Thermal Energy Optimization of Building Integrated Semi-Transparent Photovoltaic Thermal Systems

Building integrated photovoltaic (BIPV) : The concept where the photovoltaic element assumes the function of power generation and the role of the covering component element has the potential to become one of the principal sources of renewable energy for domestic purpose. In this paper, a Building integrated semitransparent photovoltaic thermal system (BISPVT) system having fins at the back sheet of the photovoltaic module has been simulated. It has been observed that this system produces higher thermal and electrical efficiencies. The increase of wind velocity by fan system and heat exchange surface accelerates the convective heat transfer between the finned surface and the fluid flowing in the duct. The system area of 36.45 m2 is capable of annually producing an amount of thermal energy of 76.66 kWh at an overall thermal efficiency of 56.07 %

A model predictive control approach to the periodic implementation of the solutions of the optimal dynamic resource allocation problem

This paper proposes a model predictive control (MPC) approach to the periodic implementation of the optimal solutions of a class of resource allocation problems in which the allocation requirements and conditions repeat periodically over time. This special class of resource allocation problems includes many practical energy optimization problems such as load scheduling and generation dispatch. The convergence and robustness of the MPC algorithm is proved by invoking results from convex optimization. To illustrate the practical applications of the MPC algorithm, the energy optimization of a water pumping system is studied

Routing versus energy optimization in a linear network

In wireless networks, devices (or nodes) often have a limited battery supply to use for the sending and reception of transmissions. By allowing nodes to relay messages for other nodes, the distance that needs to be bridged can be reduced, thus limiting the energy needed for a transmission. However, the number of transmissions a node needs to perform increases, costing more energy. Defining the lifetime of the network as the time until the first node depletes its battery, we investigate the impact of routing choices on the lifetime. In particular we focus on a linear network with nodes sending messages directly to all other nodes, or using full routing where transmissions are only sent to neighbouring nodes. We distinguish between networks with nodes on a grid or uniformly distributed and with full or random battery supply. Using simulation we validate our analytical results and discuss intermediate options for relaying of transmissions

Aerial small cells using coordinated multiple UAVs : an energy efficiency optimization perspective

Recently, unmanned aerial vehicle (UAV) communications have attracted great research interest. Due to the limited on-board energy, the optimization of energy efficiency (EE) is critical for UAV communications. In this paper, we propose an EE maximization scheme for UAV swarm-enabled small cell networks using large-scale channel state information at the transmitter (CSIT). The proposed scheme provides an agile coordination strategy for the UAVs in a swarm under energy constraints. We first formulate the EE maximization problem, where the objective function is defined as the ratio of the ergodic total data size to the total energy consumption. After that, an accurate approximation is derived to remove the intractable expectation operator in the objective function. As the newly formulated problem is non-convex, we decompose it into two subproblems to optimize the transmit power and the hovering time in an iterative way. Further by leveraging the max-min and linear optimization tools, both subproblems are efficiently solved. Simulation results demonstrate the superiority of our EE maximization scheme