Design of an Auction-based Local Energy Market for Integrated Electricity and Heat Networks Coordinated with Wholesale Market

This article presents a market-based framework for coupling of electricity and heat sectors at the local level via power-to-heat (P2H) units. The considered local energy market (LEM) is designed based on an auction-based energy trading process which is settled by the integrated energy system operator (IESO) with the objective of social welfare maximization. Moreover, as part of the suggested mechanism, the coordination between the IESO and the transmission system operator (TSO) is considered to evaluate the mutual impact of the designed LEM on the wholesale electricity market (WEM) and vice versa. To this end, a bi-level programming model is employed, in which the LEM clearing problem is implemented at its upper level (UL) while the WEM clearing problem is executed at its lower level (LL). To assess the operation of the LEM and its coordination with the WEM, a case study is considered in which an integrated energy system (IES), including a 13-node electric distribution system and a 4-node district heating system, is connected to a 6-node transmission system.© IET. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.fi=vertaisarvioitu|en=peerReviewed

Optimal planning of a virtual power plant hosting an EV parking lot

With the increasing penetration of electric vehicles (EV) in the future, VPPs can take some actions for meeting their demand. This way, VPPs can increase their income by selling electric power to EVs and utilizing the battery of EVs as energy storage to facilitate the deployment of renewable energy resources. However, investing too much in charging stations may not have an acceptable return on investment. In this paper, we study the optimal operation and planning of a VPP which is located to certain part of the network and is composed of wind turbines, PV units, as well as unidirectional and bidirectional EV charging stations. In our proposed approach, optimal planning is done considering that the system will be operated optimally. According to the simulation results, EV owners' behavior could have a significant impact on the optimal planning decision of the VPP. In addition, optimal number of the unidirectional and bidirectional EV charging stations depend on the share of the PV and wind generation and the capacity of the line between the VPP and upstream grid.©2022 IET. This paper is a postprint of a paper submitted to and accepted for publication in CIRED Porto Workshop 2022: E-mobility and power distribution systems and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.fi=vertaisarvioitu|en=peerReviewed

Optimal Planning of Residential Energy Hubs Considering Customer Desire Function

This paper proposes an optimal residential energy hub (REH) design framework where the desired tradeoff between maximizing the satisfaction level of residential user energy usage and minimizing the overall costs is obtained by establishing a customer desire function (CDF). Considering the major household appliances, the REH demands are categorized into several groups, and CDFs are formulated and applied to each group of loads. The developed mathematical model results in a mixed-integer linear programming optimization problem. Simulations were carried out on a residential building as a case study. Numerical results confirmed the presented framework effectiveness in improving the end-user convenience level and enhancing the investment benefits. They also demonstrated the significance of various energy networks and the optimal configuration of REH components on the financial and technical of the REH

Stochastic bi-level coordination of active distribution network and renewable-based microgrid considering eco-friendly Compressed Air Energy Storage system and Intelligent Parking Lot

The optimal operation of active distribution systems in the presence of private renewable-based entities is one of the primary challenges of future power networks. In this regard, developing a practical framework to deal with this kind of issue is essential. Hence, in this paper, a novel bi-level stochastic programming approach is presented for optimal energy and reserve scheduling of the active distribution system in the presence of different eco-efficient autonomous players. In the proposed model, the distribution system operator, as a leader, attempts to minimize its total operating costs. At the same time, the renewable-based microgrid owner, as an independent follower, tends to maximize its profit from exchanging energy and reserve with the distribution system operator. The suggested scheme is a non-linear bi-level problem which is transformed into a non-linear single-level problem through Karush–Kuhn–Tucker conditions. In order to find the global optima, the non-linear single-level problem is linearized by utilizing the Big-M method. Finally, to investigate the effectiveness of the provided model, it is tested on the modified IEEE 15-Bus active distribution system under different cases and scenarios. Obtained results indicate that the operation cost of the distribution system operator can be reduced up to 134.09$, from 10710.11$ to 10576.02$, and the profit of the microgrid owner can be increased significantly 906.93$, from 659.455$to 1566.39$, by considering both environmentally friendly units, IPL and CAES

A novel resource allocation model based on the modularity concept for resiliency enhancement in electric distribution networks

Paying attention to the modularity feature of electric distribution systems improves their performance against severe events and makes an outstanding opportunity for resiliency enhancement. In this paper, a novel framework based on the modularity concept is proposed in which, by deploying smart grid technologies and forming efficient modules, effective and robust energy in distribution systems is provided. Optimal placement of distributed generation (DG) resources, load control options, switching devices, and tie lines are simultaneously incorporated in the proposed linear allocation model. To consider electrical and topological characteristics in the independent functioning of the formed modules, a path-based method is employed. The effectiveness and computability of the proposed algorithm are examined by performing several simulations on two modified 37-bus and 84-bus test systems. The results demonstrate that the developed modular structure, by subdividing the system into several independent parts, creates more flexibility for the recovery process and facilitates the self-healing capabilities

Optimal probabilistic PMU placement in electric distribution system state estimation

This paper presents an algorithm for optimal placement of phasor measurement units (PMUs) in electric distribution networks to obtain predefined probabilistic relative errors in magnitude and angle for a distribution system state estimation (DSSE). The probabilistic relative error is introduced to consider the effect of failure probability (FP) and sending bad data probability (BDP) of PMUs. In this paper, the probabilistic relative error is defined as the expected value of the relative error values corresponding to the operating states of PMUs, which are calculated from Monte Carlo simulations. The binary particle swarm optimization (BPSO) is adapted to find the optimal number and locations of PMUs in a distribution network. The simulation results on 6-bus and 34-bus IEEE radial distribution networks show the effect of FP and BDP on the PMU placement as well as the performance of the proposed algorithm