Abstract[edit | edit source]
The duck curve—named after its resemblance to a duck—shows the difference in electricity demand and the amount of available solar energy throughout the day. When the sun is shining, solar floods the market and then drops off as electricity demand peaks in the evening. The Duck Curve is a graph that shows the difference in electricity demand on the grid and the amount of available solar energy throughout the day. It was created by the California Independent System Operator (ISO) to demonstrate the electric load on the ISO grid on an average spring day when it's sunny but temperatures are cool, meaning that demand is not as high as in height of summer when people are using AC or in the winter when heating homes is needed. Though adapting to changing consumer demand has been an issue that utilities have dealt with for over a century, seasonal usage patterns have changed, and the actual resources used for generating electricity have evolved. The Duck Curve illustrates an important aspect of the challenges that renewable energy such as solar poses to utility managers, and how these have evolved over a much shorter time period. The duck curve is a snapshot of a 24-hour period in California during springtime—when this effect is most extreme because it's sunny but temperatures remain cool, so demand for electricity is low since people are not using electricity for air conditioning or heating. The duck curve represents a transition point for solar energy. It was, perhaps, the first major acknowledgement by a system operator that solar energy is no longer a niche technology and that utilities need to plan for increasing amounts of solar energy. This is especially true for places that already have high solar adoption, such as California, where one day in March 2020, solar contributed nearly 40% of electricity generation in the state for the first time ever. However, PV penetration into the grid comes with its drawbacks. The inverter-interfaced nature of the PV systems significantly impacts the power system operation from protection, power flow and stability perspectives. It is therefore, important to investigate aggressive methods to ensure proper protection, power flow, and stability of the power grid. There are regions in the world that are already successfully managing an extremely high penetration of renewable VERs. For example, Portugal was run 100 percent on wind, solar, and hydropower for four days straight in May 2016, and Texas hit a record level of 45% instantaneous penetration from wind generation during one evening in February of 2020.
The purpose of this project is to investigate distributed load shifting where the consumer shifts load to help the utility obtain a higher PV penetration without being hammered by the duck curve. First, we dig in deep on appliances that are smart enough to help shift the load by making a table along with normal use kWh move amount. We focused on EPA appliance data, washing machines, dishwashers, and 3D printing during the day at home. In fact, as the coronavirus pandemic forces people across the country to shelter at home, utilities and grid operators are watching typical energy-use patterns change in unpredictable ways and trying to understand how this will affect their grid operations, power purchasing practices and long-term plans. The resulting shifts in typical energy patterns have been illuminating, according to Scott Hinson, Pecan Street's chief technology officer. "We know they're not indicative of every household in America," he said in an interview this week. "But it is illustrative of what happens when you tell people to stay home, stay cool and stay productive." By running the data through a "per cooling-degree day" calculation, Pecan Street estimates that air conditioner usage was up about 40 percent in the last week of March compared to historical averages. Then, we order the list based on most promising. Finally, the investigation shows that the strategy of success of the process implemented for appliances operating like clothes washers and dishwashers depends on consumers' willingness to accept the solution if additional costs are sponsored by energy utility or balanced by savings via energy bill. For appliances operating similar to clothes dryers, utilities must define harmonized signal for shortage of power, and define business model where energy utilities sponsor the implementation of these "Internal energy management agent" modules.
Literature Review (to be revisited)[edit | edit source]
[1] A Case Study on Optimal Sizing of Battery Energy Storage to Solve 'Duck Curve' Issues in Malaysia by Wong, L. Ai. & Ramachandaramurthy V. K. in 2020 International Conference on Smart Grid and Clean Energy Technologies (ICSGCE)[edit | edit source]
In this paper, the authors study an Optimal Sizing of Battery Energy Storage to Solve 'Duck Curve' Issues in Malaysia. Battery energy storage (BES) has the ability to solve many power system problems especially in systems with renewable energy resources integrated. Due to the intermittent nature of solar photovoltaic (PV) generation, different problems have arise such as voltage fluctuation and reverse power flow. Besides, duck curve issue has become more significant with the increasing amount of PV integrated in the power system as first raised by the Californian Independent System Operator. Studies on these issues has become important in order to solve the steep ramp and over generation problems caused by duck curve issue. The duck curve issues based on general Malaysia load profile and PV pattern are studied in this paper. Besides, the feasibility of BES in solving these issues with suitable BES capacity is investigated. The results show that the BES has the ability to solve the duck curve issues through proper control of BES charging and discharging operation.
[2] A High-Efficiency Network-Constrained Clustered Unit Commitment Model for Power System Planning Studies by E. Du, N. Zhang, C. Kang, & Q. Xia[edit | edit source]
The increasing complexity of power systems, particularly the high renewable energy penetration, raises the necessity of incorporating detailed power system operation models into long-term planning studies. The classic short-term operation model, i.e., network-constrained unit commitment (NCUC), involves many binary variables and introduces computational challenges when applied to long-term planning optimizations. A high-efficiency and simplified NCUC model is required to incorporate operational flexibility in power system planning studies. This paper proposes a linearized NCUC formulation that has a high calculation performance and minor approximation errors compared to the full NCUC model. The proposed model combines the dispatch-only (DO) operation model and clustered unit commitment (CUC) model by introducing linking constraints between them such that the overall model guarantees both the transmission security constraints that are formulated in the DO model and the start-up/shut-down constraints of generating units that are formulated in the CUC model. A case study of a modified IEEE RTS-79 system is provided to demonstrate the validation and efficiency of the proposed simplified NCUC model as well as its effectiveness for power system planning studies.
[3] A Residential Load Scheduling with the Integration of On-Site PV and Energy Storage Systems in Micro-Grid by Rasheed, Muhammad Babar & Alquthami, Shahzadi[edit | edit source]
In this paper, the authors study a Residential Load Scheduling with the Integration of On-Site PV and Energy Storage Systems in Micro-Grid. The smart grid (SG) has emerged as a key enabling technology facilitating the integration of variable energy resources with the objective of load management and reduced carbon-dioxide (CO2) emissions. However, dynamic load consumption trends and inherent intermittent nature of renewable generations may cause uncertainty in active resource management. Eventually, these uncertainties pose serious challenges to the energy management system. To address these challenges, this work establishes an efficient load scheduling scheme by jointly considering an on-site photo-voltaic (PV) system and an energy storage system (ESS). An optimum PV-site matching technique was used to optimally select the highest capacity and lowest cost PV module. Furthermore, the best-fit of PV array in regard with load is anticipated using least square method (LSM). Initially, the mathematical models of PV energy generation, consumption and ESS are presented along with load categorization through Zero and Finite shift methods. Then, the final problem is formulated as a multiobjective optimization problem which is solved by using the proposed Dijkstra algorithm (DA). The proposed algorithm quantifies day-ahead electricity market consumption cost, used energy mixes, curtailed load, and grid imbalances. However, to further analyze and compare the performance of proposed model, the results of the proposed algorithm are compared with the genetic algorithm (GA), binary particle swarm optimization (BPSO), and optimal pattern recognition algorithm (OPRA), respectively. Simulation results show that DA achieved 51.72% cost reduction when grid and renewable sources are used. Similarly, DA outperforms other algorithms in terms of maximum peak to average ratio (PAR) reduction, which is 10.22%.
[4] A Review of Strategies to Increase PV Penetration Level in Smart Grids by Aleem, Sk Abdul, Hussain, S. M. Suhail, & Ustun, Taha Selim.[edit | edit source]
In this paper, the authors study Strategies to Increase PV Penetration Level in Smart Grids. Due to environmental concerns, power system generation is shifting from traditional fossil-fuel resources to renewable energy such as wind, solar and geothermal. Some of these technologies are very location specific while others require high upfront costs. Photovoltaic (PV) generation has become the rising star of this pack, thanks to its versatility. It can be implemented with very little upfront costs, e.g., small solar home systems, or large solar power plants can be developed to generate MWs of power. In contrast with wind or tidal generation, PV can be deployed all around the globe, albeit with varying potentials. These merits have made PV the renewable energy technology with highest installed capacity around the globe. However, PV penetration into the grid comes with its drawbacks. The inverter-interfaced nature of the PV systems significantly impacts the power system operation from protection, power flow and stability perspectives. There must be strategies to mitigate these negative impacts so that PV penetration into the grid can continue. This paper gives a thorough overview of such strategies from different research fields: such as communication, artificial intelligence, power electronics and electric vehicle charging coordination. In addition, possible research directions are given for future work.
[5] An efficient solution method for integrated unit commitment and natural gas network operational scheduling under "Duck Curve" by Fallahi, Farhad, & Maghouli, Pouria[edit | edit source]
In this paper, the authors study an integrated unit commitment and natural gas network operational scheduling with renewable energy (wind and photovoltaic power plants) which changes the load curve to a duck curve. Wind and photovoltaic energy are both uncertain in nature. The availability of photovoltaic energy at certain times of day changes the pattern of the load. This load curve which is called "Duck Curve," raises the question of whether the power system could provide the necessary ramp rate and capacity for full utilization of photovoltaic energy. The use of gas power plants to deal with the sharp ramp rate would have a negative impact on the flow of gas in the gas network. That is, the uncertain output of renewable resources requires the flexibility of gas power plants which affects the gas network. Storage devices of electricity and gas, line-pack and the technology of electricity to gas transformation (P2G) could be effective solutions for reducing fluctuations and ensuring reliable operation of electricity and gas networks. The underlying problem is known to be a complex nonconvex problem. Compared to existing modeling and solution methods, we propose some efficient reformulation which enables us to rewrite the problem as a convex mixed integer program using Benders decomposition. Given the convex reformulation, we can solve the resulting convex model to optimality. We demonstrate the effectiveness of the proposed method by solving some standard examples such as the modified IEEE 24-Bus test system and the Belgian 20-node gas network.
[6] Analysis of Maximum Intermittent Renewable Energy Source Penetration on South of Sulawesi Power System by H. B. Tambunan, P. A. A. Pramana, & B. S. Munir[edit | edit source]
One of the adverse using renewable energy source is intermittency characteristic. It will have a considerable impact on power system stability and reliability. This study aims to calculate how much intermittent renewable energy source (IRES) penetration into the interconnected power system without causing collapse the system based on applicable standards. Stable conditions by standards must meet the acceptable voltage and system frequency. The level of IRES penetration based on the worst scenario that may occur in the system during intermittent such as penetration in weakest bus by sensitivity analysis, dry season, maintenance of largest generator, peak load, and off-peak load condition. The simulation showed the IRES penetration level into the South of Sulawesi power system are about 0,32% in off-peak load and about 5,24 % in peak load.
[7] Automated demand response strategies using home energy management system in a RES-based smart grid by Zunnurain, L., Maruf, M. N. I.[edit | edit source]
In this paper, the authors study Automated demand response strategies using home energy management system in a RES-based smart grid. Demand Response (DR) applications via Home Energy Management System (HEMS) at the building level in a strategically integrated RES-based electricity grid can help reduce the building peak demand as well as energy consumption and the power inefficiency in the grid respectively. Distributed Energy Generation (DEG) based on Renewable Energy Sources (RES) are seen as a reliable alternative and more efficient grid optimization to the traditional fossil energy sources-based grid. But a proper combination of demand response and the DEG can significantly make a revolutionary change in the electricity grid. This paper focuses on the impact of integrated control of Solar PV and the Wind Turbine on improving the supply-side and coordinated control strategy for automated demand response by ensuring efficient use of home appliances including Electric Vehicle (EV), air cooling, water heating etc. based on HEMS in order to reduce the peak demand and overall power inefficiency in the grid. For that purpose and analysis, a highly accurate aggregated model of Solar PV, Wind turbine and the home appliances has been developed in the Simulink (MATLAB) and an iterative algorithm based on Load Shifting technique has been established for HEMS controller with embedded MATLAB code. The obtained simulation result illustrates the effectiveness of the proposed system.
[8] Bi-Level Load Peak Shifting and Valley Filling Dispatch Model of Distribution Systems With Virtual Power Plants by Luo, Fengzhang, Yang, Xin, Wei, Wei, Zhang, Tianyu, Yao, Liangzhong, Zhu, Lingzhi, & Qian, Minhui[edit | edit source]
In this paper, the authors study Bi-Level Load Peak Shifting and Valley Filling Dispatch Model of Distribution Systems With Virtual Power Plants. Distributed energy resources (DERs) have been widely involved in the optimal dispatch of distribution systems which benefit from the characteristics of reliability, economy, flexibility and environmental protection. And distribution systems are gradually transforming from passive networks to active distribution networks (ADNs). However, it is difficult to manage DERs effectively because of their wide distribution, intermittency and randomness. Virtual power plants (VPPs) can not only coordinate the contradiction between distribution systems and DERs, but also consider the profits of DERs, which can realize the optimal dispatch of distribution systems effectively. In this paper, a bi-level dispatch model based on VPPs is proposed for load peak shaving and valley filling in distribution systems. The VPPs consist of distributed generations (DGs), energy storage devices (ESS) and demand response resources (DR). The objective of the upper-level model is smoothing load curve, and the objective of the lower-level model is maximizing the profits of VPPs. Meanwhile, we consider the quadratic cost function to quantify the deviation between the actual output and the planned output of DGs. The effectiveness of the bi-level dispatch model in load shifting and valley filling is proved by various scenarios. In addition, the flexibility of the model in participating in distribution systems dispatch is also verified.
[9] CES peak demand shaving with energy storage system by S. Park, & W. Park[edit | edit source]
This paper analyzes energy cost reduction from peak demand shaving when a CES provider adopts ESS for the CHP-based CES microgrid site in Seoul, Korea. The simulation results show that about 9% of peak shaving can be realized when a 270kWh ESS is used for three thousand CES households. When two or three ESSs are adopted, peak demand shaving increases at most into 12% or 14%, which concludes that ESS capacity enlargement is not so helpful for the peak reduction. It also concludes that peak shaving is appropriate as a supplementary usage of ESS considering that ESS is required to work only a few days for a year to achieve peak shaving.
[10] Coalitional Game-Based Cost Optimization of Energy Portfolio in Smart Grid Communities by A. Chiş, & V. Koivunen[edit | edit source]
In this paper, we propose two novel coalitional game theory-based optimization methods for minimizing the cost of electricity consumed by households from a smart community. Some households in the community may own renewable energy sources (RESs) conjoined with energy storage systems (ESSs). Some other residences own ESSs only, while the remaining households are simple energy consumers. We first propose a coalitional cost optimization method in which RESs and ESSs owners exchange energy and share their renewable energy and storage spaces. We show that by participating in the proposed game these households may considerably reduce their costs in comparison to performing individual cost optimization. We further propose another coalitional optimization model in which RESs and ESSs owning households not only share their resources, but also sell energy to simple energy consuming households. We show that through this energy trade the RESs and ESSs owners can further reduce their costs, while the simple energy consumers also gain cost savings. The cost savings obtained by the coalition are distributed among its members according to the Shapley value. Simulation examples show that the proposed coalitional optimization methods may reduce the electricity costs for the RESs and ESSs owning households by 18%, while the sole energy consumers may reduce their costs by 3%.
[11] Confronting the Duck Curve: How to Address Over-Generation of Solar Energy[edit | edit source]
In this study, the department of energy (DOE) investigated methods to address over-generation of solar energy. In 2013, the California Independent System Operator published a chart that is now commonplace in conversations about large-scale deployment of solar photovoltaic (PV) power. The duck curve—named after its resemblance to a duck—shows the difference in electricity demand and the amount of available solar energy throughout the day. When the sun is shining, solar floods the market and then drops off as electricity demand peaks in the evening. The duck curve is a snapshot of a 24-hour period in California during springtime—when this effect is most extreme because it's sunny but temperatures remain cool, so demand for electricity is low since people aren't using electricity for air conditioning or heating. The duck curve represents a transition point for solar energy. It was, perhaps, the first major acknowledgement by a system operator that solar energy is no longer a niche technology and that utilities need to plan for increasing amounts of solar energy. This is especially true for places that already have high solar adoption, such as California, where one day this past March, solar contributed nearly 40% of electricity generation in the state for the first time ever.
[12] Duck curve problem solving strategies with thermal unit commitment by introducing pumped storage hydroelectricity renewable energy by Howlader, H. O. R., Furukakoi, M., Matayoshi, H., & Senjyu, T.[edit | edit source]
In this paper, the authors study Duck curve problem solving strategies with thermal unit commitment by introducing pumped storage hydroelectricity renewable energy. In recent years, the price of photovoltaic (PV) has been decreasing dramatically, that has been increasing the installation of PVs in smart grid and roof photovoltaic (PVr). There is no doubt, this is a positive development of smart grid for the world. As we know every good thing has a bad side too, PVs definitely generate power in the day time, so huge number of PV's power penetration in the daytime changes the load demand of fossils fuel based thermal generations and load curve becomes duck shape. In duck curve, peak and off-peak gap is very large. It is a challenge to cut the peak and increase the off-peak load which means load leveling is very important. If peak and off-peak gap are more so start-up cost (SUC) of thermal generators will be more. Besides, more thermal units have to be run to fulfill the peak load. Therefore, it is very important to run thermal units optimally. As we already knew, duck curve has very high peak so the only optimization is not enough to bring good results. Therefore, energy storage system plays a vital role to level peak and off-peak load. However, battery energy system (BESS), still installation cost is very high specially NaS battery. That is why in this research considers concentrated solar power (CSP) and pumped storage hydroelectricity (PSH) as the energy storage system (ESS). In this research, optimal unit commitment (UC) of thermal generators and PSH is introduced for saving the fuel cost and SUC of thermal generators. Optimal results of the proposed research model are determined by using MATLAB® INTLINPROG optimization toolbox.
[13] Effect of Taiwan's energy policy on unit commitment in 2025 by Gerard Francesco DG. Apolinario, Chen-Nien Chung, Tai-Ken Lu, Chia-Chi Chu[edit | edit source]
This study presents the effect of Taiwan's energy policy on its unit commitment in the year 2025. Taiwan's energy policy has been changing since 2005, since when it has required the decommissioning of nuclear power plants in response to the crisis in Fukushima, the adoption of the Kyoto Protocol, and the increase of renewable sources of power generation to 20% of its energy mix. The paper models the unit commitment for the Taiwan power system under Taiwan's energy policy. The study compares unit commitments in 2018, summer 2025, and winter 2025 using AMPL Software with the CPLEX 12.9.0 Solver. The results show that the net demand curve will change by 2025, forming a "duck – curve" model due to the high penetration of renewable energy. The daily carbon dioxide emission in 2018 for five percent (5%) spinning reserve is 392,151,000 kg. The said amount is larger than in winter 2025 when it will be 311,314,000 kg indicating the importance of the full implementation of renewable energy projects in helping to reach Taiwan's goal to limit carbon dioxide emission by 2025. Pumped storage scheduling changes from conventional pumping in the early morning to pumping from around noon to late afternoon due to the high penetration of renewable energy. The construction of combined-cycle units will have a critical role in the achieving of the spinning reserve capacity goal set by the Taiwan government, to avoid the importation of energy and to maintain the energy security of the country.
[14] Energy storage in high renewable penetration power systems: Technologies, applications, supporting policies and suggestions by H. Zhu, H. Li, G. Liu, Y. Ge, J. Shi, H. Li, & N. Zhang[edit | edit source]
Integrating renewable energy is one of the most effective ways to achieve a low-carbon energy system. The high penetration of variable renewable energy, such as wind power and photovoltaic, increases the challenge of balancing the power system. Energy storage technology is regarded as one of the key technologies for balancing the intermittency of variable renewable energy to achieve high penetration. This study reviews the energy storage technology that can accommodate the high penetration of renewable energy. The basic energy storage technologies that can accommodate time-scale variation are reviewed first. The role of energy storage in the generation, transmission, distribution, and consumption for the high renewable energy penetration system is then analyzed. The supporting energy storage policies in the United States, the United Kingdom and China are summarized. Specific suggestions are proposed from the perspectives of technology, business and policy. This paper provides guidelines for planning energy storage to enable a high renewable penetration power system.
[15] Energy Storage in High Penetration of Renewable Energy Power System: Technologies, Application and Supporting Policies by L. Ma, H. Li, Y. Ge, J. Shi, G. Liu, & B. Li[edit | edit source]
Integrating renewable energy is one of the most effective way to achieve low-carbon energy system. High penetration of variable renewable energy such as wind power and photovoltaic rises the challenge of balancing the power system. Energy storage technology is regarded one of the keys technology for balancing the intermittency of variable renewable energy to achieve high penetration. This study reviews the energy storage technology that is able to accommodate high penetration of renewable energy. The basic technologies of energy storage that is effective in accommodating the variation in different time scale is firstly reviewed. The role of energy storage in the generation, transmission, distribution, and consumption for high renewable energy penetration is then analyzed. The energy storage supporting policies in the United States and Chinese are summarized. This paper provides guidelines for planning energy storage towards high penetration of renewable energy power system.
[16] Flattening the "duck curve" to get more renewable energy on the grid by Robert, David in Vox.[edit | edit source]
According to the author, the first big strategy to flatten the duck is interconnection. The more grids can be connected with one another to form larger grids over larger areas, the more spread out the potential for wind and solar will be and the more spread out load will be, both of which will serve to smooth out the peaks and valleys in the curve. The second big strategy is energy storage. If you can store some of that wind and solar energy rather than automatically sending it to the grid, you make it "dispatchable," meaning you can time it. It becomes a movable piece of the puzzle. He offers 10 practical ideas to start flattening the duck:
- Target energy efficiency to the hours when load ramps up sharply
- Acquire and deploy peak-oriented renewable resources
- Manage water and wastewater pumping loads
- Control electric water heaters to reduce peak demand and increase load at strategic hours
- Convert commercial air conditioning to ice storage or chilled-water storage
- Rate design: Focus utility prices on the "ramping hours" to enable price-induced changes in load
- Deploy electrical energy storage in targeted locations
- Implement aggressive demand response programs
- Use inter-regional power exchanges to take advantage of diversity in loads and resources
- Retire inflexible generating plants with high off-peak must-run requirements
[17] Future Challenges of Grid-Connected Photovoltaic in Java Bali Power System by H. B. Tambunan, P. A. A. Pramana, B. B. S. D. A. Harsono, A. A. Kusuma, J. Hartono, & B. S. Munir[edit | edit source]
Utilization of renewable energy sources (RES) especially photovoltaic (PV) into electrical power system including Indonesia grid massively increasing. Furthermore, high PV penetration level can create duck curve phenomenon in net load profile. This study aim to describe the challenges introduced by grid-connected PV system into Java Bali power system. High PV penetration level changes the load shape in the middle of the day. The calculation results show that system operator must prepare high ramp rate from conventional power plant before reaching the peak load time. Therefore, system operator should make proper planning to deal with duck curve phenomenon.
[18] Flattening the Duck Curve Using Grid-friendly Solar Panel Orientation by Doroshenko M., Keshav, M., & Keshav, C.[edit | edit source]
In this paper, the authors proposed the use of a Grid-friendly Solar Panel Orientation to flattening the Duck Curve. By adopting grid-scale solar power, a utility can reduce both its carbon footprint and its fuel bills for legacy thermal generation plants. However, as solar penetration increases, generation can exceed load during the middle of the day, and diurnal variations in solar generation cause rapid ramps every morning and evening. This so-called 'duck-curve' causes increased wear and tear of thermal plants and wasteful curtailment. We study how flexibility in solar panel orientation at the time of installation can be used to flatten the duck curve mitigating these ramping problems. We find that grid-friendly panel orientation can indeed reduce ramping by 25-30%, also reducing overgeneration during mid-day periods, without significantly increasing net load. Thus, it is an attractive approach for future solar deployments.
[19] INCORPORATING RENEWABLES INTO THE ELECTRIC GRID: EXPANDING OPPORTUNITIES FOR SMART MARKETS AND ENERGY STORAGE[edit | edit source]
The cost of renewable energy has been quickly dropping and renewable energy generation has been rapidly growing in the United States, spurred by state and federal policies and technological advances. Moreover, projections going forward suggest ever increasing penetration of renewables into the electricity grid. The two most rapidly growing renewable energy sources, wind and solar, provide variable energy output that depends on the time of day, location, season, weather, and other factors. Integrating high levels of these renewables onto the grid will require a reimagining of the management of the grid. It will increase the demand for grid management services, opening up a new set of important opportunities for promising technologies and approaches. This report examines economic and technical considerations related to increasing integration of variable renewable energy resources onto the existing electric grid, which highlight the importance of emerging technologies and approaches in smart markets and energy storage that can help smooth this transition. Smart markets use new communications technologies to develop integrated approaches allowing for electricity demand to respond during times of high value. Energy storage technologies allow the temporary storage of electricity so it can be released during times of high value. The key report findings are outlined below.
Wind and solar are known as "variable energy resources" (VERs) because their output is variable. Generation of wind and solar depends on when the sun is shining and the wind is blowing, which is imperfectly predictable. There are regions in the world that are already successfully managing an extremely high penetration of renewable VERs. For example, Portugal was run 100 percent on wind, solar, and hydropower for four days straight in May 2016, and Texas hit a record level of 45 percent instantaneous penetration from wind generation during one evening in February of this year.
[20] Impact of High Renewable Penetration on the Power System Operation Mode: A Data-Driven Approach by Q. Hou, E. Du, N. Zhang, & C. Kang[edit | edit source]
The high penetration of renewable energy will substantially change the power system operation. Traditionally, the annual operation of a power system can be represented by some typical operation modes and acts as the basis for the power-system-related analysis. The introduction of highly penetrated renewable energy will make the power system operation mode highly diversified and variable. These modes may not follow traditional empirical patterns. In this paper, we propose a data-driven method based on high-dimensional power system operation data (including power flow, unit generation, and load demand) to identify the pattern of the operation modes and analyze the impact of high renewable penetration. Specifically, the proposed data-driven method is composed of simulation, preprocessing, clustering, dimension reduction, and visualization with the aim to provide an intuitive understanding of the operation mode variety under high renewable penetration. In addition, several indices are introduced to quantify the space dispersion, time variation, and seasonal consistency of operation modes. A case study on actual Qinghai provincial power system in China validates the effectiveness of the proposed data-driven method and indicates that the dispersion and time variation of operation mode will significantly increase in the beginning and then saturate with the increase in renewable penetration level. The operation mode is also less correlated with seasons in renewable energy dominated power system.
[21] Improving Duck Curve Profile, Enabling Peak-shaving and Increasing Self-sufficiency by Properly Designing Community Solar Projects by M. A. Hayat, F. Shahnia, & G. M. Shafiullah[edit | edit source]
Community solar consisting of rooftop photovoltaic systems (RPVs) and battery energy storage systems, when designed properly, can address and solve many of the design and adoptability challenges brought by the individual RPVs and battery energy storage. Such systems can benefit many of the remote and rural communities, that are usually supplied by diesel generators, or long traditional distribution lines, which in addition to being expensive often don't provide the reliability at desired level. These systems can also benefit most of the urban areas since the unmanaged penetration of RPVs has resulted in the undesired duck curve profile in the network. To this end, this paper proposes and verifies the appropriate design criteria for community solar projects with an aim to improve the network duck curve profile, enable peak-shaving and increase the self-sufficiency of the community.
[22] Integrating solar into Florida's power system: Potential roles for flexibility by Hale, Elaine T., Stoll, Brady L., & Novacheck, Joshua E.[edit | edit source]
Although Florida has very little photovoltaic (PV) generation to date, it is reasonable to expect significant deployment in the 2020s under a variety of future policy and cost scenarios. To understand these potential futures, the authors model Florida Reliability Coordinating Council operations in 2026 over a wide range of PV penetrations with various combinations of battery storage capacity, demand response, and increased operational flexibility. By calculating the value of PV under a wide range of conditions, we find that at least 5%, and more likely 10–24%, PV penetration is cost competitive in Florida within the next decade with baseline flexibility and all but the most pessimistic of assumptions. For high PV penetrations, we demonstrate Florida's electrical net-load variability (duck curve) challenges, the associated reduction of PV's value to the system, and the ability of flexibility options–in particular energy-shifting resources–to preserve value and increase the economic carrying capacity of PV. A high level of demand response boosts the economic carrying capacity of PV by up to 0.5–2 percentage points, which is comparable to the impact of deploying 1 GW of battery storage. Adding 4 GW of battery storage expands the economic carrying capacity of PV by up to 6 percentage points.
[23] Investigation of Daytime Peak Loads to Improve the Power Generation Costs of Solar-Integrated Power Systems by Afonaa-Mensah, Stephen, Wang, Qian, & Uzoejinwa, Benjamin B.[edit | edit source]
In this paper, the authors investigated Daytime Peak Loads to Improve the Power Generation Costs of Solar-Integrated Power Systems. Improving daytime loads can mitigate some of the challenges posed by solar variations in solar-integrated power systems. Thus, this simulation study investigated the different levels of daytime peak loads under varying solar penetration conditions in solar-integrated power systems to improve power generation cost performance based on different load profiles and to mitigate the challenges encountered due to solar variation. The daytime peak loads during solar photovoltaic generation hours were determined by measuring the solar load correlation coefficients between each load profile and the solar irradiation, and the generation costs were determined using a dynamic economic dispatch method with particle swarm optimization in a MATLAB environment. The results revealed that the lowest generation costs were generally associated with load profiles that had low solar load correlation coefficients. Conversely, the load profile with the highest positive solar load correlation coefficient exhibited the highest generation costs, which were mainly associated with violations of the supply-demand balance requirement. However, this profile also exhibited the lowest generation costs at high levels of solar penetration. This result indicates that improving daytime load management could improve generation costs under high solar penetration conditions. However, if the generation system lacks sufficient ramping capability, this technique could pose operational challenges that adversely impact power generation costs.
