Integrating Demand Side Management Research Articles

Improving Grid Reliability in Jordan: A Proposal for Integrated Demand Side Management and Energy Storage Solutions

<p align="left">Increased use of Renewable energy systems (RES) in Jordan has posed a major challenge in maintaining our grid stability. Jordan a country that relies on imported natural resources to power up its grid is using more and more RES with an aim to cut back on costs and CO<sub>2</sub> emissions. This paper investigates the usage of Demand Side Management (DSM) and Energy Storage Systems (ESS) to improve the grid’s reliability. A survey was conducted to analyze the opinion and acceptance of the Jordanian population on the implementation of DSM in Jordan. (ESS) mentioned in detail in this paper are: Compressed Air Energy Storage Systems (CAES), Superconducting Magnetic Energy Storage Systems(SMES), and Pumped Hydro Energy Storage Systems(PHES). The survey conducted showed a general scope of willingness of participation from people with 71.7% out of the 385 individuals who participated in the survey saying that they will participate in such a program if implemented in Jordan.</p>

Day-ahead scheduling of isolated microgrid integrated demand side management

Day-ahead scheduling of isolated microgrid integrated demand side management

Integrated demand-side management for multi-energy system based on non-cooperative game and multi-energy pricing

This paper proposes an integrated demand-side management (IDSM) approach based on non-cooperative game and multi-energy pricing strategy for a regional integrated energy system (RIES). On the demand side, the competition among multi-energy users was modeled as a non-cooperative energy consumption game, and the conditions to ensure the existence and uniqueness of the Nash equilibrium of the non-cooperative game were given. Considering the privacy of user information, a distributed multi energy consumption control algorithm based on dual theory and gradient descent method was designed to search for the optimal multi-energy consumption and the multi-energy daily retail price. In addition, for the energy supply side, the scheduling strategy of energy hub (EH) was proposed based on linear programming (LP) theory to optimize equipment operation. The results show that this approach can enable users and EH to coordinate optimization, so as to reduce the peak-to-average ratio (PAR) and energy cost of the system, and ensure the balance between supply and demand of multi-energy.

Integrating demand side management into EU electricity distribution system operation: A Dutch example

The EU goals for renewable electricity cause significant changes of electrical loads in distribution systems, in which most renewable electricity sources are integrated. This poses a challenge for distribution system operators (DSOs) as their networks are not designed for such load changes. DSOs could use networks more efficiently with demand side management (DSM), where consumers of electricity alter their consumption patterns, shifting (production/consumption) loads in the distribution system. In such a setting, consumers would trade DSM services with the DSOs. However, currently, DSOs follow the ‘copper plate approach’, which assumes the system should have sufficient capacity to ensure that the desired volumes of electricity can be transported. This seeks to guarantee regulated third party access (rTPA) for all system users. Next to rTPA, based on regulated tasks, DSOs should ensure secure, reliable and efficient systems. In doing so, the DSOs are bound by unbundling requirements, which do not allow them to be involved in any activities other than those related to distribution. Therefore, especially production and supply are not allowed. Still, it seems debatable whether EU law allows DSOs to apply DSM, as it has an impact on both the access conditions to the electricity system, and the production, supply and trade of electricity. This article further analyses how DSM relates to the legal framework of DSOs, which obstacles are present, and how DSM could be traded between DSOs and system users.

Integrated Demand Side Management Game in Smart Energy Hubs

The presence of energy hubs and the advancement in smart grid technologies have motivated system planners to deploy intelligent multicarrier energy systems entitled “smart energy hub” (S.E. Hub). In this paper, we model S.E. Hub, and propose a modern energy management technique in electricity and natural gas networks based on integrated demand side management (IDSM). In conventional studies, energy consumption is optimized from the perspective of each individual user without considering the interactions with each other. Here, the interaction among S.E. Hubs in IDSM program is formulated as a noncooperative game. The existence and uniqueness of a pure strategy Nash equilibrium (NE) is proved. Additionally, the strategies for each S.E. Hub are determined by proposing a distributed algorithm. We also address the IDSM game in a cloud computing (CC) framework to achieve efficient data processing and information management. Simulations are performed on a grid consisting of ten S.E. Hubs. We compare the CC framework with conventional data processing techniques to evaluate the efficiency of our proposed approach in determining NE. It is also shown that in the NE, the energy cost for each S.E. Hub and the peak-to-average ratio of the electricity demand decrease substantially.

Evaluating the integration of wind power into distribution networks by using Monte Carlo simulation

This paper provides a probabilistic method to assess the impact of wind turbines (WTs) integration into distribution networks within a market environment. Combined Monte Carlo simulation (MCS) technique and market-based optimal power flow (OPF) are used to maximize the social welfare by integrating demand side management (DSM) scheme considering different combinations of wind generation and load demand over a year. MCS is used to model the uncertainties related to the stochastic variations of wind power generation and load demand. The market-based OPF is solved by using step-controlled primal dual interior point method considering network constraints. The method is conceived for distribution network operators (DNOs) in order to evaluate the effect of WTs integration into the network. The effectiveness of the proposed method is demonstrated with an 84-bus 11.4kV radial distribution system.

Real Time Operation of Smart Grids via FCN Networks and Optimal Power Flow

This paper proposes an Energy Management System for the optimal operation of Smart Grids and Microgrids, using Fully Connected Neuron Networks combined with Optimal Power Flow. An adaptive training algorithm based on Genetic Algorithms, Fuzzy Clustering and Neuron-by-Neuron Algorithms is used for generating new clusters and new neural networks. The proposed approach, integrating Demand Side Management and Active Management Schemes, allows significant enhancements in energy saving, customers' active participation in the open market and exploitation of renewable energy resources. The effectiveness of the proposed Energy Management System and adaptive training algorithm is verified on a 23-bus 11 kV microgrid.

Combined Operations of Renewable Energy Systems and Responsive Demand in a Smart Grid

The integration of renewable energy systems (RESs) in smart grids (SGs) is a challenging task, mainly due to the intermittent and unpredictable nature of the sources, typically wind or sun. Another issue concerns the way to support the consumers' participation in the electricity market aiming at minimizing the costs of the global energy consumption. This paper proposes an energy management system (EMS) aiming at optimizing the SG's operation. The EMS behaves as a sort of aggregator of distributed energy resources allowing the SG to participate in the open market. By integrating demand side management (DSM) and active management schemes (AMS), it allows a better exploitation of renewable energy sources and a reduction of the customers' energy consumption costs with both economic and environmental benefits. It can also improve the grid resilience and flexibility through the active participation of distribution system operators (DSOs) and electricity supply/demand that, according to their preferences and costs, respond to real-time price signals using market processes. The efficiency of the proposed EMS is verified on a 23-bus 11-kV distribution network.