Energy management for user’s thermal and power needs: A survey <s> Transformation <s> Abstract A combined cooling, heating and power (CCHP) microgrid with distributed cogeneration units and renewable energy sources provides an effective solution to energy-related problems, including increasing energy demand, higher energy costs, energy supply security, and environmental concerns. This paper presents an overall review of the modeling, planning and energy management of the CCHP microgrid. The performance of a CCHP microgrid from the technical, economical and environmental viewpoints are closely dependent on the microgrid’s design and energy management. Accurate modeling is the first and most important step for planning and energy management of the CCHP microgrid, so this paper first presents an review of modeling of the CCHP microgrid. With regard to planning of the CCHP microgrid, several widely accepted evaluation methods and indicators for cogeneration systems are given. Research efforts on the planning methods of the CCHP microgrid are then introduced. Finally, the energy management of the CCHP microgrid is briefly reviewed in terms of cogeneration decoupling, control strategies, emission reduction and problem solving methods. <s> BIB001 </s> Energy management for user’s thermal and power needs: A survey <s> Transformation <s> Abstract In this paper, a new methodology has been discussed on economical power management of a grid-connected CHP system which consists of a wind turbine, photovoltaic array, polymer exchange membrane fuel cell and an electrolyzer. Hence, the paper also attempts to present the thorough modeling of energy management of the hybrid system in the form of a nonlinear optimization problem; through which offline energy management is regarded to use the available options in order to determine the role of each generator in producing heat, power and hydrogen in the system under study. In addition to this, variable tariffs of daily exchange with local grid have been taken into account in different operation conditions so as to reach real utilization requirements. Based on these facts, choosing the most suitable model for each element of the hybrid system has been considered in regard to their dynamic behavior. The proposed hybrid system is to supply the electrical and thermal demands of renewable energy laboratory of Shahid Bahonar University of Kerman (SBUK). The economical energy management is comprehensively studied and surveyed in the form of various scenarios while the hybrid system is connected to the grid. <s> BIB002 </s> Energy management for user’s thermal and power needs: A survey <s> Transformation <s> In this paper, an optimal probabilistic scheduling model of energy hubs operations is presented. The scheduling of energy hub determines the energy carriers to be purchased as input and converted or stored, in order to meet the energy requests, while minimizing the total hub's cost. However, as many other engineering endeavors, future operating criteria of energy hubs could not be forecasted with certainty. Load and price uncertainties are the most unclear parameters that hub operators deal with. In this regard, this paper proposes a 2 $m$ + 1 point estimation probabilistic scheduling scheme for energy hubs with multiple energy inputs and outputs. One of the applicable tools of energy hubs to have an efficient participation in the liberalized power market with volatile prices is demand response programs (DRPs). While there is plenty of experience in investigating the effect of DRP, it is electricity DRP that receives increasing attention by research and industry. Therefore, the proposed DRP investigates the effect of both responsive thermal and electric loads in reducing the total cost and participation of different facilities in supplying multiple loads. The proposed model envisages the most technical constraints of converters and storages. Several test systems have been investigated in order to confirm the effectiveness of the proposed model. The results verify the capability of the proposed model in covering the energy hub time-varying output demands as well as the economic advantages of implementing the suggested strategy. In addition, the results are compared with 2 $m$ point estimate method and Monte Carlo simulation. <s> BIB003
Transformation resources refer to all DERs whose inputs and outputs are both secondary energy resources. Electric water heater uses electricity to heat water; electric heat pump (EHP) and AC system consume electricity to move heat from a cold source to a warm one. Absorption and compression chillers are coupled with prime mover in CCHP and they use waste heat or electricity to move heat between different fluids and satisfy cooling load BIB001 . The most common transformation units are included in Fig. 3 within trapezoids. In BIB003 and BIB002 , a hydrogen production plant, composed by electrolyzer and H 2 storage tank, is included into the model to supply H 2 to a FC. The electrolyzer is included among the transformation resources as it converts electricity in another energy vector, i.e., hydrogen.