
Peak Load ◽  
Developed Countries ◽  
Research Attention ◽  
Load Demand ◽  
The Impact

Like in most developing countries, meeting the load demand and reduction in transmission grid bottlenecks remains a significant challenge for the power sector in Sierra Leone. In recent years, research attention has shifted to demand response (DR) programs geared towards improving the supply availability and quality of energy markets in developed countries. However, very few studies have discussed the implementation of suitable DR programs for developing countries, especially when utilizing renewable energy (RE) resources. In this paper, using the Freetown’s peak load demand data and the price elasticity concept, the interruptible demand response (DR) program has been considered for maximum demand index (MDI) customers. Economic analysis of the energy consumption, customer incentives, benefits, penalties and the impact on the load demand are analyzed, with optimally designed energy management for grid-integrated battery energy storage system (BESS) and photovoltaic (PV)-hybrid system using the genetic algorithm (GA). Five scenarios are considered to confirm the effectiveness and robustness of the proposed scheme. The results show the economic superiority of the proposed DR program’s approach for both customers and supplier benefits. Moreover, RE inclusion proved to be a practical approach over the project lifespan, compared to the diesel generation alternative.

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