Abstract
This paper presents a scenario-based framework for energy hub (Ell) design considering the variable efficiencies of gas-fired converters, wind turbines and integrated demand response (MR) programs. The proposed hub is able to meet the electrical, heating and cooling demands and is also equipped with a power-to-gas (P2G) system. Electrical, cooling, and heating loads uncertainties have been taken into account and the final problem is modeled as a mixed-integer non-linear programming (MINLP) problem. The P2G system is precisely modeled and its impacts on hub planning, emission, and the efficiency of gas-fired converters are thoroughly investigated. The results demonstrate that the P2G system reduced CO2 emissions by 37.4% by consuming CO2 emitted by gas-fired units. In addition, the results indicate that the P2G system injects hydrogen into the gas-fired units and increases their efficiencies. Therefore, the generation rate of these units has increased and consequently a smaller capacity has been installed for them. Numerical results illustrate that the presence of the P2G system has led to a reduction of 7.7% and 16.2% of investment and operation costs, respectively. Finally, the results indicate that the implementation of the IDR program reduces the installed capacity of the equipment, thereby reducing 3.3% of total cost. Overall, the results prove that the implementation of IDR programs along with the installation of the P2G system lead to reduce costs and CO2 emissions.

Abstract
Transmission expansion planning (TEP) is an important part of power system expansion planning. In TEP, optimal number of new transmission lines and their installation time and place are determined in an economic way. Uncertainties in load demand, place of power plants, and fuel price as well as voltage level of substations influence TEP solutions effectively. Therefore, in this paper, a scenario based-model is proposed for evaluating the fuel price impact on TEP considering the expansion of substations from the voltage level point of view. The fuel price is an important factor in power system expansion planning that includes severe uncertainties. This factor indirectly affects the lines loading and subsequent network configuration through the change of optimal generation of power plants. The efficiency of the proposed model is tested on the real transmission network of Azerbaijan regional electric company using a discrete artificial bee colony (DABC) and quadratic programming (QP) based method. Moreover, discrete particle swarm optimization (DPSO) and decimal codification genetic algorithm (DCGA) methods are used to verify the results of the DABC algorithm. The results evaluation reveals that considering uncertainty in fuel price for solving TEP problem affects the network configuration and the total expansion cost of the network. In this way, the total cost is optimized more and therefore the TEP problem is solved more precisely. Also, by comparing the convergence curve of the DABC with that of DPSO and DCGA algorithms, it can be seen that the efficiency of the DABC is more than DPSO and DCGA for solving the desired TEP problem.

Abstract
Phasor measurement unit (PMU) provides beneficial information for dynamic power system stability, analysis, and control. One main application of such useful information is data-driven analysis and control. This article presents an approach for optimal signal selection and controller structure determination in PMU-based power system stabilizer (PSS) design. An algorithm is suggested for selecting the optimal input and output signals for PSS, in which a combination of system clustering, modal analysis, and principal component analysis techniques is used. The solution for the optimal PSS input-output selection is determined to increase the observability and damping of the power system. The approach can efficiently reduce the number of input-output signals, while the overall performance is not deteriorated. Then, a linear matrix inequality-based technique is elaborated to design the PMU-based PSS parameters. The stabilizer design approach is formulated as a convex optimization problem and the appropriate stabilizer for pole allocation of the closed-loop model is designed. This method is simulated on two sample power systems. Also, to compare the results with the previous methods, the system is simulated and the results of two previously developed algorithms are compared with the proposed approach. The results show the benefit of the suggested method in reducing the required signals, which decreases the number of required PMUs, while the system damping is not affected.

Abstract
Electric vehicles (EVs) are seen as a crucial tool to reduce the polluting emissions caused by the transport and power systems (PS) sector and the associated shift to a cleaner and more sustainable energy sector. The com-bination of EVs and solar photovoltaics (PV) in PS, specifically through the aggregation of EVs in parking lots (PLs), may improve the reliability and flexibility of the PS, assisting the power network in critical moments. This work proposes a novel aggregator agent in the energy system which is an EV charging station with an installed PV system. In this work, an optimal operation strategy for the solar-powered EV PL (EVSPL) operation is pre-sented. The model optimizes the EVSPL's participation in various energy and ancillary services markets, including the effects of capacity payments. The results show that the EVSPL leads to higher profits. The EVSPL's participation in ancillary services is highly influenced by the prices. The results of this work show that this novel agent can actively participate in the energy system in an economically viable manner while respecting the technical constraints of the network and providing important ancillary services to the system operator. Superscript/Subscript Available

Abstract
The trend towards a decentralized, decarbonized, and digital energy system is gaining momentum. A key driver of this change is the rapid penetration increase of Distributed Energy Resources (DER). Commercial consumers can offer significant contributions to future energy systems, especially by engaging in demand response services. Virtual Power Plants (VPP) can aggregate and operate DERs to provide the required energy to the local grid and allowing for the participation in wholesale energy markets. This work considers both the technical constraints of the distribution system as well as the commercial consumer's comfort preferences. A stochastic mixed-integer linear programming (MILP) optimization model is developed to optimize the scheduling of various DERs owned by commercial consumers to maximize the profit of the TVPP. A case study on the IEEE 119-bus test system is carried out. Results from the case study show that the TVPP provides optimal DER scheduling, improved system reliability and increase in demand response engagement, while maintaining commercial consumer comfort levels. In addition, the profit of the TVPP increases by 49.23% relative to the baseline scenario.

Abstract
This paper deals with the bi-level two-stage operation scheduling of hydrogen-based microgrids within a distribution system where the wind and solar generation and load demands are considered as uncertain variables. The distribution system is considered as a leader in the upper level and microgrids as followers in the lower level. Unlike previous approaches, the upper-level is within the day-ahead market and considered a deterministic problem, and the lower-level is considered a stochastic problem and consists of two stages. The first stage determines the purchasing power from the distribution system, while the second stage adjusts the outputs and power dispatch for any realizations of scenarios. This model is transformed from a bi-level to a linear single-level model by applying the Karush- Kuhn-Tucker (KKT) optimally conditions, strong duality, and Fortuny-Amat methods. Several comparisons have been carried out regarding the single clearing price for all microgrids or separate prices for each microgrid. Furthermore, power exchange and dispatch in the distribution system are investigated under the mentioned frameworks.