The energy transition has shown that fossil generation can be complemented with renewable energy and other resources capable of providing flexibility to the energy system’s operation, in compliance with the wholesale electricity market’s rules. This paper proposes a market-based methodology for introducing flexible demand in the energy dispatch, optimizing the scheduling of electricity system operation in the short-term, and considers the challenge of implementing an incentive scheme for participants in demand-response programs. The scheme includes the criteria of the elasticity of substitution and a renewable energy quota. This methodology is focused on a strategic demand shift to minimize the cost of supply; increase the dispatch of renewable energy; control CO₂ emissions; and satisfy the generation, demand, and transmission operating constraints. These conditions encourage the development of a simulation tool that allows a sensitivity analysis to aid decision-making by operators and agents. The proposed methodology optimizes the operational cost of generation supply and specific performance indicators to determine the percentages of demand shift, the amount of CO₂ emissions, the ratio of unserved power, the demand benefits obtained from an incentive scheme, and the natural market behavior.

The Dominican Republic has significant potential for energy generation from residual biomass, with sugarcane, rice, and coconut waste having the highest energy potential. The Eastern, Northeastern, and Southern regions were identified as the areas with the most significant potential for energy generation. This potential can be harnessed to complement intermittent or unmanageable renewable energies in distributed generation networks. Biomass generation plants can be hybridized with other sources, such as wind and solar, to provide a more stable and reliable electricity supply. The methodology developed to evaluate the energy potential of residual biomass in the Dominican Republic integrates a rigorous review of the literature and agricultural databases, incorporating criteria such as annual production, residue-to-product ratio, higher calorific value, and dry matter content, culminating in a formula that synthesizes normalized data to optimize the selection and projection of biomass sources based on their potential energy contribution. The study found that the Dominican Republic has significant potential for energy generation from residual biomass, which can be leveraged to provide a more stable and reliable electricity supply.

The dimensions of the costs and incentives necessary for integrating demand response into the wholesale electricity market are subject to energy policies and bulk system operation. The electricity industry must gain operational flexibility to support the energy transition caused by renewable energy and decarbonization. Complementary services and technologies of demand response programs can be optimized by exploiting the variety of uses of this resource. The main objective of this work is to apply the concept of elasticity of substitution in a strategic demand shift program to promote the integration of renewable energies and the reduction of non-served power, considering an economical and safe generation dispatch. The methodology is analyzed through a case study applied in the Dominican Republic’s electricity market, in which the elasticity of substitution coefficients is used to adjust variations below 10.49% of the base demand in the peak period. These variations reduce the generation operating cost by 8.4%, marginal cost by 30.19%, and non-served power by 19.1% when renewable energy increases by 5%. In addition, the operating cost was controlled when the methodology included CO2 emission costs. This study contextualizes new possibilities to optimize system operation and the wholesale electricity market based on demand response programs that encourage flexible consumption, with favorable economic and environmental results.

This dataset contains historical records of electricity demand in the Dominican Republic from January 2021 to December 2024, with hourly resolution. It was compiled to support short-term load forecasting of the National Interconnected Electric System (SENI). The dataset includes the total system demand in megawatts (MW), along with a set of exogenous variables commonly used in forecasting models. These variables include weather data retrieved from Open-Meteo (such as temperature and humidity), time-lagged demand features, and calendar-based indicators (e.g., weekends, holidays, month, hour). All data were collected from open sources, including the official website of the electricity market and system operator, the Organismo Coordinador (OC), as well as public meteorological APIs. The dataset is structured and cleaned to be directly usable for time series modeling applications. It can be reused by researchers, utility planners, and data scientists for benchmarking forecasting models, developing predictive tools, or supporting energy planning tasks in tropical, developing power systems. The data is provided in CSV format.

The transition from centralized to decentralized power generation presents a significant opportunity to enhance grid resilience and energy independence, particularly in regions with unstable grids or vulnerability to natural disasters. Distributed Generation (DG), particularly solar photovoltaics, has become a key component of modern power systems, especially in distribution networks. However, its increasing penetration at both utility and distributed levels poses challenges related to voltage, frequency, and angular stability, requiring advanced monitoring and control strategies. In this context, energy storage systems (ESS) emerge as a crucial player, playing a significant role in mitigating these challenges. ESS stabilizes power supply fluctuations and enhances grid reliability, providing a safety net for the intermittent nature of renewable energy sources. This study examines the impact of DG on the stability and operation of the National Interconnected Electric System (SENI) of the Dominican Republic, with a focus on integrating ESS at both utility and distribution levels. Using DIgSILENT, future scenarios (2027) with high renewable penetration were simulated. The methodology included data collection, modeling of actual automatic load shedding (EDAC) events from 2024, and the simulation of three scenarios: without storage, with utility-scale storage, and with both utility-scale and distributed storage. The results indicate that energy storage systems (ESS) significantly enhance system stability, reducing both the total disconnected load and the number of EDAC steps. In the absence of storage, 640 MW were disconnected; with utility-scale storage, this was reduced to 540 MW, and the addition of distributed storage further decreased the disconnected load to 440 MW while also delaying EDAC activation times. Findings highlight the critical need for ESS investments and grid flexibility mechanisms to accommodate increasing renewable penetration, particularly in Small Island Developing States (SIDS). Future research should optimize ESS deployment and conduct detailed economic analyses to support the development of sustainable power systems.

In the electricity system, the frequency behavior is an indicator of the quality of the service provider that expresses the equilibrium between the supply and demand of electricity. Demand presents challenging to predict behavior, which means that usually, the balance is corrected through changes in a generation. The operators rely on generation plants that must keep 3% of their power available for regulation. With the increase in electric vehicles (EV) and the growing vehicle-to-grid (V2G) technology, the frequency regulation service could be supplemented and mitigated by generators. This research aims to analyze the viability and feasibility of the use of V2G technology as a complementary service to primary frequency regulation. The battery model of electric vehicles with the necessary components for its operation in V2G was simulated using the PowerFactory DIgSILENT software. A single bank with all the power connected to a system Monte Carlo simulation of a single bank was carried out with all the power connected to a system bus to simulate the entire fleet of electric vehicle batteries and know how much power was always available. The results obtained in the simulations show that theso of the EVs in the primary frequency regulation does not allow sudden changes in frequency in the electrical system.