Hybrid renewable power plants consisting of collocated wind, solar photovoltaic (PV), and lithium-ion battery storage connected behind a single grid connection can provide additional value to the owners and society in comparison to individual technology plants, such as those that are only wind or only PV. The hybrid power plants considered in this article are connected to the grid and share electrical infrastructure costs across different generation and storing technologies. In this article, we propose a methodology for sizing hybrid power plants as a nested-optimization problem: with an outer sizing optimization and an internal operation optimization. The outer sizing optimization maximizes the net present values over capital expenditures and compares it with standard designs that minimize the levelized cost of energy. The sizing problem formulation includes turbine selection (in terms of rated power, specific power, and hub height), a wind plant wake loss surrogate, simplified wind and PV degradation models, battery degradation, and operation optimization of an internal energy management system. The problem of outer sizing optimization is solved using a new parallel “efficient global optimization” algorithm. This new algorithm is a surrogate-based optimization method that ensures a minimal number of model evaluations but ensures a global scope in the optimization. The methodology presented in this article is available in an open-source tool called HyDesign. The hybrid sizing algorithm is applied for a peak power plant use case at different locations in India where renewable energy auctions impose a monetary penalty when energy is not supplied at peak hours. We compare the hybrid power plant sizing results when using two different objective functions: the levelized cost of energy (LCoE) or the relative net present value with respect to the total capital expenditure costs (NPV/CH). Battery storage is installed only on NPV/CH-based designs, while the hybrid design, including wind, solar, and battery, only occurs on the site with good wind resources. Wind turbine selection on this site prioritizes cheaper turbines with a lower hub height and lower rated power. The number of batteries replaced changes at the different sites, ranging between two or three units over the lifetime. A significant oversizing of the generation in comparison to the grid connection occurs on all NPV/CH-based designs. As expected LCoE-based designs are a single technology with no batteries.

In this study, a novel coordinated market scheme is proposed, enabling the participation of distributed energy resources (DERs) in the wholesale as well as local energy market (LEM). First, a day‐ahead energy market framework is proposed that is operated by a distribution system operator (DSO) in coordination with the transmission system operator (TSO). The DERs present in a distribution system have the freedom to select among the local or wholesale electricity markets (WEM) to offer their energy. The DSO aggregates all DERs' services and power demand to represent them in a WEM operated at the transmission level. The proposed model allows the DSO to select more economical ways of allocating the resources utilising the TSO‐DSO coordination strategy. The objective is to maximise social welfare in light of network constraints. Furthermore, a practical method is developed for DSOs to redistribute any monetary surplus among different DERs participating in the WEM. Numerical simulations indicate the proposed model's economic effectiveness compared to the scenario where DERs are allocated only at the local market level.

Integration of distributed energy resources (DERs) in the distribution system (DS) raises the need to have a trading platform for their energy products. The evolution of distribution system operators (DSOs) facilitates the participation of DERs in the energy market at DS level. To utilize the potential of DERs in DS at the transmission level, an iterative coordinated market operations (CMO) scheme for a day-ahead energy market is proposed in this paper. In the proposed scheme, coordination between the transmission system operator and DSOs is established with limited exchange of information to realize an efficient and economical market framework. The communication procedure and time interval for data exchange during various intermediate operations, and convergence criteria of the proposed iterative scheme are defined. The main goal is to accommodate CMO into the existing market clearing mechanism with minimal changes. Case studies on three test systems demonstrate the viability of proposed scheme and the improvement in overall economics in comparison to the conventional method of market clearing as practiced or proposed in literature.

The nature and characteristics of distribution systems are changing continuously with the increased penetration of distributed energy resources. With this, the need for examining the transmission and distribution (T&D) interaction while assessing the voltage security has become significant. In much of the analysis and practices reported so far, voltage security assessment studies are performed separately for T&D systems. Thus, a transmission system operator (TSO) is oblivious to the operations and controls taking place at the distribution system (DS) level. Some of the recent studies examine the impact of an active DS on the voltage security assessment of future power systems. However, the effect of various factors like voltage dependency of loads, reactive power capability of renewable energy sources (RES), location of distributed generation units, and network losses on the voltage stability margin (VSM) of transmission system has not been reported comprehensively so far. This paper first theoretically examines the impact of these factors on VSM. Then, to get the more realistic results for VSM, continuation power flow (CPF) is performed in a coordinated fashion including both T&D systems. The simulations show that considering losses, load characteristics dependency on voltage and reactive power limits of RES in a DS for transmission voltage security assessment studies lead to a more rational outcome than when neglected.

The short-term uncertainties associated with renewable energy resources lead to imbalances in the power systems, posing major challenges for operators. Energy storage systems, such as batteries, are increasingly considered a promising solution to mitigate these concerns. Thus, co-located wind and battery hybrid power plants (HPPs) operating with a single grid connection are poised to play a vital role in achieving balance in future energy systems. In addition, batteries can potentially improve revenue generation for HPP owners in the electricity markets. However, assessing the profitability of HPPs across different electricity markets such as spot market and balancing market to offset initial investment costs requires a thorough investigation, making optimal HPP sizing crucial. Optimal decisions are also critical for battery operation in various electricity markets, necessitating the modeling of HPP energy management system (EMS) for market participation. Hence, this work proposes a novel EMS that captures spot and balancing markets and performs efficiently within an outer non-linear sizing optimization, aiming to determine the plant's optimal bidding strategy in different electricity markets and optimal plant design for higher returns on investment. Simulations for a wind-dominated region in Northern Europe show significant potential to enhance HPP profitability up to 4 times through strategic multi-market participation and optimal plant sizing.