The energy resource scheduling is becoming increasingly important, as the use of distributed resources intensified and massive gridable vehicle (V2G) envisaged. This paper presents a methodology for day-ahead smart grids considering intensive generation V2G. main focus comparison different EV management approaches in management, namely uncontrolled charging, V2G Demand Response (DR) programs approach. Three DR are designed tested (trip reduce, shifting reduce reduce+shifting). Other...

Summary form only given. This paper proposes a Simulated Annealing (SA) approach to address energy resources management from the point of view Virtual Power Player (VPP) operating in smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on multi-period basis according V2G users' profiles requirements. Apart using aggregated resources, VPP can also purchase additional set external suppliers. The includes case study for 33 bus distribution network...

To study and understand this type of market, we developed the Multiagent Simulator Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM model includes players with strategies for bid definition, acting in forward, day-ahead, balancing markets considering both simple complex bids. Our goal was to simulate as many market models player types possible. This approach makes a short medium term simulation well tool support long-term decisions, such those...

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for success smart grids. intensive use Distributed Energy Resources (DER) and technical contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes Particle Swarm Optimization (PSO) based methodology support minimization operation costs virtual...

This work explores the effectiveness of explainable artificial intelligence in mapping solar photovoltaic power outputs based on weather data, focusing short-term mappings. We analyzed impact values provided by Shapley additive explanation method when applied to two algorithms designed for tabular data—XGBoost and TabNet—and conducted a comprehensive evaluation overall model across seasons. Our findings revealed that selected features remained relatively consistent throughout year,...

This paper presents a simulator for electric vehicles in the context of smart grids and distribution networks. It aims to support network operators’ planning operations but can be used by other entities related studies. The describes parameters supported current version Electric Vehicle Scenario Simulator (EVeSSi) tool its algorithm. EVeSSi enables definition scenarios on networks using built-in movement engine. created with external tools (e.g., power flow) specific analysis, instance grid...

Further integration of distributed renewable energy sources in distribution systems requires a paradigm change grid management by the system operators (DSOs). DSOs are currently moving to an operational planning approach based on activating flexibility from resources day/hour-ahead stages. This paper follows DSO trends proposing methodology for active which robust optimization is applied accommodate spatial-temporal uncertainty. The proposed method entails use multi-period AC-OPF, ensuring...

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including generation based on renewable resources, demand response, storage systems, and electrical gridable vehicles. The use vehicles have a significant impact power systems management, especially in networks. Therefore, inclusion optimal scheduling be very important future network management. proposed particle swarm optimization...

A distributed, agent-based intelligent system models and simulates a smart grid using physical players computationally simulated agents. The proposed can assess the impact of demand response programs.

Wind power generation is to play an important role in supplying electric demand, and will certainly impact the design of future energy reserve markets. Operators wind plants consequently develop adequate offering strategies, accounting for market rules operational capabilities turbines, e.g., participate primary We consider two different strategies joint participation markets, based on idea proportional constant splitting potentially available from turbines. These aim at maximizing expected...

This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces so‐called smart grid. We start by providing an overview grid optimization. From variety challenges that arise context, we analyze with significance importance energy resource management problem since it is seen as one most complex challenging research. The also discussion application computational intelligence, strong emphasis...

Electricity markets are complex environments, involving a large number of different entities, playing in dynamic scene to obtain the best advantages and profits. MASCEM (Multi-Agent System for Competitive Markets) is multi-agent elect

The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type resources' particular characteristics (namely, the sources intermittent nature). smart grid concept is increasing its consensus as most suitable solution facilitate small players' participation in electric power negotiations while improving efficiency. opportunity for multiple negotiation environments (smart addition already implemented market types,...