scholarly journals Integrated Transportation, Building, and Electricity System Models to Explore Decarbonization Pathways in Regina, Saskatchewan

2021 ◽  
Vol 3 ◽  
Author(s):  
Madeleine Seatle ◽  
Lauren Stanislaw ◽  
Robert Xu ◽  
Madeleine McPherson
Keyword(s):  
Renewable Energy ◽  
Spatial Resolution ◽  
Demand Response ◽  
Energy Demand ◽  
Large Scale ◽  
Travel Demand ◽  
Electricity Demand ◽  
Demand Side ◽  
Battery Storage ◽  
Electricity System

In Canada, the majority of urban energy demand services the transportation or building sectors, primarily with non-renewable energy sources including gasoline and natural gas. As a result, these two sectors account for 70% of urban greenhouse gas (GHG) emissions. The objective of this paper is to explore the potential for co-benefits when simultaneously electrifying transportation and building demand sectors while expanding variable renewable energy (VRE) production. The investigation uses a novel integrated framework of the transportation, building, and electricity sectors to represent the operational implications of demand side flexibility on both the demand and supply side of the energy system. This original approach allows for very fine temporal and spatial resolution within models, while still performing a multi-sector analysis. First, the activity-based transportation model produces passenger travel demand profiles, allowing for investigation of potential electricity demand and demand response from electric vehicles with high spatial and temporal resolution. Second, the archetype-based building model predicts electricity demand of the residential building sector, allowing for investigation into demand-side management strategies such as load-shifting, building retrofits, and changes in appliance technology. Third, the electricity system production cost dispatch model is used to model the operations of Regina's electricity grid and has a spatial resolution capable of assessing individual and connected positive energy districts as well as VRE integration. Through linking of these three models, the effects of consumer flexibility in transportation and building energy demand are explored, especially in the context of introducing much needed flexibility for large-scale VRE integration. A utility-controlled demand response (DR) strategy is explored as means for Regina to reach their renewable target, along with battery storage. Various pathways to Regina's target are considered, based on the various proposed scopes of the target. The results show that Regina can meet their renewable target with large-scale rooftop solar and wind capacity. DR strategies are marginally effective in aiding toward the renewable target, but, when implemented in conjunction with battery storage, is able to get Regina to within 1% of their renewable target.

scholarly journals Two-Stage Optimal Scheduling of Large-Scale Renewable Energy System Considering the Uncertainty of Generation and Load

2020 ◽  
Vol 10 (3) ◽  
pp. 971 ◽  
Author(s):  
Xiangyu Kong ◽  
Shuping Quan ◽  
Fangyuan Sun ◽  
Zhengguang Chen ◽  
Xingguo Wang ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Large Scale ◽  
Thermal Power ◽  
Estimation Method ◽  
Point Estimation ◽  
Low Carbon ◽  
System Operation ◽  
Two Stage ◽  
Point Estimation Method

With the development of smart grid and low-carbon electricity, a high proportion of renewable energy is connected to the grid. In addition, the peak-valley difference of system load increases, which makes the traditional grid scheduling method no longer suitable. Therefore, this paper proposes a two-stage low-carbon economic scheduling model considering the characteristics of wind, light, thermal power units, and demand response at different time scales. This model not only concerns the deep peak state of thermal power units under the condition of large-scale renewable energy, but also sets the uncertain models of PDR (Price-based Demand Response) virtual units and IDR (Incentive Demand Response) virtual units. Taking the system operation cost and carbon treatment cost as the target, the improved bat algorithm and 2PM (Two-point Estimation Method) are used to solve the problem. The introduction of climbing costs and low load operating costs can more truly reflect the increased cost of thermal power units. Meanwhile, the source-load interaction can weigh renewable energy limited costs and the increased costs of balancing volatility. The proposed method can be applied to optimal dispatch and safe operation analysis of the power grid with a high proportion of renewable energy. Compared with traditional methods, the total scheduling cost of the system can be reduced, and the rights and obligations of contributors to system operation can be guaranteed to the greatest extent.

scholarly journals Managing Power Demand from Air Conditioning Benefits Solar PV in India Scenarios for 2040

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2223
Author(s):  
Ahmad Murtaza Ershad ◽  
Robert Pietzcker ◽  
Falko Ueckerdt ◽  
Gunnar Luderer
Keyword(s):  
Air Conditioning ◽  
Economic Value ◽  
Electricity Demand ◽  
Solar Irradiation ◽  
Demand Side ◽  
Solar Pv ◽  
Source Power ◽  
Sector Model ◽  
Electricity System ◽  
Pv Generation

An Indian electricity system with very high shares of solar photovoltaics seems to be a plausible future given the ever-falling solar photovoltaic (PV) costs, recent Indian auction prices, and governmental support schemes. However, the variability of solar PV electricity, i.e., the seasonal, daily, and other weather-induced variations, could create an economic barrier. In this paper, we analyzed a strategy to overcome this barrier with demand-side management (DSM) by lending flexibility to the rapidly increasing electricity demand for air conditioning through either precooling or chilled water storage. With an open-source power sector model, we estimated the endogenous investments into and the hourly dispatching of these demand-side options for a broad range of potential PV shares in the Indian power system in 2040. We found that both options reduce the challenges of variability by shifting electricity demand from the evening peak to midday, thereby reducing the temporal mismatch of demand and solar PV supply profiles. This increases the economic value of solar PV, especially at shares above 40%, the level at which the economic value roughly doubles through demand flexibility. Consequently, DSM increases the competitive and cost-optimal solar PV generation share from 33–45% (without DSM) to ~45–60% (with DSM). These insights are transferable to most countries with high solar irradiation in warm climate zones, which amounts to a major share of future electricity demand. This suggests that technologies, which give flexibility to air conditioning demand, can be an important contribution toward enabling a solar-centered global electricity supply.

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.

Techno-Economic Performance Evaluation and Enhancement for a PV – Diesel Hybrid System

2016 ◽  
Vol 839 ◽  
pp. 130-135
Author(s):  
Ivan Tendo ◽  
Chatchai Sirisamphanwong
Keyword(s):  
Renewable Energy ◽  
Hybrid System ◽  
Energy Demand ◽  
Storage System ◽  
System Size ◽  
Performance Ratio ◽  
Optimal Size ◽  
Battery Storage ◽  
Diesel Generator ◽  
Energy Fraction

In this research paper, an illustration for system size optimization for a stand-alone PV – diesel hybrid system is obtained. The requirement is to obtain an optimal size that can meet energy demand at an optimized cost for a given lifetime period of the project, this will be achieved using HOMER software to further improve the system parameters like performance ratio, renewable energy fraction, MATLAB will be used. This research study will be done basing on a system currently installed at the School of Renewable Energy, Naresuan University (SERT), this system has a capacity of 120 kW, and it is a hybrid system with PV array, Diesel generator and battery storage system. The cost parameters that will be addressed are; - Net present cost (NPC), Cost of Energy (COE), Capital cost (CC). The initial size of the hybrid system is PV-120kW, Diesel generator -100kW and battery storage of 200kWh after modelling and simulation with HOMER software using special models to show the predicted performance of the final outcome, the optimal size created has a PV size of 100kW, diesel generator with a size of 100kW and battery storage of 100kWh and compared to the initial system COE od 1.01$/kWh, the optimal size has a COE of 0.934$/kWh.

scholarly journals Legal and Policy Framework for Renewable Energy and Energy Efficiency Development in Vietnam

2020 ◽  
Vol 1 (1) ◽  
pp. 33-47
Author(s):  
Tran Viet Dung
Keyword(s):  
Energy Efficiency ◽  
Renewable Energy ◽  
Energy Demand ◽  
Large Scale ◽  
Negative Impact ◽  
High Energy ◽  
Renewable Energies ◽  
Policy Framework ◽  
Renewable Energy Resources ◽  
Economic Sectors

AbstractVietnam has experienced an economic growth accompanied by increasing energy demand and inadequate supplies. Like most developing countries, the increased inefficient use of energy in Vietnam leads to increased greenhouse gas emissions and high energy costs for consumers. Also, the traditional sources of energy are not sufficient to satisfy the demand of the economic sectors.With the negative impact of climate change on water resources and the depletion of coal, oil and gas reserves, Vietnam must diversify and integrate other forms of renewable energies into its energy mix. The efficient use of renewable energy resources can boost economic development. Thus, the policies for endorsing renewable energies and energy efficiency are playing a vital role in ensuring the sustainable development for Vietnam’s future. This paper examines the legal and policy framework influencing the deployment of renewable energies and energy efficiency in Vietnam. The paper also attempts to identify major barriers to a large scale deployment of renewable energies and energy efficiency technologies and offers some possible solutions.

scholarly journals Demand-Side Management of Smart Distribution Grids Incorporating Renewable Energy Sources

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 143 ◽  
Author(s):  
Gerardo J. Osório ◽  
Miadreza Shafie-khah ◽  
Mohamed Lotfi ◽  
Bernardo J. M. Ferreira-Silva ◽  
João P. S. Catalão
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Demand Response ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Demand Side Management ◽  
Pollutant Emissions ◽  
Demand Side ◽  
Renewable Energy Resources ◽  
Distribution Grids

The integration of renewable energy resources (RES) (such as wind and photovoltaic (PV)) on large or small scales, in addition to small generation units, and individual producers, has led to a large variation in energy production, adding uncertainty to power systems (PS) due to the inherent stochasticity of natural resources. The implementation of demand-side management (DSM) in distribution grids (DGs), enabled by intelligent electrical devices and advanced communication infrastructures, ensures safer and more economical operation, giving more flexibility to the intelligent smart grid (SG), and consequently reducing pollutant emissions. Consumers play an active and key role in modern SG as small producers, using RES or through participation in demand response (DR) programs. In this work, the proposed DSM model follows a two-stage stochastic approach to deal with uncertainties associated with RES (wind and PV) together with demand response aggregators (DRA). Three types of DR strategies offered to consumers are compared. Nine test cases are modeled, simulated, and compared in order to analyze the effects of the different DR strategies. The purpose of this work is to minimize DG operating costs from the Distribution System Operator (DSO) point-of-view, through the analysis of different levels of DRA presence, DR strategies, and price variations.

scholarly journals The Role of Electricity Balancing and Storage: Developing Input Parameters for the European Calculator for Concept Modeling

2020 ◽  
Vol 12 (3) ◽  
pp. 811 ◽  
Author(s):  
Miklós Gyalai-Korpos ◽  
László Zentkó ◽  
Csaba Hegyfalvi ◽  
Gergely Detzky ◽  
Péter Tildy ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Electricity Generation ◽  
New Technologies ◽  
Supply And Demand ◽  
Oil Refinery ◽  
Demand Side ◽  
The European Union ◽  
Electricity System ◽  
Input Parameters

Despite the apparent stability of the electricity system from a consumer’s point of view, there is indeed significant effort exerted by network operators to guarantee the constancy of the electricity supply in order to meet demands any time. In the energy sector models provide an important conceptual framework to generate a range of insight, examine the impacts of different scenarios and analyze the supply and demand of energy. This paper presents a user-oriented and transparent modeling concept of the European calculator, a tool for delineating emission and sustainable transformation pathways at European and member state levels. The model consists of several modules of different sectors, where the energy supply module includes sub-modules for electricity generation, hydrogen production and oil refinery. The energy storage requirement module investigates how new technologies can help the stability of the European electricity system with increasing renewables penetration, demand-side measures and decarbonization paths. The objective of this study is to introduce the concept of this module with the main logical steps, especially the input parameters, assumptions, the basic data of electricity trade and maximum energy storage potential levels. The article also introduces and explains the feasibility of the theoretical maximum gross electricity generation potential from variable renewable energy for the European Union including Switzerland, compared to the demand in 2040. According to the results the electricity systems in the future will need to show ever increasing flexibility in order to cope with variable renewable energy production on the supply side, and shifting patterns of electricity consumption on the demand side.

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