Yingying Zheng

• University of California, Davis

The microgrid is a small-scale, independent power system that plays a crucial role in the transition to carbon-neutral energy systems. Combined heat and power (CHP) systems with energy storage reduce energy waste within microgrids, enhancing energy utilization efficiency. The key challenge for a microgrid integrated with a combined heat and power s...

Photovoltaic (PV) installations contribute to more sustainable solutions in satisfying clean energy requirements and are essential to global efforts to mitigate climate change. The PV development has extensive space requirements, complicated by the increasing competition for land due to rising population growth and food demand. By installing solar...

The growing integration of renewable energy sources into the power grid has introduced unprecedented uncertainty. Ensuring an appropriately scheduled reserve is essential to accommodate renewable energy's intermittent and volatile nature. This study introduces an innovative approach to ultra‐short‐term wind power forecasting, which relies on featur...

The numerical weather prediction (NWP) is crucial to improve intraday wind power forecasting (WPF) accuracy. However, conventional WPF methods relied solely on a latest reported single NWP, overlooking hidden information from sequentially reported multiple historical NWPs that are partially overlapped over time. Additionally, it's challenging to ta...

The integration of electricity, heat, and gas networks introduces additional dimensions of flexibility, but the complex network topology makes power dispatch challenging. This paper presents a method for constructing a convex polyhedron to define the dynamic 3D flexible region (FR), which represents all possible power/heat/gas flow injection soluti...

High penetration of electric vehicles (EVs) in an uncontrolled manner could have disruptive impacts on the power grid, however, such impacts could be mitigated through an EV demand response program. The successful implementation of an efficient, effective, and aggregated demand response from EV charging depends on the incentive pricing mechanism an...

The volatile and intermittent nature of renewable energy sources (RES) has a critical impact on the electric grid. This paper aims to propose a model to quantify the impact of the uncertainty of RES on the power system operating costs in an electricity market environment considering the use of flexible ramping (FR) products, compensation for wind p...

The virtual power plant (VPP) breaks the geographical restrictions of environment and resource types by virtue of aggregating the distributed energy resources and dispatchable loads. In view of the impact of large-scale energy consumption by users on the operational safety of VPP, based on the existing demand response (DR) researches, this paper ad...

Due to its stochastic nature, wind energy imposes unprecedented challenges on the power grid, and a properly scheduled reserve is essential to accommodate wind power's intermittency and volatility. Many power reserve scheduling studies have considered the uncertainties of the renewable energy integration but few address how different wind speed for...

Due to its stochastic nature, wind energy imposes unprecedented challenges on the power grid, and a properly scheduled reserve is essential to accommodate wind power’s intermittency and volatility. Many power reserve scheduling studies have considered the uncertainties of the renewable energy integration but few address how different wind speed for...

The acquisition of information on fish stress has been recognized as an urgent need for monitoring water quality, preventing disease, and improving welfare. Minimizing the potential stress-related impact on fish health has attracted public attention by effectively and reliably identifying early signs of stress response in intensive aquaculture. To...

The integrated energy system is considered to be an important way to avoid energy supply risks by virtue of advantages in meeting diversified energy demand and improving energy utilization efficiency. Energy storage enables microgrid operators to respond to variability or loss of generation sources. In view of the difficulty of battery to fully imp...

Meta-analysis is a statistical analysis of the data obtained from multiple studies and provides a quantitative synthesis of research results. It can be a key tool for facilitating rapid progress in aquaculture by quantifying what is known and identifying what is not yet known. However, due to the complexity of the environment and problems associate...

Abstract The success of an efficient and effective aggregator‐based residential demand response system in the smart grid relies on the day‐ahead customer incentive pricing (CIP) and the load shifting protocols. An artificial neural network model is designed to generate the day‐ahead CIP for the aggregator based on historical data. Load scheduling i...

The presence of fouling in evaporators can increase energy consumption as well as capital and labor costs. During corn ethanol production, fouling occurs when thin stillage is concentrated in multiple effect evaporators to form condensed distillers solubles. Limited studies have been conducted on fouling of corn ethanol processing. Process streams...

To accomplish California's aggressive 100% clean energy by 2045, new sources of flexibility should be integrated into the system to ensure stable and reliable operation of the grid. Economical and scalable energy storage technologies are key to deliver such flexibility services. Pumped storage hydropower (PSH) is an economical and mature energy sto...

Object counting in aquaculture is an important task, and has been widely applied in fish population estimation, estimation of lobster abundance and scallop stocks, and so forth. However, underwater object counting is challenging for biologists and marine scientists because of the diversity of backgrounds of the lake or ocean, the uncertainty of the...

A load shifting algorithm based on economic linear programming with model predictive control was developed to minimize the operating cost of a biomass combined heat and power based microgrid system. The model simultaneously manages supply and demand of both electrical and thermal energy as decision variables. An algorithm was developed to optimize...

Deterministic constrained optimization and stochastic optimization approaches were used to evaluate uncertainties in biomass-integrated microgrids supplying both electricity and heat. An economic linear programming model with a sliding time window was developed to assess design and scheduling of biomass combined heat and power (BCHP) based microgri...