Efficient building energy management is essential for energy saving and green society. This paper investigates sustainable energy management for an energy building cluster with distributed transaction. The building cluster consists of several types of energy buildings, e.g., office, industrial, and commercial buildings. We first formulate utility functions for the buildings of consuming energy based on the characteristics of their controllable loads. Then a two-stage energy sharing strategy is presented. In the first stage, the total social energy cost is minimized through finding the optimal energy sharing profiles in a distributed way. In the second stage, the clearing for mutual energy sharing is modeled as a non-cooperative game, and the existence of the equilibrium of the game is illustrated and a relaxation-based algorithm is introduced to search for the equilibrium. Moreover, a real-time model for each building to overcome real-time uncertainties, such as renewable energy generation and base loads is provided. The simulation results show that the proposed energy sharing strategy is economically beneficial for the energy buildings, computationally efficient, and is promising to facilitate a sustainable regional building cluster.

Peer-to-Peer Energy Sharing Among Smart Energy Buildings by Distributed Transaction

Indoor air quality and energy management through real-time sensing in commercial buildings

Due to rapid population growth, technology, and economic development, electricity demand is rising, causing a gap between energy production and demand. With the emergence of the smart grid, residents can schedule their energy usage in response to the Demand Response (DR) program offered by a utility company to cope with the gap between demand and supply. This work first proposes a novel optimization-based energy management framework that adapts consumer power usage patterns using real-time pricing signals and generation from utility and photovoltaic-battery systems to minimize electricity cost, to reduce carbon emission, and to mitigate peak power consumption subjected to alleviating rebound peak generation. Secondly, a Hybrid Genetic Ant Colony Optimization (HGACO) algorithm is proposed to solve the complete scheduling model for three scenarios: without photovoltaic-battery systems, with photovoltaic systems, and with photovoltaic-battery systems. Thirdly, rebound peak generation is restricted by using Multiple Knapsack Problem (MKP) in the proposed algorithm. The presented model reduces the cost of using electricity, alleviates the peak load and peak-valley, mitigates carbon emission, and avoids rebound peaks without posing high discomfort to the consumers. To evaluate the applicability of the proposed framework comparatively with existing frameworks, simulations are conducted. The results show that the proposed HGACO algorithm reduced electricity cost, carbon emission, and peak load by 49.51%, 48.01%, and 25.72% in scenario I; by 55.85%, 54.22%, and 21.69% in scenario II, and by 59.06%, 57.42%, and 17.40% in scenario III, respectively, compared to without scheduling. Thus, the proposed HGACO algorithm-based energy management framework outperforms existing frameworks based on Ant Colony Optimization (ACO) algorithm, Particle Swarm Optimization (PSO) algorithm, Genetic Algorithm (GA), Hybrid Genetic Particle swarm Optimization (HGPO) algorithm.

An Optimization Based Power Usage Scheduling Strategy Using Photovoltaic-Battery System for Demand-Side Management in Smart Grid

This paper presents a comprehensive review of advanced technologies with various control approaches in terms of their respective merits and outcomes for power grids. Distributed energy storage control is classified into automatic voltage regulator and load frequency control according to corresponding functionalities. These control strategies maintain a power balance between generation and demand. Besides, three basic electric vehicle charging technologies can be distinguished, i.e. stationary, quasi-dynamic and dynamic control. For realizing charge-sustaining operation at minimum cost quasi-dynamic and dynamic strategies are adopted for in-route charging, while stationary control can only be utilized when the electric vehicle is in stationary mode. Moreover, power system frequency stability and stabilization techniques in non-synchronous generator systems are reviewed in the paper. Specifically, a synchronverter can damp power system oscillations and ensure stability by providing virtual inertia. Furthermore, it is crucial to manage the massive information and ensure its security in the smart grid. Therefore, several attack detection and mitigation schemes against cyber-attacks are further presented to achieve reliable, resilient, and stable operation of the cyber-physical power system. Thus, bidirectional electrical power flows with two-way digital control and communication capabilities have poised the energy producers and utilities to restructure the conventional power system into a robust smart distribution grid. These new functionalities and applications provide a pathway for clean energy technology. Finally, future research trends on smart grids such as IoT-based communication infrastructure, distributed demand-response with artificial intelligence and machine learning solutions, and synchrophasor-based wide-area monitoring protection and control (WAMPC) are examined in the present study.

Operational planning steps in smart electric power delivery system.

Energy management systems in buildings (EMSs-in-Bs) play key roles in energy saving and management to which an efficient energy management system in buildings (EMS-in-Bs) design contributes. Different scope-based designs of EMS-in-Bs are reviewed. The objective is to highlight different scope-based designs of EMS-in-Bs in which scopes of reviewed papers aim to implement a function of, for example, “monitor energy performance”, “estimate energy-use”, or “control energy-use”. This paper aims to constitute a comprehensive conception of how efficient such an EMS-in-Bs to perform more than one scope (i.e., function). Meaning, is the proposed EMS-in-Bs able to perform several sequential functions? This paper’s contribution is to give a function-focused EMS’s review utilizing the scope of reviewed papers. That is, reviewed papers are classified based on the scope/function the selected EMS-in-Bs is designed for. This could help select an EMS-in-Bs to perform certain scope/function(s). Another contribution is that, numerous EMSs-in-Bs are reviewed in a classified way so that the most adequate EMS-in-Bs for a certain scenario considering the performed scopes/functions e.g., “monitor” are highlighted. Findings showed that “control-optimize”-functioned EMS-in-Bs achieved highest energy-saving rates ~30% compared to “estimate-predict” with 10%. Findings, insights given by reviewed studies, current problems faced, future directions, and remarks are drawn in conclusion. Analysis done on reviewed papers has found that the highest and lowest averaged-energy saving rates were obtained with papers whose their scopes are implementing “control”-with-“optimize” and “estimate”-with-“predict”, respectively. Energy saving rates for these two classes of scopes have been equal to 22.57% and 10%, respectively. We recommend that there is a need to enhance the estimation- and prediction-related EMS-in-Bs to achieve a higher energy saving rate.

https://findresearcher.sdu.dk:8443/ws/files/182306995/Energy_Management_Systems_and_Strategies_in_Buildings_Sector_A_Scoping_Review.pdf

Energy Management Systems and Strategies in Buildings Sector: A Scoping Review

In this new era of communication, the advent of the smart grid has revolutionised the power system network. The goal of smart grids is to provide a more reliable, environment-friendly and economically efficient power system. Demand side management or demand side response is one of the key components of the smart grid which accomplishes the smart grid that would provide intelligence to the traditional grid. Here, a new approach has been proposed for the demand side management, which is based on shifting a load from peak to off-peak time. The main objective of the work is to reduce the peak hour demand and the utility bill of the consumers. To achieve these objectives, the proposed strategy is modelled as a minimised optimisation problem and it tries to find out the optimal solution. For that, two optimisation algorithms, the first one is particle swarm optimisation algorithm and the second one is grasshopper optimisation algorithm, are proposed and applied in three area loads of the smart grid, i.e. residential, commercial and industrial. The obtained simulation results show a significant reduction in peak hour demand and utility bills.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2019.0566

Hourly load shifting approach for demand side management in smart grid using grasshopper optimisation algorithm

With an increasing need for reduction in energy consumption level and continuing growth of energy use by commercial buildings has created a need to develop innovative techniques to reduce and optimize building energy use. Recently Building Energy Management System (BEMS) have gained popularity because of increasing interest in building energy conservation and savings. Building Energy Management System has the ability to control and monitor the building's energy needs. Building Energy Management System not only provides indoor thermal comfort but also creating a safe and healthy environment within residential buildings including institutional, commercial and industrial buildings and able to reduce energy consumption. In order to improve the overall energy efficiency and save electricity expenditure of the Building lead to electricity saving. The Objective of this paper is to review different methods or techniques suggested by the researchers for controlling and monitoring the energy consumption patterns in buildings. Additionally, it highlights various developed software in Building Energy Management System Especially BEMOSS (Building Energy Management Open Source Software) and also discuss benefits of Building Energy Management System.

Sonam Mittal

Papers

Hourly load shifting approach for demand side management in smart grid using grasshopper optimisation algorithm

Building Energy Management System: A Review