Demand response of medical freezers in a Business Park Microgrid

This paper presents a demand response (DR) framework that utilizes the flexibility inherent to the thermodynamic behavior of four groups of independently-controlled medical freezers in a privately-owned business park microgrid that contains rooftop photovoltaics (PV). The optimization objectives may be chosen from the following 3 options: minimizing electricity exchanges with the public grid; minimizing costs by considering prices and RES availability; and minimizing peak load. The proposed DR framework combines thermodynamic models with automated, genetic-algorithm-based optimization, resulting in demonstrable benefits in terms of cost, energy efficiency, and peak power reduction for the consumer, local energy producer, and grid operator. The resulting optimal DR schedules of the freezers are compared against unoptimized, business-as-usual scenarios with- and without PV. Results show that flexibility can be harnessed from the thermal mass of the freezers and their contents, improving the cost- and energy performance of the system with respect to the business-as-usual scenarios.</p

Microgrid design considerations for a smart-energy university campus

The goal of this paper is to propose a design approach to transform the current distribution network of the Eindhoven University of Technology campus into a smart grid. First, the needs and interests of different stakeholders are translated into a local definition of the smart grid concept. This definition is the starting point for outlining the values and services that the smart grid should provide, and the goals it needs to fulfill. Future campus loads, distributed generators, and mobile storage capabilities are modeled and simulated in order to assess their impact on the distribution grid and determine hosting capacity. Recommendations are given on the infrastructure needed for enabling the transition to smart grids, not only for the university as a concrete case study, but rather as a blueprint for future smart grid pilots

Distributed energy resources for a zero-energy neighbhourhood

Zero energy buildings are on the increasing trend. They are perceived as appropriate technology to reducing CO2 emissions, improving energy efficiency and alleviating energy poverty. The main goal is that a grid-connected building produces enough energy on site to equal or exceed its annual energy requirement while using the grid as a buffer. Many municipalities see this concept as a prospective solution for developing future neighborhoods and thereby aim to develop a neighborhood with net zero energy concept. This paper proposes passive designs measures and distributed power generations required in designing such a neighborhood

Distributed energy resources for a zero-energy neighbhourhood

Zero energy buildings are on the increasing trend. They are perceived as appropriate technology to reducing CO2 emissions, improving energy efficiency and alleviating energy poverty. The main goal is that a grid-connected building produces enough energy on site to equal or exceed its annual energy requirement while using the grid as a buffer. Many municipalities see this concept as a prospective solution for developing future neighborhoods and thereby aim to develop a neighborhood with net zero energy concept. This paper proposes passive designs measures and distributed power generations required in designing such a neighborhood

Demand response of medical freezers in a Business Park Microgrid

This paper presents a demand response (DR) framework that utilizes the flexibility inherent to the thermodynamic behavior of four groups of independently-controlled medical freezers in a privately-owned business park microgrid that contains rooftop photovoltaics (PV). The optimization objectives may be chosen from the following 3 options: minimizing electricity exchanges with the public grid; minimizing costs by considering prices and RES availability; and minimizing peak load. The proposed DR framework combines thermodynamic models with automated, genetic-algorithm-based optimization, resulting in demonstrable benefits in terms of cost, energy efficiency, and peak power reduction for the consumer, local energy producer, and grid operator. The resulting optimal DR schedules of the freezers are compared against unoptimized, business-as-usual scenarios with- and without PV. Results show that flexibility can be harnessed from the thermal mass of the freezers and their contents, improving the cost- and energy performance of the system with respect to the business-as-usual scenarios

Medical freezers as flexible load for demand response in a business park microgrid with local solar power generation

This work presents a day-ahead demand response (DR) scheduling framework that quantifies the flexibility in non-residential buildings by using thermodynamic modeling, and assesses the benefits of DR in terms of three separate optimization variants: net payment minimization, energy self-sufficiency, and peak power reduction. We test the framework in a case study of a medical research facility located in a business park with local solar power generation. The flexible loads are four groups of independently-controlled medical freezers. Our DR framework generates optimal freezer operation and solar power production/curtailment schedules that are compared against a business-as-usual scenario with no DR. We perform simulations for cases with and without end-of-horizon temperature constraints. Results show that the flexibility harnessed from the freezers’ thermal mass for DR actions improves the price-responsiveness, energy independence, and peak power consumption of the system with respect to the business-as-usual scenario. Furthermore, adding end-of horizon constraints ensures that the thermal buffer of the flexible load will be full for the next simulation time window